Generative AI as a lab partner: a case study

TL;DR

This study explores how high school students use ChatGPT during physics labs, highlighting its potential to enhance problem-solving and understanding, while emphasizing the ongoing need for teacher guidance and student training.

Contribution

It provides a case study on integrating generative AI into physics laboratory education and analyzes its role in developing students' problem-solving skills.

Findings

Students use ChatGPT to explore acoustic levitation and sound speed.

Generative AI can assist with physics problems but requires teacher oversight.

Effective use of AI in labs depends on student training and understanding of AI limitations.

Abstract

Generative AI tools, including the popular ChatGPT, have had a significant impact on discourses about future work and educational practices. Previous research in science education has highlighted the potential of generative AI in various education-related areas, including generating valuable discussion material, solving physics problems, and acting as a tutor. However, little research has been done regarding the role of generative AI tools in laboratory work, an essential part of science education, and physics education specifically. Here we show various ways in which high school students use ChatGPT during a physics laboratory session and discuss the relevance of using generative AI tools to investigate acoustic levitation and the speed of sound in air. Additionally, employing variation theory as a theoretical lens in the analysis, we identify how generative AI can be used to further develop students' problem-solving skills in the physics laboratory. However, although our study shows that generative AI tools may handle some relevant questions and problems during laboratory work, the teacher still plays a crucial role in identifying students' needs and capabilities of understanding the potential and limitations of generative AI. Finally, this study serves as an important point of discussion regarding the ways in which students need support and training to efficiently utilize generative AI to further their learning of physics.