time-on-task
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- PaperJournal of Learning Analytics18 Mar 2026
Beyond Time on Task
Paul V. Sargent, Isabel Hilliger, Jorge A. Baier
This study analyzed student workload dynamics beyond average time-on-task across 14 engineering courses, finding that workload peaks correlate with perceived learning and difficulty. The authors propose metrics for practical use in course design and suggests that considering workload dynamics provides better predictions of student learning than average measures alone.
Original abstract
Student workload analysis has the potential to play a crucial role in providing both actionable insights to inform course design and curricular adjustments that promote student learning and well-being. While numerous studies have emphasized the need for analyzing workload beyond single-value metrics, such as credit hours, the interpretation and practical application of these metrics for educational interventions remains unclear. In this study, we explore the interplay between time-on-task measurements with student-perceived learning and difficulty.We move beyond average indicators of time-on-task by proposing and examining various metrics related to the dynamics of workload over time. Across 14 engineering courses taught at Pontificia Universidad Católica de Chile, we analyze three different sources of data: (1) self-reported time-on-task and perceived difficulty obtained through a weekly timesheetsurvey, (2) interactions with the learning management system (LMS), and (3) perceived learning attainment obtained from the course evaluation survey. Our results show that LMS-based and self-reported time-on-task were highly correlated. Also, workload dynamics metrics, such as the presence of workload peaks, were highly correlated with perceived learning and perceived difficulty. As such, this study provides evidence in support of considering workload dynamics, rather than average measures of time-on-task, to predict variables related to student learning. The metrics proposed by this framework could be used to implement practical tools for educators and administrators willing to optimize course design and improve learning attainment.