Investigating student perceptions of creativity and generative ai in computational physics

TL;DR

This study explores how upper-division physics students perceive generative AI, revealing they see it as a helpful resource but remain skeptical about its accuracy and creative capabilities.

Contribution

It applies the Four C Model to analyze student perceptions of creativity and gen-AI in a computational physics context, providing insights into student attitudes.

Findings

Students view their creativity mainly as mini-c and little-c.

Students see gen-AI as a resource and learning aid.

Students are skeptical about gen-AI's accuracy and creativity.

Abstract

Generative Artificial Intelligence (gen-AI) is rapidly becoming more integrated into today's classrooms in all ranges of education. In higher education, Gen-AI is often seen as a resource for students, aiding them in drafting outlines, solving simple mathematical problems, or even decoding or constructing code. In this paper, we analyze essay-based interviews (N=6) from an upper-division computational physics course, in which physics majors addressed their views and attitudes towards Gen-AI and how it affects their learning. We analyzed the concepts of creativity and gen-AI using the Four C Model, a framework encompassing four types of creativity. Our analysis of the data involved coding and characterizing students' definitions of creativity and generative AI. Our findings revealed two main observations: first, students conceptualized their creativity primarily within mini-c and little-c; second, students perceived gen-AI as a resource and learning tool but expressed skepticism regarding its accuracy and creativity.