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Achieving deeper understanding in online learning requires adaptive support that evolves with learner needs. This paper traces the iterative design of Ivy, a generative AI coach that combines structured knowledge representations with large language models to deliver pedagogically aligned responses. Across three versions: pre-Ivy, Ivy 1.0, and Ivy 2.0, we analyzed learner interactions and preferences. Expert users consistently favored Ivy’s structured, example-driven responses, while novices often preferred the more conversational tone of a ChatGPT-powered assistant. These insights shaped Ivy’s refinement and suggest its potential to support novices in developing conceptual understanding and progressing toward expertise.

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Designing an AI Coaching System for Interactive Video-Based Skill Learning

  • 会议论文

  • 发表日期：

    2026年

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  • Cherie Lum,
  • Erin Deye,
  • Grace Brazil,
  • Tim Bydlon,
  • Shashank Verma,
  • Rochan Madhusudhana,
  • Rahul Dass,
  • Ashok Goel

摘要

Achieving deeper understanding in online learning requires adaptive support that evolves with learner needs. This paper traces the iterative design of Ivy, a generative AI coach that combines structured knowledge representations with large language models to deliver pedagogically aligned responses. Across three versions: pre-Ivy, Ivy 1.0, and Ivy 2.0, we analyzed learner interactions and preferences. Expert users consistently favored Ivy’s structured, example-driven responses, while novices often preferred the more conversational tone of a ChatGPT-powered assistant. These insights shaped Ivy’s refinement and suggest its potential to support novices in developing conceptual understanding and progressing toward expertise.