Here are details about some of the projects I've worked on recently.

StoryCoder: Teaching Computational Thinking Concepts Through Storytelling in a Voice-Guided App for Children

Griffin Dietz, Jimmy K. Le, Nadin Tamer, Jenny Han, Elizabeth Murnane, Hyowon Gweon, James A. Landay. CHI 2021.

Computational thinking (CT) education reaches only a fraction of young children, in part because CT learning tools often require expensive hardware or fluent literacy. Informed by needfinding interviews, we developed a voice-guided smartphone application leveraging storytelling as a creative activity by which to teach CT concepts to 5- to 8-year-old children. The app includes two storytelling games where users create and listen to stories as well as four CT games where users then modify those stories to learn about sequences, loops, events, and variables. We improved upon the app design through wizard-of-oz testing (N = 28) and iterative design testing (N = 22) before conducting an evaluation study (N = 22). Children were successfully able to navigate the app, effectively learn about the target computing concepts, and, after using the app, children demonstrated above-chance performance on a near transfer CT concept recognition task.

Building blocks of computational thinking: Young children's developing capacities for problem decomposition

Griffin Dietz, James Landay, Hyowon Gweon. CogSci 2019.

Computational thinking refers to a range of problem-solving skills applicable to computer science and everyday life. Although recent research in developmental cognitive science suggests mental capacities relevant to CT may emerge quite early in life, research on CT, and computer science education more generally, has made little contact with this literature. As a way to better bridge these fields, we explore the development of problem decomposition, a critical feature of CT, in the spatial domain. We ask whether young children can break a complex spatial problem down into subcomponents that can be reassembled to solve the overarching problem. Across two experiments (Exp. 1: 4- to 7-year-olds; Exp. 2: 3- to 5-year-olds) that involve constructing block structures, we demonstrate that some of the key capacities underlying problem decomposition begin to emerge in preschool years and develop throughout early childhood. Although preschool-aged children struggle to solve an open-ended decomposition problem that requires generation and execution of decomposition plans, even 4-year-olds can successfully evaluate the viability of these plans. These results suggest that experimental methods in developmental cognitive science can inform CS education research that focuses on promoting CT; by identifying when and how CT concepts emerge in early childhood, we can better create age-appropriate educational tools.