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Kamusta! I'm a Computer Science PhD student and NSF Graduate Fellow at the University of Chicago's CANON Lab working with Professor Diana Franklin. I earned my M.S. from UChicago in 2020 and my B.S. from the University of Virginia in 2017, both in Computer Science. My research interests include computer science education and human-computer interaction. My doctoral research focuses on identifying disparities young children face in CS education and developing strategies to overcome such challenges. I have published my research in the International Computing Education Research Conference (ICER), the conference on Innovation and Technology in Computer Science Education (ITiCSE), the Technical Symposium on Computer Science Education (SIGCSE), and the conference on Human Factors in Computing Systems (SIGCHI). My work has also won Best Paper at ICER and an honorable mention for Best Paper at CHI.

I'm open to internship opportunities in CS education, human-computer interaction, applied data science, software engineering, and STEM policy starting Summer 2021. Reach out!
CV   |   Google Scholar

Select Publications:
Jean Salac and Diana Franklin. If They Build It, Will They Understand It?: Exploring the Relationship between Student Code and Performance." Research Paper in the 25th Annual Conference on Innovation and Technology in Computer Science Education, 2020.

Jean Salac, Cathy Thomas, Bryan Twarek, William Marsland, and Diana Franklin. "Comprehending Code: Understanding the Relationship between Reading and Math Proficiency, and 4th-Grade CS Learning Outcomes." Research Paper in the Proceedings of the 51st ACM Technical Symposium on Computer Science Education, 2020.

Jean Salac, Cathy Thomas, Chloe Butler, Ashley Sanchez, and Diana Franklin. "TIPP&SEE: A Learning Strategy to Guide Students through Use-->Modify Scratch Activities." Research Paper in the Proceedings of the 51st ACM Technical Symposium on Computer Science Education, 2020.

Jean Salac, Qi Jin, Zipporah Klain, Saranya Turimella, Max White, and Diana Franklin. "Patterns in Elementary-Age Student Responses to Personalized & Generic Code Comprehension Questions." Research Paper in the Proceedings of the 51st ACM Technical Symposium on Computer Science Education, 2020.
Photo Credits to Kenneth J Johnson Jr