Learn Like Feynman: Developing and Testing an AI-Driven Feynman Bot
Akshaya Rajesh, Sumbul Khan

TL;DR
This paper introduces the Feynman Bot, an AI-driven tool that employs the Feynman learning technique to enhance self-regulated learning through question-answer discussions, demonstrating improved learning outcomes and confidence.
Contribution
The paper develops and tests a novel AI-powered Feynman Bot using large language models and retrieval-augmented generation, specifically designed for self-regulated learners without peer or instructor support.
Findings
Participants using the Feynman Bot showed higher learning gains.
Feynman Bot users reported increased confidence with the subject.
Typing was preferred over speech for interaction.
Abstract
The Feynman learning technique is an active learning strategy that helps learners simplify complex information through student-led teaching and discussion. In this paper, we present the development and usability testing of the Feynman Bot, which uses the Feynman technique to assist self-regulated learners who lack peer or instructor support. The Bot embodies the Feynman learning technique by encouraging learners to discuss their lecture material in a question-answer-driven discussion format. The Feynman Bot was developed using a large language model with Langchain in a Retrieval-Augmented-Generation framework to leverage the reasoning capability required to generate effective discussion-oriented questions. To test the Feynman bot, a controlled experiment was conducted over three days with fourteen participants. Formative and summative assessments were conducted, followed by a…
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