Determinants of AI Use among Gen-Z Students: Evidence from Ho Chi Minh City, Vietnam

Abstract

Background: AI supports learning through personalized content, resource access, and task automation, but concerns about privacy, ethics, and overreliance may impede adoption. This study uses the Technology Acceptance Model (TAM) to examine factors influencing AI adoption in education. Purpose: This study examines how perceived risks, digital literacy, and self-efficacy influence university students’ intentions to adopt AI in education within Vietnam’s evolving educational landscape. Methodology: A survey of 305 students in Ho Chi Minh City, Vietnam, was conducted using a structured questionnaire, validated through Cronbach’s alpha and exploratory factor analysis. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze the data. Findings: Digital literacy enhances perceived ease of use and self-efficacy, both driving AI adoption. Perceived usefulness strongly predicts acceptance, while risks like accuracy and privacy concerns hinder it. Self-efficacy mediates digital literacy’s impact on acceptance. Students prioritized AI’s functionality over accessibility. Implications and Recommendations: The findings advocate enhancing digital literacy and addressing risks to promote responsible AI use in education. Limited to one university, future research should explore diverse contexts. Contribution: This study underscores digital literacy and self-efficacy as key to AI adoption in Vietnam’s educational landscape.