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1. Is Computer Science for Me?: Understanding the Barriers of Enrollment and Engagement in Computer Science Courses in High Schools.

   Greenwood, J. (January 2023, American Sociological Association)

   This qualitative research study is part of a larger NSF-funded project entitled "Cogenerative Development of Culturally Relevant Pedagogical Guidelines for Computer Science and Computational Thinking in High Schools." During Year 1 of the project, qualitative semi- structured interviews were conducted with 26 high school students to better understand the challenges and barriers to enrollment in and/or engagement/success in Computer Science courses in high school. A grounded theory approach was used, given the exploratory nature of the study. Students were selected from three regional high schools and had to meet at least one of the criteria associated with underrepresented students in Computer Science: identifying as female; low socioeconomic status; and/or racial/ethnic minority (Black/African American; Hispanic/Latinx/Chicanx; Native American/Alaskan, and Native Hawaiian/Pacific Islander, or multi-racial). Common themes that emerged included the following: Challenges (Financial Factors, Role of Gender (i.e. identifying as female), and Race/Ethnicity Issues); Positive Influences (Role of Teacher, Role of Family); Other Interesting Insights (Wanting to be challenged in Computer Science Classes, Problems with the Marketing of Computer Science as a discipline). Social Identity Theory is used to better understand the experiences of high school students, especially what practices or beliefs keep underrepresented students of Computer Science from enrolling in Computer Science courses in the first place and/or persisting in the Computer Science field. Limitations of the current study are discussed as well as directions for future research and implications for a more culturally relevant pedagogical approach to teaching Computer Science and Computational Thinking in high schools. This project is funded by the National Science Foundation CS for All: Research and RPPs program, Award No. 2122367. 

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2. Improving Computer Science Instruction and Computer Use for African American Secondary School Students: A Focus Group Exploration of Computer Science Identity of African American Teachers

   https://doi.org/10.1145/3322385.3322399  

   Hampton, Lelia; Cummings, Robert; Gosha, Kinnis (January 2019, Proceedings of the ACM SIGMIS ‘19: 2019 on Computers and People Research Conference)

   As the demand for computing careers increases, it is important to implement strategies to broaden the participation in computer science for African Americans. Computer science courses and academic pathways are not always offered in secondary schools. Many teachers are not trained in computer science, yet are pushed to incorporate more computing, computational thinking, and computer usage. A qualitative focus group study was implemented to assess the computer science identities of African American teachers and of their respective urban secondary schools serving African American students. Three major codes were identified: district administration of computer and computing implementation, teacher attitudes towards computer science instruction, and teachers’ recommendations to improve computer science and computational thinking instruction and outreach for African American secondary school students. Findings can be used to improve computer science and technology rollout programs from county and district administrations, teacher instruction with digital tools, and computer science outreach for African American secondary school students. 

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3. Fostering Greater Persistence Among Underserved Computer Science Undergraduates: A Descriptive Study of the I-PASS Project

   https://doi.org/10.1177/15210251221086928  

   Mickelson, Roslyn_Arlin; Mikkelsen, Ian; Dorodchi, Mohsen; Cukic, Bojan; Horn, Tytianna (March 2022, Journal of College Student Retention: Research, Theory & Practice)

   Female, Black, Latinx, Native American, low-income, and rural students remain underrepresented among computer science undergraduate degree recipients. Along with student, family, and secondary school characteristics, college organizational climate, curricula, and instructional practices shape undergraduates’ experiences that foster persistence until graduation. Our quasi-experimental project, Improving the Persistence and Success of Students from Underrepresented Populations in Computer Science (I-PASS), is designed to augment students’ persistence until they earn their computer science degree. Drawing on prior research, including Tinto's model of effective institutional actions for retention, I-PASS Scholars—all low-income, female and/or members of underserved demographics groups— receive a four-year scholarship; mentoring, tutoring, advising; and opportunities to integrate into the academic and social life of the campus. Students’ written reflections and attitude surveys suggest I-PASS's components foster their retention by, among other mechanisms, enhancing their computer science identity development and sense of belonging in the major. 

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4. Accessible Computational Thinking in Elementary Science.

   Bernier, J.; Cabrera, L.; Figueroa, F.; Ha, J.; Kramarczuk, K.; Mak, J.; Su, M.; Xin, Y.; Yan, L.; Ketelhut, D. J.; et al (January 2022, Proceedings of the 16th International Conference of the Learning Sciences - ICLS 2022.)

   Chinn, C.; Tan, E.; & Kali, Y. (Ed.)

   Computational thinking (CT) is ubiquitous in modern science, yet rarely integrated at the elementary school level. Moreover, access to computer science education at the PK-12 level is inequitably distributed. We believe that access to CT must be available earlier and implemented with the support of an equitable pedagogical framework. Our poster will describe our Accessible Computational Thinking (ACT) research project exploring professional development with elementary teachers on integrating computational thinking with Culturally Responsive Teaching practices. 

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5. Accessible Computational Thinking in Elementary Science

   Bernier, J.; Cabrera, L.; Figueroa, F.; Ha, J.; Kramarczuk, K.; Mak, J.; Su, M.; Xin, Y.; Yan, L.; Ketelhut, D. J.; et al (January 2022, Proceedings of the 16th International Conference of the Learning Sciences - ICLS 2022)

   Chinn, C.; Tan, E.; Chan, C.; Kali, Y. (Ed.)

   Computational thinking (CT) is ubiquitous in modern science, yet rarely integrated at the elementary school level. Moreover, access to computer science education at the PK-12 level is inequitably distributed. We believe that access to CT must be available earlier and implemented with the support of an equitable pedagogical framework. Our poster will describe our Accessible Computational Thinking (ACT) research project exploring professional development with elementary teachers on integrating computational thinking with Culturally Responsive Teaching practices. 

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