Generative AI in Everyday Academic Work: An Exploratory Survey of Usage Patterns, Perceived Effectiveness, and Concerns among Indonesian University Students

Abstract

Background. Generative artificial intelligence (generative AI) tools have diffused rapidly into university study, yet, in the literature reviewed for this study, most empirical evidence concerns designed interventions or Western student populations. How students in Southeast Asia draw on these tools in unsupervised, self-directed academic work is sparsely documented in that literature. Objective. This exploratory study describes self-reported generative AI use, perceived effectiveness, and the benefits and concerns articulated by university students, primarily in Indonesia. Methods. A cross-sectional online survey was administered via Google Forms in June 2026. Twenty-four students accessed the survey; one declined consent, yielding 23 analysable cases (21 Indonesian, 2 Chinese). The instrument comprised seven usagefrequency items referring generically to “AI tools” and seven perceived-effectiveness items, both on five-point Likert scales (α = .92 across the 14 items), and two open-ended questions. Analysis was restricted to descriptive statistics, one descriptive correlation coefficient (not interpreted inferentially), and reflexive thematic analysis. No inferential group comparison was attempted. Results. Students reported using generative AI most often to understand difficult course materials (M = 3.65, SD = 1.27) and to brainstorm ideas or generate explanations (M = 3.52, SD = 1.16), and least often as part of a daily study routine (M = 2.65, SD = 1.15). Perceived effectiveness was highest for comprehension (M = 3.61, SD = 1.34) and lowest for overall learning achievement (M = 3.00, SD = 1.13). The two composite scores correlated at r = .87 in this sample; because both derive from a single instrument at one occasion, the coefficient is reported descriptively and is not interpreted as evidence of a relationship between distinct constructs. Thematic analysis of the open responses identified time efficiency (27% of 22 respondents) as the most frequently reported benefit, with personalized tutoring, brainstorming support, and improved comprehension each cited by 18% of 22 respondents. The most frequently reported concern was over-reliance diminishing independent thinking (37% of 19 respondents), followed by doubts about the accuracy of AI output (26% of 19 respondents) and difficulty formulating effective prompts (16% of 19 respondents).