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GPT-4 as a Homework Tutor can Improve Student Engagement and Learning Outcomes

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arxiv 2409.15981 v1 pith:POWYNAUR submitted 2024-09-24 cs.CY

classification cs.CY
keywords homeworkgpt-4learningengagementhigh-schoolinteractiveoutcomesschools
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This work contributes to the scarce empirical literature on LLM-based interactive homework in real-world educational settings and offers a practical, scalable solution for improving homework in schools. Homework is an important part of education in schools across the world, but in order to maximize benefit, it needs to be accompanied with feedback and followup questions. We developed a prompting strategy that enables GPT-4 to conduct interactive homework sessions for high-school students learning English as a second language. Our strategy requires minimal efforts in content preparation, one of the key challenges of alternatives like home tutors or ITSs. We carried out a Randomized Controlled Trial (RCT) in four high-school classes, replacing traditional homework with GPT-4 homework sessions for the treatment group. We observed significant improvements in learning outcomes, specifically a greater gain in grammar, and student engagement. In addition, students reported high levels of satisfaction with the system and wanted to continue using it after the end of the RCT.

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Cited by 3 Pith papers

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  1. Superstudent intelligence in thermodynamics

    cs.CE 2025-06 conditional novelty 6.0 of 10

    OpenAI's o3 model scored higher than all 90 students on a real university thermodynamics exam, zero-shot, including problems with graphical output.

  2. Educators' Perceptions of Large Language Models as Tutors: Comparing Human and AI Tutors in a Blind Text-only Setting

    cs.ET 2025-06 conditional novelty 6.0 of 10

    In blind pairwise comparisons, educators rated an LLM tutor (MWPTutor) as better than human tutors from MathDial on empathy, scaffolding, and conciseness, with no significant advantage on engagement.

  3. Designing Needs- and Attention-Aware AI Learning Tools for Engineering Education: Insights from Psychological Outcomes

    cs.HC 2026-07 conditional novelty 5.0 of 10

    Engineering students perceive AI chatbots as most helpful for relieving competence frustration, less for autonomy, and least for relatedness; inattention weakens those perceived benefits.

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