International Journal of
Information and Education Technology

Abstract—Generative artificial intelligence has ushered in a new phase of technological progress, and its effects are increasingly evident across various sectors, particularly in education. These advanced AI models, capable of generating human-like text, code, and even artwork, have the potential to transform both learning and teaching methods. As these technologies become more accessible and sophisticated, educators and students are evaluating the opportunities and challenges they present. This study aims to thoroughly investigate the usage profiles of college students by examining their characteristics and attributes, using a comprehensive twostage cluster analysis as the primary methodological approach. Students from different colleges and universities participated in the survey. To effectively justify the clustering and profiling of students based on the identified attributes, the research employed the Technology Acceptance Model (TAM) in conjunction with the Theory of Planned Behavior (TPB). Through multiple iterations utilizing orthogonal fractional factor design, along with noise handling and the silhouette measure of cohesion and separation, students were categorized based on gender, type of institution, and preferred platforms. The analysis identified three primary clusters of students. The ‘Enthusiasts’ group consists of students who exhibit strong confidence and a high level of comfort using generative AI tools for their academic assignments and projects. The ‘Practitioners’ group comprises students who focus on applying their knowledge in real-world scenarios and benefit from a balanced learning approach. Meanwhile, the ‘Cautious Experts’ group includes students who critically evaluate AI usage and require further development in critical thinking and ethical considerations. The insights from this study can assist school administrators in creating a solid support framework and guidelines for educators and students who incorporate generative AI into their academic work. Awareness campaigns could promote responsible AI practices among students, including informative sessions on best practices and cautions against misuse. By implementing these strategies, the education system can foster a conducive learning environment that empowers students to use AI to enhance their education and prepare them for future careers.

Keywords—generative Artificial Intelligence (AI), academic tasks, two-stage cluster analysis, attitude, student awareness, AI usage

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Cite: Ramachandra C. Torres, "College Students’ Use of Generative AI in Academic Tasks: Integrating Two-Stage Cluster Analysis," International Journal of Information and Education Technology, vol. 15, no. 9, pp. 1906-1914, 2025.

Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).