Determinants of University Students' Intent to Adopt Artificial Intelligence (AI): A Case Study of the National University of Battambang, Cambodia
Year: 2026
Type: article
Study design: Observational Study
Abstract: This research investigated the factors that affect students' intention to adopt artificial intelligence (AI). This included examining students' adoption of AI technologies, the factors that affect their intention to adopt AI, and the relationship between AI technology use and the factors that affect adoption intention. This research used a quantitative approach, collecting data through a questionnaire from 316 university students at the National University of Battambang using simple random sampling. The data were analyzed using descriptive statistics, reliability analysis, Pearson correlation, and multiple linear regression. All respondents (100%) adopted AI technologies such as ChatGPT (84.8%), Google Gemini (14.2%), and Microsoft Copilot (0.9%). Students' behavioral intention to adopt AI was high (M = 2.84 on a 4-point scale). Mean scores for the factors affecting students' intention to adopt AI all fell within the high-agreement band (M = 2.63–3.03). Among the factors that influence students' intention to adopt AI, performance expectancy had the highest mean (M = 3.03; highest item M = 3.142). Social influence was the strongest regression predictor (β = .293, p < .001). Furthermore, multiple linear regression indicated a statistically significant positive relationship between the five independent constructs and behavioral intention (F(5, 310) = 53.65, p < .001, R2 = .464), supporting all proposed hypotheses (H1, H2, H3, H4, and H5). Importantly, the students expressed a strong commitment to ethical AI usage and maintaining academic integrity (M = 3.174). Higher education institutions should integrate dedicated AI training modules into curricula and strengthen digital support.
Institution: National University of Battambang
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7223807697