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This study explores how an educational chatbot, typically used for individual assistance, can be repurposed to support collaborative learning in higher education. The goal was to examine whether integrating a chatbot into a structured peer discussion environment could enhance students’ conceptual understanding and academic performance. A total of 148 students from management, economics, and engineering programs participated in a repeated crossover experiment. In the Test condition, students used a chatbot trained on course materials to answer open-ended questions, then collaborated via WhatsApp to critique and refine the chatbot’s responses before completing assignments. The control group (CG) completed the same tasks individually using only written resources. Findings revealed that students in the Test group (TG) performed better, showed higher engagement, and reported greater satisfaction. Their discussions demonstrated critical thinking, peer support, and active reworking of AI-generated responses. The chatbot acted as a starting point for conversation, rather than a standalone tutor, and worked best when used in a structured collaborative context. In contrast, control group students experienced more difficulty and reported lower engagement. The results suggest that chatbots, when used within well-designed collaborative activities, can foster deeper learning and digital literacy. However, without pedagogical guidance, chatbot use alone does not support meaningful educational outcomes. Educators are encouraged to embed chatbot interactions in peer-based tasks, promote questioning and reflection, and use messaging platforms to support conversation. This approach highlights the value of combining AI tools with human collaboration to create more engaging and effective learning environments.

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Integrating a Chatbot in a Collaborative Learning Scenario: A Pedagogical Approach in Hybrid Contexts

  • 会议论文

  • 发表日期：

    2026年

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  • Hiba Gharbaoui,
  • Souad Ahriz,
  • Khalifa Mansouri,
  • Franck Poirier

摘要

This study explores how an educational chatbot, typically used for individual assistance, can be repurposed to support collaborative learning in higher education. The goal was to examine whether integrating a chatbot into a structured peer discussion environment could enhance students’ conceptual understanding and academic performance. A total of 148 students from management, economics, and engineering programs participated in a repeated crossover experiment. In the Test condition, students used a chatbot trained on course materials to answer open-ended questions, then collaborated via WhatsApp to critique and refine the chatbot’s responses before completing assignments. The control group (CG) completed the same tasks individually using only written resources. Findings revealed that students in the Test group (TG) performed better, showed higher engagement, and reported greater satisfaction. Their discussions demonstrated critical thinking, peer support, and active reworking of AI-generated responses. The chatbot acted as a starting point for conversation, rather than a standalone tutor, and worked best when used in a structured collaborative context. In contrast, control group students experienced more difficulty and reported lower engagement. The results suggest that chatbots, when used within well-designed collaborative activities, can foster deeper learning and digital literacy. However, without pedagogical guidance, chatbot use alone does not support meaningful educational outcomes. Educators are encouraged to embed chatbot interactions in peer-based tasks, promote questioning and reflection, and use messaging platforms to support conversation. This approach highlights the value of combining AI tools with human collaboration to create more engaging and effective learning environments.