Year: 2025
Type: conference-paper
Study designs: Randomized Controlled Trial, Clinical Trial
Abstract: This work contributes to the scarce empirical literature on LLM-based interactive homework in real-world educational settings and offers a practical, scalable solution to improve homework in schools.Homework is an important part of education in schools across the world, but to maximize benefit, it must be accompanied by feedback and follow-up 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 effort in content preparation, one of the key challenges of alternatives such as home tutors or ITSs.We carried out a Randomized Controlled Trial (RCT) in four highschool classes, replacing traditional homework with GPT-4 homework sessions for the treatment group.We found that the treatment group had higher levels of satisfaction and desire to keep using the system among the students.This occurred without compromising learning outcomes, and one group even showed significantly better learning gains.
Institutions: University of Zurich, ETH Zurich
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4412889732