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Choice-making in an adaptive learning system with motivational pedagogical agents
Man Su1, Belle Dang2, Andy Nguyen2
1Saarland University, Saarland Informatics Campus, Department of Computer Science, Saarbrücken, Germany.
None:
Adaptive learning systems increasingly employ pedagogical agents (PAs) to enhance students' engagement and learning outcomes, yet little is known about how motivational PAs influence students' conceptual understanding and strategic choice-making. This study compared 49 school students (at 9th and 10th grade) using an adaptive algebra learning environment with either motivational PAs or instructional prompts (non-PAs). Results revealed that while all students demonstrated learning gains, prior knowledge significantly moderated outcomes. Lower-knowledge students achieved the greatest gains through reflective engagement with foundational tasks, whereas higher-knowledge students often adopted intuitive but error-prone strategies. Notably, process mining and lag sequential analysis revealed distinct choice-making trajectories, uncovering how motivational PAs influenced self-regulation patterns over time. This study advances the field by operationalizing choice-making as a measurable self-regulated learning construct and reframing strategic disengagement as an adaptive, agentic behavior. Findings underscore the importance of designing adaptive systems that support both content mastery and strategic choice-making.
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