Chapter Overview

This introduction welcomes readers to the work of advancing equity in computer science education (CS Ed). It presents some of the inequities that CS students and teachers face, as well as some of the efforts that are underway to work toward equity in CS and CS Ed. It also describes the values and goals that are the foundation of this guide.

Chapter Objectives

After reading this introduction, I can:

• Describe recent efforts to work toward equity in CS and CS Ed.
• Identify inequities that continue in CS and CS Ed.
• Explain the values that shaped how the authors of this guide approached their work.

Key Terms:

broadening participation; critical consciousness; culturally sustaining pedagogies; equity as access; equity as transformation; praxis

Getting Started

Welcome! This guide focuses on advancing equity work in CS Ed. To begin, we wish to recognize how we as authors come to this work. We are a collective of CS educators and scholars who came together to work on a multi-year project focused on equity in CS Ed in New York City. We hold different identities at the intersections of disability, gender, language, and race among others. We have collaborated on many equity-related CS efforts, and this guide is a product of those collaborations. See the Preface for more details about our positionalities and the history of the guide.

We also acknowledge that you, our readers, come to this guide with different backgrounds and experiences that shape how you do this work. Some of the ideas presented here may resonate strongly with you. Some may make you pause or feel discomfort. We hope that as you explore these ideas, you’ll feel compelled to process your responses, talk out what you’re learning with colleagues, and importantly, try out something new in your settings. Equity work takes time, critical reflection, commitment, and individual and collective action. There’s no one perfect way to do it. We hope this guide helps you take steps big and small to create more accessible, just, and ethical forms of CS Ed for your students.

To get started on our journey, let’s meet Marilyn, a CS teacher who is asking some important questions about what equity looks and feels like in CS Ed.^{[footnote]Marilyn is a composite character based on New York City public school teacher Susan Murray and the collective experiences of the authors, teachers, and collaborators of this guide.[/footnote]}

Marilyn’s Story

It was a few minutes after the last bell on the last day of school at STEM Preparatory Academy, a diverse school in New York. Students had just cleared out of the building, and Marilyn, a sixth and seventh grade CS teacher, began to clean her classroom. On the walls were posters of “giants” in computing, people like Katherine Johnson, Jerry Lawson, and Alan Turing, whose racial, ethnic, and gender identities reflected the diverse student body at her school.^{[footnote]See Resource 1 at the end of the chapter and this calendar of leaders in CS for more resources: https://sites.google.com/schools.nyc.gov/cs4all-equity/pioneer-calendar?authuser=0[/footnote]} Marilyn had hung them up after attending a professional development (PD) workshop about representation in CS Ed earlier in the year. As she took down the posters, she sighed. A math teacher for fifteen years, this was Marilyn’s first year tentatively entering the world of CS. She found the PD trainings intellectually interesting and the mission to bring CS to all students a compelling one. But she couldn’t deny that her entry into CS this year had left her with many questions.

Marilyn’s PD trainings had shared troubling statistics about how young women and girls are often excluded from CS Ed and careers. Inspired to change this, Marilyn adopted a curriculum from the Girls Who Code organization and convinced her principal to fund an after-school club.^{[footnote]To learn more about Girls Who Code, visit https://www.girlswhocode.com/[/footnote]} Marilyn reflected on her experience:

Marilyn’s questions point to complex issues. On the one hand, programs like Girls Who Code are designed to address the fieldwide issues that Marilyn learned about at her PD by helping girls spark an interest in computing. This interest might lead more girls to major in CS-related fields, create innovative tech tools, found tech companies, experience economic mobility, and have an impact on society. On the other hand, Marilyn recognized that programs like Girls Who Code might not feel welcoming or relevant to all of her students. Marilyn acknowledged how the diverse groups of boys at her school were not always interested in a coding club framed for girls. And we would add that non-binary and gender non-conforming students might also not feel comfortable in a program called Girls Who Code.

Marilyn’s questions might also prompt us to reflect on the girls at her school. They were alike in some ways, but they also had varying abilities, racial and ethnic identities, language practices, and lived experiences. What kinds of CS learning opportunities might help her reach girls with disabilities? Black and Latine girls? Black and Latine girls with disabilities? Girls who are bi/multilingual? The questions that Marilyn asked about recognizing the diverse identities and needs of her students are thought provoking, especially when teachers, including Marilyn, have limited time, resources, and capacity. Where is the best place to put that energy?

There are also issues related to equity in CS that Marilyn didn’t touch on in her quote. She was inspired to bring CS Ed to her school in response to statistics about a lack of gender diversity in technology industries. Is that the core reason to do CS Ed? Are there other purposes for learning and doing computing that might resonate more deeply with students? Or that might serve students’ communities? Or that might push toward social change?

Marilyn’s ultimate goal is to support her students to realize their potential and thrive, and she thinks that CS Ed is a part of reaching that goal. But she wonders what kinds of changes in policy, curricula, and pedagogy would be needed — not just in her club, but in her school, her district, and even her state — to engage all students and their diverse identities in meaningful and equity-oriented computing education.

CS for All?

Marilyn isn’t the only one with questions about equity in CS Ed. The initial movement to provide CS Ed for all students in the United States, known as Computer Science for All (CSforAll), took off in the 2010s. More than a decade later, educators and policy makers are still grappling with how to make CS Ed more equitable. For years, those working toward equity in CS Ed have focused on providing “access” to the kind of CS Ed that will “make them job-ready on day one,” a goal that President Barack Obama identified at a 2016 Hour of Code event at the White House (Smith, 2016). To meet those and similar goals, hundreds of millions of dollars from the government, private foundations, and industry were committed to broadening participation in computing. This vision worked to help young people from a range of backgrounds learn the kinds of CS skills that would help them join fast-growing and exciting industries.

Responding to these national initiatives, educators across the nation worked hard. They expanded CS course offerings, recruited students to take new courses, and built up after-school programs like Girls Who Code. They spent hours in professional development learning new CS skills, worked to keep up with emergent professional standards, taught new courses like Advanced Placement Computer Science Principles (AP CSP) from the College Board AP program, and integrated CS concepts and skills into other subject areas. They created new CS departments and industry partnerships and advocated for CS graduation mandates. These efforts have made progress toward the broadening participation vision: access to CS classes increased from approximately half a million students in 2013 to 46 million students in 2019, and booming enrollments continue in CS departments across the United States (Code.org, 2020). There is also increased infrastructure for CS Ed and a greater awareness of the importance of CS Ed.

However, CS Ed equity has not yet been fully realized. CS Ed still disproportionately benefits the students who have historically been centered in education: white students, male students, students from affluent backgrounds, and students who attend high-resourced schools. Inequities related to CS Ed, industry, and technology continue to abound. A recent report documented how students with marginalized gender and racial and ethnic identities, multilingual learners, low-income youth, and students with disabilities continue to be excluded at nearly all levels of CS Ed, from K-12 to higher education (100Kin10, 2021). A similar report specifically about New York City Public Schools found that the schools who made the most progress toward CSforAll initiatives were schools who served fewer Black and Latine students (Fancsali et al., 2022).

Some argue that these disparities persist because those working to promote CS for all students simply haven’t found the right combination of funding, courses, policies, and curriculum to truly broaden participation. But the causes of inequity in CS Ed are complicated and multilayered, and they reflect deeper social and structural realities. Schools and districts serving higher proportions of bi/multilingual learners, low-income students, and racially marginalized students are often under resourced. Implementing equitable instruction in content areas like math and literacy in these settings is a struggle in its own right, which often means that CS Ed gets further sidelined. When CS is offered to marginalized groups, it is often presented in culturally irrelevant ways or delivered with negative assumptions about students’ computing abilities.

Cultures of exclusion also exist in higher education settings and tech companies, centering white, middle class, male, nondisabled cultural norms. These settings become unwelcoming and marginalizing for well-trained and qualified CS experts who have identities that are not centered in the CS industry. Even tools produced by the tech industry disproportionately harm marginalized groups through biases embedded in the tools’ algorithms, interfaces, and systems (Benjamin, 2019). Tech industries also negatively impact society at large by polluting our environments, promoting misinformation and labor exploitation, and enabling mass surveillance and new ways to wage war (see Ko et al., 2020; Philip & Sengupta, 2021; Vossoughi & Vakil, 2018). As with tech tools, these industrial impacts also disproportionately affect those from marginalized groups.

Focusing on broadening participation alone can’t address issues of inequity that are deeply rooted in our educational systems, in computing industries, and in wider society. As one CS teacher, Anna, pointed out, it’s often “implicitly assumed that creating better CS education programs [is] the same thing as getting more kids to participate in said programs.” However, getting students to participate in unjust CS programs doesn’t achieve the visions many of us have for a more just world. We argue that access to and transformation of CS industries, CS Ed, and society are needed if we are to advance equity in CS Ed.

What Can Educators Do?

In the face of these challenges and our students’ needs, what can educators do to advance equity in CS Ed?

This question is at the center of this guide. For five years, the authors of this work — a collective of educators, district leaders, educational researchers, students, and other stakeholders in CS Ed — have collaborated to support public school teachers, preparing them to provide K-12 students with meaningful CS learning experiences. (See our Preface and Crawford et al., 2023, for more about us.)

As we’ve engaged in this work, we’ve connected with some incredible agents of change. These include educators who have been named Equity Fellows by the U.S. Computer Science Teachers Association (CSTA) and members of the CSforAll Ingenuity Team in New York City Public Schools.^{[footnote]To learn more about the CSTA Equity Fellows, visit https://csteachers.org/pd-opportunities/equity/. To learn more about the NYCPS Ingenuity Team, visit https://sites.google.com/schools.nyc.gov/cs4all-equity/ig-team/ig-team[/footnote]} We’ve also met many educators making quiet changes in small and practical ways in their classrooms on a daily basis. These educators vary just as their students do. They hold different identities around disability, gender and sexual orientation, and race and ethnicity. They work in urban, suburban, and rural settings with different student populations. They use many languages, teach different content areas, and have different backgrounds in CS.

What all of these teachers have in common is a commitment to advancing equity in CS Ed. They are working to build on the strengths of the students and communities who have been marginalized in computing and in education. They advocate for and promote expansive, just, and ethical kinds of CS and CS Ed. They recognize that equity work requires self-examination and self-awareness and involves building community and coalitions. And these teachers understand that advancing equity in CS Ed is a long-term effort and an ongoing process that is never done — a marathon, not a sprint. It’s hard work, but through learning, action, and connecting with others, these educators have found joy and purpose in their efforts. Recognizing the transformational work that educators across the nation are doing, we highlight a few real stories from their classrooms in Table 1.

Table 1

Meet Some Equity-Focused CS Teachers

Our work with teachers has shown us that educators, working together in community, can and are making a huge difference. Because inequities have been created by humans over time, they can be dismantled by people too. Resource 2, Historical Efforts to Advance Educational Equity, describes some of these examples, which include the 1960s New York City School Boycott, efforts in the 1970s to address the needs of bilingual students and those with disabilities, and contemporary efforts against gun violence in schools. People are also working to bring about change in CS industries. Joy Buolamwini is one contemporary example of someone working to dismantle inequities in technology. Read more about Buolamwini below.

Following the examples of these change agents and others, we too can work to make change in CS Ed and computing fields. Promoting equitable change requires tenacity and nerve. It calls for the stirring up of what Congressman and civil rights activist John Lewis called “good trouble” (see Hayden, 2020). It requires collective action and people who are “coconspirators” against inequity, using their privilege to challenge and undo inequitable status quos (Love, 2019).^{[footnote]Love spells this word without a hyphen.[/footnote]} As U.S. state and federal legislation prohibit attention to diversity, equity, and inclusion in schools (Betts, 2024; Gross, 2022), our collective efforts as CS educators to work toward equity and justice are needed now more than ever.

Our Guide and Values

This guide is designed to support educators who want to advance equity in CS Ed for themselves, their students, and their communities. It will provide you with a foundation and tools to develop a praxis, or mindsets and theory put into action, that can advance equity in CS Ed.

What do we mean by advancing equity in CS Ed? This is a question that we will explore throughout the chapters of this guide. However, the authors of this guide share core values that are important to highlight at the outset. As a collective, we believe that advancing equity begins by acknowledging that inequities in education, in CS, and in CS Ed exist and persist. We recognize that the inequities we live with today are a result of choices made by individuals, groups, and institutions historically. We also acknowledge that injustices are continually reproduced today through systems of oppression, or socially organized patterns of mistreatment, and not solely through the actions of individual people or “bad actors.” These systems create inequities based on social categories like race and ethnicity, class, disability, gender and sexual orientation, religion, and more. Inequities are reproduced by individuals, groups, and institutions in ways that contribute to unjust conditions and outcomes for marginalized individuals and groups. Because these systems are woven into our social life, how we understand ourselves and our students, how we interact, and how we learn are all influenced by inequities, shaping what happens in our schools and classrooms.

We also recognize that we as individuals and groups have the power to resist and change social patterns and norms. For equity to become a sustained reality, we need to think of it not as an object or thing that can be acquired. Instead, equity is an ongoing effort to disrupt inequitable systems and to create dynamic structures that reinforce and replicate equitable ideas, habits, resources, distribution of power, and outcomes. Working toward equity in CS Ed doesn’t happen in isolation. It’s part of a conversation about educational equity more broadly. There’s also not one perfect way to do this work. The work will naturally look different in different communities that have different histories and interests. We may make mistakes along the way, but we can take responsibility for them, learn from them, and move forward. As we know better, we can do better. And what is better or right may look a little different for each teacher, classroom, school, and community.

Many educators, researchers, and scholars are making significant contributions to these efforts. In our own work, we were particularly influenced by the ideas of Zaretta Hammond (2014), Gloria Ladson-Billings (1994, 2021), Gholdy Muhammed (2020, 2023), and Django Paris and H. Sami Alim (2017). Their scholarship centers teaching that honors and incorporates students’ histories, identities, and experiences into instruction to create culturally sustaining pedagogical practices.

We have drawn on the work of these equity-oriented scholars as we have thought about what it means to promote equitable changes in CS Ed. Their ideas have helped us define the futures we want to see, futures that include:

• Access to relevant computing tools and literacies so that learners whose identities have been marginalized in society have what they need to learn and thrive and to contribute to and sustain their communities’ cultural and language practices.
• Equipping all learners with critical consciousness about computing tools, cultures, and industries so that they can work toward the ethical and just transformation of those tools, cultures, and industries.

We also share some principles that guide how we act in service of these goals that might also inspire educators to act. We hope you will notice the following principles in action in the coming chapters:

• We critically examine our own identities and relationships to CS Ed and industry.
• We exercise creative courage to disrupt the status quo. We invite our students to do the same (Anaissie et al., 2021).
• We actively elevate multiple ways of knowing, being, and computing, especially those ways that have been marginalized in and by our systems.
• We support multiple goals, cultural and language practices, and pathways for success, including those not always valued or accepted by our systems.
• We promote all learners’ agency to tinker with, create, and modify computing tools for purposes that matter to them.
• We create supportive CS learning environments where each student has what they need to participate meaningfully.
• We cultivate collaboration within and outside of institutions and together with marginalized communities to dismantle oppressive systems in education, computing, and CS Ed.

We share these values and principles with you as the foundation of this guide. The guide is intended to help you examine and reimagine how you understand yourself, your students, and your teaching. With those new perspectives, you can identify concrete ways to transform what happens in your contexts every day. You will find ways to support all of your students to use computing to meet their personal goals, to reach their potential, and to become change agents for their communities and the CS field.

Revisiting Marilyn’s Story

In reflecting on her efforts as a CS educator, Marilyn expressed very real concerns about how to “build equity without being inequitable” given her students’ diverse backgrounds, identities, interests, and needs. Marilyn’s questions point to the complexity of doing equity work. Marilyn discussed these challenges with her colleagues several times during the summer. During their conversations, Marilyn and her fellow teachers realized that there wasn’t a quick solution. They recognized that these conversations were just the start and that they needed more time to figure out how to “do equity equitably.” They worked to plan time and space for collaboration into the coming school year. They look forward to getting to know their students and making concrete changes that will benefit their classrooms as the new year begins. We’ll follow their thinking about how to best support their students’ needs and work toward equitable outcomes in CS in the chapters that follow. We hope that this book will inspire you to engage in your own conversations about equity in CS like Marilyn and her colleagues.

Reflection Questions:

1. Which pieces of Marilyn’s story resonated with you? What challenges do you face or anticipate facing in your work as a CS educator?
2. What kinds of inequities are you aware of in your teaching settings? In the communities where you and your students live?
3. What values and principles currently shape your work as an educator generally? As an educator in CS specifically? As an equity-oriented educator? How do these align with, differ from, or build on the values and principles that shape this guide?

Takeaways for Practice:

• Review the current state of CS Ed in your setting. Inventory who has access to CS Ed currently, what assets you have to support CS teaching and learning, and what resources you need to work toward equitable CS Ed in your setting.
• Consider which of the seven CS equity principles listed above you would prioritize in your own teaching in the near and long term and how you might center those principles.
• Learn more about some of the diverse leaders in CS and CS Ed by exploring Resource 1. Consider integrating these individuals into your existing lessons to help students recognize themselves in CS.

Glossary

References

100Kin10. (2021). unCommission research summary on the communities most excluded from STEM learning. https://docs.google.com/document/d/1xOgL3AvDkYjyjVTxgxaDUfpUIEC7c0czPUsDSfLhYzE/edit

Anaissie, T., Cary, V., Clifford, D., Malarkey, T., & Wise, S. (2021). Liberatory design: Mindsets and modes to design for equity. Liberatory Design. https://static1.squarespace.com/static/60380011d63f16013f7cc4c2/t/60b698f388fe142f91f6b345/1622579446226/Liberatory Design Deck_June_2021.pdf

Benjamin, R. (2019). Race after technology: Abolitionist tools for the new Jim code (1st ed.). Polity. https://doi.org/10.1093/sf/soz162

Betts, A. (2024, May 23). What to know about state laws that limit or ban D.E.I efforts at colleges. New York Times. https://www.nytimes.com/2024/04/21/us/dei-education-state-laws.html

Buolamwini, J. (2023). Unmasking AI: My mission to protect what is human in a world of machines (1st ed.). Random House.

Code.org. (2020, February 20). Code.org 2019 annual report: The state of K-12 computer science. https://code.org/files/Code.org-Annual-Report-2019.pdf

Crawford, C., Kuyenga, M. A., Talley, L., Mirakhur, Z., & Clark, H. (2023). Organizing for educational equity in computer science: Lessons from New York City’s CS4All initiative. New York City Public Schools.

Fancsali, C., Lee, J., Adair, A., Hill, K., Rivera-Cash, E., & Clough, S. (2022). CS4All: Examining equity in computer science access and participation in NYC schools. NYU Research Alliance. https://steinhardt.nyu.edu/research-alliance/research/cs4all-examining-equity

Gross, T. (2022, February 3). From slavery to socialism, new legislation restricts what teachers can discuss. NPR. https://www.npr.org/2022/02/03/1077878538/legislation-restricts-what-teachers-can-discuss

Hammond, Z. L. (2014). Culturally responsive teaching and the brain: Promoting authentic engagement and rigor among culturally and linguistically diverse students. Corwin.

Hayden, C. D. (2020, July 19). Remembering John Lewis: The power of “good trouble.” Library of Congress. https://blogs.loc.gov/loc/2020/07/remembering-john-lewis-the-power-of-good-trouble/

Ko, A. J., Oleson, A., Ryan, N., Register, Y., Xie, B., Tari, M., … & Loksa, D. (2020). It is time for more critical CS education. Communications of the ACM, 63(11), 31-33. 4:01. https://doi.org/10.1145/3424000

Ladson-Billings, G. (1994). The dreamkeepers: Successful teachers of African American children. Jossey-Bass.

Ladson-Billings, G. (1995). But that’s just good teaching! The case for culturally relevant pedagogy. Theory Into Practice, 34(3), 159-165. https://doi.org/10.1080/00405849509543675

Ladson-Billings, G. (2021). Culturally relevant pedagogy: Asking a different question. Teachers College Press.

Love, B. L. (2019). We want to do more than survive: Abolitionist teaching and the pursuit of educational freedom. Beacon Press.

Muhammad, G. (2020). Cultivating genius: An equity framework for culturally and historically responsive literacy. Scholastic.

Muhammad, G. (2023). Unearthing joy: A guide to culturally and historically responsive curriculum and instruction. Scholastic.

Paris, D., & Alim, H. S. (2017). Culturally sustaining pedagogies: Teaching and learning for justice in a changing world. Teachers College Press.

Philip, T. M., & Sengupta, P. (2021). Theories of learning as theories of society: A contrapuntal approach to expanding disciplinary authenticity in computing. Journal of the Learning Sciences, 30(2), 330-349. https://doi.org/10.1080/10508406.2020.1828089

Smith, M. (2016, January 30). Computer science for all. The White House. https://www.obamawhitehouse.archives.gov/blog/2016/01/30/computer-science-all

Vossoughi, S., & Vakil, S. (2018). Toward what ends? A critical analysis of militarism, equity, and STEM education. In A. I. Ali & T. L. Buenavista (Eds.), Education at war: The fight for students of color in America’s public schools (1st ed., pp. 117–140). Fordham University Press. https://doi.org/10.2307/j.ctt2204pqp

Resource 1: Historical Giants in Computing

Resource 2: Historical Efforts to Advance Educational Equity

Chapter Overview

This chapter considers the idea of diversity and why it matters for computer science (CS) industries and CS education (CS Ed). It defines what diversity is and then explores how diversity (or a lack of diversity) impacts CS industries and CS Ed. The chapter concludes with some implications for what diversity means for CS teachers’ everyday practices in their classrooms with their students.

Chapter Objectives

After reading this chapter, I can:

• Define what diversity is and what diversity is not.
• Explain how diversity is related to (in)equity in CS and CS Ed.
• Recognize why diversity is important in CS and CS Ed.
• Identify strategies to recognize and draw on diversity as a resource in my classroom.

Key Terms:

ableism; culturally sustaining pedagogies; diversity; essentialization; funds of knowledge; gatekeeping; intersectionality; invisible disabilities; marginalized/minoritized identities; opportunity hoarding; othering; tokenism; xenophobia

Marilyn’s Story

In Chapter 1, we met Marilyn, a CS teacher who was grappling with how to equitably include all of her students from different backgrounds in her after-school coding club.^{[footnote]Marilyn is a composite character based on New York City public school teacher Susan Murray and the collective experiences of the authors, teachers, and collaborators of this guide.[/footnote]} Marilyn shared her thoughts:

Marilyn raised real concerns, asking questions that don’t have easy answers. However, Marilyn’s description surfaces something foundational to understanding and working toward equity: the notion of diversity.

Marilyn recognized that her students were different from one another. They had different identities, backgrounds and experiences, interests, talents, and abilities. Marilyn also recognized that because of the “-isms” that shape society (like ableism, classism, racism, etc.), her students could be centered or marginalized in school and in computing based on their differing traits. For example, she acknowledged that her students differed around gender, and girls have been historically underrepresented in computing fields. This reality motivated Marilyn to start her after-school coding club in the first place.

But Marilyn was also aware that if she focused only on girls in her program, not everyone, including boys and gender non-conforming students, would feel comfortable or like they belonged in that space. She wondered about how to reach other students whose identities are underrepresented in computing, like Black and Arab students. Marilyn was aware of the diversity that existed in her classes and her students. And Marilyn recognized how limiting students’ identities to only one or two labels, like gender or race, or grouping them into buckets based on labels and trying to focus on different groups didn’t seem to be an ideal solution. She wondered how she could recognize the diversity of her students in ways that would meet all of their needs.

What Is Diversity?

Diversity comes from recognizing a simple fact: people are different from one another. We define diversity as differences in people’s identities, backgrounds, and perspectives. Most often, diversity is described in terms of social categories like age, disability, gender identity and sexual orientation, educational background, language, national origin, race and ethnicity, religion, and socioeconomic status. All individuals have varied physical features, lived experiences, physical, emotional, and intellectual abilities, language and cultural practices, and so forth. Given this reality, no one person in isolation can be diverse. Instead, diversity describes variation in collectives of individuals with differing identities and backgrounds. We emphasize this definition of diversity as something that applies to a group.

People often think that committing to diversity means making a special effort to reach diverse populations or people, where the term “diverse” stands in for members of marginalized groups, or groups whose social categories are devalued by society. For example, committing to “racial diversity” in CS often involves the unstated reality that most people in CS are racialized as white and implies a focus on recruiting individuals who are racialized in ways that are marginalized by society (e.g., Asian, Black, Latine). Representing a diversity of perspectives and experiences matters, as we will see throughout this chapter. However, when “diversity” is used as a stand-in or euphemism for members of marginalized groups, it becomes a harmful way to suggest that a person deviates from the implicit white, male, English-speaking, nondisabled norm that society has deemed “acceptable.” CS teacher Brandie expanded on this idea:

Rather than using the term as a stand-in for marginalized groups, we can use the word diversity to acknowledge variation among the people in a collective. We should also recognize that within diverse groups, there are people whose identities, backgrounds, and practices are implicitly valued and catered to in learning, professional, and disciplinary spaces more than others. This way of defining diversity helps us avoid treating some groups as “other” and can help us recognize which perspectives might be overrepresented (e.g., white males in CS) and which perspectives are missing.

Valuing diversity also helps us ask questions about the systemic and structural factors that create barriers to a group’s participation (see Chapter 5 for more on how to do this). For example, teachers can reflect on how policies that privilege the use of English in classrooms might create barriers for multilingual students’ participation in CS Ed. They can examine their own implicit biases that lead them to perceive multilingual learners as “less capable” of doing computing. They might design an activity that leverages multilingual learners’ expertise to help students critique the usability of an English-only computing tool. Actions like these help educators intentionally create spaces that elevate marginalized voices into positions with power.

How Is Diversity Related to Inequity?

That we differ from one another along many dimensions is a fact about humanity. However, when those differences get filtered through society’s power hierarchies, diversity becomes closely intertwined with inequity. Hierarchies have been created over time through human activities — historical and cultural processes such as slavery and colonialism — and have become embedded in society’s institutions and structures. These activities transform human differences into markers and labels that are still being used by people and institutions to organize and implicitly “rank” people. These rankings systematically privilege some human characteristics and marginalize others. In education, those with socially privileged traits are often afforded more power because learning spaces and teaching practices tend to be designed for them and have their experiences, goals, languages, and interests in mind. By contrast, those with identities that are marginalized by society often experience learning spaces where their identities and cultural practices are not always welcomed, recognized, or valued.

The relationship between diversity and inequity is evident in many of the “-isms” that pervade society. For every dimension of human difference, there is an associated way that biases tend to reinforce inequity. Differences in ability are filtered through ableism, or an implicit or explicit preference for bodies and minds that are socially constructed as nondisabled, creating prejudice for disability and the oppression of disabled people. Differences in physical appearance and place of origin are filtered through racism and xenophobia, or fear or prejudice against foreigners, which impacts how people move through society. How society perceives one’s age, gender, sexual orientation, linguistic background, socioeconomic class, and the many other facets of our identities and experiences shape how people are included (or not) in different spaces, including CS spaces. At the same time, the identity markers people claim and are assigned are not static, and they do not predetermine people’s experiences. There are many factors that shape whether and how people experience oppression or privilege based on their differences across different contexts.

For example, the collective group of school children in the United States is very linguistically diverse (National Center for Education Statistics, 2024). However, power hierarchies around language filter those differences in different ways. In U.S. schools, speaking English is a privileged trait. Children who speak “standard” English as a home language tend to have more access to social privilege and educational resources. Those who speak other varieties of English like African American Vernacular English or those who speak languages other than English must often adapt and learn the “idealized” version of English to access the same opportunities (Chang-Bacon, 2020). Students’ linguistic expertise in language varieties other than “standard” English” gets overlooked or even penalized in school spaces (Flores & Rosa, 2015). Filtering based on linguistic hierarchies creates inequities that benefit English speakers over speakers of other languages. While these trends manifest at the level of most social institutions and structures (e.g., the medical system, the criminal justice system, the education system), whether or not and how an individual experiences linguistic injustice also depends on their own particular identities, circumstances, experiences, and contexts.

Because everyone has many different identities, the concept of intersectionality is also important in understanding diversity. Intersectionality captures the reality that people experience inequities in ways that are unique to how their identities intersect and overlap. For example, Marcos, a Latine, bilingual English/Spanish-speaking child with a disability would experience oppression related to disability differently than his peer Ethan, a white, monolingual, English-speaking child. Marcos may experience disability as it intersects with racial and linguistic oppression, while Ethan’s experiences with disability may be shaped by racial and linguistic privilege. We examine the role of intersectionality further in Chapter 5.

As we’ll see in future chapters, the drastic inequities that exist in CS and CS Ed often mirror the broader institutionalized and systematic ways that people can be oppressed or privileged based on their differences. How people experience inequities in CS are shaped by the identity markers society has assigned them in different settings and how those markers have been filtered through the social power hierarchies operating in those settings. These realities significantly impact the CS field and students’ experiences in CS classrooms.

Why Does Diversity Matter in CS Industries?

Working toward equity in CS Ed requires understanding why diversity matters. In this section, we consider why diversity is important to the CS industry. We critically examine diversity in the CS industry because many students will be interested in applying their skills and knowledge there and because tech companies play an outsized role in funding and supporting CS Ed. As a result, the industry’s values and track record on diversity matter. We also recognize that promoting diversity in CS industries is not the only reason to care about diversity in CS Ed, and we consider other reasons in the sections that follow.

Diversity in Computing Industries

Although people vary widely, there is a consistent pattern of homogeneity, or sameness, in the CS industry with respect to demographics like class, disability, gender, language, and race. For example, 78% of CS bachelor’s degrees awarded in the United States in 2021 went to men. Of non-international CS degree earners, 81% were white or Asian American (Zweben & Bizot, 2022). These statistics highlight how the CS industry tends to be homogenous in terms of gender and race.

Similarly, privileged communities who hold identities that society has constructed as “normative” (e.g., white, English-speaking, upper class) have historically been afforded preferential access to the tools, capital, and knowledge needed to create computational technologies and to use them for their own ends (see Patitsas et al., 2014, for a gendered example). These groups’ preferential access and power has been maintained in many ways, including through practices like gatekeeping (policies and structures that limit participation in computing for marginalized groups) and opportunity hoarding (processes through which privileged groups control and prevent access to resources for marginalized groups; see Ko, 2024, for a fuller discussion).

The history of CS has translated into the contemporary perception of a “bro” culture in coding and computing: white male coders in jeans and hoodies sitting alone at their computers for long stretches of time. When presented with this description, CS teacher Anjeliqe noted that it was “the exact description that students give you when you ask them what a computer scientist looks like.” Media reflect this perception back to us in ways that emphasize the lack of diversity in the CS field as normal. For example, HBO’s television show Silicon Valley represents CS professionals as stereotypically white, male, college dropouts whose computing expertise will allow them to get rich. These representations subtly broadcast the idea that those who do not look or act like a stereotypical coder do not belong in CS and would find it difficult to fit in and be happy in the CS industry. CS teacher Karime identified how this reality “make[s] the field unwelcoming … [and] extremely unappealing for anyone that doesn’t fit this description.”

The Impact of a Lack of Diversity on Technology

Diversity matters in the CS industry because people vary — so our tech tools and ways of doing computing should too. The sameness in the CS industry, whether real or perceived, shapes which technologies get developed and their impacts on society. The lack of diversity also influences which problems technologies are designed to solve, which communities technologies are developed for, and who sees or wants a future in the CS community. When CS professional communities are homogenous, technological development tends to focus on the needs and concerns of those communities, overlooking the needs, interests, and desires that underrepresented groups have for themselves and their members. Biases associated with the shared identities of computer scientists get embedded into technology, whether by design or inadvertently, adversely impacting communities not represented among creators.

The development of facial recognition technology is an example that illustrates the impact that a lack of diversity has on computing. Computer scientists who developed facial recognition technology often boast about its accuracy, averaging about 90% overall (Najibi, 2020). However, when that data is broken down into different categories based on identity markers, a different story emerges. Facial recognition algorithms are much less accurate at recognizing women and people with darker skin tones. As a result, women of color are recognized even less accurately (Najibi, 2020). The algorithms are most accurate when identifying white male faces — faces most similar to those who created them.

The consequences of these biased algorithms are significant, affecting more than just unlocking your phone (or someone else’s) or getting ahead in airport lines. Facial recognition technology is used by law enforcement to apprehend suspects (Algorithmic Justice League, n.d.). This means that being mistaken for someone else can lead to an unwarranted interaction with police, which could become a permanent part of someone’s criminal record, regardless of whether they’re innocent or not.

Similarly, judges use artificial intelligence (AI)–based recidivism algorithms to determine sentence length for convicted individuals. Recidivism algorithms make inferences based on data from sources like arrest records and demographic information. They are used to predict whether someone charged with a crime may be at “high risk” of committing another crime in the future (Larson et al., 2016; Lee et al., 2019). Researchers have found that these algorithms — and the data they draw on — are racially biased. This bias results in longer sentences for racially minoritized suspects (Angwin et al., 2016). A lack of diversity in those designing technological tools can result in highly consequential and inequitable outcomes for marginalized groups.

The lack of diversity in the tech industry is not the only explanation for these dynamics. They are also influenced by historical and cultural processes that have worked to eliminate diversity and reinforce sameness. For example, some recidivist algorithms may weigh the zip code of where a person lives as part of calculating the probability that they will be a repeat criminal offender. The contemporary racial demographics of zip codes reflect historical redlining policies and current real estate biases that restrict and shape where racially minoritized people live. Many of these realities were established in the United States during the Jim Crow era, after the end of the Civil War, when state and local laws reinforced racial segregation. Scholar Ruha Benjamin names these data points that carry embedded biases as the “outputs of Jim Crow.” She argues how the outputs of Jim Crow become the “inputs of New Jim Code,” creating technologies that continue to perpetuate racist outcomes in the present day (Benjamin, 2019).

While inequitable impacts of technology are complex, a lack of diversity only contributes to these problems. Limited diversity in CS fields means that there are missing and underrepresented perspectives. Centering diversity can bring in perspectives that lead to new ideas, better solutions, and technology that helps everyone. Diversity in CS fields can result in people questioning the technologies that are created, what their purposes are, whom they might help, and why.

At the same time, promoting a diverse workforce within CS fields can only go so far. Many technology companies report diverse hiring practices, but when individuals attempt to raise critical questions or change inequitable company practices, they may be ignored or even fired. In one case, technologist Timnit Gebru was fired from Google because of her work that critiqued how large language models used in AI (including Google’s AI) can spread disinformation (Allyn, 2020; Perrigo, 2022). In another instance, Meta founder Mark Zuckerberg ended certain company practices related to fact checking misinformation and moderating hate speech on products like Facebook, Whatsapp, and Instagram, ignoring the protests from a global community of fact checkers they had hired. The policy change is expected to have adverse impacts especially for LGBTQ people, women, and culturally and racially minoritized groups around the world (International Fact-Checking Network, 2025). Not only must CS industry workers and leaders reflect the diversity of the nation and world, but companies whose products shape the lives of so many must be held accountable to values that reflect the safety, desires, and interests of the diverse collectives who are impacted by them.

Despite these issues, there has been incremental progress that we can celebrate and take inspiration from. Many diverse CS teams have already succeeded in creating more inclusive products, such as voice recognition software that understands speech patterns of people with disabilities, accents, and language varieties (e.g., fluent.ai, n.d.; voiceitt.com, n.d.). Benjamin (2019) provided examples of ways that people have drawn on their unique perspectives and experiences to create tools that resist embedded biases and challenge tech norms. One example is Hyphen-Labs, a team of racially diverse women who work “at the intersection of technology, art, science, and the future” (MIT Open Documentary Lab, n.d.).^{[footnote]Learn more about Hyphen-Labs at https://hyphen-labs.com/[/footnote]} They developed designs for jewelry and clothing that can record police interactions and prevent facial recognition, counteracting some of the tools that disproportionately harm racially minoritized people. Another development team, Brian Clifton, Sam Lavigne, and Francis Tseng, created a White Collar Crime Risk Zones tool to counteracts the anti-Black technology used in crime tracking (Clifton et al., n.d.).^{[footnote]Learn more about White Collar Crime Risk Zones at https://whitecollar.thenewinquiry.com/[/footnote]} Using machine learning, the tool flags city blocks where financial crimes are likely to occur and provides facial recognition programs to identify likely perpetrators (in this case, generally white and male). Their tool flips the script on algorithms used to track crime and surfaces the biases embedded in those systems.

These examples illustrate how technology can be used to actively contest the inequities it often reproduces. However, making this resistance happen requires the industry and the governments that regulate it to not just promote diversity but to empower marginalized people and perspectives. Making space for diverse backgrounds, perspectives, and experiences in CS fields can generate new imaginings that allow us to reform existing systems and to transform inequities into new possibilities and futures (Benjamin, 2024).

Why Does Diversity Matter in CS Ed?

To have diversity in CS industries, we must support diverse groups of students who can see futures for themselves in CS fields. Many students whose identities have been marginalized and who have been excluded from CS Ed have important ideas and perspectives that could empower them and bring essential change to CS. CS educator Tarek captured this connection:

Lack of Student Diversity in CS Ed

Achieving a vision of full and meaningful participation in CS Ed requires addressing barriers to diversity that exist in CS Ed. The homogeneity or sameness that exists in the CS industry is mirrored in CS Ed. Research has shown that students taking CS courses in their K-12 education is a predictor of choosing a STEM major in college (Lee, 2015). However, students do not all have the same access to CS courses. Marginalized students are less likely to attend schools with CS course offerings (Code.org et al., 2022), and not all students see CS as a place where they belong. Marilyn’s concerns at the beginning of this chapter reflect this reality. Marginalized students often experience CS learning environments as unsupportive or irrelevant (Margolis et al., 2017; Ryoo et al., 2020). Research also shows that even when students are good at STEM-related subjects, they may opt out of those course pathways because of social stigma or prejudice (Eccles et al., 2020). The cost-benefit analysis of their choices and interests leads them away from STEM and CS-related paths (DiSalvo et al., 2014; Eccles et al., 2020). These patterns all contribute to limited diversity in CS Ed.

While these statistics and research point to the challenges we face, we can also acknowledge the incremental progress that has been made. In 2017, when the AP CSP exam was first offered, 26.4% of test takers identified as female, and 47.7% identified as Asian, Black, Indigenous, Latine, or Pacific Islander. In 2023, those percentages had increased to 30.9% and 56%, respectively, illustrating progress in increasing participation in CS for students who have historically been marginalized based on gender and race (Code.org, 2025). In 2016, Chicago Public Schools was the first U.S. school district to make CS a graduation requirement, an example of structural and systemic changes that increase access to CS Ed for all students (Chicago Public Schools, 2020).

Lack of Diversity in CS Ed Curriculum

We might also understand the lack of diversity in CS Ed in terms of the topics covered in CS courses and curriculum. Because CS Ed tends to mirror CS industries, the focus of CS Ed also mirrors priorities of CS industries — programming examples used in textbooks may overemphasize commercial applications over public sector, civic, or recreational types of software development. This approach erases the computational practices embedded in non-Western societies (e.g., Indigenous beadwork, hair braiding patterns).

Mainstream CS curricula tend to center white, male, or English-speaking norms. For example, a typical programming assignment might require students to create a program that asks users to input their first and last names and add them to a list or array. However, budding programmers might not recognize the diversity embedded in names as a cultural practice. They might fail to consider things like accents and scripts beyond the Roman alphabet to write names, a need to include maternal and paternal family names, and cultures where family names precede given names in their designs. Without explicitly exploring this diversity as part of the assignment, students may create exclusionary input options. Similarly, textbooks often overlook teaching novice programmers how to use or program multilingual or accessibility features in computing environments, despite the fact that this skill is critical for developing software for broad adoption. A lack of diversity in curriculum topics impacts the kinds of tools that students use, the kinds of CS tools they create, and their understanding of what CS is, who it is for, and what “counts” as successful computing.

Many educators have worked to change this state of affairs by incorporating computing practices and tools grounded in histories and practices of different communities into CS Ed curricula. One resource is the set of Culturally Situated Design Tools (CSDT) developed by CS educators to connect STEM and computing principles to cultural practices like African fractals, Appalachian quilting algorithm, and Native and Indigenous beadwork.^{[footnote]Learn more about Culturally Situated Design Tools at https://csdt.org[/footnote]} There are also many resources that explore the diversity of the CS field that existed historically and continues to exist today but that often gets erased or excluded from CS curriculum (see Chapter 3 for more on erasure). Jean Ryoo, Jane Margolis, and Charis JB’s 2022 graphic novel Power On! is one resource.^{[footnote]Learn more about Power On! at https://www.poweronbook.com[/footnote]} This book emphasizes how diverse computer scientists’ identities and perspectives shaped their work and commitments, leading them to contribute to computing in transformative ways. Teachers can also include examples of historical and contemporary CS creatives who come from backgrounds that reflect their students’ identities. Resource 1 in Chapter 1 provides some historical examples to get started. Other contemporary examples that some of our teachers have used to represent their own students include people like the winners of the Ada Lovelace Award,^{[footnote]Learn more about the Ada Lovelace Award at https://awc-hq.org/ada-lovelace-awards.html[/footnote]} Ayanna Howard,^{[footnote]Learn more about Ayanna Howard at https://engineering.osu.edu/about/office-dean/about-dean-ayanna-howard[/footnote]} Joshua Miele,^{[footnote]Learn more about Joshua Miele at https://www.macfound.org/fellows/class-of-2021/joshua-miele[/footnote]} Angelica Ross,^{[footnote]Learn more about Angelica Ross at https://time.com/collection/closers/6564908/angelica-ross-tech/[/footnote]} and Erin Spiceland.^{[footnote]Learn more about Erin Spiceland at https://github.blog/developer-skills/career-growth/leader-spotlight-erin-spiceland/[/footnote]} Chapter 4 also highlights several activist groups who are using CS to work toward social justice for marginalized groups. These examples offer ways to incorporate reasons for computing into CS curricula that go beyond the commercial purposes that are often prioritized.

CS educator Tarek shared some strategies that he has used to address the lack of diversity in CS curricula:

Through his efforts, Tarek has worked to resist stereotypes of who does (not) belong in CS and to help students see themselves reflected in his CS classroom. Given the importance of diversity for both CS industries and CS Ed, CS educators can work to center diversity as a resource for learning in their classrooms.

How Can CS Educators Center Diversity?

Centering diversity can involve (1) welcoming students who may be excluded from CS spaces; (2) recognizing students’ diversity; and (3) building on and affirming student diversity.

Welcoming Diversity

To welcome students whose identities have been marginalized in CS Ed classrooms, it is important for teachers to investigate why particular groups of students might not be participating in CS learning opportunities and to create welcoming spaces. Marilyn’s dilemma around her Girls Who Code club illustrates the need to create spaces that center cultural practices and values that are not always included in mainstream CS Ed settings. There are several approaches that can help address this need. One approach is to create spaces that prioritize historically marginalized groups. This might look like creating affinity groups where those with an affinity or shared set of values can come together and center their cultural practices, ways of knowing, and experiences. Another way to create welcoming spaces is to center plurality within mainstream spaces using approaches like culturally responsive and sustaining pedagogies. A third approach blends the first two, creating spaces that foster syncretism, or combining different traditions, perspectives, and practices to create something new (see Chapter 14 for more on syncretism in CS Ed).

As an example of what it might look like to welcome diversity in practice, let’s consider Sophie, a fictional teacher of AP CS. Sophie recognized that most of the students in her class were typically white and male. She asked herself why more of her school’s growing population of West African immigrant students weren’t enrolled in the course. Was it a language issue? Were students not satisfying gatekeeping prerequisites? Were competing courses happening at the same time? Were students unaware of the course as an option? Did they feel that they wouldn’t belong or be interested in the course? Many of these reasons could be overlapping and contributing to Sophie’s enrollment patterns. Sophie resolved to stay curious as she worked to understand the issues by talking to the school guidance counselor and students about enrollment.

Recognizing Diversity

Educators can learn to recognize students’ backgrounds and experiences across a range of dimensions and use that understanding to plan and facilitate CS learning activities. Recognizing diversity is harder than it might seem. Even with the best intentions, as we seek to notice variation and difference, we can inadvertently perpetuate assumptions about groups of people, causing harm to students. One way this happens is when we act on incomplete knowledge of how our students differ from ourselves and from each other.

For example, Sophie needed to be careful not to assume that because most of her current students were male and white, they were all the same. Her students had varied motivations for participating in CS and different prior experiences with technology. Sophie couldn’t immediately recognize students who had hidden or undocumented barriers to CS learning. These challenges included things like invisible disabilities, varying language backgrounds, family income, and Internet access at home. Similarly, Sophie did not immediately notice the personal resources or cultural assets her students and their families could contribute to the CS classroom. One of Sophie’s white male students had a reading disability that was exacerbated by the way a particular programming environment displays text on the screen. That same student had a family member with a disability that motivated his participation in CS. As Sophie got to know this student, his goal to develop tools with and for his loved one became a valuable asset for his CS class. Creating diverse and inclusive CS Ed environments requires gathering information about students’ experiences and questioning assumptions about sameness.

Our ability to recognize diversity might be constrained by the categories we use to describe students. Not all differences can be reduced to demographic categories. For example, the identity categories commonly used in U.S. education to label students along racial and ethnic (e.g., Asian American, Black, Latine/Hispanic, Native American or Indigenous) or gender lines (e.g., male, female, non-binary) may be helpful in the aggregate to provide a high-level overview. However, these labels can quickly collapse individual students’ backgrounds, experiences, and interests. We need to be careful not to essentialize, or assume or imply sameness within a group, especially within minoritized and marginalized groups.

Instead of relying on demographic categories to recognize diversity, a teacher like Sophie might seek to understand and build on students’ funds of knowledge, or the bodies of knowledge and experience that students bring with them from their home lives and cultural communities (González et al., 2005). Understanding students’ funds of knowledge requires deeply learning about students’ family and community practices rather than making assumptions about or essentializing students based on demographic labels. For example, one student in Sophie’s school, Dee, shared that their family had funds of knowledge related to hair styling. At home, they were responsible for doing their siblings’ hair, and they spent time learning and observing at the barber shop where their parents worked. Sophie took time to learn more about Dee and their family’s funds of knowledge. She considered the relationship that these caretaking and hairstyling practices had to CS. Sophie also reflected on how everyone in the classroom could learn from the knowledge that Dee brought from their home and family.

Building On and Affirming Diversity

Equipped with knowledge about students and their communities’ differences and strengths, teachers can affirm this diversity through their CS instruction. There are many ways to do this, which will be explored in the chapters that follow (e.g., Chapters 8-17). In this chapter, we’ll focus on Sophie’s attempt to build on Dee’s family’s funds of knowledge in her planning.

A popular resource on the CSDT website has students explore African and African diasporic cornrow braiding patterns in hair and use a block-based coding interface to design their own cornrow patterns.^{[footnote]See the activity at https://csdt.org/culture/cornrowcurves/index.html[/footnote]} Braiding as a cultural practice inherently requires sophisticated computational thinking and is related to Dee’s home practices and funds of knowledge. Sophie reasoned that these activities might help Dee explore CS in the context of their interests while providing opportunities for others to learn about the practices of groups who are different from them and see computing in a new light.

In the process of planning this activity, Sophie needed to take care not to appropriate or oversimplify cornrow braiding, instead treating the practice with respect and care. She first worked to understand her own relationship to cornrow braiding, considering if and how it was something practiced in her own communities and culture. She also identified where cornrow braiding practices originated and researched who practiced them in the past and who practices them today by learning from (and compensating or reciprocating) local experts, reading, and watching media created by and for cornrow braiders. Sophie also considered how different households have different practices related to braiding. Rather than assume that any of her students who were a part of the African diaspora had braiding as a household practice, Sophie explored how different households have different relationships with cornrow braiding and how and why the practice might have been (or might not have been) handed down over generations. She also considered how these practices came about, what they mean in different contexts, and how they are related to computation. She reflected on how these practices play a role in the everyday lives of students whose families carry this expertise and how they demonstrate, share, and pass along braiding as a relational and caregiving practice.

Sophie brought some of the examples she discovered through her research to the classroom for her students to explore. She also asked Dee and Dee’s family members to share their histories and practices related to haircare and cornrow braiding. As students were given opportunities to get inspired by those examples, they were able to experience mirrors of people who reflected back to them aspects of their own identities or experience windows into practices that let them experience other ways of computing (Bishop, 1990). Windows and mirrors can create a new vision of what CS is, who practices it, and for what purposes, promoting cultural awareness and cultural competence for all students, whether or not they are members of groups who have been marginalized in computing.

As she facilitated discussions about the topic, Sophie also worked to avoid tokenizing students. Tokenizing occurs when a single individual is treated as representative of an entire group, such as asking a student with disabilities to speak for all people with disabilities instead of only from their own experience. Because everyone has different funds of knowledge and lived experiences, no single person can speak for an entire group. Teachers may be more likely to inadvertently tokenize students when they ask learners to share expertise that they assume students have based on perceived identities. Instead, teachers can get to know individual students, understand how those students identify themselves, and learn about their personal backgrounds and experiences.

This meant that Sophie avoided singling Dee out to explain cornrow braiding in general as a broad cultural practice. Instead, all students were invited to share specific hair care practices from their families, and Dee shared one example of cornrow braiding. Reflecting on Sophie’s story, CS teacher Christina shared her insights:

As we work to avoid assumptions of sameness, essentialization, and tokenization, we can ensure that the diversity in our classrooms is a resource that truly benefits all.

Revisiting Marilyn’s Story

Diversity is central to the questions Marilyn raised about her after-school coding program. She recognized that her students were different and that while social labels are one way to name those differences, they don’t always help capture the power of diversity. Marilyn ended up using Girls Who Code as her after-school program and acknowledged its limitations as she worked to better center her students’ diverse backgrounds. Her colleague Rebecca described how she navigated this tension in her own context:

Marilyn and Rebecca worked to recognize diversity by deliberately lifting it up in their after-school spaces to make all students feel welcome. This approach can help foster inclusive learning environments in diverse CS classrooms and schools. At the same time, as we’ll see with other teachers throughout the book, sometimes promoting diversity is best achieved through creating affinity spaces specifically for historically marginalized groups so that their experiences can be centered. Both approaches can help navigate the tensions that Marilyn raised and promote equitable teaching and learning.

As we hope this chapter has shown, diversity applies to everyone. We can learn to recognize diversity even in groups that may appear to seem the same on the surface. At the same time, because diversity is often intertwined with inequity, we need to be thoughtful about how we cultivate diversity in ways that make space for and center the perspectives and experiences of those who hold marginalized and minoritized identities. Diversity can become a powerful resource for learning in more equitable and transformational ways.

Reflection Questions:

1. After reading this chapter, what does diversity mean to you? How would you define it? How would you explain the role that diversity plays in CS Ed to someone else?
2. What barriers to diversity have you observed in your own experiences with CS and CS Ed? How might you advocate or work to change some of those barriers in your own setting?
3. What kinds of diversity are present in your CS Ed setting? What aspects of diversity do your students bring that might you not have initially recognized? How do you support all of your heterogeneous students and provide them with opportunities to learn?

Takeaways for Practice:

• Consider the diversity that exists in a CS Ed setting that you are in or will be in. Think about diversity that may be readily apparent and diversity that might be harder to recognize. Create a representation (e.g., collage, mindmap, word cloud) that helps you capture the different kinds of diversity that exist in this setting. Consider how you might be able to use these different perspectives as resources for learning.
• Reflect on how the concept of “funds of knowledge” might apply to your CS Ed setting. Consider the funds of knowledge that students already use and how you could learn more about other practices that students have. Explore ways to incorporate these practices into CS learning experiences.

Glossary

Chapter Overview

This chapter considers how inequities created by social beliefs, structures, and interactions influence computer science (CS) and CS education (CS Ed). It explores some of the historical and contemporary inequities that shape CS and CS Ed. The chapter focuses specifically on inequities that happen through the unjust distribution of CS resources and CS Ed learning opportunities, exclusion from CS and CS Ed, deficit narratives about marginalized groups in CS and CS Ed, erasure and a narrowing of what “counts” as CS and CS Ed, and embedded bias and the unjust impacts of technology on marginalized groups.

Chapter Objectives

After reading this chapter, I can:

• Describe inequities that shape CS and CS Ed.
• Identify how inequities impact CS students and CS teaching and learning.

Key Terms:

bias(es); deficit narratives; dysgraphia; erasure; exclusion; gatekeeping; inequity; intersectionality; marginalized/minoritized identities

Ms. Morales’ Story

Working toward equity in CS and CS Ed requires an understanding of the challenges created by the inequities that exist and persist in the industry and in classrooms, influencing what happens from day to day. Ms. Morales, an elementary CS teacher, recognizes some of the inequities that she and her students face and is working hard to change them.^{[footnote]Ms. Morales’ experiences are shared with permission.[/footnote]}

Ms. Morales is a New York City–based K-8 public school teacher involved in an equity-focused CS professional development (PD) community. Different experiences and aspects of Ms. Morales’ identity have shaped how she engages in equity work. When asked to describe herself during an interview with the authors of this guide, Ms. Morales named some of the identities she holds, including that of CS teacher, artist, and stepmother. She shared that she has Puerto Rican and Chinese heritage and speaks English and conversational Spanish with her family. She also described how “when I was younger, I was dealing with mild dysgraphia in school and helping my brother who has hearing impairments.” Ms. Morales’ background shaped her desire to teach, and an early interest in technology eventually led her to become a CS teacher.

Ms. Morales also shared some of the issues that she needs to address as a CS teacher. Those challenges include things like:

• meeting the needs of her students from different cultural and linguistic backgrounds,
• supporting her students with disabilities,
• helping students feel like they belong in CS Ed,
• developing her own CS skills to support her students,
• making sure that all of the students she services have CS learning opportunities, and
• having access to the technology (working computers, wireless internet access, etc.) needed to teach CS.

Ms. Morales can address some of these problems within her own classroom and in collaboration with educators at her school. Other problems are more complex and tied to broader systems of inequity. These problems require us to organize collectives and build power and resources to work toward change.

Inequities in CS Industry and CS Ed

Ms. Morales’ concerns represent inequities that impact CS students and teachers across the country. Many of them fall into five categories: (1) the unjust distribution of CS resources and learning opportunities; (2) exclusion from CS; (3) deficit narratives about marginalized groups; (4) erasure and a narrowing of what “counts” as valuable knowledge and practices; and (5) embedded biases and unjust impacts of technology. We look at the historical roots of these inequities and how they continue in CS industry and CS Ed today. While we break them out into separate groups, it’s important to recognize that inequities are intertwined and often overlap, as the examples that follow illustrate.

Unjust Distribution of Resources

One foundational inequity is the reality that access to resources that facilitate CS learning are not equitably distributed in U.S. society or across U.S. schools. Resources include things like technological tools, rigorous CS instruction, and well-qualified teachers. Not all students have the same access to the resources needed to learn CS.

Schools with large populations of racially marginalized and low-income students tend to have more limited access to technology (like computers, tablets, and modems) and the programs and infrastructure needed to do computing (like websites and apps, software, internet connections, and power; Blikstein, 2018). Historically, only school districts that served high-income students had the resources to spend on new technology. School districts serving low-income and racially marginalized students could not afford the high costs of computers (Sutton, 1991). Today, while most households and schools have access to devices, many groups lack access to broadband internet connectivity (King et al., 2022). Students might be “smartphone-only” internet users, because these tools tend to be less expensive than other computing devices (Pew Research Center, 2024). Smartphones lend themselves well to entertainment, information seeking, taking and sharing photos and videos, and communication. However, many tasks valued in school, like extended research and writing tasks, web publishing, and coding and programming are more difficult to accomplish on a smartphone. These realities demonstrate how societal hierarchies contribute to an unjust and inequitable distribution of and access to the technological resources needed to engage in computing.

Resources related to rigorous CS instruction are also inequitably distributed. When computers started appearing in classrooms in the 1980s and 1990s, their use was often tied to racially constructed norms of behavior that favored students racialized as white. These students were perceived as “better behaved” and had more opportunities to use computers (Arias, 1990; Sutton, 1991). This trend continues today. Students who are perceived as “struggling” or as “troublemakers” may end up being tracked on remediation pathways, giving them fewer chances to take electives like CS. Even in schools where all students have opportunities to take courses related to technology, middle- and upper-class white students are more likely to use computers for activities like programming. By contrast, lower-income and racially marginalized students are more likely to use computers for drill and practice (Margolis et al., 2008). This distinction is important, as it highlights the difference between simply using computers and actually engaging in practices of computing.

Lack of access to well-prepared CS educators is another example of inequitable distribution of resources. Students from historically marginalized groups are more likely to attend elementary schools with fewer CS Ed opportunities, and a recent study found that only 8% of low-income schools offered the AP Computer Science course compared to 37% of high-income schools (Code.org et al., 2022). This could be in part from a lack of teachers who are qualified to teach CS. STEM teacher J. Lauren reflected on the impact that the unjust distribution of resources has on CS education:

CS teachers need to be aware of the different ways that unjust distribution of resources can impact students. Educators may perpetuate inequity if they assume that all students have access to things like a computer or internet. Karime, a CS teacher, shared an example of how this plays out at school:

These examples illustrate how the unjust distribution of resources, including access to hardware and software, rigorous CS learning experiences, and well-qualified CS teachers, contributes to inequities in CS Ed.

Exclusion

At Ms. Morales’ school, CS learning experiences were offered mostly to 6th through 8th graders because of scheduling issues and misconceptions about what Computer Science for All was. How to structure things to achieve the “for all” goal was a challenge. Ms. Morales was often assigned more middle school classes than elementary classes and did not have enough time in her schedule to reach all the grades. These factors contributed to students in younger grades not consistently receiving CS instruction and feeling excluded from CS. The situation at Ms. Morales’ school shows how inequity often persists because of constraints that limit what is possible in a given space and time in tangible ways. It takes collective and intentional efforts to find creative solutions to overcome these challenges.

Nevertheless, in many cases, exclusion as a form of inequity is and has been built into the social fabric of CS. Exclusion can often be recognized by a lack of diversity and representation in CS Ed and CS fields. For example, those with certain identities may have easier access to CS courses, labs, and jobs than others who are excluded from those opportunities. Exclusion operates at two levels: an external level of oppression, where individuals may be kept from opportunities to participate in CS; and a psychological or emotional level of internalized oppression, where individuals may feel excluded and unwelcome in a space even though they are physically present.

External exclusion is often reproduced through practices like gatekeeping, or institutional systems and policies that control who gets to participate in opportunities and who has access to resources. For example, course policies in U.S. school systems may push students with marginalized identities onto an academic track that prevents them from enrolling in CS courses (Margolis et al., 2008). This gatekeeping in CS Ed also impacts the field. Keeping high schoolers from exploring CS in K-12 schooling may prevent them from choosing CS-related college majors or pursuing CS careers.

Exclusion also happens implicitly. Society and its institutions have invisibilized norms, policies, and practices that send messages about who can or should be involved in computing. For example, Ms. Morales’ teaching schedule seemed to be aimed toward the upper elementary and middle school grades, which, whether intentional or not, perpetuated a notion of not needing to provide coding or technology opportunities to younger students. This form of gatekeeping limits young children’s CS opportunities despite research that shows the benefits of teaching coding skills and CS concepts as a form of literacy through both “unplugged” activities and age-friendly tech tools (e.g., Bers, 2019; Wohl et al., 2015). Advocating for other teachers to integrate CS into their practice and have access to CS resources that they could use within their existing curriculum were some of the ways that Ms. Morales worked to include young children in CS at her school.

Exclusion and gatekeeping have persisted since the earliest days of the field of CS.^{[footnote]To learn more about the history of CS, see the book Critically Conscious Computing (Ko et al., 2024); https://criticallyconsciouscomputing.org/[/footnote]} Backus (1980) described how early on, the CS field developed a culture of “priesthood,” where access to the power of digital computers was restricted to a chosen few. He described this priesthood as a fraternity of members selected because of “a colorful personality [or] … an extraordinary feat of coding … [instead of] for intellectual insight” (Backus, 1980, p. 127). These original programmers, generally white males who held social power and privilege, prided themselves on being a part of this select group. They resisted efforts to “make programming so easy that anyone could do it” (Backus, 1980, p. 128).

This resistance led to exclusion and the discrediting of work done by individuals who held marginalized identities. The differences between how early computer scientists Alexandra Forsythe and her husband George were treated illustrate this. Both Alexandra and George made significant contributions to the CS field. Alexandra wrote the first CS textbook (Forsythe et al., 1969), and George coined the term “computer science” and helped found the Department of Computer Science at Stanford University. Alexandra and George both began as Ph.D. students at Brown University. While George graduated with his Ph.D., a dean canceled Alexandra’s fellowship because, as Alexandra explained, “he [the dean] didn’t think I properly stayed on the sidelines like a woman should do” (Forsythe, 1979, p. 9). Despite the gatekeeping that prevented Alexandra from earning her doctoral degree, she went on to teach at Vassar College and eventually at Stanford alongside her husband.

Unfortunately, exclusion persists in CS industries and CS Ed today. Recent statistics illustrate how exclusion in CS impacts marginalized groups (100Kin10.org, 2021):

These statistics highlight how exclusion in CS and CS Ed occurs for those with socially marginalized identities around class, disability, gender, language, and race. But the data in the report did not look at how individuals who hold overlapping marginalized identities are excluded. Intersectionality (explored further in Chapter 5) helps us understand how those with multiply marginalized identities experience inequity at the intersections of their exclusion. While the data identify Black people and women as being excluded from CS, it does not consider how Black women are uniquely impacted because their identities lie at the intersections of being Black and being female. Similarly, the report noted that data often wasn’t even available to understand many groups’ participation in CS. For example, there was no data on non-binary students and employees, limited data on those with disabilities, and no data on multilingual learners and employees beyond the PK-12 school system. The fact that data for these groups wasn’t even collected emphasizes how exclusion continues to persist in CS and CS Ed.

Deficit Narratives About Marginalized Groups

Ms. Morales observed that many of the adults around her had a “mindset that kids can’t grasp computing at a young age.” But Ms. Morales resisted this story about her students. She knew it wasn’t true from her own experience. Observing her students after the COVID-19 experience, Ms. Morales recognized that even students in kindergarten and first grade “had experiences navigating websites and gaining new [computing] skills.” In identifying the incorrect assumptions she was hearing about her students, Ms. Morales was noticing another common inequity in CS and CS Ed: deficit narratives. In this case, those narratives were myths about young learners’ potential to do CS that created inequitable access to CS learning opportunities at her school.

Deficit narratives are broadly held beliefs, including stereotypes, that position groups of people as deficient or lacking in some way (Louie et al., 2021; Steele, 2011). In Ms. Morales’ school, young children were positioned as lacking the skills or ability to engage meaningfully in computing. Deficit narratives often show up as “common sense” statements like “kids can’t grasp computing at a young age.”^{[footnote]When naming something as “common sense,” we align with scholars who have pointed out that what is often considered common sense is neither common nor sensical (Fairclough, 2014; Garfinkel, 1967).[/footnote]} These statements make assumptions about the abilities of a group or blame individuals instead of the systems around them that reproduce inequities (Philip, 2011).

Deficit narratives might sound like, “Women just aren’t naturally as good at math as men,” or, “Students of color just aren’t interested in CS.”^{[footnote]This deficit narrative is also problematic because it collapses the different experiences of racially marginalized people into an overly broad category of “students of color” and fails to consider individual experiences.[/footnote]} What makes deficit narratives problematic is that they aren’t based in truth. Women can be just as successful in math as men (Steele, 2011), and studies have found that Black and Hispanic students are more likely to be interested in CS coursework than their white peers (Gallup, 2020).^{[footnote]We use Hispanic here to match the term used in the original source. See On Terminology for a full discussion of terms used in the guide.[/footnote]} Deficit narratives come out of assumptions about groups of people who differ in some way from what has been constructed as normal (and implicitly, the “ideal”) by society, not out of what is true. In the United States, society positions identities like white, male, upper-middle class, English-speaking, cis-gender, and heterosexual, among others as the “norm.” Individuals and groups who differ from these norms are positioned by society as lacking in some way, and the narratives told about them reproduce the social hierarchies that perpetuate inequity.

Deficit narratives about marginalized groups are embedded into the policies and practices of U.S. education in general. Historically, schooling was used as a tool to assimilate immigrant groups, to “civilize” Indigenous peoples, and to segregate Black people.^{[footnote]U.S. public schooling was first founded by African Americans following their emancipation from enslavement and reflected their deep commitment to education. Segregation policies then worked to maintain underfunding in schools for Black and other marginalized students. See Anderson (1988) for a full discussion.[/footnote]} Deficit thinking about Black, Latine, low-income, immigrant, and other minoritized children persists in education today. Educators often offer deficit beliefs as rationales for how schools fail racially marginalized youth. These narratives include statements like, “the parents just don’t care, these children don’t have enough exposure/experiences, these children aren’t ready for school, their families don’t value education” and so on (Ladson-Billings, 2007, p. 318). Again, these narratives are not based in reality. Recent research shows that Black and Hispanic caregivers are actually more likely to value CS Ed and to recognize the need for CS in future careers than white caregivers (Gallup, 2020). However, deficit-based explanations can lead educators and institutions to lower expectations for marginalized youth, blaming students and families rather than the systems that underserve them.

Those lowered expectations often result in limited meaningful CS learning opportunities for low-income youth and students with marginalized identities. An examination of three different schools in Los Angeles showed how the forces that reproduced inequity went beyond the availability of technology and CS courses (Margolis et al., 2008). Low expectations were set for racially marginalized students regardless of whether they attended a school where a majority of the student body held racially marginalized identities or a school where they were integrated with white, upper-middle class students. School tracking policies funneled low-income and racially minoritized students into basic computing classes, while students who came from the most prepared, technologically equipped households were encouraged to take advanced CS coursework. The researchers concluded that “technology has not been the great equalizer because schools are providing different learning opportunities, and these opportunities vary according to the racial and socioeconomic demographics of the students” (Margolis et al., 2008, p. 134). More than a decade after that research, concerns still exist about “the unequal presence of CS in public schools, the quality of instruction, and the educators’ and counselors’ unconscious bias regarding who is ‘suited’ to take CS classes” (Blikstein, 2018, p. 34).

Ms. Morales appreciated arguments about the need for young children to get off screens and into settings where they play and interact with each other. But she had also read about the benefits of having students explore computational thinking through “unplugged activities” that don’t use technology, having young learners code digital stories using age-appropriate tools like Scratch Jr. and even having them engage in critical conversations about tech tools in their own lives (Bers, 2019; Wohl et al., 2015). Ms. Morales recognized that having moments of offline activities that reinforce key skills are important in all core subjects, including CS. She hoped to resist the deficit narratives that framed her young students as less capable at computing.

Erasure and Narrowing What “Counts” as Valuable

Another concern that Ms. Morales identified in her work as a CS educator was how to best include her students’ different backgrounds and meet their different needs. Ms. Morales’ students typically come from many different countries: Albania, Georgia, Honduras, Mexico, Russia, Turkey, and Uzbekistan, among others. Her students speak a range of languages, bring with them a variety of cultural experiences and practices, and have diverse abilities. Ms. Morales described how she wants her students to “be very comfortable” sharing and participating in class so that they feel like they belong. One challenge for Ms. Morales was that only a few coding websites (e.g., code.org and Scratch[footnote]Visit https://code.org and https://scratch.mit.edu/ to learn more.[/footnote]) provide multiple languages for students to learn from. Given her students’ diverse language abilities, this meant that many resources that Ms. Morales might use presented challenges for her students from the very beginning. She recognized that the CS curriculum doesn’t always center or make space for her students’ different languages, experiences, and interests.

The lack of relevant curriculum for Ms. Morales’ diverse students is part of a broader inequity that comes from a narrowing within CS and CS Ed of what kinds of knowledge and computing “count” as valuable. The computational knowledge that is valued has typically been determined by people who hold socially powerful and privileged identities. Yet those who have historically been excluded also have rich knowledge that can contribute to and (re)shape the CS industry and CS Ed. Gaskins (2021) emphasized that although many creative “innovations [are] produced by ethnic groups,” these contributions “are often overlooked” (p. 5). The limited recognition of the knowledge, practices, and contributions of marginalized and minoritized people often remains unacknowledged through a process known as erasure. Erasure refers to efforts that render invisible the presence and labor of minoritized and oppressed groups, contributing to a narrow view of what is valued in CS and CS Ed. Below, we share some examples of creative innovations that people marginalized based on their race and gender identities have contributed to the field, despite efforts to erase their contributions.

One historical example appears in the experiences of Katherine Johnson,^{[footnote]Learn more about Katherine Johnson at https://www.nasa.gov/centers-and-facilities/langley/katherine-johnson-biography/[/footnote]} Dorothy Vaughan,^{[footnote]Learn more about Dorothy Vaughan at https://www.nasa.gov/people/dorothy-vaughan/[/footnote]} and Mary Jackson,^{[footnote]Learn more about Mary Jackson at https://www.nasa.gov/people/mary-w-jackson-biography/[/footnote]} often known as the “Hidden Figures.”^{[footnote]Their story was told in Margot Lee Shetterly’s 2016 book, Hidden Figures: The American Dream and the Untold Story of the Black Women Mathematicians Who Helped Win the Space Race, and the 2016 film based on Shetterly’s book.[/footnote]} These three Black women worked as human computers for NASA in the 1960s (see Shetterly, 2016). Their mathematical and computing expertise were central to supporting major innovations in space exploration and rocketry. Yet the women faced workplace discrimination and racial segregation throughout their employment. Their intellectual contributions were discredited and ignored for many years until they were finally recognized as mathematicians by NASA. Similar histories shaped the development of artificial intelligence (AI). Six women (Frances Bilas, Betty Jean Jennings, Ruth Lichterman, Kathleen McNulty, Elizabeth Snyder, and Marlyn Wescoff) were trained as human programmers for one of the first electronic digital computers. Despite their mathematical expertise and the computational skills needed for the job, the women’s work was framed as “clerical” work, and they received little credit (Schwartz, 2019).

Another stark example of erasure comes from the early days of CS. The Fairchild Semiconductor company was an important early influence in Silicon Valley. The company established a manufacturing plant in Shiprock, New Mexico, to utilize the skills of Navajo women. These women’s traditional knowledge of weaving and their handiwork skills proved essential to laying out computer circuitry. However, the Navajo women’s labor and expertise were never treated as an important intellectual contribution to CS. Instead, their work was labeled as a “labor of love” that reinforced Western stereotypes of Indigenous women as docile and their skills were reduced to simply having “nimble fingers” (Nakamura, 2014). The Fairchild company eventually called their Navajo collaboration a failure, although they continued to use techniques perfected by the Navajo women. Their decisions illustrate processes of erasure: they extracted the Indigenous knowledge held by the Navajo women; disconnected that knowledge from those women, their labor, and their cultural practices; and then erased the history of the Navajo influence on circuitry entirely.

Erasure and the narrowing of what counts as valuable in CS continue in CS Ed today. As Ms. Morales noticed, many CS curricula are narrow, focusing on specific sets of skills like knowing the syntax of particular programming languages or, for younger students, doing coding puzzles. This emphasis means that CS courses tend to be taught as if the code on screens, the people behind the screens, and the screens themselves were politically neutral, which is never the case (Benjamin, 2019). As a result, CS courses fail to engage students in exploring biases that are embedded in technology (Noble, 2018). CS Ed can also continue the history of erasure when curricula exclude people like the Hidden Figures or the Navajo women described above. Students often have limited opportunities to deeply engage with the worlds around their technology or the worlds they create through their tech. When students are rarely asked to confront injustices and be agents of change, disrupting inequity by broadening what might count as valuable computing is limited.

Embedded Bias and Unjust Impacts of Technology

As Ms. Morales was talking to her colleague Ms. Kors, they named another inequity they deal with as CS teachers — recognizing biases embedded in technology. Ms. Kors shared an experience from her middle school class that illustrated this problem. She had asked her students to produce a Scratch project that shared a family story. One of her students, John, had lived most of his life in eastern Africa and was a recent arrival to the United States. He decided that he wanted to add a picture to his project to represent his mother — a Black woman who wears traditional Eritrean dress. John used Google Images to search for a picture. When he typed “woman” into the search bar, John and Ms. Kors noticed that almost all of the women in the images that came up were young, white, and wearing Western outfits. Ms. Kors shared this example with Ms. Morales to illustrate how the biases (prejudice in favor of or against a group) embedded in technologies and the negative impacts of technology can disproportionately affect minoritized and marginalized groups, including their CS students (see Vogel, 2020, for more on John and Ms. Kors’ experience).

There are many reasons to do CS, and these reasons differ across cultures. In many instances in the United States, CS has been used to advance military and law enforcement goals and has been linked to consumer capitalist purposes. Computing industries tend to focus on solving problems faced by white, male, middle-class/wealthy people (Vossoughi & Vakil, 2018). As a result, the interests of those groups become embedded as biases in algorithms, interfaces, and systems that make up the computing tools in our world, causing harm to marginalized groups.

Biases have been embedded into technology since the development of the CS field began. The early “priesthood” of male computer scientists programmed in binary, a language of 0s and 1s that is compatible with the on/off switches of circuit boards. As the field grew, computer scientists continued to code in binary as a way to keep computing knowledge in the hands of a few (Backus, 1980). Over time, fluency in binary faded and other forms of in-group/out-group boundaries evolved. For example, students at many schools with computing programs developed “hacker” cultures and worked to create codes of ethics that sought to counter traditional militaristic and capitalistic objectives, including making software open to freely share and modify (Vadén & Stallman, 2002). Yet, even though this hacker culture was intended to open up access to computing, it often created new ways to exclude people, notably women (Steinmetz et al., 2019).

Many efforts to disrupt these embedded biases came from people marginalized in the CS field. Women like Kathleen Booth and Grace Hopper tried to create more accessible ways to program. Booth invented early assembly language (programs composed of mnemonic letters and digital numbers) that humans could read more easily than machine language (strings of binary digits). Hopper invented the first programming language that used elements of English grammar and vocabulary to further simplify programming. While these efforts still reproduced embedded biases that favor English as a dominant computing language, Booth, Hopper, and others shaped the trajectory of CS in ways that led to the creation of high-level, more user-friendly programming languages.

Many of the tools and tech created and used today are treated as neutral and benign, despite biases that are embedded into their designs that make them anything but neutral. Scholar Ruha Benjamin named the racism that is embedded into digital technologies the “New Jim Code,” referencing the Jim Crow segregation policies that existed in the United States from 1877 through the 1950s (Benjamin, 2019). Ms. Kors and John discovered these racial biases in the search algorithms and data sets they used trying to find a picture to represent John’s mother. Their experience echoes similar research by scholar Safiya Noble (2018) who found that biases in Google search engine algorithms perpetuated the hypervisibility and hypersexualization of Black women that have been historical realities in the United States. Other examples of embedded biases in technology that lead to harm of individuals and communities include the following:

• Social media algorithms that signal-boost racist and sexist ideologies in advance of elections (Guess et al., 2023).
• Voice recognition software that frequently incorrectly processes language from people who speak with accents that deviate from a standard (Paul, 2017).
• Cryptocurrency mining operations that emit carbon dioxide at the same rate as entire countries. This results in environmental impacts that especially harm low-income and racialized communities (Mahoney, 2024; United Nations University, 2023).
• Body scanners used by airport security that have disproportionately flagged trans individuals for additional screening (Costanza-Chock, 2020).
• Police departments that have used and mis-used facial recognition software in ways that have surfaced major privacy violations and racial profiling errors. These violations have in turn led to police violence against innocent people and false imprisonment (Najibi, 2020).
• Content moderation to develop AI that has come at the expense of underpaid and exploitative labor (Data Workers Inquiry, 2024; Perrigo, 2023).

These realities make it clear that to work toward equitable outcomes in CS and CS Ed, we need definitions of equity that prepare us to resist or dismantle unjust technology. We need definitions that reimagine the purposes of technology and how it is created and ensure that the impacts of technology are more just.

Revisiting Ms. Morales’ Story

In their PD community, Ms. Morales and her colleagues grappled with the different inequities that we’ve considered here: the unjust distribution of CS resources; exclusion from CS; deficit narratives about marginalized groups in CS; erasure and a narrowing of what counts as CS; and embedded biases and the unjust impacts of technology. Recognizing the weight of what they and their students faced in their CS classrooms felt heavy. Yet Ms. Morales and her colleagues took strength from their relationships with each other. They were creative and dedicated teachers, and while they would not be able to solve all of these issues at once, they were committed to doing something to bring about changes within their communities. In Chapter 4, we’ll dive deeper into the work of their equity-focused PD community and explore how they developed definitions of equity that could help resist the inequities they were seeing.

Reflection Questions:

1. Which inequities discussed in this chapter exist in your settings? The inequities considered here are an incomplete list. Are there other patterns of inequity that are apparent in your CS spaces?
2. What have you noticed about the relationship between equity and inequity in your work? How do the ways that people define equity impact the problems and inequities they are working to solve?

Takeaways for Practice:

• Analyze your CS Ed context through the lenses of the inequities discussed in this chapter:
  • Unjust Distribution of Resources: Evaluate the CS resources that are available. What do students have access to (or not)? How are they invited to engage in computing instead of simply “using computers”? What access to well-prepared CS educators do they have?
  • Exclusion: Evaluate the CS opportunities that are available. Who is included? Who is not present? How welcoming are those spaces to students with different marginalized and minoritized identities?
  • Deficit Narratives: Listen to the conversations around you. What do you notice about how students are discussed? Is the focus on students’ strengths and contributions or on what students are missing and lack? You may also want to analyze a school or district policy to see if/how deficit narratives are institutionalized in your setting.
  • Erasure: Evaluate your curriculum. Are there perspectives, voices, or identities that have been erased? Consider some ways you might include them and expand what counts as valuable in your space. The resource Historical Giants in Computing from Chapter 1 may be a helpful starting point.
  • Embedded Bias: Think about the different tech tools you use in your classroom. What kinds of biases might be embedded in these tools? How could you help students recognize these biases? What can you do as a CS Ed instructor to help students navigate the biases and create tools that challenge them?

Glossary

References

100Kin10. (2021). unCommission research summary on the communities most excluded from STEM learning. https://docs.google.com/document/d/1xOgL3AvDkYjyjVTxgxaDUfpUIEC7c0czPUsDSfLhYzE/edit

Anderson, J. D. (1988). The education of Blacks in the South, 1860-1935. University of North Carolina Press.

Arias, M. B. (1990). Computer access for Hispanic secondary students. In C. J. Faltis & R. A. DeVillar (Eds.), Language minority students and computers (pp. 243-256). The Haworth. https://doi.org/10.1300/J025v07n01_12

Backus, J. (1980). Programming in America in the 1950s — Some personal impressions. In N. Metropolis, J. Howlett, & G. C. Rota (Eds.), A History of Computing in the Twentieth Century (pp. 125-135). Academic Press. https://doi.org/10.1016/B978-0-12-491650-0.50017-4

Benjamin, R. (2019). Race after technology: Abolitionist tools for the new Jim code (1st ed.). Polity.

Bers, M. U. (2019). Coding as another language: A pedagogical approach for teaching computer science in early childhood. Journal of Computers in Education, 6, 499-528. https://doi.org/10.1007/s40692-019-00147-3

Black, C., Cerdeña, J. P., & Spearman-McCarthy, E. V. (2023). I am not your minority. Lancet Regional Health Americas, 19. https://doi.org/10.1016/j.lana.2023.100464

Blikstein, P. (2018). Pre-college computer science education: A survey of the field. Google LLC. https://services.google.com/fh/files/misc/pre-college-computer-science-education-report.pdf

Code.org, CSTA, & ECEP Alliance (2022). 2022 State of Computer Science Education: Understanding Our National Imperative. https://advocacy.code.org/stateofcs

Collins, P. H. (2019). Intersectionality as critical social theory. Duke University Press.

Costanza-Chock, S. (2020). Design justice: Community-led practices to build the worlds we need. MIT Press. https://doi.org/10.7551/mitpress/12255.001.0001

Crenshaw, K. (1991). Mapping the margins: Intersectionality, identity politics, and violence against women of color. Stanford Law Review, 43(6), 1241-1299. https://doi.org/10.2307/1229039

Data Workers Inquiry. (2024). https://data-workers.org/

Fairclough, N. (2014). Language and power (3rd ed.). Routledge. https://doi.org/10.4324/9781315838250

Flores, N., & Rosa, J. (2015). Undoing appropriateness: Raciolinguistic ideologies and language diversity in education. Harvard Educational Review, 85(2), 149-171. https://doi.org/10.17763/0017-8055.85.2.149

Forsythe, A. (1979, 16 May). An interview with Alexandra Forsythe [Interview]. Charles Babbage Institute, University of Minnesota. https://conservancy.umn.edu/server/api/core/bitstreams/563c9e36-1ecd-47a8-abfe-4204ec0ea11d/content

Forsythe, A. I., Keenan, T., Organic, E., Sternberg, W. (1969). Computer science: A first course (1st ed.). Wiley.

Gallup, Inc. (2020). Current perspectives and continuing challenges in computer science education in U.S. K-12 schools. https://services.google.com/fh/files/misc/computer-science-education-in-us-k12schools-2020-report.pdf

Gaskins, N. R. (2021). Techno-vernacular creativity and innovation: Culturally relevant making inside and outside of the classroom. MIT Press. https://doi.org/10.7551/mitpress/12379.001.0001

Garfinkel, H. (1967). Studies in ethnomethodology. Polity Press.

Guess, A. M., Malhotra, N., Pan, J., Barberá, P., Alcott, H., Brown, T., Crespo-Tenorio, A., Dimmery, D., Freelon, D., Gentzkow, M., González-Bailón, S., Kennedy, E., Kim, Y. M., Lazer, D., Moehler, D., Nyhan, B., Rivera, C. V., Thomas, D. R., Thorson, E., … Tucker, J. A. (2023). How do social media feed algorithms affect attitudes and behavior in an election campaign. Science, 381(6656), 398-404. http://doi.org/10.1126/science.abp9364

King, H., Martin, M., McArdle, S., Goldberg, R., & DeSalvo, B. (2022, May 13). New digital equity act population viewer shows broadband access and demographic characteristics. United States Census Bureau. https://www.census.gov/library/stories/2022/05/mapping-digital-equity-in-every-state.html

Ko, A. J., Beitlers, A., Wortzman, B., Davidson, M., Oleson, A., Kirdani-Ryan, M., Druga, S., & Everson, J. (2024). Critically conscious computing: Methods for secondary education. https://criticallyconsciouscomputing.org

Ko, A. J., Oleson, A., Ryan, N., Register, Y., Xie, B., Tari, M., Davidson, M., Druga, S., & Loksa, D. (2020). It is time for more critical CS education. Communications of the ACM, 63(11), 31-33. 4:01 https://doi.org/10.1145/3424000

Ladson-Billings, G. (2007). Pushing past the achievement gap: An essay on the language of deficit. Journal of Negro Education, 76(3), 316-323.

Louie, N., Adiredja, A. P., & Jessup, N. (2021). Teacher noticing from a sociopolitical perspective: The FAIR framework for anti-deficit noticing. ZDM-Mathematics Education, 53, 95-107. https://doi.org/10.1007/s11858-021-01229-2

Mahoney, A. (2024, July 9). Crypto-mining creates new environmental injustices for Black Texans. Capital B News. https://capitalbnews.org/crypto-mining-natural-gas-black-communities/

Margolis, J., Estrella, R., Goode, J., Holme, J. J., & Nao, K. (2008). Stuck in the shallow end: Education, race, and computing. MIT Press.

Najibi, A. (2020). Racial discrimination in face recognition technology. Harvard Online: Science Policy and Social Justice, 24. https://web.archive.org/web/20240730143205/https://projects.iq.harvard.edu/sciencepolicy/blog/racial-discrimination-face-recognition-technology

Nakamura, L. (2014). Indigenous circuits: Navajo women and the racialization of early electronic manufacture. American Quarterly, 66(4), 919-941. https://doi.org/10.1353/aq.2014.0070

Noble, S. U. (2018). Conclusion: Algorithms of oppression. In Algorithms of oppression, pp. 171-182. New York University Press. https://doi.org/10.2307/j.ctt1pwt9w5.11

Paul, S. (2017, March 20). Voice is the next big platform, unless you have an accent. Wired. https://www.wired.com/2017/03/voice-is-the-next-big-platform-unless-you-have-an-accent/

Perrigo, B. (2023, January 18). Exclusive: OpenAI used Kenyan workers on less than $2 per hour to make ChatGPT less toxic. Time. https://time.com/6247678/openai-chatgpt-kenya-workers/

Pew Research Center. (2024, November 13). Internet, broadband fact sheet. Pew Research Center. https://www.pewresearch.org/internet/fact-sheet/internet-broadband/

Philip, T. M. (2011). An “ideology in pieces” approach to studying change in teachers’ sensemaking about race, racism, and racial justice. Cognition and Instruction, 29(3), 297-329. https://doi.org/10.1080/07370008.2011.583369

Schwartz, O. (2019, March 25). Untold history of AI: Invisible women programmed America’s first electronic computer. IEEE Spectrum. https://spectrum.ieee.org/untold-history-of-ai-invisible-woman-programmed-americas-first-electronic-computer

Shetterly, M. L. (2016). Hidden figures: The American dream and the untold story of the Black women mathematicians who helped win the space race. William Morrow.

Steele, C. M. (2011). Whistling Vivaldi: How stereotypes affect us and what we can do. W. W. Norton.

Steinmetz, K. F., Holt, T. J., & Holt, K. M. (2019). Decoding the binary: Reconsidering the hacker subculture through a gendered lens. Deviant Behavior, 41(8), 936–948. https://doi.org/10.1080/01639625.2019.1596460

Sutton, R. E. (1991). Equity and computers in the schools: A decade of research. Review of Educational Research, 61(4), 475-503. https://doi.org/10.3102/00346543061004475

United Nations University. (2023, Oct 24). UN study reveals the hidden environmental impacts of Bitcoin: Carbon is not the only harmful by-product. https://unu.edu/press-release/un-study-reveals-hidden-environmental-impacts-bitcoin-carbon-not-only-harmful-product

Vadén, T., & Stallman, R. (2002). The hacker community and ethics [Interview]. GNU Operating System. https://www.gnu.org/philosophy/rms-hack.html

Vogel, S. (2020). Translanguaging about, with, and through code and computing: Emergent bi/multilingual middle schoolers forging computational literacies. [Doctoral Dissertation, City University of New York]. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=5015&context=gc_etds

Vossoughi, S., & Vakil, S. (2018). Toward what ends? A critical analysis of militarism, equity, and STEM education. In A. I. Ali & T. L. Buenavista (Eds.), Education at war: The fight for students of color in America’s public schools (1st ed., pp. 117–140). Fordham University Press. https://doi.org/10.2307/j.ctt2204pqp

Wohl, B., Porter, B., & Clinch, S. (2015). Teaching computer science to 5-7 year-olds: An initial study with Scratch, Cubelets, and unplugged computing. In J. Gal-Ezer, S. Sentance, & J. Vahrenhold (Eds.), WiPSCE ‘15: Proceedings of the Workshop in Primary and Secondary Computing Education (pp. 55-60). Association for Computer Machinery. http://doi.org/10.1145/2818314.2818340

Chapter Overview

This chapter unpacks what we mean by the term “equity” broadly and within the contexts of computer science (CS) and CS education (CS Ed) specifically. Given that equity is the central focus of this guide, it is important to understand what we mean by the term. However, in many contexts, equity is not well defined. This chapter explores how different definitions of equity are connected to the inequities that CS educators want to work to address. The chapter also considers how working toward equity in CS Ed may require multiple ways of thinking about equity.

Chapter Objectives

After reading this chapter, I can:

• Explain the relationship between inequity and equity.
• Define equity as it applies to CS and CS Ed in different ways.
• Recognize the advantages and limitations of different definitions of equity in relation to CS and CS Ed.

Key Terms:

assimilation; broadening participation; equality; equity as access; equity as transformation; ethnocomputing; generative computing; inequity; language agnostic; marginalized/minoritized identities; social justice; underrepresentation

Ms. Morales’ Story

As shared in Chapter 3, K-8 public school teacher Ms. Morales and her colleagues attended professional development (PD) sessions where they learned about many of the inequities embedded in CS fields and CS Ed. After these PD sessions, the teachers clearly recognized how inequities were shaping their work as educators and their students’ experiences in CS Ed. Less clear to them, however, was what exactly “equity" meant. The term was clearly being set up as a counterpoint to inequity, but it still seemed like a buzzword. As they reflected together, they hoped to better understand both equity in general and how specific definitions of equity could shape their work as CS educators.

The Relationship Between Equity and Inequity

Ms. Morales and her colleagues’ efforts to understand equity demonstrates an important point: equity is not an easy word to define or unpack. It gets used by policy makers in the media, by educators in schools, and by people in society generally. It can be defined in many ways, but people are often not clear about how they are using it and may not share the same definition. People may use “equity” interchangeably with “equality” (giving everyone the same thing) or as an empty buzzword, like Ms. Morales and her colleagues noticed. Although it can be hard to define, how we think about equity matters, because our definitions of the term guide how we understand policies and programs and the actions we take to work toward more equitable outcomes in CS and CS Ed.

People’s approaches to equity often grow out of how they think about inequity. When we identify inequities, we point to problems that we think we need to solve. Then, we define equity in ways that work toward solutions to those problems. For example, one problem that has been identified in CS is that people with marginalized identities (e.g., racially and gender minoritized individuals, people with disabilities) are underrepresented in the computing workforce. When the field frames the limited presence of marginalized people in the workforce as a problem of underrepresentation, they often define equity as broadening participation. Working toward equity as broadening participation looks like creating opportunities for marginalized people to participate in CS and CS Ed. Those focused on working toward equity in this way might measure the success of their efforts based on the diversity of students taking CS Ed courses or on the number of employees in the CS industry who hold marginalized identities.

While these efforts help address the problem of underrepresentation, they don’t necessarily consider whether those who hold marginalized identities feel welcome in CS and CS Ed spaces. Similarly, a broadening participation approach to equity might not examine whether the products that workers design and program are having just and ethical impacts. These are different inequities that generate different understandings of equity and lead us to take different actions. Most approaches to equity are limited in some way, which means it is often helpful to draw on different perspectives of equity at different times for different purposes, or even to use multiple understandings of equity together (National Academies of Sciences, Engineering, and Medicine [NASEM], 2022). Taking a multifaceted approach can enable us to work toward equity in different ways and address different levels of inequity in tandem.

Exploring Definitions of Equity

As Chapter 3 showed, there are many inequities that society and our students face related to computing and CS Ed. This means that defining equity to address those problems is complex. Exploring this complexity, Ms. Morales and her colleagues worked to refine their understanding of equity. They hoped that having a clearer definition would allow them to better respond to the challenges they faced, better support their diverse students, and work toward more equitable outcomes in their classrooms. Ms. Morales’ personal experiences with her students and the topics that her PD community focused on (like disability, language, and race) made her an important voice as she and her colleagues reflected together on what equity means.

The PD community began by looking at a set of images about equity that often circulates around social media (Figure 1). Each of the three images in the series shows three young people of different heights trying to watch a baseball game from behind a tall fence. The first image is meant to show “reality.” It illustrates the tallest person standing on a set of seven boxes. The next tallest person stands on a single box, and the shortest person stands in a pit underground. This image suggests that some individuals disproportionately receive the social resources they need to be successful, but others have to deal with extra disadvantages. The second image represents “equality.” All three people stand on one box each, and the pit is gone. Although they all received the same resources, the shortest person still cannot see over the fence. In the final image, all three people receive the appropriate amount of boxes that they individually need to see over the fence to view the game. This image is meant to show “equity.”

Figure 1
Illustrations of Reality, Equality, and Equity

The “reality” image resonated with Ms. Morales and her colleagues. They agreed that we don’t all start from the same place or with the same resources. Similarly, our students don’t all start with the same experience with or access to CS Ed. The teachers also found the images useful in helping them distinguish between “equity” (the third image) and “equality” (the second image) or giving everyone the same thing (like the same type of education, jobs, money, healthcare).

The image representing equality illustrates that while giving everyone the same thing might seem “fair” on the surface, it only gets us so far in meeting students’ needs. In a classroom based on equality, all students would get an identical computer, compatible with English, but with the “r” keyboard letter key missing. When students needed to type out their names, even though everyone has the same computer, not everyone would be able to accomplish the task. Students who had an “r” in their name, or students whose names were written in other writing systems (like the Arabic alphabet or Chinese characters), or students who needed assistive technologies to type because of disabilities would not be able to use their computers to type their name. Giving everyone the same opportunities and resources doesn’t necessarily result in equal outcomes.

The concept of equity offers an alternative to equality. The National Equity Project defines equity as providing “each child … [with] what they need to develop their full academic and social potential” (National Equity Project, n.d., emphasis added). A key phrase in this definition is “what they need.” In a classroom based on equity, each student would receive a personalized laptop with a keyboard and settings in their desired language and any accessibility tools they needed. This tailored approach would support students to successfully complete the assigned task of typing their name.

The CS teachers in Ms. Morales’ PD community appreciated the distinction between equity and equality. But as they sat with that definition of equity — that it is about providing people with what they need to thrive — more questions surfaced. Ms. Morales shared how she had “a love-hate” relationship with the images:

Recognizing Ms. Morales’ point, many people add a fourth panel to Figure 1. This last image shows all three people watching the game, but the fence has been removed entirely. The removal of the fence symbolizes “social justice,” or the dismantling of oppressive conditions and systems that act as barriers to opportunities and resources.

Ms. Morales and her colleagues agreed that these four images together (see Figure 2) provided a metaphor for giving students what they need and breaking down barriers to access (in this case, access to a baseball game).

Figure 2
Illustrations of Versions of (In)Equity

But the teachers still had questions about different parts of the metaphor and places where the analogy seemed to break down and fall short. Specifically, they asked questions about the three individuals in the picture, the fence, and the game itself:

The thought-provoking questions that Ms. Morales and her colleagues raised show how complex it is to define and understand equity in ways that can lead to potential solutions for the inequities discussed in Chapter 3. Making sense of equity requires understanding and dismantling historical and present-day barriers, being clear about what the purposes of equity work are and who the beneficiaries are, and recognizing those communities’ goals, aspirations, and needs.

Exploring Tensions in Defining Equity

One core question that the teachers considered as they viewed the images above centered around using the game of baseball as a metaphor. They wondered why baseball was drawn as the activity that the individuals in the images were attempting to gain access to. They figured it might have something to do with baseball’s traditional reputation as the “great American pastime.” Applying this to education, the teachers related the baseball game to the kinds of schooling that equity initiatives often seek to provide students access to. Those ways of schooling tend to center the speaking, reading, writing, and computing practices of those with more power in society (e.g., white, English-speaking, middle class, college-educated, male, nondisabled). Yet there are so many ways to be, speak, read, write, and compute. Ms. Morales highlighted this reality:

Inequities like those discussed in Chapter 3 exist because many diverse ways of being are not perceived as legitimate in society’s institutions, including schooling. Teachers wondered what would shift if they changed the game in the picture, centering the interests, cultures, and aspirations of those often considered “on the margins” in their teaching.

As teachers discussed these possibilities, one teacher raised her hand to ask a question: Would teaching students to achieve goals outside the mainstream purposes of schooling mean that students wouldn’t get a chance to learn the knowledge, skills, and programming languages they’d need to pass a test or succeed during a job interview? The group acknowledged that to an extent, they did have a professional responsibility to prepare their students for the world around them. They grappled with the desire to “change the game” (e.g., baseball) to something more relevant to their students and communities and to prepare their students with the knowledge they would need to succeed in the game that was already being played.

These tensions are captured in two common ways of conceptualizing or thinking about equity (see Table 1).

Table 1
Conceptualizing Equity
(see Grapin et al., 2023; Philip & Azevedo, 2017; NASEM, 2022)

These conceptions of equity can work together and be complementary, or they might be in opposition. There are also many other ways to think about equity. Along with understandings about access and transformation, the field of CS Ed has developed different frameworks that lay out multiple dimensions of equity in CS Ed. Some of these frameworks are summarized in Table 2. You may find that one or more of these frameworks is useful to help you think about equity in your own context.

Table 2
Some Equity Frameworks in Computer Science Education

Regardless of how we frame it, unpacking different notions of equity is important to ensure that our definitions address the problems that we, our students, and our communities care about. In the next sections, we explore what equity as access and equity as transformation mean and consider limitations of these definitions as well.

Equity as Access to Mainstream Ways of Doing CS: Playing the Game

As teachers pointed out during the PD session, there are benefits to being able to achieve success within mainstream systems of schooling. Because certain practices and knowledge are privileged by society, efforts toward equity as access support marginalized students to engage in the practices and learn the knowledge that afford power in society (Delpit, 1988). This is sometimes referred to as helping students learn to “play the game” (Gutiérrez, 2009). In other words, if U.S. educational systems have decided that baseball is the game that should be played, then ensuring that all students have access to the skills and tools they need to play baseball is one way to engage in equity work.

What does it mean to “play the game” in CS Ed? CS benefits from being a subject that is not required or tested in many states. This means that the rules of the CS “game” are still being written. At the same time, there are ways of doing CS that teachers and schools might perceive as “mainstream” or particularly powerful because they support entry into CS careers. These ways of computing are often aligned with expectations of beginning-level CS courses in college (e.g., CS 101) that prioritize using programming languages like Java to code applications that solve decontextualized problems. Over the years, courses like AP Computer Science A have worked to teach students this code. Similarly, efforts like Code.org’s Hour of Code have worked to broaden participation by encouraging students around the country, including those who have been historically marginalized from CS Ed, to get early exposure to programming.^{[footnote]To learn more about Hour of Code, visit https://code.org/hourofcode[/footnote]} As Ms. Morales pointed out, “Opening the door to CS is the first step, ensuring that it doesn’t lead to another closed door requiring many keys to open. Students should be able to continue to progress with CS skills and have multiple opportunities from elementary school on.”

Early exposure to computing and related efforts can increase the “pipeline” of underrepresented groups who enter CS careers, becoming a first step toward some equity goals. However, this approach may fall short of meeting other equity goals (Perez & Garcia, 2023). Equity as access doesn’t guarantee a sense of relevance, belonging, or power in the CS field for those who enter. Even marginalized learners who work to speak, read, write, and compute in ways that align with mainstream cultural expectations still experience racism, sexism, and linguistic injustice in educational spaces (Flores & Rosa, 2015). Furthermore, broadening participation arguments don’t address the negative environmental, social, and political impacts of computing described in Chapter 3. Those issues prompt us to ask the question: What kind of CS do we want to broaden participation into?

We propose that advancing equity in CS might mean not just providing learners with access to the CS knowledge valued in industry but also transforming and expanding the valued reasons for doing CS and what counts as CS knowledge. We consider below what equity as transformation might encompass.

Equity as Transformation of the Status Quo: Changing the Game

Our students do not code in a vacuum. They are computing in a complex world that often tries to assimilate them, erase them, surveil them, and label them. But they also code and compute in a world that they are actively participating in and find joy in. They may have ideas about how to remake and transform their world, too. We are inspired by scholar Zaretta Hammond, who defines equity as ensuring that all students have the ability to be “powerful learners,” engaged in “deep learning,” who are full of “intellectual curiosity and engagement” (Hammond, as quoted in Rebora, 2021, pp. 14-15).

This way of thinking about equity resonated with Ms. Morales. She wondered:

Equity as transformation pushes us to think beyond giving students access to mainstream ways of computing, to question what lies beyond the status quo, and to consider alternative possibilities. Equity-as-transformation perspectives move us closer to alternatives to playing “baseball.” Instead of merely providing students with access to play the game that society has already established, we can consider what it might look like to “change the game” and transform it into something new (Gutiérrez, 2009).

A first step toward changing the game in CS involves interrogating what the purposes of CS are. Mainstream purposes for CS often seek to reproduce militaristic and industrial ends (Vossoughi & Vakil, 2018; Jones & melo, 2021). A common purpose for CS education is assimilation into the dominant status quo. At best, assimilation ignores, and at worse it violently suppresses, the cultural expertise and experiences, the goals and aspirations, and the language and cultural practices of students with diverse gender, racial and ethnic, and linguistic and cultural identities, as well as students with different abilities (González et al., 2005).

Equity as transformation involves recognizing that there are a range of benefits that learners and their communities want to and already gain from computing. Transformative ways of computing include ethnocomputing, or studying the computational practices that are entwined in minoritized communities’ cultural practices (Eglash et al., 2006; Lachney et al., 2021; New York City Public Schools, n.d.), and generative computing, or connecting computing practices to local community practices in culturally responsive ways (Lachney et al., 2021). Transformative computing also mobilizes traditions and histories from feminist, Black, Latine, Asian, and Indigenous perspectives.^{[footnote]See the On Terminology section of this guide for an explanation on our use of different identity-related terms.[/footnote]} Lewis et al. (2018), for example, employs aspects of Indigenous ways of knowing to unpack artificial intelligence.

In CS Ed, transformation might include mobilizing computing to promote project-based and inquiry models of learning; to innovate and solve local and global problems of interest; to participate in civic life; to promote joy and creativity; and to work toward social justice through critique, organizing, activism, and holding power to account (Vogel et al., 2017). If our schools only define equity as “broadening participation” for industry, they miss these other purposes and rationales for equitable computing that benefit everyone. CS teacher Karime reflected on students’ varied values and interests and how those might drive them to do CS for different purposes:

In some classrooms, teachers are guiding students to reckon with the tensions between dominant ways of developing technology and more “justice-centered” CS approaches. Tarek, a New York City-based CS educator, shared an example of how he did this by asking his students to “design an app to solve a problem in their community.” Tarek explained that “at first, they all focused on things in their own neighborhoods. But when I encouraged them to think about problems faced by other communities, their ideas exploded!” Tarek described some of the apps his students created:

• One group created an app called Parking Superhero to help teachers find parking.^{[footnote]View the Parking Superhero app athttps://www.figma.com/proto/Rw9WhgnyrpdJLyoryYDg58/Parking-SuperHero-(Copy)?node-id=813-9\&starting-point-node-id=237:848\&t=qBrvFkBfDpG5C2iV-1[/footnote]} They really understood the challenges teachers face.
• Another group made an app called Confusing Words to help English Language Learners learn new vocabulary.^{[footnote]View the Confusing Words app athttps://www.figma.com/proto/OYm2wQIPnDuBHlmD9RSIs4/Confusing-Words?node-id=15-11\&starting-point-node-id=15:11\&t=42X4BiI2UNIvlSh7-1[/footnote]}
• There was a group who noticed all the stress their friends were feeling, so they built Calm It Down to help them manage daily challenges.^{[footnote]View the Calm It Down app athttps://www.figma.com/proto/00k4tysppZNDlJegEfj4uE/Calm-It-Down-2?node-id=1-2\&starting-point-node-id=1:2\&t=dlfLjiD99dqIxuic-1[/footnote]}

Other educators begin to move toward equity-as-transformation orientations by exploring the contributions of diverse groups and their active efforts to resist the unjust impacts of technology. Some examples of those using technology for social action appear in Table 3. These organizations and others like them actively resist inequity and work to transform computing that supports a more equitable world.

Table 3
Computing to Promote Social Justice

Inspired by students and the diverse computing practices of people in the world, CS educators have created new kinds of curriculum and opportunities for students who have been traditionally excluded from CS Ed. One core effort has been the creation of culturally relevant and culturally responsive computing curricula that is rooted in theories of culturally relevant and culturally responsive pedagogy and teaching (Gay, 2018; Hammond, 2014; Ladson-Billings, 1995; Madkins et al., 2020; Scott et al., 2015). For example, Margolis and colleagues (2015) shared their popular Exploring Computer Science (ECS) curriculum. This curriculum is meant to introduce students — especially those from underrepresented backgrounds — to CS concepts and practices through the lens of project-based and inquiry-driven units. These approaches benefit all students by centering their voices and perspectives as students use computing to address social issues that they personally care about.

Equity in the Everyday

Thus far, we’ve presented equity as access and equity as transformation as separate and in tension. Yet these ideas are also interrelated and overlapping. Doing equity work in the day-to-day often requires drawing on both notions in tandem.

The AP CS Principles course provides one example of this reality. Historically, high schools with CS courses mostly offered AP Computer Science A to prepare students for beginning-level CS courses in college. These AP courses, however, lost female, Black, and Latine test takers over the years (Apraci-Dusseau et al., 2013). Acknowledging this reality, the College Board and other stakeholders came together to design and introduce the AP CS Principles (AP CSP) course and exam. Instead of focusing on teaching a particular programming language, the new AP CSP exam is language agnostic, focusing on core skills that can be applied across different programming languages. The AP course and exam center big ideas about computing and computational thinking practices.^{[footnote]The AP CSP big ideas and computational thinking practices can be found athttps://apcentral.collegeboard.org/media/pdf/ap-computer-science-principles-course-overview.pdf[/footnote]} In AP CSP, students are asked to use computing for real-world problem solving. The course has proven popular and has led to an increase in students taking the AP CSP exam, making modest gains in promoting more diversity among test takers.

While still aiming to provide “access” to college credit and skills needed for success in higher education and industry spaces, the AP CSP revision has had some modest transformational impacts as well. It expanded what “counted” as valuable CS knowledge to include skills beyond programming, like collaboration and creativity. It also engaged students in exploring the impacts of computing technology (Blikstein, 2018, p. 17). Equity-oriented CS teachers may not need permission to incorporate this content into their CS instruction. However, by explicitly including those topics in the AP CSP course design, it is less risky for all teachers to move in those directions.

At the same time, these modest efforts toward transformation are not guaranteed. The same AP CSP course taught by a less equity-oriented teacher could reproduce narratives of computing that support industrial and militaristic ends and fail to adequately meet marginalized learners’ needs and experiences. AP CS teachers will also navigate situations where working toward equity as access and equity as transformation might clash, such as needing to balance time spent discussing issues related to social justice and computing with time spent preparing students for the AP exam. These tensions show how complex equity work can be, how we often need to think about equity in multiple ways at the same time, and how educators play a critical role in working toward equity in all kinds of CS Ed spaces. See Resource 1 at the end of the chapter for another example of how teachers can identify inequities in their classrooms and work to further multiple definitions of equity.

Our Vision of Equity

In defining equity for this guide, we echo academic Scott Grapin and colleagues who argue that efforts should “attend to equity as access while pushing toward equity as transformation” (Grapin et al., 2023, p. 1018). This notion is core to this book’s mission. Thinking of equity in these terms, we hope to work toward a future where:

• learners whose identities have been marginalized in CS and in society have what they need — including access to relevant computing tools and literacies — to learn, to thrive, and to sustain and contribute to the evolution of their communities’ cultural and language practices; and
• all learners are equipped with critical consciousness about computing tools, cultures, and industries so they might work toward transforming those tools, cultures, and industries to become ethical and just.

We emphasize our focus on access to relevant computing that is meaningful for our students — not just access to the kinds of CS that have been mainstreamed. We want our students to thrive by supporting their critical awareness of the sociopolitical games embedded in society, technology fields, and education and empowering them to choose how they want to play. We also want educators and students to practice changing the game.

Scholars Alim, Paris, and Wong (2020) provide us with one more vision of what it would be like to change the game:

What would our pedagogies look like if these hegemonic gazes weren’t the dominant ones? What if, indeed, the goal of teaching and learning with young people of color was not ultimately to see how closely they could perform white middle-class norms, but rather was to explore, honor, extend and, at times, problematize their cultural practices and investments? What would our educational contexts look like in a world where we owed no explanations, to anyone, about the value of our children’s culture, language and learning potential? (p. 262)^{[footnote]By White, middle-class norms, the authors refer to cultural practices such as how people comport themselves and language practices like using “standard” English (see Delpit, 1988). The specific norms and practices might be different based on geography, population, and so on but are associated with power and status that confirm a certain type of success within a given local context.[/footnote]}

Educators play a key role in their classrooms to enact pedagogies that value and honor students’ cultures and experiences. However, administrators, policy makers, and industry leaders are also responsible for engaging in this transformational work. Collective efforts will change the game not only within individual classrooms but also through more lasting structural and system-wide changes.

Revisiting Ms. Morales’ Story

Ms. Morales is on the path toward that vision in her own CS classroom. She shared an example of one project that she developed as an introduction to CS. Recognizing the cultural and linguistic diversity of her students, Ms. Morales focused on computing tools as a form of self-expression to support social-emotional learning. She wanted students to share their identities: “what makes them unique, special and how we represent ourselves.” Drawing on students’ experiences in their communities (e.g., language, culture, hobbies), her students created projects in Scratch that blended computing with other forms of expression, like poetry, illustrations, and song in multiple languages to share about themselves and make connections to each other and to CS as a resource to support understanding. Ms. Morales described her students’ reactions to this experience:

Ms. Morales’ project used multiple strategies to give all her students access to participating but also worked toward transforming CS from a decontextualized discipline for a few to a powerful way for her students to express themselves in ways that “value[d] … [their] culture, language and learning potential” (Alim et al., 2020, p. 262).

In the chapters that follow, you’ll continue to think about equity in terms of access and transformation and their overlaps. You’ll be invited to reflect on the purposes of CS Ed in your settings and will consider concrete suggestions for pedagogical strategies and approaches that can help you enact changes toward transforming what CS looks like in your classrooms and schools. We also recognize, as we noted earlier, that no single definition of equity is enough (NASEM, 2022). We invite you to consider the inequities you notice around you and develop your own definitions of equity that help you address those inequities in your local contexts and spaces. As you do so, you can become change agents for your colleagues, your students, and the field of CS Ed.

Reflection Questions:

1. Based on what you have read in this chapter, how would you personally define equity? What is your own vision of equity?
2. In your contexts, what efforts are being made to help students “play the game”? To help students “transform the game”?
3. How have you seen tensions related to different equity efforts play out in the settings where you work?

Takeaways for Practice:

• Analyze the computing spaces you work in through the framings of equity we explored in this chapter. Are definitions of equity clearly stated in these spaces? Where and how do you recognize efforts to work toward equity as access? Where and how do you recognize efforts to work toward equity as transformation?
• Identify one small change you can make in your personal CS Ed context that can work toward your definition of equity from Reflection Question 1 above.

Glossary

References

Alim, H. S., Paris, D., & Wong, C. P. (2020). Culturally sustaining pedagogy: A critical framework for centering communities. In N. S. Nasir, C. D. Lee, R. Pea, & M. McKinney de Royston (Eds.), Handbook of the cultural foundations of learning (pp. 261-276). Routledge. https://doi.org/10.4324/9780203774977-18

Annamma, S. A., Connor, D., & Ferri, B. (2013). Dis/ability critical race studies (DisCrit): Theorizing at the intersections of race and dis/ability. Race Ethnicity and Education, 16(1), 1-31. https://doi.org/10.1080/13613324.2012.730511

Apraci-Dusseau, A., Astrachan, O., Barnett, D., Bauer, M., Carrell, M., Dovi, R., Franke, B., Gardner, C., Gray, J., Griffin, J., Kick, R., Kuemmel, A., Morelli, R., Muralidhar, D., Osborne, R. B., & Uche, C. (2013). Computer science principles: Analysis of a proposed advanced placement course. In T. Camp, P. Tymann, J. D. Dougherty, & K. Nagel (Eds.), SIGCSE ‘13: Proceeding of the 44th ACM technical symposium on computer science education (pp. 251-256). ACM Special Interest Group on Computer Science Education (SIGCSE). https://doi.org/10.1145/2445196.2445273

Black, C., Cerdeña, J. P., & Spearman-McCarthy, E. V. (2023). I am not your minority. Lancet Regional Health Americas, 19. https://doi.org/10.1016/j.lana.2023.100464

Blikstein, P. (2018). Pre-college computer science education: A survey of the field. Google LLC. https://services.google.com/fh/files/misc/pre-college-computer-science-education-report.pdf

Computer Science Teachers Association. (n.d.). Inclusive teaching pedagogies. https://csteachers.org/inclusive-teaching-pedagogies/

Davis, K., White, S. V., Becton-Consuegra, D., & Scott, A. (2021). Culturally responsive-sustaining computer science education: A framework. Kapor Center. https://www.kaporcenter.org/wp-content/uploads/2021/07/KC21004_ECS-Framework-Report_final.pdf

Delpit, L. D. (1988). The silenced dialogue: Power and pedagogy in educating other people’s children. Harvard Educational Review, 58(3), 280-299. https://doi.org/10.17763/haer.58.3.c43481778r528qw4

Eglash, R., Bennett, A., O’Donnell, C., Jennings, S., & Cintorino, M. (2006). Culturally situated design tools: Ethnocomputing from field site to classroom. American Anthropologist, 108(2), 347-362. https://doi.org/10.1525/aa.2006.108.2.347

Fletcher, C. L., & Warner, J. R. (2021). CAPE: A framework for assessing equity throughout the computer science education ecosystem. Communications of the ACM, 64(2), 23-25. https://doi.org/10.1145/3442373

Flores, N., & Rosa, J. (2015). Undoing appropriateness: Raciolinguistic ideologies and language diversity in education. Harvard Educational Review, 85(2), 149-171. https://doi.org/10.17763/0017-8055.85.2.149

Gay, G. (2018). Culturally responsive teaching: Theory, research, and practice (3rd ed.). Teachers College Press.

González, N., Moll, L., & Amanti, C. (2005). Funds of knowledge: Theorizing practices in households, communities, and classrooms. Lawrence Erlbaum Associates.

Grapin, S. E., Pierson, A., González-Howard, M., Ryu, M., Fine, C., & Vogel, S. (2023). Science education with multilingual learners: Equity as access and equity as transformation. Science Education, 107, 999-1032. https://doi.org/10.1002/sce.21791

Gutiérrez, R. (2009). Framing equity: Helping students “play the game” and “change the game.” Teaching for Excellence and Equity in Mathematics, 1(1), 4-8. https://www.todos-math.org/assets/documents/TEEMv1n1excerpt.pdf

Hammond, Z. L. (2015). Culturally responsive teaching and the brain: Promoting authentic engagement and rigor among culturally and linguistically diverse students. Corwin.

Jones, S. T. & melo, n. a. (2021). We tell these stories to survive: Towards abolition in computer science education. Canadian Journal of Science, Mathematics and Technology Education, 21, 290-308. https://doi.org/10.1007/s42330-021-00158-2

Lachney, M., Babbitt, W., Bennett, A., & Eglash, R. (2021). Generative computing: African-American cosmetology as a link between computing education and community wealth. Interactive Learning Environments, 29(7), 1115-1135. https://doi.org/10.1080/10494820.2019.1636087

Ladson-Billings, G. (1995). Toward a theory of culturally relevant pedagogy. American Education Research Journal, 32(3), 465-491. https://doi.org/10.3102/00028312032003465

Lewis, J. E., Arista, N., Pechawis, A., & Kite, S. (2018). Making kin with the machines. Journal of Design and Science. https://doi.org/10.21428/bfafd97b

Madkins, T. C., Howard, N. R., & Freed, N. (2020). Engaging equity pedagogies in computer science learning environments. Journal of Computer Science Integration, 3(2), 1-27. https://doi.org/10.26716/jcsi.2020.03.2.1

Margolis, J., Goode, J., & Chapman, G. (2015). An equity lens for scaling: A critical juncture for exploring computer science. ACM Inroads, 6(3), 58-66. https://doi.org/10.1145/2794294

McDermott, R. P. (1993). The acquisition of a child by a learning disability. In S. Chaiklin & J. Lave (Eds.), Understanding practice (pp. 269-305). Cambridge University Press. https://doi.org/10.1017/CBO9780511625510.011

National Academies of Sciences, Engineering, and Medicine. (2022). Science and engineering in preschool through elementary grades: The brilliance of children and the strengths of educators. National Academies Press. https://nap.nationalacademies.org/catalog/26215/science-and-engineering-in-preschool-through-elementary-grades-thebrilliance

National Equity Project. (n.d.). Educational equity definition. https://www.nationalequityproject.org/education-equity-definition

New York City Public Schools. (n.d.). Ethnocomputing: Computational thinking of indigenous and vernacular cultural designs. New York City Public Schools CS4All. https://sites.google.com/schools.nyc.gov/cs4all-equity/eecs/ethnocomputing

Perez, M., & Garcia, P. (2023). Tracing participation beyond computing careers: How women reflect on their experiences in computing programs. ACM Transactions on Computing Education, 23(2), 1-23. https://doi.org/10.1145/3582564

Philip, T. M., & Azevedo, F. S. (2017). Everyday science learning and equity: Mapping the contested terrain. Science Education, 101(4), 526-532. https://doi.org/10.1002/sce.21286

Rebora, A. (2021). Zaretta Hammond on equity and student engagement. Educational Leadership, 79(4), 14-18. https://www.ascd.org/el/articles/zaretta-hammond-on-equity-and-student-engagement

Scott, K. A., Sheridan, K. M., & Clark, K. (2015). Culturally responsive computing: A theory revisited. Learning, Media and Technology, 40(4), 412–436. https://doi.org/10.1080/17439884.2014.924966

Vogel, S., Santo, R., & Ching, D. (2017). Visions of computer science education: Unpacking arguments for and projected impacts of CS4All initiatives. In M. E. Caspersen, S. H. Edwards, T. Barnes, & D. D. Garcia (Eds.), Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computing Education (pp. 609-614). ACM Special Interest Group on Computer Science Education. http://doi.org/10.1145/3017680.3017755

Vossoughi, S., & Vakil, S. (2018). Toward what ends? A critical analysis of militarism, equity, and STEM education. In A. I. Ali & T. L. Buenavista (Eds.), Education at war: The fight for students of color in America’s public schools (1st ed., pp. 117–140). Fordham University Press. https://doi.org/10.2307/j.ctt2204pqp

Resource 1: Working Toward Equity in CS Classrooms

Chapter Overview

This chapter offers some theoretical tools to think with as educators engage in equity-focused work. Specifically, the chapter examines the idea of intersectionality and a framework called “the Four I’s” that illuminates how inequity can be reproduced through systems of oppression at ideological, institutional, interpersonal, and internalized levels. The chapter uses these theories as lenses to bust myths that are often given as explanations for why inequity exists in computer science (CS) and CS education (CS Ed).

Chapter Objectives

After reading this chapter, I can:

• Identify common myths in CS Ed and explain how these myths reproduce inequities.
• Apply the theory of intersectionality to make sense of inequities in CS and CS Ed.
• Apply the theory of the Four I’s of Oppression and Advantage to make sense of inequities in CS and CS Ed.

Key Terms:

ableism; classism; the Four I’s of Oppression and Advantage; ideological oppression; ideologies; imposter syndrome; institutional oppression; internalized oppression; interpersonal oppression; intersectionality; marginalization; matrix of domination; microaggression; racism; sexism; structural oppression; theory; tokenism; xenophobia

Emily’s Story

Emily is an elementary teacher who is concerned about equity at her school.^{[footnote]Emily’s experiences are shared with permission.[/footnote]} She has heard several myths about students and recognizes how those myths contribute to the inequity she sees. Emily shared:

Emily noticed that when teachers believe this myth, they often don’t expose their students to CS in their classrooms, which “widens the inequity for these students as they go through their education.” Emily finds it “very frustrating to hear these sentiments” and wants to learn how she can speak back to these myths to support more equitable instruction at her school.

Theories as Tools to Think With

Understanding why and how inequities persist is an important part of working toward educational equity. People offer many different explanations for why there are inequities in CS and CS Ed. Some of these explanations may sound like the following:

• Computer science is for “techies.” It’s a hard, technical field, so not everyone is cut out for it, which is why you don’t see a lot of diversity.
• If tech companies could find enough women and racially minoritized coders with the right skills, they’d hire them. It’s not about bias, it’s about qualifications.
• Since CS tends to attract certain types of students, like male students, there’s no need to spend extra time or resources supporting them. They already have an advantage.

While these explanations may make sense on the surface, there are a lot of false assumptions embedded in them. For example, the explanations suggest that participating in computing requires a certain set of abilities or identities but overlook the fact that anyone with interest and support can thrive in CS. They collapse differences between individuals, assuming that everyone from a certain group is the same, and they place blame on individuals without acknowledging systemic patterns that contribute to inequity.

Despite the fact that these statements are all actually myths based on incomplete information, these and other stories about inequity in CS have become second nature in CS educational spaces. There are many pitfalls, traps, tropes, and detours that people working toward equitable outcomes can fall into when they make assumptions like those described above (Dugan, 2021). To reach our goal of equity-centered CS Ed, we need to constantly examine the assumptions we are making about our students, CS as a discipline, and our classrooms.

Theories are one tool we can use to examine our assumptions. Developed by scholars, educators, activists, and people in their everyday lives, theories offer explanations for phenomena that can help us interpret what is happening around us so we can more effectively take action. In this chapter, we consider two theories: intersectionality and the Four I’s of Oppression and Advantage (ideological, institutional, interpersonal, and internalized).

Sometimes, the writing that describes theories from academic disciplines like sociology, law, and education can use dense language. We attempt to provide examples and explanations to make the theories presented in this chapter more relevant to CS educators and provide a glossary for support. Engaging with theoretical ideas and lingo, even though it can be challenging, can be an important way to support equity-focused growth, because it helps us take up new perspectives outside of our own experiences.

As we explore the theories of intersectionality and the Four I’s in this chapter, we use them to challenge common myths you might hear in the media, from administrators and colleagues, or even from students themselves. By using theory and facts to demystify these myths, we can’t promise that working toward equitable changes in CS Ed will get easier. However, if we better understand the systems that have led to pervasive issues and challenges in the field, we can better understand how to work to change those systems and guide our students to be change agents too. Hopefully, by thinking with us about these theories and myths, you’ll be prepared with a powerful response the next time you hear a myth being perpetuated.

Intersectionality

Intersectionality starts with a recognition of the fact that people’s identities are multifaceted and complex. It also draws on the idea that identities are socially constructed and that people can experience oppression and marginalization related to particular identities, while other identities afford access to social power and privilege. Building on these two principles, intersectionality as a theory argues that different aspects of people’s identity (e.g., disability, gender, race) overlap and intersect in ways that result in forms of oppression that cannot be understood or addressed by focusing on each identity separately (Crenshaw, 1991; Collins, 2019).

The concept of intersectionality has long been used in efforts to work toward social justice — even before legal scholar Kimberlé Crenshaw coined the term in the late 1980s. For example, Sojourner Truth was a formerly enslaved Black abolitionist who lived in the United States in the mid-1800s. During her life, emancipation efforts gave Black men the right to vote and suffrage movements worked to grant the right to vote to white women. Truth named how her identity as a Black woman left her overlooked by both of these movements (The Sojourner Truth Project, 1851; Collins, 2019).

Truth’s experience illustrates how social dynamics marginalize Black women in unique ways that cannot be described or understood by paying attention to just race or gender in isolation. Scholars have shown how intersectionality is important when working for social justice because everyone has different overlapping identities that are perceived in different ways by society. Kimberlé Crenshaw (1989) used this analogy to explain why intersectionality matters:

Consider an analogy for traffic in an intersection, coming and going in all four directions. Discrimination, like traffic through an intersection, may flow in one direction, and it may flow in another. If an accident happened in an intersection, it can be caused by cars traveling from any number of directions and, sometimes, from all of them. Similarly, if a Black woman is harmed because she is in the intersection, her injury could result from sex discrimination or race discrimination. (p. 149)

Sociologist Patricia Hill Collins calls these intersecting systems of power the matrix of domination (Combahee River Collective, 1977; Collins, 2019). The matrix of domination creates dynamics that produce distinct and interlocking forms of oppression based on identities like gender and race. Those who hold multiple marginalized identities experience domination and oppression at the intersections of their identities.

Intersectionality can help educators recognize why equity-based initiatives might fall short. Often, equity initiatives consider the marginalization a student might face in an “additive” way. For example, an initiative might assume that by addressing issues of racial discrimination, gender discrimination, and class discrimination separately, they will have helped a student who faces all three issues. But intersectionality emphasizes how our identities don’t just get added on top of each other. Instead, our identities intersect and overlap to result in distinct lived experiences, oppression, biases, and access or lack of access to power and privilege (Esposito & Evans-Winters, 2021).

Sometimes, the intersectional nature of identity gets obscured. For example, a Computer Science for All (CSforAll) initiative might consider statistics about girls’ pass rates for the AP CS Principles (AP CSP) course to measure progress toward broadening participation in CS. In 2022, 61% of girls and 64% of boys passed the AP CSP exam (Ericson, 2023). These numbers make it seem like the gender gap is closing. However, looking at the statistics in terms of gender and race highlights how large disparities still exist. In 2022, 70% of white girls passed the exam, but only 32% of Black girls, 38% of Hispanic girls, and 34% of Pacific Islander girls who took the exam passed.^{[footnote]We use the racial and gender categories that were used on the exam. We acknowledge that these categories do not fully capture students’ diverse racial and gender identities.[/footnote]} Looking at the data only through gender or only through race obscures how racially minoritized girls continue to be marginalized in CS at the intersections of their racial and gender identities.

Mythbusting Time!

The Four I’s of Oppression and Advantage

One myth about education in general is that just having “bad actors” or individuals change their behaviors would fix inequities. But the reality is more complicated than that. Inequities are shaped by interlocking systems of oppression and advantage like ableism, classism, racism, or sexism. These cultural, economic, and political systems were established during periods of slavery, colonialism, and imperialism and continue to shape society today (Tatum, 2003). They reproduce different forms of identity-based discrimination and exclusion through a combination of individual prejudiced action and power embedded in institutional structures (Bell, 2013). They are systems of oppression and advantage because some identities are afforded a more dominant status in society and provide people with those identities with power and privilege.

This differential distribution of power creates social hierarchies (Wilkerson, 2020). For example, in the United States, racial hierarchies afford people racialized as white with access to particular social privileges while racially marginalized people face discrimination, exclusion, and oppression around their racial identities. Members of groups who are granted more privileged status may be socialized not to talk about or even notice these -isms, while members of marginalized groups may experience their direct consequences frequently (Tatum, 2003). How hierarchies are structured and how individuals experience injustice as a lived reality vary across cultures and countries. However, because benefits and privileges are embedded in social structures, inequities get (re)produced across social contexts.

The Four I’s of Oppression and Advantage (Four I’s) is a theory that helps us understand how systems of oppression and advantage are produced across multiple layers of society: ideological, institutional, interpersonal, and internalized (Chinook Fund, n.d.). Table 1 summarizes the Four I’s and their application to CS and CS Ed.

Table 1
The Four I’s of Oppression and Advantage

Dynamics at all four levels of oppression shape CS education and computing professions. This means that working toward equitable outcomes in CS Ed requires more than just having people change by taking up equity-minded behaviors and mindsets. Real change also requires disrupting what we assume to be common sense, changing the policies and practices of institutions, and attending to how resources and benefits get distributed across society. The Four I’s are not exhaustive, but they can offer us a way to think about the interconnected systems that support oppression and advantage in society. Looking at each one individually, we can use them to debunk common myths in CS Ed.

Ideological Oppression and Inequity

One important way that inequity is maintained is through ideologies, or systems of ideas that circulate in society. Dominant ideologies that reproduce inequity are harmful because they perpetuate ideas that reinforce the supremacy of certain groups over others and contribute to ideological oppression. Ideologies are often hard to recognize because they get embedded in narratives and myths that are accepted as “common sense” by society.^{[footnote]We use the term “common sense” in line with scholars who have noted that what society names as common sense is generally neither common nor sensical (Fairclough, 2014; Garfinkel, 1967).[/footnote]}

For example, in many CS classrooms, solving problems quickly and without asking questions is associated with intelligence. Valuing the ability to solve problems quickly may at first seem like “common sense.” But it actually draws on several ideologies that reproduce inequities. This unspoken value is rooted in Western cultural ideologies that equate time with money as part of a capitalist system. Valuing quick problem solving also promotes ableist ideologies that discriminate against neurodivergent students who process information differently and at different speeds. It may also marginalize bi/multilingual learners who draw on their full linguistic repertoires to complete a task. Prioritizing this value in CS classrooms can create inhospitable conditions for learners, creating competitive environments that reproduce other ideologies like individualism, which values individual achievement over collective growth.

Amanda, an elementary CS teacher, shared an example of ideological oppression in her context. She explained: “In my school, a well-spoken student is automatically thought of as ‘smarter.’ People assume that they must have ‘a well-educated family.’” Amanda named narratives that draw on language ideologies that equate intelligence and education with certain, privileged language practices. People often equate being “well-spoken” to using “standard” or “academic” English, and “well-educated” with having attended college, despite there being many ways of communicating and learning. Amanda challenged this ideological influence as she reflected that “I don’t think enough time is spent thinking about [how] we can call people into these spaces and make our teaching more culturally responsive and relevant to families.” Amanda’s call to think about how to create learning environments that value and center students’ language and cultural practices could be one way to contest ideological oppression in her space.

Mythbusting Time!

Institutional Oppression and Inequity

Ideologies that contribute to inequity often become embedded into policies and routines in social structures. These practices create inequitable opportunities and outcomes for different groups of people. Oppression can be institutionalized (reproduced at individual institutions like a single school or a single tech company) or structural (present across similar institutions over time, like schooling in general or the technology industry).

Institutional and structural oppression in the tech industry can be seen in how African American, Native American, and Latine women may become stuck in low-level positions in tech companies. Despite well-intended recruitment and retention policies, structural barriers may prevent racially marginalized people from advancing in their careers (McKinsey & Company, 2024; Smith, 2022).

In CS Ed, institutionalized inequity may appear in recruitment policies for CS Ed programs. For example, a school might have a policy that requires students to have received high grades, completed prerequisite courses, and have a “squeaky clean” disciplinary record to participate in CS classes. This kind of policy is advantageous for students who have been able to afford tutoring and support to succeed in courses — often those from more affluent households. However, it disadvantages students who did not have the same opportunities and who may have been disciplined more frequently. This kind of policy that institutionalizes inequity at one school becomes structural if similar practices occur at schools across the country and over time.

In fact, these kinds of structural systems of disadvantage and oppression do exist and work to exclude racially minoritized students, bi/multilingual students, and students with disabilities from CS learning opportunities. Across schools in the United States, Black and Latine students are disciplined at higher rates than their white peers (Losen, 2011; Noguera, 2003). This means that policies requiring a squeaky clean record to participate in CS may exclude Black and Latine students who would otherwise be interested in and successful at CS. Similarly, bi/multilingual students and racially minoritized students are overrepresented in special education programs (Annamma et al., 2013). Structural policies that situate CS as an enrichment course may mean that students in special education programs are excluded from CS opportunities as well (Wille et al., 2017). These institutionalized and structural layers of oppression create a situation where CS courses come to be treated as clubhouses, reserved for students who meet particular standards for what an average or typical CS student looks, sounds, and acts like (Margolis & Fisher, 2003). As a result, inequitable access to CS educational opportunities continues.

Dawn, another elementary CS teacher, described how institutional oppression reproduced inequity at her school. She shared:

Dawn identified several institutional factors at play in her context: the budget cuts that eliminated the CS program, the expectation for teachers to incorporate CS into an already full curriculum with limited time, and the lack of training for teachers to feel confident teaching CS. All of these institutional factors have contributed to inequitable access to CS at Dawn’s school, despite the fact that at one time, all children did have CS opportunities.

Mythbusting Time!

Interpersonal Oppression and Inequity

Inequities that are based in ideologies and embedded in institutional and structural policies are often felt most oppressively in individual and group interactions as a form of interpersonal oppression. People may assume that interpersonal issues are simply “bad people” acting on their prejudices and biases, but interpersonal oppression goes deeper than that. Interpersonal layers of inequity are reproduced in everyday actions when people make racist or sexist jokes or share comments that perpetuate stereotypes about groups of people. It also occurs in interactions like harassment, threats, violence, and police brutality against marginalized groups. Interpersonal forms of advantage can happen when someone privileges a member of a particular group over others in interactions like hiring and promoting decisions or when approving a loan. Ideologies and institutional and structural policies shape people’s interpersonal interactions and vice versa, creating a continual feedback loop.

Interpersonal oppression is shaped by power. While all people can act on prejudiced ideas that harmfully assert the supremacy of some groups over others, not all people’s actions are socially powerful in the same way (Kendi, 2019; Leonardo, 2007). When individuals with social and institutional power act on prejudice in ways that draw on power, they contribute to the harmful reproduction of society’s -isms in a way that is not possible for those who lack social or institutional power. For example, in 2020, a white woman called the police on a Black man in New York City’s Central Park for doing nothing more than “birding while Black” (Gross, 2023). She could marshall and rely on the power of law enforcement in ways that marginalized individuals may not feel safe doing, even when reporting actual hate crimes (Devine et al., 2018).

Interpersonal forms of oppression occur in CS Ed too. CS educators may wittingly or unwittingly hold lower expectations for their racially minoritized students, their students with disabilities, or their bi/multilingual students learning English. These expectations may be revealed in their interactions with or about students. For example:

• A teacher might comment to another teacher, “Oh that Spanish-speaking student is so well spoken,” reproducing the assumption that this student is an exception to a norm.
• A teacher might give the benefit of the doubt to a student who has a missing homework assignment because they perceive them as coming from a “good” family (e.g., with two professional, college-educated parents or caregivers).
• A teacher might want to raise awareness about ableism and unwittingly tokenizes a student with a disability by asking them to “represent” people with disabilities during class discussions.
• Male students might exclude their female and non-binary peers from contributing to a group project and question their capabilities.

While our interpersonal interactions can convey negative biases that reproduce inequitable power dynamics, they can also be used to contest inequities. As CS educators, we can work to understand our negative biases. We can strive to have interactions with students and families that are driven by a spirit of curiosity and openness rather than by stereotypes we might have been socialized into. When appropriate, we can call our colleagues in when we see interpersonal oppression happening around us and invite them to reflect on their own actions as a step toward disrupting inequity.

Amanda, the elementary CS teacher who shared about the ideological oppression she saw in her school, also recognized interpersonal oppression in her experiences with her students that resulted in lowering expectations for her bi/multilingual learners. She described:

By adjusting her interpersonal interactions with her students to center their expertise and challenge them, Amanda was able to disrupt some of the inequities in her space and transform her students’ experiences with CS.

Mythbusting Time!

Internalized Oppression and Inequity

Systems of oppression can also include internalized oppression felt by individuals. Individuals who hold identities that are marginalized are often socialized, sometimes harshly, into the idea that they have no place in CS and related fields. Similarly, those who hold identities that are afforded power and privilege are socialized to the idea that they do belong in CS and “others” don’t.

How do students develop and internalize these deficit views of themselves? The other three I’s can contribute to the internalized layer of oppression. The ideological myth of meritocracy positions success as solely linked to skill or effort, so if students struggle in CS courses, they might internalize their difficulties as a personal weakness. This interpretation can create doubt in their abilities and erode confidence. Interpersonal interactions may also contribute to internalized oppression as students may hear messages from peers, family members, educators, and even guidance counselors about what they would or would not be good at, leading them to avoid CS courses. Institutionalized policies like those that require prerequisites for CS courses (e.g., calculus or algebra) can lead a student to second-guess their abilities even though skills from the prerequisite courses may not be required to succeed in the CS course.

Internalized oppression is often based on harmful stereotypes and assumptions (McGarr et al., 2023). The effects of negative stereotypes are often addressed, but expecting students to live up to positive stereotypes like the model minority myth described earlier can be just as damaging to students’ sense of belonging, self-efficacy, and agency (McGee, 2018). Research has shown that just knowing that a stereotype exists and being afraid of confirming that stereotype can interfere with learning and performance (Steele & Aronson, 1995). Anything that makes stereotypes more apparent in a setting, like asking students to identify their race or ethnicity on an exam, makes learners more likely to respond in ways that reinforce the stereotype (Steele, 2011). Introductory “weed out” courses that are intentionally designed to push out students who are considered less likely to succeed in CS are one example. Historically, students who are “weeded out” have been disproportionately Black, Indigenous, Latine, and female (Weston et al., 2019).

While internalized forms of oppression can be particularly harmful and pervasive, educators can also have a great deal of influence when it comes to students’ mindsets. We can support our students to think critically about and resist messages that frame them and their communities in deficit ways. We can also expose them to role models that represent where they come from and advocate for policies that foster their budding interests in CS fields.

CS teacher Nicole described how reflecting on her own biases helped her recognize how interpersonal and internalized oppression might be connected in her work. Nicole noticed that she might be making assumptions that contribute to inequitable interpersonal interactions. Nicole shared:

Nicole recognized how rather than stereotyping teachers, she could address her own assumptions and biases. Then, she could intentionally plan for interactions that might explore and potentially alleviate some of the teachers’ concerns that could come from internalized negative views about CS.

Mythbusting Time!

Revisiting Emily’s Story

As Emily learned about the theories discussed in this chapter, she recognized that the myth about multilingual students at her school not being able to do CS was connected in part to an institutionalized layer of inequity. Thankfully, the administration at Emily’s school also recognized this. Emily described how the admin “are very adamant about students receiving CS education and have now tied parent events to the CS courses. Parents are invited a few times a year to see what their child has worked on and the events are very well attended.” Connecting CS learning to a schoolwide event helped disrupt institutional inequity because the teachers at Emily’s school have become more diligent in implementing CS for all students. Emily concluded that “the students LOVE showing off their work and the parents are really thankful for the CS education their children are receiving.” Emily’s experience shows how using theories can help us recognize how inequities are being reproduced in our environments so that we can work to disrupt them.

Reflection Questions:

1. How does applying the theories of intersectionality and the Four I’s of Oppression and Advantage help you make sense of inequities in CS Ed? How might you apply these theories in your contexts?
2. What myths exist in the spaces you work in? How can you use the theories in this chapter to understand and combat those myths?

Takeaways for Practice:

• Reflect on how intersectionality applies to you and how your intersectional identities influence your work as an educator. Consider changes you might make in your setting to better attend to the intersectional identities of students.
• Identify one myth in this chapter that is relevant to your work. Apply the Four I’s to determine whether that myth is influenced by ideological, institutional/structural, interpersonal, or internalized oppression (or some combination of the four). Create an action plan to start addressing this myth in your setting.

Glossary

References

Annamma, S. A., Connor, D., & Ferri, B. (2013). Dis/ability critical race studies (DisCrit): Theorizing at the intersections of race and dis/ability. Race Ethnicity and Education, 16(1), 1-31. https://doi.org/10.1080/13613324.2012.730511

Bang, M., Warren, B., Rosebery, A. S., & Medin, D. (2012). Desettling expectations in science education. Human Development, 55(5-6), 302-318. https://doi.org/10.1159/000345322

Bell, J. (2013). The four “I’s” of oppression. Begin Within. https://beginwithin.info/articles-2/

Beyer, S. (2014). Why are women underrepresented in Computer Science? Gender differences in stereotypes, self-efficacy, values, and interests and predictors of future CS course-taking and grades. Computer Science Education, 24(2-3), 153-192. https://doi.org/10.1080/08993408.2014.963363

Boaler, J., & Greeno, J. G. (2000). Identity, agency, and knowing in mathematics worlds. In J. Boaler (Ed.), Multiple perspectives on mathematics teaching and learning (pp. 171-200). Ablex Publishing. https://doi.org/10.5040/9798400688362.0011

Bui, Q., & Miller, C. C. (2016, Feb 25). Why tech degrees are not putting more Blacks and Hispanics into tech jobs. New York Times. https://www.nytimes.com/2016/02/26/upshot/dont-blame-recruiting-pipeline-for-lack-of-diversity-in-tech.html

Buolamwini, J. (2019, Jan 25). Response: Racial and gender bias in Amazon Rekognition—Commercial AI system for analyzing faces. Medium. https://medium.com/@Joy.Buolamwini/response-racial-and-gender-bias-in-amazon-rekognition-commercial-ai-system-for-analyzing-faces-a289222eeced

Carey, R. L. (2024). Criminalized or stigmatized? An intersectional power analysis of the charter school treatment of Black and Latino boys. Urban Education, 00420859241227947. https://doi.org/10.1177/00420859241227947

Chan, E. L., & Coney, L. (2020). Moving TESOL forward: Increasing educators’ critical consciousness through a racial lens. TESOL Journal, 11(4), 1-13. https://doi.org/10.1002/tesj.550

Chen, G. A., & Buell, J. Y. (2018). Of models and myths: Asian (Americans) in STEM and the neoliberal racial project. Race Ethnicity and Education, 21(5), 607-625. https://doi.org/10.1080/13613324.2017.1377170

Chinook Fund. (n.d.) 4 I’s of oppression. https://chinookfund.org/wp-content/uploads/2015/10/Supplemental-Information-for-Funding-Guidelines.pdf

Collins, P. H. (2019). Intersectionality as critical social theory. Duke University Press. https://doi.org/10.1515/9781478007098

Combahee River Collective. (1977). The Combahee River Collective statement. BlackPast. https://www.blackpast.org/african-american-history/combahee-river-collective-statement-1977/

Crenshaw, K. (1989). Demarginalizing the intersection of race and sex: A Black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. University of Chicago Legal Forum, 1(8), 139-167.

Crenshaw, K. (1991). Mapping the margins: Intersectionality, identity politics, and violence against women of color. Stanford Law Review, 43(6), 1241-1299. https://doi.org/10.2307/1229039

Daniels, J., Nkonde, M., & Mir, D. (2019). Advancing racial literacy in tech: Why ethics, diversity in hiring & implicit bias trainings aren’t enough. Data and Society Fellowships Program. https://datasociety.net/wp-content/uploads/2019/05/Racial_Literacy_Tech_Final_0522.pdf

Devine, C., Byington, L., & News21 Staff. (2018, Aug 16). Millions are victims of hate crimes, though many never report them. Center for Public Integrity. https://publicintegrity.org/politics/millions-are-victims-of-hate-crimes-though-many-never-report-them/

Dugan, J. (2021). Beware of equity traps and tropes. Educational Leadership, 78(6), 35-40.

Ericson, B. (2023, April 10). AP CS data for 2022. Computing for Everyone. https://cs4all.home.blog/

Esposito, J., & Evans-Winters, V. (2021). Introduction to intersectional qualitative research (1st ed.). SAGE Publications.

Fairclough, N. (2014). Language and power (3rd ed.). Routledge. https://doi.org/10.4324/9781315838250

Garfinkel, H. (1967). Studies in ethnomethodology. Polity Press.

Gross, T. (2023, June 12). Central Park birder Christian Cooper on being “a Black man in the natural world.” NPR. https://www.npr.org/2023/06/12/1181314626/central-park-birder-christian-cooper-on-being-a-black-man-in-the-natural-world

Jin, C. H. (2021, May 25). 6 charts that dismantle the trope of Asian Americans as a model minority. NPR. https://www.npr.org/2021/05/25/999874296/6-charts-that-dismantle-the-trope-of-asian-americans-as-a-model-minority

Kendi, I. X. (2019). How to be an antiracist. One World.

Kuttner, P. J. (2016). Hip-hop citizens: Arts-based, culturally sustaining civic engagement pedagogy. Harvard Educational Review, 86(4), 527-555. https://doi.org/10.17763/1943-5045-86.4.527

Leonardo, Z. (2007). Teaching whiteness in a multicultural context and color-blind era [Video-stream]. University of British Columbia Centre for Culture, Identity and Education. https://www.youtube.com/watch?v=Lma988cWi5A

Losen, D. J. (2011). Discipline policies, successful schools, and racial justice. National Education Policy Center. http://nepc.colorado.edu/publication/discipline-policies

Margolis, J. & Fisher, A. (2003). Unlocking the clubhouse: Women in computing. MIT Press.

McGarr, O., Exton, C., Power, J., & McInerney, C. (2023). What about the gatekeepers? School principals and school guidance counselors attitudes towards computer science in secondary schools. Computer Science Education, 33(2), 168-185. https://doi.org/10.1080/08993408.2021.1953296

McGee, E. (2018). Black genius, Asian fail: The detriment of stereotype lift and stereotype threat in high-achieving Asian and Black STEM students. AERA Open, 4(4). https://doi.org/10.1177/2332858418816658

McGee, E. O., & Bentley, L. (2017). The equity ethic: Black and Latinx college students reengineering their STEM careers toward justice. American Journal of Education, 124, 1-36. https://doi.org/10.1086/693954

McKinsey & Company. (2024, September 17). Women in the workplace 2024: The 10th-anniversary report. https://www.mckinsey.com/featured-insights/diversity-and-inclusion/women-in-the-workplace

Noble, S. U., & Roberts, S. T. (2019). Technological elites, the meritocracy, and postracial myths in Silicon Valley. In R. Mukherjee, S. Banet-Weiser, & H. Gray (Eds.), Racism Postrace (pp. 113-129). Duke University Press. https://doi.org/10.1515/9781478003250-007

Noguera, P. A. (2003). Schools, prisons, and social implications of punishment: Rethinking disciplinary practices. Theory into Practice, 42(4), 341-350. https://doi.org/10.1207/s15430421tip4204_12

Radke, S. C., Vogel, S. E., Ma, J. Y., Hoadley, C., & Ascenzi-Moreno, L. (2022). Emergent bilingual middle schoolers syncretic reasoning in statistical modeling. Teachers College Record, 124(5), 206-228. https://doi.org/10.1177/01614681221104141

Rankin, Y. A., Thomas, J. O., & Erete, S. (2021). Black Women Speak: Examining Power, Privilege, and Identity in CS Education. ACM Transactions on Computing Education, 21(4), 1-31. https://doi.org/10.1145/3451344

Shah, N. (2021, Mar 19). Asians are good at math? Why dressing up racism as a compliment just doesn’t add up. The Conversation. https://theconversation.com/asians-are-good-at-math-why-dressing-up-racism-as-a-compliment-just-doesnt-add-up-128731

Shew, A. (2020). Ableism, technoableism, and future AI. IEEE Xplore, 39(1), 40-85. https://doi.org/10.1109/MTS.2020.2967492

Smith, R. A. (2022, July 31). Black and Hispanic employees often get stuck at the lowest rung of the workplace. Wall Street Journal. https://www.wsj.com/articles/black-hispanic-employees-stuck-lowest-rung-workplace-11659131490

Steele, C. M. (2011). Whistling Vivaldi: How stereotypes affect us and what we can do. W. W. Norton & Company.

Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69(5), 797-811. https://doi.org/10.1037/0022-3514.69.5.797

Tatum, B. D. (2003). Why are all the Black kids sitting together in the cafeteria? And other conversations about race. Basic Books.

The Sojourner Truth Project. (1851). The Sojourner Truth project. https://www.thesojournertruthproject.com/

Tiku, N. (2021, March 4). Google’s approach to historically Black schools helps explain why there are few Black engineers in Big Tech. Washington Post. https://www.washingtonpost.com/technology/2021/03/04/google-hbcu-recruiting/

Tucker, A. (2003). A model curriculum for K–12 computer science: Final report of the ACM K–12 task force curriculum committee. Association for Computing Machinery (ACM). https://dl.acm.org/doi/pdf/10.1145/2593247

Vogel, S. (2020). Translanguaging about, with, and through code and computing: Emergent bi/multilingual middle schoolers forging computational literacies. [Doctoral Dissertation, City University of New York]. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=5015&context=gc_etds

Walker, D. L., & Saklofske, D. H. (2023). Development, factor structure, and psychometric validation of the impostor phenomenon assessment: A novel assessment of imposter phenomenon. Assessment, 30(7), 2162-2183. https://doi.org/10.1177/10731911221141870

Weston, T. J., Seymour, E., Koch, A. K., & Drake, B. M. (2019). Weed-out classes and their consequences. In E. Seymour & A. Hunter (Eds.), Talking about leaving revisited: Persistence, relocation and loss in undergraduate STEM education, (pp. 197-243). Springer. https://doi.org/10.1007/978-3-030-25304-2_7

Wilkerson, I. (2020). Caste: The origins of our discontents. Random House.

Wille, S., Century, J., & Pike, M. (2017). Exploratory research to expand opportunities in computer science for students with learning differences. Computing in Science and Engineering, 19(3), 40-50. https://doi.org/10.1109/MCSE.2017.43

Resource 1: Applying the Theories in Action

Acknowledgements: Melissa M. Parker

Chapter Overview

This chapter lays a foundation for developing an equity-oriented praxis, or engaging in reflection and learning to take action to transform computer science education (CS Ed). The chapter offers guidance to support educators in journaling and dialogue practices to develop self-awareness. There are six reflection topics with prompts that invite teachers to consider their own identities and what that means for talking about topics like race, identity, and power with students; their past experiences with schooling and CS; and their motivations as CS educators. Journaling and reflection as part of developing self-awareness are important practices that are part of building an equity toolkit.

Chapter Objectives

After reading this chapter, I can:

• Explore my identities, past experiences, and motivations and how they shape my work as a CS educator.
• Journal and dialogue with critical friends to practice self-awareness and educate myself about historical and contemporary issues of (in)equity in CS Ed as part of personal development.
• Identify actions that I can take to work toward equity in CS Ed that are based on my reflections.

Key Terms:

ableism; affinity group; antisemitism; archaeology of self; classism; critical friend; dead angle; gatekeeping; homophobia; intersectionality; praxis; racism; self-efficacy; sexism; transmisia/transphobia; trigger

Amanda and Yeidy’s Stories

One of the most important steps you can take in your journey toward equity-centered CS Ed is to deepen your self-awareness and continue your learning about equity. These ongoing efforts will help you strengthen the skills you’ll need to notice, process, and respond to issues of inequity. As CS educator Karime noted, “There is no script that you can follow to respond to equity issues. This type of preparation is essential to be able to think on your feet and respond appropriately without creating further issues yourself.”

Given the intensity of an average school day, it can be difficult for teachers to stop and notice when their practices or when policies and wider systems are causing inequitable outcomes or harms. It can also be a challenge to find space and time to work toward interrupting inequitable patterns and resolving situations in an equitable manner. This chapter provides supports to hold space for this work. It will help you better understand yourself and your own role in systems that create just or unjust outcomes (Stevenson, 2014). Critical and continuous learning about your own identities and about historical and current power dynamics is a key part of this work (Price-Dennis & Sealey-Ruiz, 2021). Teachers in CS should pay special attention to the dynamics that shape CS fields, education, and broader society.

Most of this chapter is dedicated to providing you with resources so that you can learn through journaling and self-reflection. We wish to begin the chapter with an important note. Some of the topics and prompts invite you to dig deeply into your past and may be connected to challenging or traumatic past experiences that surface difficult emotions (e.g., fear, overwhelm, shame). Grappling with strong emotions can be an important part of this learning. However, we encourage you to prioritize caring for yourself — mentally, physically, and emotionally — as you do this work. Caring for yourself will look different for everyone. We provide some suggested social-emotional supports in Resource 2 that can help as you engage in the activities in this chapter. We also invite you to draw on additional resources as needed.

With this caution in mind, to begin this journey, we share stories from two teachers, Amanda and Yeidy, who described their personal growth as they have engaged in practices to support self-awareness and become more equity-minded CS educators.

Amanda shared:

Yeidy described her experiences as well:

These stories show how equity work is personal work. Amanda and Yeidy described unique journeys deeply linked to their own identities. Engaging in the practices outlined in this chapter supported both of them to expand their perspectives and grow to become CS teachers working toward equity in powerful ways.

The Role of Self-Awareness in Building an Equity Toolkit

As we recognize the complex inequities in CS and CS Ed (see Chapter 3), getting started doing equity work can feel daunting. But avoiding equity work because of its nuance and complexity only reinforces the status quo. At the same time, addressing equity issues is a long-term process. It isn’t a “quick fix” that you can easily add to your existing teaching practices. It’s something more fundamental and transformational, requiring committed work every day. It requires self-examination and learning that lead to intervening in and changing harmful policies, practices, and systems. It also requires accepting that there is no way to do this work perfectly. Everyone will make mistakes and can learn from them and do better. What works for one teacher may not work well for another because we all have different backgrounds, serve different groups of students, and face different situations. What is most important is to continue our efforts as part of an ongoing journey.

A key foundational step of this work is self-awareness, or being able to “read, discuss, and write about situations that address … inequity and … bias as part of the norm of the schooling process” (Price-Dennis & Sealey-Ruiz, 2021, p. 22). Self-awareness goes beyond learning one-off techniques to use with students. Instead, it involves committing yourself to lifelong, continuous learning that leads to individual and collective action. Self-awareness is a key component of an equity-oriented praxis.

We experience the world through our own perspectives and angles. As teachers, we bring our whole selves into the classroom — our bodies, our experiences, our beliefs and values. All of these shape what we notice and prioritize and whether and how we feel empowered to act (Rodgers & Scott, 2008). Our personal perspectives can support us to promote equitable change. We can influence practice by being positively biased toward values like social justice and affirming diversity. At the same time, we may also have dead angles, or areas related to equity work that we can’t see from our current perspectives, that keep us from promoting equitable classroom changes (Copur-Gencturk et al., 2020). These dead angles may come simply because we lack awareness or experience with a given topic. When this is the case, learning more about an issue can help us expand our perspectives and make changes. Other times, our dead angles may be based in negative biases about groups of people. In these instances, we may need to engage in deep self-reflection to shift our mindsets and beliefs. Learning to recognize and work on both types of dead angles is an important part of self-awareness as part of our equity toolkit. CS teacher Christina shared how she recognized a dead angle that she was previously unaware of as she heard students share their experiences and made changes to her classroom practice as a result:

As we noted in the beginning of the chapter, given our past experiences and backgrounds, particular conversations about power and oppression in society might be difficult. Everyone has topics that are challenging for them to engage with. These topics might trigger us, or surface strong emotions or memories. Triggers can motivate us to take actions that promote equitable practice, or they can lead us to reproduce patterns that limit equitable changes. It is important to be aware of our triggers and develop coping strategies to manage our emotional responses to these topics. (See Resource 2 for ideas.) Stronger self-efficacy, or confidence in discussing topics related to identity, can help us better notice and respond to equity issues in our settings. Proactive coping strategies in the moment can also help groups address conflicts that may arise or tensions that prevail when dialoguing about equity issues. As we develop these strategies for ourselves as individuals, we are better able to create classroom cultures that can support students when they face triggers of their own. Although addressing equity issues out loud can be challenging, it is necessary. Silence often contributes to inequity and marginalization.

While this chapter centers on self-awareness, it is important to recognize that promoting equitable CS Ed is the work of collectives, not just individuals. Equity work can be emotionally stressful and taxing when taken on by just a few. This can lead to burn-out, which doesn’t advance equitable changes at all! People whose identities have been marginalized in CS Ed often end up doing a disproportionate amount of equity work because they can’t as easily ignore inequity. But people who are afforded privilege based on their identities also have a responsibility to learn for themselves about equity issues and to use their privilege to work toward changes for educational justice (Love, 2019).

Journaling and Dialogue to Develop Self-Awareness

Being willing to probe deeply into your experiences, beliefs, values, and motivations is key to developing self-awareness on your journey to becoming a CS Ed equity leader. Scholars like Sealey-Ruiz call this work an archaeology of self, or the “deep excavation and exploration of beliefs, biases, and ideas that shape how we engage in the work [of equity]” (Sealey-Ruiz, 2022, p. 22).

There are many ways to engage in this reflection toward self-awareness. In this chapter, we focus on journaling and dialogue as activities that can deepen your understanding of equity and lead to meaningful action. Journaling involves reflecting and recording your thoughts in words, images, mapping, or another format that resonates with you. Dialoguing involves sharing some of those thoughts and reflections with critical friends and engaging in open conversation about the topics. (See Resource 3 for more on finding critical friends.) We invite you to tailor both practices to what works best for you. Below is an overview of how to engage in these practices.

Remember that journaling and dialogue are merely steppingstones on your path to embracing equitable change in CS. Let curiosity be your compass, dialogue your fuel, and action your ultimate destination.

This chapter provides prompts to reflect on the following topics:

• Unpacking identity
• Talking about race, identity, and power
• Examining school experiences
• Understanding your relationship to computing and CS
• Considering your motivations
• Relating your motivations to your students

Each topic begins with some background context and a rationale, followed by some questions to invite reflection. Feel free to focus on a specific question instead of all of them, follow the topics in any order, or return to a topic more than once. These topics are meant as a guide for your own personal journey, so you should use them in ways that are most helpful to you.

Reflection Topic 1: Unpacking Identity

Psychologist Beverly Daniel Tatum (2003) writes about “the complexity of identity.” She notes that identity is not just about how you self-define but also about who the world tells you that you are, and how you and others like you are represented in the world. Are people like you missing from the story? Highlighted or privileged in the story?

Many aspects of identity combine with social contexts to help us integrate the past, the present, and the future into a cohesive sense of self. Tatum (2003) argues that there are seven core components of identity that most shape people’s experiences in the United States: age, class, disability, gender, racialization/race, religion, and sexual orientation. Other salient identity markers in U.S. culture include our language practices, our nationality/ethnicity, our immigration status, our political party, and our geographic locations.

Identities are socially negotiated between the way we perceive ourselves and the way others and society position us. For example, in his book Dreams from My Father (1995), former President Barack Obama described how his own identity as a Black man developed in relation to the different places he lived. Because conceptualizations of race differ across cultures, Obama’s experiences around race were not the same in Indonesia, Hawaii, and the continental United States. Although he was a Black man living in each of these places, the way he understood this identity and the way others interacted with him differed greatly across contexts.

The distinction between how society assigns us identities and how we choose to identify ourselves is sometimes complicated. An individual may identify as belonging to a particular racial group, but when filling out a government survey, that option might not appear. An individual might self-identify as a member of a socially marginalized racial group but may have physical features that lead others to assume that the individual is racialized as white, affording them certain social privileges (known as “passing”). How we and others self-identify and how identities are assigned to us based on social norms are important distinctions to be aware of.^{[footnote]Efforts to articulate this distinction have led to expressions like “racialized as” that imply that racial identity labels are socially constructed, and individuals may or may not self-identify with those labels.[/footnote]}

While individuals may experience marginalization or oppression for different reasons in different contexts, in the United States, certain identity groups have been systematically afforded privileges while other groups have been systematically afforded disadvantages. This inequity is due to long-standing historical and present-day processes that shape individual action and institutional practices. (See Chapter 5 for more on this.) For example, people racialized as Black Americans have been systematically afforded less power in U.S. society. Those racialized as white Americans have been afforded more power through processes like slavery, Jim Crow laws, and many other ways that racism has been reproduced in society over time. Groups have fought to change this reality over time, but racism remains a persistent fact of U.S. life. Because identity-based inequity shapes U.S. society, CS, and CS Ed, reflecting on our own identities is key to developing self-awareness.

How someone identifies with regard to one aspect of their identity (e.g., race or gender) doesn’t necessarily imply a certain life experience. The labels applied to a person’s identity may influence, but do not fully determine, their experiences. How people are socially identified in categories is a dynamic process. The theory of intersectionality, explored in Chapter 5, can shed light on how marginalization is experienced uniquely by groups at the intersections of multiple identity categories (Crenshaw, 1991).

As teachers, our identities can afford us privileges and/or disadvantages in our professional lives. For example, Kohli (2018) describes the racist microaggressions and race evasive discourse that racially minoritized teachers reported having to navigate. These oppressions took a toll on their ability to stay in the teaching workforce.

The questions below will help you begin to unpack how power dynamics are connected to your identity and how they shape how you experience and perceive your teaching context and how others perceive you in that space. As you consider your many interrelated identities, we also invite you to think about how you can become what scholar activist Bettina Love calls “coconspirators.” Coconspirators is a positive term that describes those who move beyond allyship to take action and conspire against inequitable systems. They draw on the power and privilege afforded to them by society to work toward equitable change in educational spaces (Love, 2019).^{[footnote]Love spells this word without a hyphen.[/footnote]}

Reflection Topic 2: Talking About Race, Identity, and Power

We all have different identities. We also have different comfort levels and experiences with talking about power and identity. Given our cultural backgrounds, some topics may be considered “taboo” or unacceptable to talk about in a given community. Some of us may hesitate to have conversations on topics like race, gender and sexual orientation, and power out of fear that such conversations could get us in trouble. Because these topics are hotly contested in the United States, some avoid conversations about power and identity entirely. In some states and districts, discussing such topics in classrooms might even be grounds for disciplinary action, a lawsuit, or harsh community backlash. This reality has been manifest in recent years through book bans and legislation limiting how teachers can discuss topics like race and gender.^{[footnote]You can track legislation related to different equity-related topics at https://www.edweek.org/policy-politics/map-where-critical-race-theory-is-under-attack/2021/06 and https://www.hrc.org/resources/state-maps[/footnote]}

Some educators may feel more comfortable bringing up these topics and questioning social hierarchies. They may have had firsthand experience coping with oppressive conditions. They may have been in environments where curiosity about these issues was encouraged. They may be coming from a place of privilege, so they risk less by bringing up issues related to power. Or, they may have not experienced negative impacts from talking about these issues.

It is important to recognize that those who may feel comfortable talking about some issues of identity and power may feel less comfortable or prepared to talk about others. For example, one chapter author, a white Jewish woman, grew up talking about the effects of antisemitism with friends, family, and members of her community. Yet she also internalized a climate that put taboos around discussions about disability and race.

Part of building an equity toolkit is becoming more comfortable discussing issues of power and identity. Becoming a CS equity teacher leader means engaging in these topics proactively with students and colleagues. You can create a solid foundation for engaging in dialogue on these topics by considering your own socialization into these topics, triggers that are difficult for you, and dead angles related to these concepts.

Reflection Topic 3: Examining School Experiences

Like most aspects of our lives, people’s experiences with schooling are shaped by social and political influences related to identity. School systems may have biases embedded toward or against students with particular identities. For example, you may have been offered many opportunities to sign up for extracurricular programs to enrich your learning outside of school, or you may have had no such opportunities.

Your interpersonal interactions with classmates and educators also likely influenced how you experienced schooling. For example, if you are a member of a group that is afforded less power in society, you may have been exposed to oppressive conditions, prejudice, or microaggressions related to that identity that have added up over time. If you are a member of a group that is typically afforded more social power, you may have received positive messages about your potential. Or perhaps your experiences resist these patterns for particular reasons.

Your experiences affect your impressions of school growing up, which can inform how you currently teach. It’s important to understand these schooling experiences so that you can understand why you may react in certain ways to things in your current school environment. Reflecting on your schooling experiences can also help you avoid recreating harms you may have experienced and help you pass on opportunities that were afforded to you.

It is equally important to recognize how your experiences may not be shared by students in your school, even when they share similar identities. These differences may be due to students’ personal lives, how schools function, or how society has changed over time.

Reflection Topic 4: Understanding Your Relationship to Computing and CS

How we relate to CS is shaped by our exposure to it. And our exposure to computing is often shaped by broader systems of oppression and advantage (see Chapter 5). Like any school subject, there are ways in which we have been encouraged or discouraged to engage with CS. Some of us may have been provided with access to new tools and technology at home from a young age. Others may have had to rely on low-resourced schools to expose them to technology. Some of us may have been encouraged to tinker with code or have been praised for our creativity for trying to “hack” or “mod” our favorite games. Others may have been outright discouraged from or denied access to CS or been informed that CS exploration was a waste of time.

In formal school settings, you may have been told that you were smart enough to take a CS class, or you may have been told that you would never make it in that environment. You may have associated technology with a nerdy subculture, which might have attracted you to computing or repelled you away. All of these factors affect your relationship to CS and influence how you talk to students and colleagues about their CS abilities. Understanding our own relationship to CS can help us break unhealthy cycles of exclusion and create more inclusive CS experiences for others.

Reflection Topic 5: Considering Your Motivations

Educators come to teaching for many reasons, and CS educators come to CS teaching for many reasons. To promote equitable practices, it’s important to understand your “why,” or your motivation(s) for what you do. Are you looking to prepare the next generation for economic opportunities? Do you hope to support young people in expressing themselves creatively about issues they care about? Are you looking to promote skills like problem solving, collaborating, and persistence? Is coding with young people fun and fulfilling for you?

Our whys are unique and may be connected to our own histories. For example, some educators may feel a responsibility to provide opportunities for children because they did not get those same opportunities when they were students themselves. Conversely, they may wish to provide those opportunities because they did experience them as students and found them powerful and motivating.

Our whys propel us to act and keep us motivated on tough days. At the same time, not all rationales promote equitable classroom practices. For instance, we may make assumptions about who can thrive in CS based on our own experiences with gatekeeping in the field. Similarly, we should interrogate or challenge motivations for CS Ed that are rooted in savior complexes seeking to “save” or “rescue” marginalized groups through technology. These motivations can reproduce deficit narratives about students and disempower them. The following prompts will help you consider your own motivations for teaching CS.

Reflection Topic 6: Relating Your Motivations to Your Students

Your whys and your experiences should inform and motivate your classroom work. At the same time, it is important to recognize that your students’ whys will likely be different from yours because of their differing identities and experiences. Focusing on a narrow set of purposes for CS Ed in your classroom, like getting a high-paying job as a software engineer, might leave out students who don’t resonate with that rationale. CS educator Christina built on this idea:

Listening to students’ interests and motivations can help you shape your curriculum or standards in ways that meet your students’ interests and goals.

To explore this topic, it’s important to think about who your students are and how you get to know about their backgrounds, experiences, interests, and talents. As you narrow in on your motivations, consider how who your students are might shape the motivations they have. Consider as well how their experiences with CS and CS Ed might be shaped by their different identities and how those identities have been positioned in society. Reflections like these can help you understand how historical and current power dynamics shape your experiences with your students.

Revisiting Amanda and Yeidy’s Stories

Amanda and Yeidy are not the only ones who have found journaling, dialogue, and reflection beneficial. Many of the teachers we have worked with shared how these practices helped them develop self-awareness and gave examples of how their learning led to changes in their practice. Journaling, dialogue, and reflection are key to building an equity toolkit and the foundation for an equity-oriented praxis.

Amanda concluded her thoughts with the following reflection on journaling as a practice:

Reflection Questions:

1. What do you think about the journaling and dialogue practices described in this chapter? How can you see them being beneficial? What challenges might arise trying to engage in these practices?
2. The topics covered in this chapter are not comprehensive. What other topics might you benefit from reflecting on as you engage in equity work in your setting?

Takeaways for Practice:

• Choose one topic and journal about it. Reflect on the experience and consider how you might adapt the journaling practices described in this chapter to fit your personal preferences and circumstances.
• Engage in dialogue with a critical friend about a topic in this chapter. Reflect on the new insights that you came away with as a result of your conversation.

Glossary

References

Collins, P. H. (2019). Intersectionality as critical social theory. Duke University Press. https://doi.org/10.1215/9781478007098

Copur-Gencturk, Y., Cimpian, J. R., Lubienski, S. T., & Thacker, I. (2020). Teachers’ bias against the mathematical ability of female, Black, and Hispanic students. Educational Researcher, 49(1), 30-43. https://doi.org/10.3102/0013189X19890577

Crenshaw, K. (1991). Mapping the margins: Intersectionality, identity politics, and violence against women of color. Stanford Law Review, 43(6), 1241-1299. https://doi.org/10.2307/1229039

Kohli, R. (2018). Behind school doors: The impact of hostile racial climates on urban teachers of color. Urban Education, 53(3), 307-333. https://doi.org/10.1177/0042085916636653

KosmicKult. (2020, July 19). Hate is NOT fear: Reframing homophobia, biphobia, and transphobia. Medium. https://medium.com/@kosmickult/hate-is-not-fear-reframing-homophobia-biphobia-and-transphobia-beabec366dc6

Love, B. L. (2019). We want to do more than survive: Abolitionist teaching and the pursuit of educational freedom. Beacon Press.

Obama, B. (1995). Dreams from my father. Three Rivers Press.

Planned Parenthood. (n.d.). What’s transphobia, also called transmisia? Planned Parenthood. https://www.plannedparenthood.org/learn/gender-identity/transgender/whats-transphobia

Price-Dennis, D., & Sealey-Ruiz, Y. (2021). Advancing racial literacies in teacher education: Activism for equity in digital spaces. Teachers College Press.

Rodgers, C. R., & Scott, K.H. (2008). The development of the personal self and professional identity in learning to teach. In Cochran-Smith, M. Feiman-Nemser, McIntyre, D. J., & Demers, K. E. (Eds.), Handbook of Research on Teacher Education (3rd ed., pp. 732-755). Routledge & Association of Teacher Educators. https://doi.org/10.4324/9780203938690

Sealey-Ruiz, Y. (2022). An archaeology of self for our times: Another talk to teachers. English Journal, 111(5), 21-26. https://doi.org/10.58680/ej202231819

Shew, A. (2020). Ableism, technoableism, and future AI. IEEE Xplore, 39(1), 40-85. https://doi.org/10.1109/MTS.2020.2967492

Stevenson, H. C. (2014). Promoting racial literacy in schools: Differences that make a difference. Teachers College Press.

Tatum, B. D. (2003). Why are all the Black kids sitting together in the cafeteria: And other conversations about race. Basic Books.

Resource 1: Journal Prompts Reference

Resource 2: Therapeutic Techniques to Support Reflection

Resource 3: Finding Critical Friends

Acknowledgements: Melissa M. Parker

Chapter Overview

This chapter builds on previous chapters, inviting readers to set commitments and lead out in equity-centered computer science education (CS Ed). The chapter considers making commitments in four areas: (1) self-awareness and personal learning; (2) ways of seeing and being with others; (3) advancing CS pedagogy; and (4) advocating for equitable change in CS Ed. The chapter also offers tools to create a plan for setting commitments and identifying goals that work toward change.

Chapter Objectives

After reading this chapter, I can:

• Explain how commitments are part of an equity-oriented journey.
• Set commitments as a CS educator that are specific to myself, my students, and my CS Ed context.
• Identify action steps I can take to work toward equity in my CS Ed context.

Key Terms:

advocacy; commitment; critical consciousness; deficit framings; host leadership; praxis; savior complex

Christina’s Story

Chapter 6 focused on journaling, dialogue, and reflection as key practices in developing self-awareness and the ability to discuss inequity. An important next step is setting commitments, or pledging to a course of action, that will work toward equity in CS Ed. This chapter will explore four areas where you can commit to engage in a journey of equity-oriented praxis.

To get started, let’s hear from Christina, a CS teacher who has made multiple commitments as part of her equity journey that have led to changes in her classroom and her work as an educator.

Christina’s story illustrates how making commitments leads to taking action. Christina’s commitment to personal development led her to take PDs and read. Her commitment to advocacy led her to “fight” for CS opportunities for all students. However, her story also shows how commitments are part of the ongoing process of working toward equity in CS Ed. For example, her commitment to giving students a voice in the classroom is not something that is always comfortable for students because it is new. This commitment is something that Christina and her students are still working on. In this chapter, you’ll consider which commitments can best help you take action in your CS Ed settings.

Committing Yourself to a Journey

As an educator in CS, you stand at the threshold of a discipline and an industry that continues to reshape our world. Computing is social and political — computing fields and tools can improve lives but also cause harm and perpetuate injustice. This tension is often not made explicit in classrooms where students are learning CS. Teachers who explicitly acknowledge power dynamics in CS fields and education in their classrooms can promote more relevant, inclusive, and empowering CS Ed for everyone.

As Christina’s story shows, this work is a journey. The nature of this journey requires committing yourself to ongoing efforts that promote and center equity. While you make personal commitments focused on your own sphere of influence, this work is not meant to be done alone. Equity work is most successful when you are supported in your commitments by colleagues, school and district leadership, and broader institutions and policies. Your role requires working to develop personal self-awareness, working for change in your classroom and beyond, and engaging in shared leadership in community.

This chapter considers four areas in which you can make commitments and plan to take action for yourself, your students, and your teaching to serve as an advocate and leader.

These areas include:

• self-awareness and personal learning;
• ways of seeing and being with others;
• advancing CS pedagogy; and
• advocacy for equitable change in CS Ed.

We provide examples of commitments in each area to help you get started. But we also invite you to draw on your reflections from previous chapters, especially Chapter 6, to create commitments that represent yourself, your identities, your work, and the communities that you are a part of.

Area #1: Self-Awareness and Personal Learning

The first area involves committing to taking action to understand yourself and your own identity, to strengthen your ability to engage in dialogue about equity issues, and to continue your personal learning. We invite you to commit to developing your knowledge about social dynamics that shape educational contexts broadly and within CS and CS Ed specifically. This includes things like expanding your understanding about issues related to topics like class, disability, gender and sexual orientation, language, and race and ethnicity. An important related skill is learning to take stock of your in-the-moment emotional reactions to issues of identity and power. Developing this self-awareness is essential to adequately respond to equity-related challenges in the classroom. We begin with critical self-reflection and then become students of historical and contemporary social inequities in computing, computing education, and the wider society. We can then examine the veracity of our own assumptions and beliefs and take steps toward interrupting harmful myths. We can also give ourselves grace, space, and time to do this work. There is no way to develop perfect self-awareness. Everyone will make mistakes, learn, and move forward. The key is to continue in the process. Changing our own ideas over time is necessary to change how we show up for our students.

CS teacher Amanda shared an example of how her classroom practices changed as a result of her commitment to continual learning and an awareness of her own racial identity in relation to her students and her CS curriculum.

Amanda’s commitment to critical learning about issues related to race and gender led to rich discussions about social justice topics with her students. Her awareness of her own internal hesitancy to engage in conversations about race and her commitment to continued learning allowed her to take action and deepen her conversations with her students in ways that addressed broader issues of identity and power.

Area #2: Ways of Seeing and Being with Others

The second area to consider is how you perceive and share spaces with others, including students and their families, your colleagues, and the communities to which you belong.

Because our own perspectives shape the work we do in classrooms, we must critically examine and expand the lenses through which we view those around us. Some teachers perceive students through deficit framings and focus on what students lack or cannot do. This may lead to savior complexes, or a sense of needing to “save” or “rescue” marginalized groups. By contrast, students know when a teacher values who they are as a full person and respects their dignity as a learner by “recogniz[ing] and cultivat[ing] one’s mind, humanity, and potential” (Espinoza et al., 2020, p. 326). We can counter deficit narratives about learners by learning about our students and respecting their humanity, their full identities, their insights and contributions, and their potential. When we see and interact with students in these ways, students are more likely to feel a greater sense of belonging and succeed.

Respecting the dignity of our students and cultivating their humanity and potential can be done in many ways. One key way is supporting our students to enact changes that they think are important in the world. We can use our classrooms, curriculum, and pedagogical practices as tools that promote our students’ critical consciousness, or a social and political awareness of how social inequities are created and reproduced. Critical consciousness is a powerful tool for students who are afforded power based on their identities and those who may be marginalized because of their identities. As students come to recognize their own power, even as youth, they can use computing to become change agents in their communities and beyond.

Amanda, the CS teacher from the previous section, shared one of her commitments related to seeing and being with students:

Amanda’s commitment has already shaped her practice — from how she decorates her classroom to her curriculum to the expectations she has for her students. Even more significantly, Amanda’s commitments are guiding her current and future work. Her plans to take action by inviting her colleague to revise an existing project will engage students in critically examining the role of colonization and create a more equity-oriented learning opportunity.

Area #3: Advancing CS Pedagogy

Another place to commit to take action is with regard to CS pedagogy. It has been well documented that CS is often taught in ways that can exclude some groups. Given the history of inequitable practices in CS Ed, we invite you to consider commitments related to advancing pedagogy in ways that support all learners to take part in deep, rigorous CS learning (Hammond, as cited in Rebora, 2021).

Accomplishing this goal involves building on the diversity of learners and their backgrounds. As Black feminist scholar, educator, and activist bell hooks noted in her book Teaching to Transgress, “pedagogy must insist that everyone’s presence is acknowledged. That insistence cannot be simply stated. It has to be demonstrated through pedagogical practices.” (hooks, 1994, p. 8). Culturally and linguistically responsive pedagogies acknowledge everyone’s presence and affirm, value, and extend the diverse abilities, experiences, language practices, and identities of marginalized communities. They involve teaching responsively by developing new strategies to learn about our students and to transform the way we teach based on what we learn. Such approaches push back on the notion that the cultures that dominate CS and CS Ed now are the only or best cultures for CS. These kinds of pedagogies deepen and transform learning for all students, including those from dominant groups, and they can especially benefit marginalized students (Eglash et al., 2013; Lachney et al., 2021; Mirakhur et al., 2021; Vogel et al., 2020). The remainder of this guide (Chapters 8-17) focuses on specific techniques, rooted in critical pedagogy and research in equity-centered CS Ed, that can help you accomplish goals related to these commitments.

CS teacher Brandie shared an example of an activity that she incorporated into her CS instruction that was tailored to students’ interests and also worked to develop their critical consciousness.

Brandie explained her approach:

Last year, I started What’s News in Tech? lessons. I was inspired by wanting to incorporate current events into the curriculum so that students were knowledgeable about current developments in tech, but I also wanted students to be critical of the tech — considering benefits and harms.

I was inspired by the Teaching Black History All Year Institute presented by Sonja Cherry-Paul and Colleen Cruz who shared a note-taking structure that included four key components. I created my own structure for analyzing tech and guided the kids in using this graphic organizer. (See Figure 1.)

Figure 1
Graphic Organizer to Evaluate Technology Tools

I was intentional about including the second and third question in the Pros and Cons section because I thought it was a good way to include equity as a lens through which to analyze text. Having the questions present as an expectation for the kids to think about was a powerful framework for teaching kids to be critical about accessibility, effectiveness, and the impact of technology on everyone.

Brandie’s commitment to equity-centered pedagogy led her to tailor an existing tool and adapt it to her CS context. This move empowered her students to develop skills to critically analyze technological tools and their impact on society through an equity lens.

Area #4: Advocacy for Equitable Change in CS Ed

An equity-oriented praxis also includes shared leadership and advocacy for broader equitable changes in CS educational policies and structures. No individual person can wave a magic wand and make CS, education, or anything else equitable. And yet, as professionals and teachers, CS educators can make a tremendous difference in how just or unjust the lives of our students will be. The ways we show up, the choices we make, the relationships we form in classrooms, and how we use our own voices to amplify students’ voices have profound impacts on society and on students. It can be tempting to imagine solving problems of oppression in CS by focusing solely on our own classrooms. Yet these problems, by their nature, require engaging the larger world, and as education professionals, we have an ethical responsibility to do so.

The National Equity Project describes this advocacy as leading as a “host” rather than as a “hero” (National Equity Project, n.d.). Hero leadership is described by the National Equity Project as “planning the work and working the plan.” Because a hero approach is often done in isolation or is disconnected from the communities impacted by an inequitable status quo, hero leadership may fall short of lasting change and can lead to savior complexes. By contrast, host leadership requires building coalitions across communities that involve listening, multiple perspectives, and working collectively for change. Liberatory design mindsets can help build these coalitions (Anaissie et al., 2021). Liberatory design mindsets include building relational trust, practicing self-awareness, recognizing oppression, embracing complexity, focusing on human values, seeking liberatory collaboration, working with fear and discomfort, attending to healing, working to transform power, exercising creative courage, taking action to learn, and sharing instead of selling ideas. Enacting these orientations in community with others can allow groups to navigate the complexity of equity work and develop creative and lasting solutions. Change may begin in our own classrooms, but by necessity it must be larger, encompassing not only our own hearts and minds but the hearts and minds of those around us.

Planning for Change

Committing to equity work in CS Ed is a multi-layered process. Figure 2 illustrates this idea through three nested circles that cover the four areas explored in this chapter. While equity work starts within, it quickly expands outward to encompass leading for transformative change.

Figure 2
Committing to Equity Work

Committing to equity work across these different areas might feel overwhelming. But it is important to remember that this work is not something to be accomplished all at once. Small, consistent efforts can make a big difference, a concept that scholar Ruha Benjamin referred to as “viral justice” (Benjamin, 2022). Commitments help provide a sense of purpose and direction on our journey, offering an orientation that can guide our everyday actions. It may help to translate your commitments into small, concrete action steps. You might break down a broader commitment into actions that span different amounts of time. (e.g., Today, I will …; This week, I will …; This month, I will …; This quarter or semester, I will …). The size of your commitments and actions is not important. What matters most is that you find ways that work for you and are consistent in your efforts on this journey.

We invite you to try setting a commitment below. Consider the thoughts, ideas, and experiences that have come to your mind as you have read this chapter. Resource 1 is a similar worksheet that can help you identify and set your CS equity commitments.

Revisiting Christina’s Story

Christina’s practice of setting commitments and taking action as part of her own equity journey has continued, and she has identified ways to hold herself accountable and to monitor her growth. Christina shared:

Christina also highlighted how her efforts have been amplified as she has joined in communities beyond her classroom and moved toward advocacy:

Like Christina, in this chapter we have invited you to begin a journey of transformation. This journey will make your own CS teaching more inclusive and equitable and help you advocate for equitable changes in CS Ed and CS fields. To change how our classrooms function, we have to focus on our own roles in systems of oppression or liberation and better understand how power affects both the historical and current world of CS. As we raise our own self-awareness of how those systems have affected our experiences with society, with schooling, and with technology, we can commit ourselves to being a part of more systemic change. That will, of course, impact how we teach or what we might do in our own classrooms, but it can also put us on a path to act as advocates, leaders, and movement builders in our communities. As we become “hosts not heroes,” we turn personal goals for equity into shared work toward equitable change.

Reflection Questions:

1. Which suggested commitments from this chapter resonate with you? What ideas come to mind for how those commitments apply to your own CS Ed context?
2. What stands out to you about making commitments and taking action from the teacher examples in this chapter? How can you remind yourself that this work is an ongoing process and journey?

Takeaways for Practice:

• If you haven’t already, set some commitments based on this chapter. The chapter resources can help with this.
• Identify 2-3 individuals with whom you can share your commitments. Create an action plan to periodically check in with them and discuss your progress, challenges that have arisen, and successes that you’ve experienced.

Glossary

References

Anaissie, T., Cary, V., Clifford, D., Malarkey, T., & Wise, S. (2021). Liberatory design: Mindsets and modes to design for equity. Liberatory Design. https://static1.squarespace.com/static/60380011d63f16013f7cc4c2/t/60b698f388fe142f91f6b345/1622579446226/Liberatory+Design+Deck_June_2021.pdf

Benjamin, R. (2022). Viral justice: How we grow the world we want. Princeton University Press. https://doi.org/10.1515/9780691222899

Eglash, R., Gilbert, J. E., Taylor, V., & Geier, S. R. (2013). Culturally responsive computing in urban, after-school contexts: Two approaches. Urban Education, 48(5), 629-656. https://doi.org/10.1177/0042085913499211

Espinoza, M. L., Vossoughi, S., Rose, M., & Poza, L. E. (2020). Matters of participation: Notes on the study of dignity and learning. Mind, Culture, and Activity, 27(4), 325-347. https://doi.org/10.1080/10749039.2020.1779304

hooks, b. (1994). Teaching to transgress. Routledge. https://doi.org/10.3366/para.1994.17.3.270

Lachney, M., Bennett, A. G., Eglash, R., Yadav, A., & Moudgalya, S. (2021). Teaching in an open village: A case study on culturally responsive computing in compulsory education. Computer Science Education, 31(4), 462-488. https://doi.org/10.1080/08993408.2021.1874228

Ladson-Billings, G. (1995). But that’s just good teaching! The case for culturally relevant pedagogy. Theory Into Practice, 34(3), 159-165. https://doi.org/10.1080/00405849509543675

Louie, N., Adiredja, A. P., & Jessup, N. (2021). Teacher noticing from a sociopolitical perspective: The FAIR framework for anti-deficit noticing. ZDM-Mathematics Education, 53, 95-107. https://doi.org/10.1007/s11858-021-01229-2

Mirakhur, Z., Fancsali, C., & Hill, K. (2021). The potential of CR-SE for K-12 computer science education: Perspectives from two leaders. Voices in Urban Education, 50(1). https://doi.org/10.33682/3en3-cbgn

National Equity Project. (n.d.). Networks and communities of practice. https://web.archive.org/web/20240808060608/https://www.nationalequityproject.org/networks

Rebora, A. (2021). Zaretta Hammond on equity and student engagement. Educational Leadership, 79(4), 14-18. https://www.ascd.org/el/articles/zaretta-hammond-on-equity-and-student-engagement

Steele, C. M. (2011). Whistling Vivaldi: How stereotypes affect us and what we can do. W. W. Norton & Company.

Vogel, S., Hoadley, C., Castillo, A. R., & Ascenzi-Moreno, L. (2020). Languages, literacies and literate programming: Can we use the latest theories on how bilingual people learn to help us teach computer literacies? Computer Science Education, 30(4), 420-443. https://doi.org/10.1080/08993408.2020.1751525

Resource 1: My Commitments to Equitable CS Ed

Resource 2: Suggested Commitments to Equitable CS Ed

Chapter Overview

This chapter introduces the concept of digital racial literacy as an application of frameworks that examine racial literacy in the context of technology. Digital racial literacy involves developing students’ awareness of the relationships between race and technology, preparing students to manage emotions connected to racism in computer science (CS), and empowering students to critique and use technology to disrupt inequities. The chapter begins by exploring how racism and racial-ethnic bias shape computing. It then considers how to promote digital racial literacy in CS education (CS Ed) through internal reflection and self-examination and through an examination of racial socialization processes. The chapter concludes with strategies to develop digital racial literacy in CS classrooms. This chapter is intentionally written for self-reflective practice in community with others. It is highly recommended that this chapter is read and discussed individually and with colleagues or critical friends to pause, reflect, and identify steps to take action.

Chapter Objectives

After reading this chapter, I can:

• Identify ways that racial bias has impacted technology.
• Define digital racial literacy and explain its connection to CS and CS Ed.
• Reflect on my racial identities and experiences in preparation for developing my students’ digital racial literacy.
• Define racial socialization and identify ways that students are socialized about race in my CS Ed context.

Key Terms:

critical race theory; digital racial literacy; Four I’s of Oppression and Advantage; racial-ethnic; racial-ethnic socialization; racial literacy; racism; RECAST framework

Brandie’s Story

Brandie is an elementary CS teacher committed to an equity-oriented CS practice. One of her commitments involves helping students become aware of inequities that exist in technology fields. Brandie described a lesson she created for her students:

Through her lesson Brandie sought to develop her students’ digital racial literacy about technology — their awareness of bias in technology, their ability to navigate emotions that surface when exploring racial and ethnic issues in tech, and their ability to take action to disrupt inequity in tech. In this chapter, we’ll consider the relationships between race and ethnicity, technology, and CS Ed as part of understanding the important need to develop digital racial literacy in CS Ed.

The Racialized Landscape of Computing and CS Ed

Tech is racist and sexist and ableist because the world is so. Computers just reflect the existing reality and suggest that things will stay the same — they predict the status quo. By adopting a more critical view of technology, and by being choosier about the tech we allow into our lives and our society, we can employ technology to stop reproducing the world as it is, and get us closer to a world that is truly more just.

-Broussard (2023)

In her powerful text, More than a Glitch, professor and journalist Meredith Broussard shares the above quote that serves as a stark reminder of the pervasive social biases that are deeply entrenched in our society. One of the most pervasive of these systems is racism. By racism, we mean the individual prejudice, systemic oppression, and inequitable access to power and resources that result from perceived differences between one socially constructed racial category and another (Harris, 1993; Kendi, 2019).^{[footnote]We recognize that racism also encompasses inequitable access to power and resources based on socially constructed ethnic categories. In this chapter, when we refer to race, we also include ethnicity in that discussion. The term “racial-ethnic” is used to emphasize this relationship.[/footnote]} CS educators face immense challenges, as they are at the front lines of teaching in a world that is inherently racist and where technology, rather than serving as a neutral tool, instead serves to embed, amplify, and perpetuate racism.

Educators bear a profound responsibility to support children and young people to navigate this complex landscape and to work together to achieve a more just and inclusive understanding of technology. The enormity of this task is underscored by the need to teach the technical aspects of computing as well as address deeply ingrained biases to dismantle the discriminatory structures embedded within the field.

Despite ongoing efforts to reduce harm and bias in tech, these efforts have often fallen short. In part, this is due to a lack of attention to developing the digital racial literacy of those who work in tech-related industries. By digital racial literacy, we mean an awareness of bias in technology, an ability to navigate emotions that surface when exploring racial and ethnic issues in tech, and an ability to take action to disrupt inequity in tech (Talley, 2022). Digital racial literacy brings together existing frameworks (Daniels et al., 2019; Price-Dennis & Sealey-Ruiz, 2021; Stevenson, 2014) to offer a concrete application of these ideas in CS Ed.

This chapter will help educators get started on their journey to develop digital racial literacy. It begins with an overview of the realities of computing and computing education in a racialized world to build factual awareness. The remainder of the chapter explores what we mean by digital racial literacy in CS and how we promote it in our CS classrooms. Journaling and reflection prompts are embedded throughout the chapter to help readers develop emotional preparedness. (See Chapter 6 for further guidance on journaling and dialogue practices.)

Computing in a Racialized World

A complex web of racial biases affects every facet of society, perpetuating disparities that span all Four I’s of Oppression (ideological, institutional, interpersonal, and internalized; see Chapter 5). Computing technologies and their deployment in marginalized communities amplify negative racial biases in our society and unjustly impact these communities. As was introduced in Chapters 2 and 3, racial biases shape algorithms that impact everything from search engine results to job hiring processes to criminal sentencing procedures. Below are some specific examples of how racial bias in technology pervades tech industries.

Racial biases embedded in technology play a significant role in perpetuating injustice across many areas of social life. At the same time, some have mobilized computing tools and technologies to promote social activism and to advocate for racial justice. Activist groups have organized in digital spaces, including social media. One notable example is the #BlackLivesMatter social media strategy, led by Tamia Mallory. See Table 3 in Chapter 4 for additional examples.

Computing Education in a Racialized World

Statistical realities cast a somber light on the impact of racial biases on the state of computing education. Black, Latine, and Indigenous youth in the United States are excluded from CS Ed at alarming rates.^{[footnote]See the On Terminology section of this guide for an explanation on our use of different identity-related terms.[/footnote]} Furthermore, these groups often encounter barriers that impede their access to quality CS Ed, contributing to a troubling lack of diversity in the field. Asian youth across many ethnic groups also face stereotyping and harassment in CS Ed.

The tech workforce, access to CS Ed, and new technology development are all inherently political and subject to the racialization processes embedded in U.S. society. This reality raises the stakes for CS educators who want to advance equitable CS Ed. Acknowledging the severity of these issues in the real world can be scary. However, we must not avoid empowering our students to be informed consumers of technology and their social world. When confronted with a field that has been shown to both exclude and perpetuate harm toward racially marginalized communities, CS educators might feel helpless and overwhelmed. The task can seem even more difficult when we are asked to promote the racial-ethnic diversification of the CS industry and to prepare students to be wise consumers of technology as central goals of many CS Ed efforts in schools today.

Despite broad-scale efforts to increase equitable practice in CS, translating these aims into tangible classroom practices remains challenging. Much rich work is being done examining race in relation to CS and CS Ed using a variety of different constructs (see, for example, Jones & melo, 2021; Lachney et al., 2019; Lachney et al., 2023; Tanksley, 2023; Tanksley, 2024). The concept of digital racial literacy aids in translating equity aims into classroom practice. Central to these efforts is promoting students’ awareness of and ability to manage topics related to race-ethnicity in their daily lives and tech spaces, particularly for students who are underrepresented in tech, such as African American students, Latine students, and students from Indigenous nations.

What Do We Mean By Digital Racial Literacy in CS?

CS educator Dawn shared an example of how she worked to promote students’ awareness of topics related to race and ethnicity in their lives:

As Dawn’s example shows, many of the issues that impact equity in CS and CS Ed are undergirded by a fundamental lack of digital racial literacy. CS Ed often falls short of preparing students to gain an awareness of bias in technology, an ability to navigate emotions that surface when exploring racial and ethnic issues in tech, and an ability to take action to disrupt inequity in tech (Talley, 2022).

While scholarly frameworks like critical race theory are helpful to understand macro level racial inequities, they fail to instruct us in the day-to-day practices that will shape a more equitable CS field (Bell, 2023; Delgado & Stefancic, 2023; Ledesma & Calderón, 2015). By contrast, digital racial literacy can help educators assess their own readiness for discussing and confronting topics related to racial bias with students in their classrooms. It can also help teachers prepare students to be knowledgeable consumers of tech and prepare those who aspire to tech careers for the racialized encounters they will experience in the workforce.

Digital racial literacy can be especially empowering for minoritized students who have experienced marginalization around race and ethnicity. Yet ultimately, this kind of learning helps all students become more conscientious makers and consumers of technology. Incorporating digital racial literacy practices into computing education helps students develop an appreciation of how racial-ethnic minoritized people have shaped CS and recognize how our actions can shape the future diversity of the tech workforce and the experiences of their fellow citizens.

Race and racial conflicts impact educational spaces broadly. Seeking to address this reality, Stevenson (2014) developed frameworks to explore notion of racial literacy. Racial literacy involves a historical and factual awareness of racial issues in the classroom and the emotional preparedness needed to discuss and engage with these issues. Stevenson proposed the Racial Encounter Coping Appraisal Socialization Theory (RECAST) framework as a practical way to address racial stress and trauma. It has three components: READ, RECAST, and RESOLVE. READ focuses on developing a historical and factual awareness of race and racial politics and of your own racial identity. RECAST offers strategies to manage and cope with racial stress and trauma, including developing emotional preparedness. RESOLVE focuses on addressing and taking action against the root causes of racial tension and trauma. The RECAST framework is explored in greater detail in Chapter 9.

As discussed above, race intersects with the digital world in important and unique ways. Given the need to make technologies and the industries that produce them more racially equitable and diverse, practitioners and scholars have defined what it means to practice racial literacy specifically within the realm of technology. Building on Stevenson’s (2014) work, Daniels and colleagues (2019) developed a foundational definition for racial literacy in technology.

These tenets provide a set of broad goals for CS educators to aspire to as they orient themselves to teaching youth about racial-ethnic contributions and bias in CS.

Scholars Price-Dennis and Sealey-Ruiz (2021) have considered specifically how to support teachers to develop racial literacy in the digital age. They offer strategies such as archaeology of the self as a process that allows teachers to come to terms with how racism, stereotypes, and bias shape them individually. These strategies are practical ways that support developing racial literacy in tech.

How Can We Promote Digital Racial Literacy in CS Classrooms?

Digital racial literacy pairs Daniels and colleagues’ (2019) racial literacy in tech framework with Price-Dennis and Sealey-Ruiz’s (2021) focus on helping teachers develop racial literacy and applies them through Stevenson’s (2014) RECAST theory of racial literacy. Digital racial literacy offers a novel way for teachers and students to concretely engage with racial inequity in technology. Within the computer classroom, digital racial literacy can be translated into the following three efforts.

In terms of classroom practice, this means intentionally incorporating the contributions and experiences of racial-ethnic minoritized people in tech into our classroom practice. It also means exploring with students the harms and challenges that technology presents to racial-ethnic minoritized communities. We must attend to the social-emotional component of this content by embedding appropriate therapeutic and emotional management strategies into our discussions of race-ethnicity to bolster students’ abilities to process and face racialized encounters in the tech space. With this intellectual and emotional preparedness, students can then harness CS to promote justice.

There are many avenues to focus on when addressing racial-ethnic inequities in CS. However, there are four that are particularly important in school-based CS Ed. These issues closely follow the CS Ed-to-tech workforce pipeline and are areas that can be directly influenced by CS educators.

Incorporating these four areas into CS teaching can promote diversity and inclusion in tech and prepare students to promote justice in their local and national communities.

To prepare you as an educator to engage in this work with your students, we invite you to pause and reflect on what you have read so far by completing the following reflection prompts. (See Chapter 6 for additional guidance on journaling and reflection.)

Looking Inside: Exploring Our Internal Landscape

In our journey toward digital racial literacy in CS Ed, it is imperative to begin by turning inward and examining our personal responses to issues of race. Broussard’s (2023) quote at the beginning of the chapter serves as a poignant reminder that technology, like any other facet of our society, reflects existing biases and inequalities. To break away from perpetuating the status quo, we must first engage in an introspective process.

Much of this chapter has grown out of a collaboration with the Exploring Equity in Computer Science (EECS) in New York City Public Schools as part of their Computer Science for All initiative (see Preface for more information). When EECS began, there was a measurable need to improve educators’ awareness, emotional management, and social justice orientation toward race and ethnicity. In our work with EECS educators, we consistently found that the topic of race-ethnicity is one of the more confusing and viscerally stressful social identity categories that they encounter daily (Crawford et al., 2023). In EECS program sessions, it became evident that many CS educators hold misconceptions about (1) race-ethnicity, (2) how discrimination manifests in tech, and (3) the contributions of marginalized CS innovators. These responses to the stressfulness of racialized experiences are a microcosm of global social dynamics on race, which are especially apparent in CS and tech.

Working with educators across all disciplines, integrating the topics of race and bias into classroom practice consistently elicits similar reactions (Talley, 2021; Talley, 2022). When encountered, these misconceptions are often met with avoidant, fearful, and even angry responses from educators. Similarly, it is difficult for those with a strong passion for racial and ethnic justice to manage their anger, fear, and avoidance when advocating for their views about race and ethnicity in tech. So if you are feeling any of these things right now, know you are not alone.

As we embark on the journey of teaching computing in a racialized world, let us recognize the transformative potential within our hands. The challenges are immense, but the impact of educators in shaping a more equitable future is equally profound. Together, let us navigate the front lines of equitable practice, armed with knowledge, empathy, and a commitment to dismantling the negative biases that pervade our technological landscape. Take a moment to consider your own position with regard to racial-ethnic issues.

While Chapter 6 invites you to engage in this process holistically about your identity and past experiences, in this chapter, we invite you to engage in reflection specifically around your racial identities. The prompts below will help get you started (Talley, 2022). Remember you can refer to Chapter 6 for guidance on journaling, as well as supports for navigating emotions that may arise while engaging in this reflection.

As CS educators, we all possess racial identities and opinions about race in tech. Recognizing that these conversations may be sensitive, we must actively engage in the Archeology of Self to navigate and understand our own emotional responses (Price-Dennis & Sealey-Ruiz, 2021). By doing so, we equip ourselves to create a more inclusive and equitable learning environment, fostering the social-emotional capacities necessary for addressing racial stress and trauma in the CS classroom.

Looking Around: How Our Students Learn About Race

CS educators must recognize that race can be a sensitive and challenging topic to discuss in the classroom. However, avoiding these issues leaves a significant gap in CS Ed by continuing patterns of silence and race-evasiveness or avoiding discussions of race and ethnicity, that reproduce existing inequities. To ensure that future technologists understand the human experience and can build technologies that appreciate human diversity, we as CS educators must intentionally support our students’ social-emotional capacities and computational abilities.

To explore digital racial literacy in CS, we begin by analyzing the messages about race we deliver in the classroom. By doing so, we can move beyond a limited, unintentional, and haphazard incorporation of race and ethnicity in CS Ed to a more intentional and purposeful practice of digital racial literacy. By examining these messages we can better understand how our own and our students’ racial identities have formed.

Race Messages Matter

Though the practice is centuries old, the concept of racial literacy was formally introduced by sociology scholar France Twine (2004). Twine studied the strategies, messages, and practices that adults, specifically parents and caregivers, use to prepare and buffer their children from the impacts of racial-ethnic bias. Interestingly, her work began with studying the white parents of multi-racial children in the United Kingdom. The parents in this work expressed that at the heart of racial literacy is an acceptance and awareness that racial-ethnic discrimination and bias is unavoidable for racially and ethnically minoritized youth. By accepting this reality, CS educators can recognize the importance of tending to students’ racial awareness and preparation as part of their classroom practice. To address this dynamic, we must understand how our students learn about and cope with racial-ethnic bias and stressors in their lives.

Much of our understanding and management of racialized experiences are derived from socialization messages that inform our racial identity. These ideologies, biases, and reactions to racial encounters are primarily shaped by implicit and explicit messages. This process is known as racial-ethnic socialization. Hughes and colleagues (2006) define racial socialization as the “process by which individuals develop racial identities and a sense of racial meaning, which shapes their attitudes, beliefs, and behavior” (p. 7).

The knowledge we receive from family, media, and society compose the majority of these messages. Although a significant portion of children’s racial-ethnic learning occurs with caregivers, teachers and peers also play a critical role in the racial socialization of youth. The messages transmitted by caregivers, teachers, and peers are integral in developing students’ awareness, understanding, and emotional preparedness to deal with issues of race and ethnicity in all aspects of their lives.

In their research on parental racial socialization in the United States, Hughes and colleagues (2006) identified five common racial socialization messages delivered by parents: (1) egalitarianism; (2) silence about race; (3) preparation for bias; (4) promotion of (mis)distrust; and (5) cultural socialization. Understanding these common racial socialization messages is helpful for educators’ self-analysis of their racial socialization trajectories and racial identity development. Table 1 outlines these messages and connects them to classroom practices.

Table 1
Common Racial Socialization Messages and CS Classroom Practices

Unpacking the implicit and explicit messages about race that educators have received over the course of their life is a necessary reflective step to identify current dispositions and reactions to race-based content. To help with this, review Table 1, and then take a moment to reflect.

It’s important to remember that when it comes to digital racial literacy, the work begins with ourselves. As educators, we must be willing to examine our biases and assumptions, our racial identity development, and life course socialization experiences. We can only effectively teach our students digital racial literacy if we actively engage in it ourselves. We must also be willing to listen to our students’ experiences and perspectives, recognizing how their identities shape their understanding of and experiences in the world.

Integrating messages about race into CS Ed can enable educators to be intentional and purposeful in their curricula. It can also lay the foundation for how students make sense of and evaluate racialized encounters. By informing our intellectual understanding of common racial socialization messages, we can better appraise racial encounters and assess the stressfulness of race-based events and our coping responses to these events.

Revisiting Brandie’s Story

It may seem daunting to tackle racial issues and develop students’ digital racial literacy in CS Ed, but students are able and ready to engage with these ideas. Brandie shared her students’ reactions to her Power On! lesson:

Brandie’s lesson and her students’ reactions illustrate the power that can come from working to develop digital racial literacy in CS Ed. In the next chapters, we’ll consider some concrete tools and strategies that you can use to do this work in your own context.

Reflection Questions:

1. When have you recognized or experienced racialized bias in technology? After reading this chapter, do other examples come to mind? Why is it important to make students aware of these realities?
2. What stands out to you about the concept of digital racial literacy? What connections do you notice between developing racial literacy in general and developing digital racial literacy within the context of CS Ed?
3. Why do you think it is important to develop our own digital racial literacy in tandem with supporting students to develop their digital racial literacy? What role does racial-ethnic socialization play in the need to develop digital racial literacy?

Takeaways for Practice:

• Review the descriptions of the recommended areas of digital racial literacy in CS Ed (Technical; Representation; Pipeline and Access; Advocacy and Empowerment) discussed in the chapter. Consider which of these areas already appear in your current curriculum and where you might make changes to incorporate examples from these areas into your instruction.
• Take some time to reflect on your racial identities by completing Activity 1. Remember that you can journal through writing, drawing, coding, or any other creative medium to convey your thoughts, ideas, and feelings.

Glossary

References

Bell, D. A. (2023). Who’s afraid of critical race theory? In E. Taylor, D. Gillborn, & G. Ladson-Billings (Eds.), Foundations of critical race theory in education (3rd ed., pp. 30-41). Routledge. https://doi.org/10.4324/b23210-4

Bell, J. (2013). The four “I’s” of oppression. Begin Within. https://beginwithin.info/articles-2/

Broussard, M. (2023). More than a glitch: Confronting race, gender, and ability bias in tech. MIT Press. https://doi.org/10.7551/mitpress/14234.001.0001

Cesario, J., Johnson, D. J., & Eisthen, H. L. (2020). Language in job ads may contribute to underrepresentation in the tech industry. Proceedings of the National Academy of Sciences, 117(16), 8981-8984.

Chan, E. L., & Coney, L. (2020). Moving TESOL forward: Increasing educators’ critical consciousness through a racial lens. TESOL Journal, 11(4), 1-13. https://doi.org/10.1002/tesj.550

Chinook Fund. (n.d.) 4 I’s of oppression. https://chinookfund.org/wp-content/uploads/2015/10/Supplemental-Information-for-Funding-Guidelines.pdf

Crawford, C., Kuyenga, M. A., Talley, L., Mirakhur, Z., & Clark, H. (2023). Organizing for educational equity in computer science: Lessons from New York City’s CS4All initiative. New York City Department of Education. https://sites.google.com/schools.nyc.gov/cs4all-equity/about-us/impact-report?authuser=0

Daniels, J., Nkonde, M., & Mir, D. (2019). Advancing racial literacy in tech: Why ethics, diversity in hiring & implicit bias trainings aren’t enough. Data and Society Fellowships Program. https://datasociety.net/wp-content/uploads/2019/05/Racial_Literacy_Tech_Final_0522.pdf

Delgado, R., & Stefancic, J. (2023). Critical race theory: An introduction (4th ed.). NYU Press. https://doi.org/10.18574/nyu/9781479818297.001.0001

Ge, Q., & Knittel, C. R. (2019). Racial and gender discrimination in transportation network companies. Proceedings of the National Academy of Sciences, 116(12), 5365-5370.

Grother, P., Ngan, M., & Hanaoka, K. (2019). Face recognition vendor test (FRVT) part 3: Demographic effects. National Institute of Standards and Technology. https://doi.org/10.6028/NIST.IR.8280

Harris, C. I. (1993). Whiteness as property. Harvard Law Review, 106(8), 1701-1791. https://www.jstor.org/stable/1341787

Hughes, D., Rodriguez, J., Smith, E. P., Johnson, D. J., Stevenson, H. C., & Spicer, P. (2006). Parents’ ethnic-racial socialization practices: A review of research and directions for future study. Developmental Psychology, 42(5), 747. https://doi.org/10.1037/0012-1649.42.5.747

Jones, S. T. & melo, n. a. (2021). We tell these stories to survive: Towards abolition in computer science education. Canadian Journal of Science, Mathematics and Technology Education, 21, 290-308. https://doi.org/10.1007/s42330-021-00158-2

Kendi, I. X. (2019). How to be an antiracist. One World.

Kuttner, P. J. (2016). Hip-hop citizens: Arts-based, culturally sustaining civic engagement pedagogy. Harvard Educational Review, 86(4), 527-555. https://doi.org/10.17763/1943-5045-86.4.527

Lachney, M., Babbitt, W., Bennett, A., & Eglash, R. (2019). Generative computing: African-American cosmetology as a link between computing education and community wealth. Interactive Learning Environments, 29(7), 1115–1135. https://doi.org/10.1080/10494820.2019.1636087

Lachney, M., Allen Kuyenga, M. C., Phelps, J., Yadav, A., & Drazin, M. (2023). “Everybody’s searching their roots”: Centering Black nature-cultures of belonging in non-compulsory computer science education. Computer Science Education, 34(4), 829-863. https://doi.org/10.1080/08993408.2023.2268378

Laskowski, M. P., & Kumar, A. (2018). Representation matters: The effect of avatar race in a virtual world and implications for educational and career opportunities. Computers & Education, 123, 147-160.

Ledesma, M. C., & Calderón, D. (2015). Critical race theory in education: A review of past literature and a look to the future. Qualitative Inquiry, 21(3), 206-222. https://doi.org/10.1177/1077800414557825

Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447-453. https://doi.org/10.1126/science.aax2342

Price-Dennis, D., & Sealey-Ruiz, Y. (2021). Advancing racial literacies in teacher education: Activism for equity in digital spaces. Teachers College Press.

Sealey-Ruiz, Y. (2013). Building racial literacy in first-year composition. Teaching English in the Two-Year College, 40(4), 384-398. https://doi.org/10.58680/tetyc201323603

Stevenson, H. (2014). Promoting racial literacy in schools: Differences that make a difference. Teachers College Press.

Tanksley, T. (2023). Employing an abolitionist, critical race pedagogy in CS: Centering the voices, experiences and technological innovations of Black youth. Journal of Computer Science Integration, 6(1). https://doi.org/10.26716/jcsi.2023.12.27.49

Tanksley, T. C. (2024). “We’re changing the system with this one”: Black students using critical race algorithmic literacies to subvert and survive AI-mediated racism in schools. English Teaching: Practice & Critique, 23(1). https://doi.org/10.1108/ETPC-08-2023-0102

Talley, L. M. (2021). Exploring equity in computer science programs [Professional development program]. New York City Department of Education.

Talley, L. M. (2022). Exploring equity in computer science pilot series (EECS Pilot): Program plan and curriculum. New York City Department of Education. https://sites.google.com/schools.nyc.gov/cs4all-equity/eecs/eecs

Twine, F. W. (2004). A white side of black Britain: The concept of racial literacy. Ethnic and Racial Studies, 27(6), 878-907. https://doi.org/10.1080/0141987042000268512

Chapter Overview

This chapter offers two tools to develop digital racial literacy in computer science (CS) and CS education (CS Ed). First, the chapter introduces and explores Howard Stevenson’s (2014) Racial Encounter Coping Appraisal Socialization Theory (RECAST) model by applying the model to a case study of a CS classroom experience. Second, the chapter considers digital racial literacy as a form of social and emotional learning. It offers examples of therapeutic techniques and practices that can be used in CS classrooms to support CS educators and their students in navigating racial stress and trauma. This chapter is intentionally written for self-reflective practice in community with others. It is highly recommended that the chapter is read and discussed individually and with colleagues or critical friends to pause, reflect, and identify steps to take action.

Chapter Objectives

After reading this chapter, I can:

• Explain what the RECAST framework is and identify ways to apply this framework to develop digital racial literacy.
• Explain why digital racial literacy can be understood as social-emotional learning and identify therapeutic practices that can be used to develop digital racial literacy.

Key Terms:

digital racial literacy; intercultural competence; racial-ethnic; racial literacy; racial self-efficacy; RECAST framework; social-emotional learning; therapeutic practices

Kwame’s Story

This chapter offers tangible strategies to apply the theories of digital racial literacy introduced in Chapter 8 to the day-to-day work of CS teaching and learning. First, we provide a framework (RECAST) for navigating racial encounters in the classroom (Stevenson, 2014). Second, we consider how developing digital racial literacy is also social-emotional work and explore how teachers can leverage therapeutic techniques to support digital racial literacy development. To get started, let’s meet Kwame, an eighth grade CS teacher.^{[footnote]This vignette was developed with Kwame’s permission.[/footnote]}

You’ll return to Kwame’s story later to consider the steps that he took to foster his own and his students’ digital racial literacy. We turn now to a framework that can help us consider how to develop digital racial literacy in CS classrooms like Kwame did.

The RECAST Framework

As CS continues to grow as a field, educators may wonder, how can we possibly combat systemic racism from our classrooms?^{[footnote]We recognize that racism also encompasses ethnic conflict and prejudice based on ethnicity. In this chapter, when we refer to race, we include ethnicity in that discussion. The term “racial-ethnic” is used to emphasize this relationship.[/footnote]} The CS students of today are the industry and field leaders of tomorrow. This means they, and we, have great power to re-define and re-make the cultures of the technology industry. Amid the complexities and challenges, there is a resounding call to action for CS educators. Beyond the theoretical discussions, this chapter is a call to engage, to question, and to guide students toward a more informed and conscientious interaction with technology through developing digital racial literacy. As discussed in Chapter 8, digital racial literacy involves:

1. Developing students’ awareness of the role of human bias in shaping algorithmic bias and the ways in which racially marginalized communities are represented in and threatened by current and existing technologies.
2. Preparing students and colleagues to manage the emotions they will face as they interact with CS products and possible workplace experiences that embed racism.
3. Empowering students to critique the impact of technologies on their communities and in their daily lives and empowering students to use technology to disrupt systems of oppression and galvanize their communities.

There are many tools that can be used to support CS teachers and students to develop digital racial literacy. The RECAST framework from Howard Stevenson (2014) is one model that helps explain the relationship among racial encounters, socialization messages (see Table 1 in Chapter 8), and our coping responses to stressful situations. According to Stevenson, overcoming our biases and improving our reactions to racial encounters requires ongoing practice and can’t be resolved just through accumulating knowledge.

The RECAST framework offers a practical approach to addressing racial stress and trauma in the CS classroom. The framework has three key components: READ, RECAST, and RESOLVE.

• READ focuses on developing an historical and factual awareness of race and racial politics, and your own racial identity.
• RECAST aims to manage and cope with racial stress and trauma.
• RESOLVE focuses on addressing and taking action against the root causes of racial tension and trauma.

Let’s look more closely at how we can apply this framework to the practice of digital racial literacy in CS Ed.

In the READ component, CS teachers can educate themselves about the impacts of issues like algorithmic bias, cyber surveillance, and workplace discrimination in the world. Educators can explore — individually and with their students — the underlying biases that shape the design and implementation of computer systems and software and seek to understand how these biases can marginalize certain groups. Additionally, teachers can work to create a classroom environment that values diversity and inclusivity, where students can feel comfortable expressing their experiences with racial bias in tech.

In the context of RECAST, the increasing use of social media/forums and online communication (e.g., internet, dark web) has created a new source of racial stress for many students. Online racial interactions, such as cyberbullying, trolling, and hate speech can cause significant emotional distress and trauma. Teachers can help students develop coping strategies to manage these stressors, such as mindfulness techniques and therapeutic strategies. They can also encourage students to seek support from counselors or mental health professionals.

Finally, the RESOLVE component of the framework emphasizes the importance of social action and taking steps to address the root causes of racial stress and trauma. In the context of CS, this can involve advocating for greater diversity and inclusivity in the tech industry, challenging the underlying biases in algorithms and computer systems, and promoting social justice.

It is important to note that the growing reliance on virtual communication and technology can also hinder youths’ development of in-person social skills and engagement in collective action. Therefore, teachers can also encourage their students to engage in community-based activism and civic activity, helping them build the skills necessary to make a difference in the world. Through these efforts, CS teachers can help students develop the tools and strategies needed to effectively manage and respond to racial stress and trauma in their personal and professional lives.

The socialization that occurs throughout the course of our lives and the coping responses we develop through our experiences shape what Stevenson defines as racial self-efficacy, or our belief that we can cope with and manage racial-ethnic encounters in everyday life (Stevenson, 2014). As educators develop their digital racial literacy by building ongoing awareness, managing their emotional responses, and committing to promoting social justice through CS, they are better prepared to support their students to do the same. To foster your own and your students’ racial self-efficacy, it is essential to focus on developing digital racial literacy as an ongoing practice, including how to address stressful racial-ethnic encounters in the moment.

Applying the RECAST Framework in the Classroom

CS educator Brandie teaches at a predominantly white school in a district that prioritizes developing students’ digital racial literacy.^{[footnote]See the On Terminology section of this guide for an explanation on our use of different identity-related terms[/footnote]} A few years ago, the district started an initiative to develop a curriculum that highlights the racial and cultural challenges of marginalized groups to elevate the voices of those whose stories are not often told. Brandie’s fifth grade students read Ghost Boys by Jewell Parker Rhodes. The novel was inspired by Tamir Rice and includes Emmett Till as a character.^{[footnote]See https://en.wikipedia.org/wiki/Killing_of_Tamir_Rice and https://en.wikipedia.org/wiki/Emmett_Till[/footnote]} Brandie described the novel as “definitely a hard read. The first page starts with the character’s internal monologue as he lays on the ground dying after having just been shot.” Recognizing the racial stress and trauma that this novel would raise for students, Brandie’s fifth grade team used the RECAST framework to support their students’ digital racial literacy as they engaged with the text. In Table 1, Brandie shares what she did as she taught the novel.

Table 1
Applying the RECAST Framework in the Classroom

Now that you have read Brandie’s experience, reflect on the examples she shared. Where do you notice the different elements of the RECAST framework? How did Brandie develop an awareness of racial stress and trauma for herself? For her students? How did she plan to manage and cope with her own and her students’ stress? How did the unit allow students to address and take action against racial tension and trauma?

Digital Racial Literacy as Social-Emotional Learning

Because a key component of the RECAST framework involves managing and coping with stress related to racial-ethnic encounters, CS teachers need strategies and approaches to help manage stress. This section considers how to do this in the CS classroom by considering how digital racial literacy can be considered social-emotional learning (SEL). SEL refers to learning skills and behaviors to develop healthy identities, manage emotions, and maintain healthy and supportive relationships (Collaborative for Academic, Social, and Emotional Learning [CASEL], n.d.).

With the technology industry’s narrow focus on products and efficiency, issues of emotional and social participation can be overlooked. Similarly, in CS, it is also easy to narrowly focus on students’ computational thinking and abilities with little regard to their social-emotional competencies.

However, this narrow focus on computational abilities leaves us with a major challenge. It produces technologists who do not understand the human experience and may not have the ability to build technologies that appreciate human diversity. To address this, CS educators must be proactive and intentional in how they support their students’ social-emotional capacities while also developing their computational faculties.

Recognizing feelings related to racial-ethnic encounters as a response to stress rather than as an inability to deal with the issues overall is a key starting place to resolving them. Our CS students today are the CS leaders and workforce of tomorrow and will shape the future of human-technological interaction. With this in mind, developing our students’ sociocultural awareness and respect for the contributions and experiences of racial-ethnic minorities in the field is key to a more equitable tech landscape. Even students who may not be inclined to seek a career in CS must be equipped with a basic digital racial literacy to promote racial justice in society.

While SEL programs are typically framed as a broad strategy to promote students’ executive functioning and emotional management, digital racial literacy can be leveraged as a specific and targeted form of SEL to address racial-ethnic inequities and disparities in technology fields and in CS Ed. Applying strategies that promote historical accuracy and intercultural competence, emotional management, and social/civic empowerment to CS instruction is the cornerstone of an ethical and sensitive practice of digital racial literacy in CS Ed (Talley, 2022). By integrating a digital racial literacy mindset into tech education, we can achieve several learning objectives:

1. Building students’ cultural humility and empathy toward multicultural influences in tech.
2. Preparing students for experiences of stress and discrimination that may impact their lives as tech consumers and employees.
3. Providing students with the technical and civic skills to resist and respond to racial-ethnic inequities exacerbated by technologies and producers.

To develop digital racial literacy as a form of social-emotional learning in CS classrooms, educators need strategies to navigate moments of racial stress that will arise when seeking to promote equity-oriented instruction. Because CS and technology are sites where youth develop racial identities and are racially socialized, we must remain aware of and continually attend to how our students interact with technology and its racial implications.

This question defines your practice of digital racial literacy in the CS classroom. The RECAST theory of digital racial literacy pushes us to recognize our ability to respond to these moments or “encounters” by creating an ongoing and intentional practice of recognizing, processing, and responding to these moments.

Using counseling-based strategies can help educators incorporate digital racial literacy into the CS classroom as a form of social-emotional learning. The use of therapeutic practices can create a supportive classroom environment and scaffold students’ preparedness to discuss topics of race. Common SEL therapeutic practices include active listening, creative expression, controlled breathing, debate, journaling, mindful relaxation, peer co-counseling, role play and drama, self-care, and storytelling. These techniques and how they can support developing digital racial literacy in CS Ed are described below.

Integrating these practices into CS instruction can enable educators to sensitively engage students with race-related CS knowledge. Educators can also use these strategies for themselves as they prepare to engage with these topics with students or colleagues.

Applying Therapeutic Practices in the Classroom

Brandie drew on therapeutic practices to support her students throughout the Ghost Boys unit. She was acutely aware of the racial stress that this unit surfaced and incorporated some of the practices described above into her instruction to support students’ digital racial literacy as social-emotional learning. Table 2 illustrates how Brandie integrated these practices into the unit.

Table 2
Applying Therapeutic Practices in the Classroom

Take a moment again to reflect on Brandie’s experiences. How did Brandie tailor these practices for her students’ specific needs? Which practices that she described could apply in your own context? What additional supports might you need?

Revisiting Kwame’s Story

We close this chapter with an invitation for you to revisit Kwame’s story and consider how he applied the concepts presented in this chapter. After you reflect, you can find commentary on Kwame’s story from the chapter author in Resource 1.

1. After reading this chapter, what stands out to you about the importance of integrating a digital racial literacy mindset into CS Ed?
2. One reality of developing digital racial literacy is that it requires you as an educator to become aware of, manage, and address your own racial stress as a key part of supporting your students to do the same. What resources are available to you in your context to support you in doing this work? What other supports might you need?

Takeaways for Practice:

• Select a CS unit, lesson, or activity. Analyze it using the RECAST framework. Consider where you are already incorporating aspects of the framework and where you can make changes to more fully address racial stress and trauma.
• Using the same unit, lesson, or activity from above, identify at least one therapeutic practice that you could incorporate to support students’ digital racial literacy as a form of social-emotional learning.

Glossary

References

Collaborative for Academic, Social, and Emotional Learning. (n.d.). What is the CASEL framework? https://casel.org/fundamentals-of-sel/what-is-the-casel-framework/

Ravitch, S. M. (2020, August 11). Why teaching through crisis requires a radical new mindset. Harvard Business Publishing Education. https://hbsp.harvard.edu/inspiring-minds/why-teaching-through-crisis-requires-a-radical-new-mindset

Rosati, J. (2020, October 22). Recasting the moment: Professor Howard Stevenson on creating change through racial literacy. Penn GSE Magazine. https://www.gse.upenn.edu/news/recasting-moment-professor-howard-stevenson-creating-change-through-racial-literacy

Stevenson, H. (2014). Promoting racial literacy in schools: Differences that make a difference. Teachers College Press.

Talley, L. M. (2022). Exploring equity in computer science pilot series (EECS Pilot): Program plan and curriculum. New York City Department of Education. https://sites.google.com/schools.nyc.gov/cs4all-equity/eecs/eecs

Resource 1: Author Commentary on Kwame’s Story

Chapter Overview

This chapter builds on Chapters 8 and 9 by providing resources for computer science (CS) teachers to examine their CS education (CS Ed) practices through the lens of digital racial literacy. The chapter applies the Racial Encounter Coping Appraisal Socialization Theory (RECAST) framework for racial literacy by offering guidance for educators to complete audits of their CS classroom practice and specific CS lesson plans or activities. This chapter is intentionally written for self-reflective practice in community with others. It is highly recommended that the chapter is read and discussed individually and with colleagues or critical friends to pause, reflect, and identify steps to take action.

Chapter Objectives

After reading this chapter, I can:

• Complete audits of my classroom practice and CS units, lessons, and activities to evaluate how I incorporate digital racial literacy into my CS instruction.

Key Terms:

audit; digital racial literacy; racial-ethnic; RECAST framework; social-emotional learning; therapeutic practices

Your Story

This chapter builds on Chapters 8 and 9 to give you a chance to apply what you’ve learned as you audit your CS practices and CS curriculum through the lens of digital racial literacy, or the process of developing awareness of the relationships between race and technology, managing emotions connected to racism in tech, and critiquing and using technology to disrupt inequity. Let’s begin with a reflection. As we begin, we invite you to apply the different strategies you’ve been learning about to navigate stressors that might emerge related to developing digital racial literacy (see Table 2 in Chapter 9). Remember that it is important to pause and okay to sit with discomfort. As you practice these strategies yourself, you’ll be better prepared to support your students in their own journeys.

Now that you have been introduced to frameworks and techniques to strengthen your knowledge of digital racial literacy in the CS classroom, this chapter offers two tools to evaluate your current practice: a general digital racial literacy classroom practice audit and an audit to evaluate digital racial literacy within a specific lesson or activity.

CS Digital Racial Literacy Classroom Practice Audit

When most people hear the word “audit,” fear strikes. However, auditing, or systematically reviewing your CS curriculum and instructional practices, can be a valuable way to assess where you are and where you need to grow. Auditing might include analyzing your lesson plans to consider how they incorporate social equity issues and your students’ identities and lived experiences. It might also involve examining your stress and emotional responses to equity issues that may arise in your classroom and taking steps to manage these emotions healthily.

Technology impacts every aspect of our lives, but the field has been plagued with issues of underrepresentation and bias, particularly against racial-ethnic minoritized groups.^{[footnote]We recognize that racial issues also encompass ethnicity. In this chapter, we include ethnicity in discussions of race. The term “racial-ethnic” is used to emphasize this relationship.[/footnote]} For this reason, teachers can promote equity and inclusion by developing students’ digital racial literacy in CS classrooms by focusing on the areas of:

• technology;
• representation;
• access and workforce development; and
• justice, advocacy, and empowerment.

Chapter 8 unpacks these four areas in greater detail. Audits of how we consider these areas in our CS curricula allow us to address systemic barriers that have prevented racial-ethnic minoritized groups from fully participating in the field of CS. For instance, representation in CS has historically been limited to a small group of people, leading to a lack of diversity in mainstream technology development (see Chapters 2 and 3). Access and workforce development determine who has the opportunity to enter into and succeed in the field. Promoting justice, advocacy, and empowerment helps address the power dynamics often at play in technology development and usage. Exploring and engaging in discussions about these topics with students can promote more equitable CS learning.

The Classroom Practice Audit tool below (Tables 1a-c; Talley, 2022) can be used to assess your efforts in promoting equity and inclusion in your CS spaces. Drawing on the RECAST framework introduced in Chapter 9 (Stevenson, 2014), the tool is divided into the three parts of the framework: READ, RECAST, and RESOLVE. The audit builds on Stevenson’s framework by applying it specifically to developing digital racial literacy. The READ section focuses on awareness and knowledge of issues related to racial-ethnic minoritized people in CS. The RECAST section addresses emotional management and therapeutic practices for students related to racism in tech, and the RESOLVE section focuses on social action and understanding to disrupt racial inequity in tech. Teachers can use the questions provided in each category to reflect on their efforts in promoting equity and inclusion in CS and identify areas for improvement.

Digital Racial Literacy Classroom Practice Audit Tool

Table 1a
READ (Awareness): Knowledge of Racial Issues in CS

Table 1b
RECAST (Emotional Management): Social-Emotional Learning and Therapeutic Practices

Table 1c
RESOLVE (Action): Social Action and Understanding

By applying the READ-RECAST-RESOLVE framework to CS pedagogy, classroom management, and ethics, CS teachers can work toward creating more equitable and inclusive learning environments for all students. This requires a commitment to ongoing self-reflection, learning, and action, as well as a willingness to engage in difficult conversations and challenge systemic inequalities inside and outside the classroom.

CS Digital Racial Literacy Unit Plan, Lesson Plan, or Activity Audit

Similar to the above Classroom Audit, the CS Digital Racial Literacy Unit Plan, Lesson Plan, or Activity Audit (Table 2; Talley, 2022) is a reflective journey that empowers you to critically assess and enhance the social impact of your CS lessons. Again applying the RECAST framework (Stevenson, 2014) to digital racial literacy development, this activity invites you to revisit one of your favorite lesson plans focusing on the domains of READ, RECAST, and RESOLVE.

In the READ section, examine how your lesson plan incorporates a relevant social issue to contextualize your CS lesson within social equity in the real world. Consider whether you have invited your students to be critical thinkers by analyzing how the CS concept at hand can shape possibilities and contribute to inequities. Take a moment to reflect on how your students’ lived experiences and identities might influence their interpretation of the technology or CS assignment.

In the RECAST section, assess whether you have integrated relevant social, emotional, and coping skills into your lesson to model stress management and promote digital racial literacy among your students. Explore how you have examined your own stress about social equity issues that may surface during the CS lesson, recognizing the importance of creating a supportive learning environment.

Finally, in the RESOLVE section, consider whether you have asked your students to develop a social action response or plan to address the real-world implications of the technology and social inequity discussed in your lesson. Evaluate whether you have equipped your students with concrete sociopolitical knowledge or skills, like as digital organizing or Freedom of Information Act requests, to operationalize and address their social equity concerns through a CS project.

Throughout your audit, consider how you might scaffold students’ abilities to engage with these topics by incorporating elements of social-emotional learning (SEL), including the therapeutic practices introduced in Chapter 9.

Table 2
Racial Literacy Unit Plan, Lesson Plan, or Activity Audit

This audit is an opportunity for growth and refinement, aiming to elevate the social impact of your CS lessons. Embrace the chance to make your lessons more inclusive, relevant, and empowering for your students. Let’s embark on this journey of self-reflection and improvement together.

Considerations for Auditing Your Practice

Many CS educators have audited their practice in their efforts to increase opportunities to develop digital racial literacy in their CS instruction. Here we share some considerations based on their experiences.

First, when completing the audit process, it is important to give yourself enough time and space to complete the task. This includes taking care of yourself and managing your own racial stress that may arise as part of the process. The therapeutic techniques in Chapter 9 can support you in this. CS educator Jami recommended:

Remember that making equity-oriented change is an ongoing process. It is okay to make small changes as part of a consistent effort to improve. CS educator Brandie acknowledged some of the challenges that might arise in planning changes based on the results of your audit:

It can be important to find a balance between developing digital racial literacy well and still ensuring that standards and objectives are met. Similarly, Brandie noted that “talking about issues of race and equity are and can be heavy.” Jami added that it’s important to balance engaging students with these important issues but also “center joy and the accomplishments of marginalized communities.”

Second, while completing your audit, it is important to remember your students and consider their identities, needs, and backgrounds. Brandie and Jami shared that their students experienced lessons focused on digital racial literacy in different ways. Brandie teaches at a predominately white school:

Jami faces a different but related challenge. Her school is predominantly Latine.^{[footnote]See the On Terminology section of this guide for an explanation on our use of different identity-related terms.[/footnote]} She noted:

As you consider changes to make based on your audits, consider what supports different students in your class might need and how you can make your instruction relevant to students with different experiences and backgrounds. While Brandie and Jami acknowledged that this process was challenging, they both emphasized the importance of preparing to engage students about these topics.

Finally, it may seem daunting to seek to develop digital racial literacy due to concerns about how students will respond. Some educators, especially those who teach elementary grades, may feel that students are too young to engage with these topics. While how you engage students and the supports you provide may differ based on students’ ages, it is possible. Brandie described her fifth grade students’ reactions to lessons that developed digital racial literacy:

Ethan, a middle school CS teacher, shared similar responses from his older students:

Students come to the classroom with a familiarity with technology, an awareness of inequity, and many feelings and questions. Providing students with support to develop digital racial literacy in connection with technology and opportunities to take action is an essential part of becoming an equity-oriented CS educator.

Revisiting Your Story

Now that you’ve completed the audits, take a moment to reflect on the insights you gained from the process and the changes and enhancements you envision for your teaching.

As a CS educator, you are at the front lines of CS Ed and workforce development. Your knowledge of the sociocultural landscape of CS is integral to your students’ development. Digital racial literacy frameworks are critical because they offer practical guidance on identifying and addressing social equity issues in real-world contexts. Without digital racial literacy, we risk perpetuating and exacerbating social inequities in CS Ed and the tech workforce.

The consequences of not engaging in digital racial literacy in CS classrooms are vast and dire. Ignoring the intersection of race and technology may inadvertently perpetuate harmful stereotypes or allow implicit bias to go unchecked. However, with a concerted effort to recognize and challenge structural inequalities in CS, you can avoid excluding and marginalizing students in your classroom.

We must be intentional in our approaches to teaching CS. This means incorporating relevant social issues and critical discussions of real-world racial bias in tech into our curriculum. It also includes ensuring that our examples and projects reflect the implications of implementing technology for racial-ethnic minoritized communities. We can prioritize offering our students concrete civic and sociopolitical knowledge and skills that they can use to operationalize and address their social equity concerns through CS projects.

As educators, we must be willing to examine our own biases and assumptions, as well as our racial identity development and life course racial socialization messages. We can only effectively teach our students digital racial literacy if we actively engage in it ourselves. We must also be willing to listen to our students’ experiences and perspectives, recognizing how their identities shape their understanding of and experiences in the world.

Ultimately, engaging in digital racial literacy in your CS classroom is crucial for advancing equity and inclusion in tech and preparing your students to be informed and responsible citizens in an increasingly diverse and complex world. By prioritizing digital racial literacy in your practice, you help create a more just and equitable society that recognizes and values the unique contributions of all individuals of various racial and ethnic backgrounds. Ultimately, advancing equity in CS requires ongoing learning, growth, and action. We can create a more inclusive and equitable future for all by continuing to develop our digital racial literacy practice.

Reflection Questions:

1. Have you ever completed an audit before? If so, what were the benefits? If not, how do you think auditing your practice can help you become a more equity-oriented CS educator?
2. How might you be able to connect what you’ve noticed about your practice and what you’ve learned from this chapter to the equity commitments you set in Chapter 6?

Takeaways for Practice:

• Use the tools in this chapter to complete an audit of digital racial literacy in your CS education context. Consider how you might create a plan to set goals to improve, check in on your progress, and re-audit your practices periodically.

Glossary

References

Collaborative for Academic, Social, and Emotional Learning (n.d.). What is the CASEL Framework? https://casel.org/fundamentals-of-sel/what-is-the-casel-framework/

Stevenson, H. (2014). Promoting racial literacy in schools: Differences that make a difference. Teachers College Press.

Talley, L. M. (2022). Exploring equity in computer science pilot series (EECS Pilot): Program plan and curriculum. New York City Department of Education. https://sites.google.com/schools.nyc.gov/cs4all-equity/eecs/eecs

Chapter Overview

This chapter examines how inequities related to language manifest in computer science (CS) and CS education (CS Ed). It explores examples of how language injustice operates at ideological, institutional, interpersonal, and internalized levels in CS and CS Ed contexts. The chapter concludes by considering how CS educators can work toward language justice in their CS Ed settings.

Chapter Objectives

After reading this chapter, I can:

• Identify inequities related to language in CS and CS Ed.
• Explain how language injustice is manifested in CS Ed at the ideological, institutional, interpersonal, and internalized levels.
• Define language justice and give examples of language justice in CS Ed.

Key Terms:

bi/multilingual learners; the Four I’s of Oppression and Advantage; gatekeeping; intersectional identities; language ideologies; language injustice; language justice; raciolinguistic ideologies; standard English

John’s Story

Linguistic diversity is ever increasing in contemporary K-12 U.S. classrooms, including CS classrooms. Teachers may find themselves wondering how to reach all learners, regardless of how they communicate. This question is complex and multilayered and involves deeply understanding the students we are trying to support and the policies and beliefs about language that shape our educational spaces. To begin exploring these issues, let’s meet John, a sixth grade CS student.

As you read the introduction to John’s story below, consider these questions: What do you notice and wonder about John? How is he described here?

Language and Equity in CS Ed

Have you ever been judged for how you speak or write? Many people share the experience of feeling excluded when their way of communicating doesn’t align with how others are communicating. Sometimes this is because they misunderstood an “inside joke,” or felt out of place for not using the right “techie jargon,” or because they pronounced words differently than someone else. Others have had experiences of being mocked or stigmatized for their accent or for using languages or varieties deemed “inappropriate” to a particular situation.

While people may feel judged for their language in interpersonal interactions, inclusion and exclusion based on language are also structural features of our society. Language-based inequities occur systematically across many institutions, fields, and contexts, including education and CS Ed. Bi/multilingual learners, or students who use more than one language and who may be learning English, often experience significant marginalization in school.^{[footnote]In this chapter we use the term “bi/multilingual learners” to emphasize these students’ linguistic resources. We also opt to use this term because it is strengths-based. We use it synonymously with emergent bilinguals. These terms stand in contrast to terms such as “English Language Learner” or “Limited English Proficient.” See the On Terminology section of this guide for an explanation on our use of identity-related terms.[/footnote]} Bi/multilingual students may be separated from their peers in remedial-style English classes that have lowered expectations for academic learning and limited ways for bi/multilingual students to show what they do know. Standardized tests measure what students know and can do in English but fail to consider what students can express using other languages and modalities. Furthermore, bi/multilingual students may not have opportunities to learn CS at all. In 2022, for example, about 11.2% of students were designated English learners but only about 5.6% of them were enrolled in CS (100Kin10.org, 2022). In CS classrooms that do serve bi/multilingual learners, resources may not be provided in languages that students and their families can understand.

Bi/multilingual learners aren’t the only ones who experience marginalization due to their language and communication practices. CS programs may not have the resources or expertise to support learners with speech disabilities or other language-related disabilities. Educators may (even unwittingly) lower expectations for learners who have accents or speech patterns they perceive as “ethnic” or “uneducated” or for students who appear to not know specific technical or disciplinary vocabulary.

School systems and educational policies use many terms to label learners who are bi/multilingual and who are learning English at school. John, for example, was labeled as an English Language Learner (ELL) at his school. Each label used in education is attached to associations and assumptions about learners and educational expectations for them (García & Kleifigen, 2018). The terms have important consequences for students’ experiences in school.

Historically, the U.S. federal government has labeled bi/multilingual students with terms that take a deficit-based perspective on their abilities (e.g., limited English proficient, language-minority). This approach embeds those deficit views into U.S. schooling structures. Other labels center white, middle class, “standard” English language and culture as the desirable norm (e.g., ELL; culturally and linguistically diverse children; language minority students). In recent years, many school systems, states, and educators have worked to shift those perspectives by using terms that highlight both the assets of these students and the historical and ideological systems that marginalize them (e.g., emergent bi/multilingual; racialized bi/multilingual). A more comprehensive list of these labels and their associations appear in Table 1.

Throughout these chapters, you’ll notice that we use several of the terms in the table. We use “bi/multilingual learner” and “emergent bi/multilingual learner” to foreground students’ rich and fluid language practices. When we use “language-minoritized” or “racialized,” we seek to highlight how systems marginalize those who are perceived to have language practices that don’t conform to a dominant standard. In some cases, we may also refer to bi/multilingual learners who are receiving services for English learning at school as “bi/multilingual English Learners.”

Table 1
Language Labels in U.S. Educational Settings