mlsanityData to 14 Oct 2026

Imitating Mistakes in a Learning Companion AI Agent for Online Peer Learning

arXiv 2507.12801 ↗First posted 17 Jul 2025cs.AI cs.MAcited by 3

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Abstract (arXiv)

In recent years, peer learning has gained attention as a method that promotes spontaneous thinking among learners, and its effectiveness has been confirmed by numerous studies. This study aims to develop an AI Agent as a learning companion that enables peer learning anytime and anywhere. However, peer learning between humans has various limitations, and it is not always effective. Effective peer learning requires companions at the same proficiency levels. In this study, we assume that a learner's peers with the same proficiency level as the learner make the same mistakes as the learner does and focus on English composition as a specific example to validate this approach.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 6 of its 29 references that are in the map. First posted on arXiv 17 Jul 2025.

Builds on

6 of 29 references.

References · 6

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  3. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
  4. 2023ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debatecited by 742
  5. 2024Scaling Synthetic Data Creation with 1,000,000,000 Personascited by 417
  6. 2023Controlled Generation with Prompt Insertion for Natural Language Explanations in Grammatical Error Correctioncited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.