When the Finish Line Moves: Immediate Corrective Practice and Implications for Design in Digital Math Learning

Digital learning platforms often give students a chance to solve a similar problem immediately after an incorrect response, a design we refer to here as "immediate corrective practice" (ICP). While prior work suggests that immediate feedback and targeted retries can support learning, less is known about how various implementations of ICP affects performance and engagement in real-world settings. We study ICP using extant large-scale log data from a K-12 mathematics platform where teachers can choose whether to enable a feature that presents supplementary similar problems after errors on eligible items within an assignment. Focusing on students who answered the first eligible problem in an assignment incorrectly, we compare those shown ICP with those assigned the same problem sets but not shown ICP because their teachers did not use the feature. Students who encountered ICP performed better on the next problem, but were also less likely to complete the assignment. One possible explanation is that additional practice after an error shifts students' perceived endpoint of the assignment, creating a moving-goalpost effect that discourages continued engagement. As large language models make it easier to generate corrective problems and feedback at scale, our findings offer design insights for supporting learning while minimizing disengagement.