Rising Stars 2020:

Jean Salac

PhD Candidate

University of Chicago

Areas of Interest

  • Education
  • Human-Computer Interaction


Beyond Child's Play: Understanding & Supporting Program Comprehension in Young Learners


Worldwide, many countries are integrating Computer Science (CS) and Computational Thinking (CT) instruction into elementary school curricula. This push for CS/CT instruction in younger ages increases the need to better understand how young learners come to a comprehension of programs and how they can be effectively supported in their learning. However, research into this age group (ages 10-15) is relatively thin, especially when compared with research into university-age learners. Research for university-age students is unlikely to directly translate to younger learners, who do not have the same cognitive load, maturity, or motivation. Further, the context and environment in which students learn computing in elementary schools differ greatly from the university setting, making direct translation difficult, if not impossible.

This poster outlines a series of studies that illuminate the contributing factors to comprehension, the different types of comprehension achieved, and the strategies that support program comprehension in young learners. We have found that societal factors, such as school environment, gender, and under-represented minority status, and academic factors, such as reading and math proficiency, contribute to various aspects of program comprehension. Further, our studies revealed that students frequently use code that they only demonstrate a functional, not a structural, understanding of, when learning in an open-ended curriculum. To bridge these gaps in elementary program comprehension, we developed two strategies: TIPP&SEE, inspired by previewing and navigating strategies in reading, and diagramming, inspired by similar strategies used in university CS and elementary math. Exploratory studies have shown TIPP&SEE to be associated with positive performance differences in summative CT assessments and in project completion rates, as well as with narrowed gaps between students with and without academic challenges. This poster also presents a final set of studies to investigate the effectiveness of diagramming as a strategy for elementary computing. Taken together, this body of work aims to deepen our collective understanding of program comprehension in young learners for more effective and equitable implementations of elementary CS/CT curricula.


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.

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