8 Getting Started with Digital Racial Literacy in Computer Science Education

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).^[1] 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.^[2] 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

Racial Socialization Message	CS Classroom Practices
Egalitarianism Promoting the idea that all individuals are equal and should be treated fairly regardless of their race or ethnicity. This type of racial socialization message emphasizes the importance of treating everyone with respect and discourages stereotyping and prejudice based on race. Egalitarianism racial socialization messages are intended to promote equality and fairness and to help individuals develop a positive and inclusive view of people from different racial and ethnic backgrounds.	Encourage youth to value individual qualities and cultural knowledge over racial group membership. This message and practice can promote an inclusive and equitable environment for all students regardless of their racial background. Precaution: Although this egalitarian message may feel equitable and fair, without balanced acknowledgement of difference, it can become a reinforcement of color-blindness, or a way to ignore the impacts of racism on society and on individuals
Silence about Race The absence of direct messages or practices related to racial issues, such as the exclusion of topics related to racial equity and inclusion in educational curricula or the avoidance of discussing incidents of racial bias or discrimination. This lack of discussion can contribute to a culture of racial insensitivity and reinforce systemic racism.	The implicit or explicit avoidance of the topic of race can exclude racially minoritized students from important conversations and contribute to their marginalization. All teachers should incorporate conversations about algorithmic racial bias and racial-ethnic leaders in all CS classrooms. Educators should create a safe and inclusive learning environment where students can openly discuss the impact of racial inequality on the tech industry.
Preparation for Bias Promoting awareness and preparedness to cope with discrimination can help students of color to navigate potential discrimination they may face.	Teachers can inform their students about incidents of racial bias in tech organizations and marginalized communities to prepare them for possible biases they may encounter in their future careers. Teachers can support students to be co-conspirators and allies, to recognize and disrupt bias when they recognize it, instead of leaving the work only to those experiencing racial bias.
Promotion of (Mis)Distrust Practices that emphasize wariness and distrust in interracial interactions can further contribute to racial tensions and discrimination.	Educators should focus on promoting cross-cultural understanding, empathy, and respect to create a more inclusive learning environment for all students.
Cultural Socialization Messages and practices that teach children about their racial or ethnic heritage and history; promote cultural customs and traditions; and encourage cultural, racial, or ethnic pride can foster a sense of belonging and pride among students of color.	Teachers can incorporate culturally relevant materials, historical events, and cultural holidays to create a more inclusive and welcoming classroom environment. For instance, teachers might incorporate the tradition of braiding from continental Africa into a lesson regarding computing circuitry to make connections between cultural practices and computing. However, as discussed in Chapter 2, teachers should be sure to incorporate these examples in ways that avoid essentializing students or assuming that such examples are automatically relevant to students from a given background.

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

Term	Definition
critical race theory	A scholarly theory that frames race as a socially constructed reality embedded into society. Critical race theory recognizes racism as complex and intersectional with other social identities. It seeks to center racially marginalized voices through a commitment to challenge the status quo and work toward social justice (Bell, 2023; Delgado & Stefancic, 2023; Ledesma & Calderón, 2015).
digital racial literacy	Fostering digital racial literacy in CS Ed 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 to use technology to disrupt systems of oppression and galvanize their communities.
Four I’s of Oppression and Advantage	A theory that illustrates how systems of oppression and advantage (like ableism, classism, or racism) are produced across multiple layers of society. The four I’s are ideological, institutional, interpersonal, and internalized. (See Bell, 2013; Chan & Coney, 2020; Chinook Fund, n.d.; Kuttner, 2016.)
racial-ethnic	This term recognizes race and ethnicity as social constructions. Both race and ethnicity — and the conflicts that emerge related to them — are relevant to issues of inquiry in CS and CS Ed. This term captures how both constructs need to be considered as part of developing digital racial literacy.
racial-ethnic socialization	The process by which we as individuals develop racial identities and a sense of racial meaning based on social norms and expectations. Our racial-ethnic socialization shapes our attitudes, beliefs, and behavior, especially related to racial issues (Hughes et al., 2006).
racial literacy	The historical and factual awareness of racial issues in the classroom and the emotional preparedness needed to discuss and engage with these issues (Stevenson, 2014).
racism	A system of prejudice and discrimination based on race that privileges individuals racialized as white and oppresses racially minoritized individuals.
RECAST framework	The Racial Encounter Coping Appraisal Socialization Theory or RECAST framework offers support to address racial stress and trauma and discuss racial topics in the classroom. The RECAST framework has three parts: 1. READ or becoming aware of racial stress and trauma 2. RECAST or managing and coping with racial stress 3. RESOLVE or taking action against the root causes of racial tension (Stevenson, 2014).

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