AN EMPIRICAL STUDY OF UTAUT MODEL ON THE ADOPTION OF AI TECHNOLOGIES IN VIETNAMESE HIGHER EDUCATION
Description
This dataset supports an empirical study examining factors influencing the adoption of AI technologies in Vietnamese higher education. Guided by an integrated framework based on UTAUT, TAM, and Perceived Organizational Support (POS), the study tests whether performance expectancy, effort expectancy, social influence, facilitating conditions, perceived usefulness, perceived ease of use, and organizational support predict users’ intention to adopt AI technologies. The data consist of anonymised survey responses collected online from participants affiliated with Vietnamese universities, including students and academic staff. Questionnaire items were adapted from validated technology acceptance scales and measured using Likert-type responses. Results indicate that perceived usefulness, ease of use, performance expectancy, and organizational support significantly influence positive attitudes and behavioural intention toward AI adoption. The dataset can be reused for replication studies, comparative research, or further modelling of technology adoption in higher education contexts.
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Steps to reproduce
The data were obtained through a quantitative survey study conducted in Vietnamese higher education institutions. A structured questionnaire was developed based on established and validated measurement scales from the Unified Theory of Acceptance and Use of Technology (UTAUT), the Technology Acceptance Model (TAM), and Perceived Organizational Support (POS). All items were adapted to the context of AI technologies in higher education. The survey was administered online using a web-based questionnaire platform. Participants were recruited through institutional networks and voluntarily completed the survey. Responses were recorded using Likert-type scales. No personally identifiable information was collected. Data cleaning involved screening for incomplete responses and response inconsistencies prior to analysis. The dataset was prepared in spreadsheet format for statistical analysis. The data can be reproduced by administering the same questionnaire to comparable higher education populations and analysing the responses using standard quantitative techniques such as regression or structural equation modelling.