The Effect of Informing Agency in Self-Directed Online Learning Environments


Choices learners make when navigating a self-directed online learning tool can impact the effectiveness of the experience. But these tools often do not afford learners the agency or the information to make decisions beneficial to their learning. We evaluated the effect of varying levels of information and agency in a self-directed environment designed to teach programming. We investigated three design alternatives: informed high-agency, informed low-agency, and less informed high-agency. To investigate the effect of these alternatives on learning, we conducted a study with 79 novice programmers. Our results indicated that increased agency and information may have translated to more motivation, but not improved learning. Qualitative results suggest this was due to the burden that agency and information placed on decision-making. We interpret our results in relation to informing the design of self-directed online tools for learner agency.

Proceedings of the Seventh (2020) ACM Conference on Learning @ Scale


Summer 2020: Codeitz was used by University of Washington undergraduates of color to teach introductory Python to 40+ high school students from predominantly underrepresented backgrounds as part of a virtual STEM summer camp. Codeitz was both an introduction to programming to both students attending the workshop as well as some workshop organizers. This workshop was organized by UW AVELA, a student organization.