Sharin Rawhiya Jacob, Researcher in Computational Thinking Pathways, Digital Promise Global
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Sharin Rawhiya Jacob specializes in educational research focused on computer science curricula and digital technologies, such as generative AI, exploring their impact on language, literacy, and culture in educational settings. She employs unmatched expertise across 15+ years of experience in various fields. She adopts asset-based and culturally sustaining approaches to ensure all students, particularly those from diverse linguistic and cultural backgrounds, have equitable learning opportunities.
With a strong background in research, Dr. Jacob has worked with a wide range of students from K-12 English as a Second Language to university courses covering language, literacy, and technology topics. In her current role as an Educational Researcher at Digital Promise, she works with educational leaders from across the nation pioneering the implementation of advanced K-12 Computational Thinking Pathways. She has also fiscally supported the research of that and her colleagues, acting as major author on federal grants that have secured several millions of dollars in funding to maximize impact. As a participant in the Cal State University Chancellor's Doctoral Incentive Program (CDIP), she receives financial support, professional development, and mentorship to prepare for a future career as faculty in the CSU system. In 2021, she was honored as a UCI Public Impact Distinguished Fellow for her dedication to improving educational outcomes for multilingual students in computing. Additionally, she received the 2021 Haynes Lindley Doctoral Dissertation Fellowship in recognition of her innovative research addressing pressing social and economic issues in Southern California. |
What's new
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New Special Issue!
Are you doing research related to equity in CS education? We have edited a special issue of the Journal of Research on Technology in Education on Computer Science for All. Find the Special Issue here. |
New Publications!
Jacob, S., Montoya, J., Prado, Y., Coenraad, M., Burke, Q., & Warschauer, M. (2025). Designing for All: Computational thinking meets Universal Design for Learning for multilingual students. Proceedings of the 2025 Research on Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT). Newark, NJ.
Jacob, S., & Burke, Q. (2025). Leveraging Generative AI for Translanguaging Support in Computational Thinking Education: A Work in Progress. Leveraging Generative AI for Translanguaging Support in Computational Thinking Education: A Work in Progress (Conference Paper). Considering Cultural and Linguistic Diversity in AI Applications Workshop (CALD-AI workshop). Irvine, CA.
Fuhrmann, T., Rabinowitz, G., Peel, A., Jacob, S., Burke, Q., Krakowski, A., Greenwald, E., Gupta, P., Chaffee, R., Anderson, E., Perret, B., Malyn-Smith, J., Peterson, K., Chen, J., Wilensky, U., Wendel, D., Han, A., Wagh, A., Blikstein, P., Wilkerson, M., Moore, K., Zhang, H., Weckel, M., Shah, S. A., Park, J. H., Ali, S., Perez, A., Grover, S., & Lee, I. (2025). Computational thinking without writing code: What’s next for computational modeling? In Proceedings of the 2025 International Conference on the Learning Sciences (ISLS), Helsinki, FI.
Lui, J., Goodwin, E., Saito-Stehberger, D., Jacob, S., Warschauer, M., Franklin, D. (2025). Teacher Decisions and Perspectives in Scratch TIPP&SEE Implementation. Proceedings of the ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE’23).
Coenraad, M., Ahn, W., Dunbar, K., Yadav, A., Rangel, A., Jacob, S. (2025) Design Principles for CT Integrated Lesson Design and Implementation. Proceedings of the ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE’23).
Jacob, S., & Burke, Q. (2025). Leveraging Generative AI for Translanguaging Support in Computational Thinking Education: A Work in Progress. Leveraging Generative AI for Translanguaging Support in Computational Thinking Education: A Work in Progress (Conference Paper). Considering Cultural and Linguistic Diversity in AI Applications Workshop (CALD-AI workshop). Irvine, CA.
Fuhrmann, T., Rabinowitz, G., Peel, A., Jacob, S., Burke, Q., Krakowski, A., Greenwald, E., Gupta, P., Chaffee, R., Anderson, E., Perret, B., Malyn-Smith, J., Peterson, K., Chen, J., Wilensky, U., Wendel, D., Han, A., Wagh, A., Blikstein, P., Wilkerson, M., Moore, K., Zhang, H., Weckel, M., Shah, S. A., Park, J. H., Ali, S., Perez, A., Grover, S., & Lee, I. (2025). Computational thinking without writing code: What’s next for computational modeling? In Proceedings of the 2025 International Conference on the Learning Sciences (ISLS), Helsinki, FI.
Lui, J., Goodwin, E., Saito-Stehberger, D., Jacob, S., Warschauer, M., Franklin, D. (2025). Teacher Decisions and Perspectives in Scratch TIPP&SEE Implementation. Proceedings of the ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE’23).
Coenraad, M., Ahn, W., Dunbar, K., Yadav, A., Rangel, A., Jacob, S. (2025) Design Principles for CT Integrated Lesson Design and Implementation. Proceedings of the ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE’23).
New Pre-prints Available!
Baek, C., Saito-Stehberger, D., Jacob, S., Nam, A., & Warschauer, M. (2023). Computer Science Framework to Teach Community-Based Environmental Literacy and Data Literacy to Diverse Students. arXiv preprint. arXiv:2309.14098.