Understanding the Dynamics of ChatGPT Adoption Among Undergraduate Students: Dataset from a Philippine State University

The article presents raw inferential statistical data related to explaining the factors influencing ChatGPT acceptance and utilization among undergraduate students in Philippine Higher Education. In this dataset, we have generated a series of variables based on the Unified Theory of Acceptance and Utilization of Technology dimensions. The factors considered are Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price Value, Habit, Age, Gender, Experience, Behavioral Intention, and Use Behavior. A structured questionnaire was distributed via an online survey to 524 undergraduate students, and 461 valid responses were analyzed. An analysis of the data was conducted using structural equation modeling through WarpPLS version 8.0. In addition, student demographic information was provided. An analysis of the measurement model was conducted to establish the reliability and validity of each construct, and a structural model analysis was conducted to test the hypotheses. The outcomes obtained from this dataset demonstrate the direct influence of the factors identified and the moderating role of age, gender and experience. This dataset is crucial in gaining a deeper understanding of AI-powered chatbots, and this dataset is useful for reference and consideration. Also, countries with similar characteristics to the Philippines can benefit from this dataset.