Author(s) :

Yuhan Dong.

Volume/Issue :

Abstract :

As Artificial Intelligence (AI) becomes increasingly prevalent, questions have arisen regarding the motivations that drive students to rely on it. This study investigates the factors influencing the likelihood of AI use among undergraduate students, and how these factors vary by year of study and broad subject area. A Chi-Square Test for Homogeneity was conducted for each factor within these groups to determine whether significant differences existed in the proportions of students selecting particular motivations or uses. The dataset analyzed was drawn from a survey of 1,041 undergraduate students in the United Kingdom. The findings indicate that students primarily use AI to save time, improve the quality of their work, and obtain instant support, while they are less likely to use AI when concerned about accusations of cheating or the risk of false or biased results. Significant differences emerged in students’ use and motivations behind the likelihood of AI for data analysis, summarization, and improving work quality across years of study. Differences were also observed in generating text, summarizing, coding, saving time, and concerns about cheating across subject areas. These results underscore the need for educators to provide greater support to younger students, as well as equitable education and access to AI resources across disciplines. Moreover, educators should refine guidelines for AI use to reflect disciplinary differences, and future research should examine how these needs evolve within specific fields.