Research on the acceptance of ChatGPT among different college student groups based on latent class analysis

Abstract

Artificial intelligence, such as ChatGPT, is advancing rapidly, driving significant transformations in various social areas such as education. This study aimed to divide the student group and test the acceptance of ChatGPT in different student groups through the established model. This study used college students as the research object and the latent class model to distinguish the AI digital ability of students. In this study, the sample of students was divided into groups of weak and strong AI digital based on the latent class model. Taking the whole sample, students with weak and strong digital ability as the research objects, the structural equation model of technology acceptance model and planned behavior theory were established to study the acceptance of ChatGPT among different student groups. The results showed significant heterogeneity in the acceptance of ChatGPT among the student groups. Across the whole sample, perceived behavioral control was the most important factor affecting students' acceptance of the ChatGPT. For students with weak AI digital ability, both attitude and perceived behavioral control play significant roles in their acceptance of ChatGPT. Students with strong AI digital ability are influenced by attitude, subjective norms, and perceived behavioral control when considering their acceptance of ChatGPT.

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