A Study of Keystroke Data in Two Contexts: Written Language and Programming Language Influence Predictability of Learning Outcomes
Year: 2020
Type: conference-paper
Study design: Observational Study
Abstract: We study programming process data from two introductory programming courses. Between the course contexts, the programming languages differ, the teaching approaches differ, and the spoken languages differ. In both courses, students' keystroke data -- timestamps and the pressed keys -- are recorded as students work on programming assignments. We study how the keystroke data differs between the contexts, and whether research on predicting course outcomes using keystroke latencies generalizes to other contexts. Our results show that there are differences between the contexts in terms of frequently used keys, which can be partially explained by the differences between the spoken languages and the programming languages. Further, our results suggest that programming process data that can be collected non-intrusive in-situ can be used for predicting course outcomes in multiple contexts. The predictive power, however, varies between contexts possibly because the frequently used keys differ between programming languages and spoken languages. Thus, context-specific fine-tuning of predictive models may be needed.
Authors: John Edwards, Juho Leinonen, Arto Hellas
Institutions: Utah State University, University of Helsinki, Aalto University
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W3009486343