In a recent study, students were periodically prompted to self-report engagement while working on computer programming assignments in a CS1 course. A regression model predicting time-on-task was proposed. While it was a significant improvement over ad-hoc estimation techniques, the study nevertheless suffered from lack of error analysis, lack of comparison with existing methods, subtle complications in prompting students, and small sample size. In this paper we report results from a study with an increased number of student participants and modified prompting scheme intended to better capture natural student behavior. Furthermore, we perform a cross-validation analysis on our refined regression model and present the resulting error bounds. We compare with threshold approaches and find that, in at least one context, a simple 5-minute threshold of inactivity is a reasonable estimate for whether a student is on-task or not. We show that our approach to modeling student engagement while programming is robust and suitable for identification of students in need of intervention, understanding engagement behavior, and estimating time taken on programming assignments.
Fri 17 MarDisplayed time zone: Eastern Time (US & Canada) change
13:45 - 15:00 | |||
13:45 25mPaper | Accurate Estimation of Time-on-Task While ProgrammingIn-Person Papers Kaden Hart Utah State University, Christopher Warren Utah State University, John Edwards Utah State University DOI | ||
14:10 25mPaper | Providing a Choice of Time Trackers on Online AssessmentsIn-Person Papers Robbie Hott University of Virginia, Nada Basit University of Virginia, Ziyao Gao University of Virginia, Ella Truslow University of Virginia, Nour Goulmamine University of Virginia DOI | ||
14:35 25mPaper | Understanding and Measuring Incremental Development in CS1In-Person Papers Anshul Shah University of California, San Diego, Michael Granado University of California, San Diego, Leo Porter University of California San Diego, William Griswold UC San Diego, Adalbert Gerald Soosai Raj University of California, San Diego DOI |