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This demo paper presents SIMBA, a web-based tool designed to support instructors in creating learning activities with LLM-powered chatbots. It functions as a Socratic tutor, fostering students’ metacognitive skills through structured questioning. By defining learning objectives and a sequence of guiding questions, instructors generate customized chatbots that act as learning companions. These can be shared with students, while instructors monitor interactions via an interactive analytics dashboard. SIMBA was evaluated during a workshop with eight instructors and the results suggest that SIMBA holds promise as a scaffolding tool for active learning, leveraging LLMs to enhance metacognitive engagement while providing instructors with actionable insights.

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SIMBA: A Tool for Designing Generative AI Agents for Reflective Learning and Critical Thinking

  • 会议论文

  • 发表日期：

    2026年

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  • Gabriel Ferrettini,
  • André C. A. Nascimento,
  • Mar Pérez-Sanagustin,
  • Isabel Hilliger

摘要

This demo paper presents SIMBA, a web-based tool designed to support instructors in creating learning activities with LLM-powered chatbots. It functions as a Socratic tutor, fostering students’ metacognitive skills through structured questioning. By defining learning objectives and a sequence of guiding questions, instructors generate customized chatbots that act as learning companions. These can be shared with students, while instructors monitor interactions via an interactive analytics dashboard. SIMBA was evaluated during a workshop with eight instructors and the results suggest that SIMBA holds promise as a scaffolding tool for active learning, leveraging LLMs to enhance metacognitive engagement while providing instructors with actionable insights.