Assessing Students' Satisfaction with AI Tools in Higher Education

Abstract

Nowadays, AI-powered applications are increasingly integrated into academic fields, and numerous studies have discussed the acceptance of this technology among higher education students. With AI worldwide establishment, empirical research remains necessary to evaluate user satisfaction, effectiveness, and long-term sustainability. Since cultural, social, and economic factors influence how AI is implemented in education, the level of acceptance of AI tools among students also may vary from one country to another. This study aims to explore university students' satisfaction with AI tools in the context of higher education in Malaysia, specifically in Kelantan. This study examines how satisfied students are with AI technologies used for their learning, with an emphasis on emotional well-being, content quality, and perceived utility of the tools. Using a cross-sectional approach, 105 undergraduate students from various faculties at Universiti Teknologi MARA (UiTM) Kelantan were selected to participate in the study. Students were given a self-administered questionnaire using Google Forms to obtain the data. Simple random sampling was used in the study, and the data analysis was conducted using Multiple Linear Regression (MLR). The findings showed that the only significant variables influencing students' satisfaction with AI tools in their education are emotional well-being and perceived utility, while the quality of the content is not statistically significant. The findings show that how students feel when using AI tools together with their perception of the tool’s benefit is crucial despite the content itself. The results indicate that, to drive user satisfaction and long-term usage of this technology, developers may prioritize usability, perceived benefits, and emotional engagement rather than solely enhancing algorithmic reliability or refining instructional content.