Home⇛International Journal of Multidisciplinary: Applied Business and Education Research⇛vol. 7 no. 4 (2026)

Patterns and Extent of Generative AI Use Among College Students: A Demographic-Based Quantitative Analysis

Neil J. Pelino | Junry P. Bacalso | Jellow S. Painagan

Discipline: Artificial Intelligence

 

Abstract:

This research investigated the trends and levels of generative artificial intelligence (AI) application among the students of the Bachelor of Sci- ence in Information Systems (BSIS) at Carmen Municipal College in the Academic Year 2025 to offer a localized approach to a Philippine-based context of higher education. Data was gathered aligned with descriptive quantitative design, 389 respondents (72.6% response rate) were sur- veyed using a standardized questionnaire and analysed with descriptive statistics and non-parametric tests. It has been found that the most com- mon types of tasks by which students use generative AI are academically related and efficiency-based, namely, completing homework, brain- storming, seeking advice, and brainstorming, with an average usage of 3.15, meaning that AI is a facilitating learning tool, not an alternative to learning on their own. Inferential statistics showed that the difference in perceived AI influence was statistically significant among genders (U = 16,654, p =.047), year level (H (2) =11.40, p =.003), and age (H (4) = 9.95, p =.041), which means that perceived AI influence is different among the demographic groups in the institution. In contrast to the previous re- search that tends to generalize the application of AI by students in a larger context, the given study notes the patterns of its usage as condi- tioned by academic level and demographics of learners in a particular in- stitutional environment. The findings can be used as context-specific in- formation that can be used to develop evidence-based policies, AI liter- acy-focused programs, and responsible integration strategies in other similar public institutions of higher education.



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