Exploring the role of human-AI collaboration in solving scientific problems

[This paper is part of the Focused Collection in Artificial Intelligence Tools in Physics Teaching and Physics Education Research.] Recent research in science education has largely focused on using ChatGPT to solve problems and evaluating its accuracy and problem-solving features. However, as artificial intelligence (AI) is becoming an important tool for human development, effective strategies for learning and education using human-AI collaboration (HAI) learning remain underexplored. HAI is emerging as a powerful tool for enhancing educational outcomes, especially with the integration of advanced natural language AI systems such as ChatGPT-4o. This study explores the role of HAI in solving scientific problems, comparing its efficacy with human-human collaboration (HHC) among high school students. We employed two different groups: one using HAI with ChatGPT-4o, and the other using HHC, focusing on their performance in scientific knowledge and scientific thinking tasks. Results showed that while both collaboration methods significantly improved students’ performance in solving scientific problems, HHC exhibited a greater effect size compared to HAI. The use of ChatGPT-4o was particularly noted for its ability to provide interactive learning experiences and guide students through problem solving; however, challenges such as inconsistencies in responses and image recognition hindered its effectiveness. Additionally, students tended to use ChatGPT-4o as a tool for obtaining answers rather than engaging in deeper collaborative explorations. This study underscores the importance of developing targeted training for students in effectively collaborating with AI tools. The results can also provide useful information for future exploration on methods to strengthen HHC by integrating AI tools, leveraging the strengths of both approaches to enhance education outcomes.