Simulating Learners' Task-Selection Strategies and System Constraints in Mastery Learning

TL;DR

This paper presents a simulation framework using student data to analyze how different task-selection strategies and system constraints impact the efficiency of mastery learning in intelligent tutoring systems.

Contribution

It introduces a data-driven simulation approach to evaluate the effects of learner strategies and system constraints on mastery learning efficiency before real-world deployment.

Findings

Risk-averse strategies lead to higher overpractice, especially in complex problems.

Targeted system constraints reduce inefficiencies for maladaptive strategies.

Simulation can guide system redesign prior to classroom implementation.

Abstract

Intelligent Tutoring Systems often grant learners shared control over skill and problem selection. Prior work suggests learners exhibit diverse task-selection strategies, such as avoiding challenge, which may interact with mastery learning systems that optimize task selection based on estimated knowledge. Algorithmic constraints on problem selection may help mitigate these effects, but testing such constraints in classrooms is costly. We propose a simulation-based framework to examine how learner task-selection strategies and system constraints shape mastery learning efficiency. Using interaction data from 261 students across two mathematical domains (equation solving and graph interpretation), we simulate strategies such as Weakness Targeting and Interleaving. We evaluate how these strategies affect overpractice as a measure of efficiency. Results show substantial variability across strategies, with risk-averse strategies producing higher levels of overpractice, especially for complex multi-step problems. Targeted system constraints significantly reduce inefficiencies for maladaptive strategies while minimally affecting already efficient strategies. These findings show how simulation grounded in student data can guide the redesign of shared-control tutoring systems before classroom deployment.