Student Effort Measurement via Response-Time Propensities

Key Findings

Adaptive learning systems produce substantial learning gains, yet many students engage too briefly or superficially to benefit. This paper addresses the central challenge of measuring student effort during multi-step problem solving using response-time propensities.

The authors develop models that infer student effort from response-time patterns, finding that common log-based proxies like time-on-task are insufficient. They propose response-time propensity modeling as a more nuanced approach to identifying when students are superficially engaging versus deeply working through problems.

Connections to AIED

This work directly connects to Learning Analytics by providing a validated method for inferring effort from interaction logs. It has implications for Adaptive Learning that could use early effort detection to intervene before students disengage.

The approach also relates to Engagement Assessment Video and broader Assessment frameworks, suggesting that response-time analysis could complement other engagement signals in multi-modal effort detection systems.

Connected Concepts

Connected Articles

Citation

Borchers, C., Zhang, L., Yang, K., Nagashima, T., & Domingue, B. W. (2026). Understanding student effort using response-time propensities during problem solving. arXiv:2605.08943.