Does AI Assistance Drive Better Independent Problem-Solving? Assessing Potential Skill Retention Post-Human-AI Collaboration

This research proposes to examine how AI assistance affects undergraduate students’ independent problem-solving skill retention through a three-phase quasi-experimental design. Using the Tower of Hanoi (primarily motor) and Missionaries & Cannibals (primarily cognitive) problem-solving tasks, the study aims to assess baseline performance, AI-assisted collaboration, and post-assistance skill retention. We plan to employ a four-way mixed-modeling ANOVA-based approach to analyze (1) task performance changes during human-AI collaboration (HAIC), (2) the extent of the retention of problem-solving skills after AI withdrawal, and (3) the moderating effects of temporal delay, task complexity, and cognition type. Anticipated contributions include advancing frameworks for assessing the cognitive impacts of HAIC and providing evidence-based guidelines for human-AI (HAI) task allocation in learning environments.