The influences of ChatGPT on undergraduate students’ demonstrated and perceived interdisciplinary learning

The significance of interdisciplinary learning has been well-recognized by higher education institutions. However, when teaching interdisciplinary learning to junior undergraduate students, their limited disciplinary knowledge and underrepresentation of students from some disciplines can hinder their learning performance. ChatGPT’s ability to engage in human-like conversations and massive knowledge grounded in different disciplines holds promise in enriching undergraduate students with the disciplinary knowledge that they lack. In this exploratory study, we engaged 130 undergraduate students in a three-condition quasi-experiment to examine how ChatGPT influences their demonstrated and perceived interdisciplinary learning quality, as measured by their online posts and surveys, respectively. The content analysis results show that overall, students’ online posts could be coded into four interdisciplinary learning dimensions: diversity, disciplinary grounding, cognitive advancement, and integration. The means of the first three dimensions were close to the middle level (ranging from 0.708 to 0.897, and the middle level is 1), whereas the mean score of integration was relatively small (i.e., 0.229). Students under the ChatGPT condition demonstrated improved disciplinary grounding. Regarding their perceived interdisciplinary learning quality, we did not find significant differences across the three conditions in the pre- or post-surveys. The findings underscore ChatGPT’s ability to enhance students’ disciplinary grounding and the significance of further fostering their integration skills.