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This study investigates the impact of activities using an AI-driven robot on the metacognitive behaviors and mathematical problem solving performance of primary school students. In collaboration with four teachers, we developed a pedagogical sequence combining educational robotics learning activities that embed an AI algorithm (AI-ERLA) with transfer tasks in mathematical problem solving. Qualitative and quantitative results, based on teacher observations and pre-post math tests (N = 85), demonstrate positive effects of AI-ERLA, with three significant findings: (1) a change in students’ metacognitive behavior regarding errors, promoting active engagement; (2) an improvement in problem-solving strategies, with more reflective strategies and analytical thinking; and (3) a statistically significant increase in overall performance, particularly among low-achieving students and those with special needs. The results highlight the potential of AI-ERLA to improve students’ metacognitive skills and mathematical problem solving. While promising, further experimental studies with larger samples are needed to validate these initial findings.

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Fostering Metacognitive Behaviors Through AI-Driven Educational Robotics in Mathematical Problem Solving

  • 会议论文

  • 发表日期：

    2025年

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  • Marie Absalon,
  • Thomas Deneux,
  • Maud Besançon,
  • Morgane Chevalier

摘要

This study investigates the impact of activities using an AI-driven robot on the metacognitive behaviors and mathematical problem solving performance of primary school students. In collaboration with four teachers, we developed a pedagogical sequence combining educational robotics learning activities that embed an AI algorithm (AI-ERLA) with transfer tasks in mathematical problem solving. Qualitative and quantitative results, based on teacher observations and pre-post math tests (N = 85), demonstrate positive effects of AI-ERLA, with three significant findings: (1) a change in students’ metacognitive behavior regarding errors, promoting active engagement; (2) an improvement in problem-solving strategies, with more reflective strategies and analytical thinking; and (3) a statistically significant increase in overall performance, particularly among low-achieving students and those with special needs. The results highlight the potential of AI-ERLA to improve students’ metacognitive skills and mathematical problem solving. While promising, further experimental studies with larger samples are needed to validate these initial findings.