What Does it Take to Trigger Intention to Use Artificial Intelligence among Students in Higher Education Institutions?

The increasing integration of Artificial Intelligence (AI) in higher education institutions necessitates a student prepared for this transformative change. This study investigates the factors influencing students' intention to use AI tools in their study. Drawing upon the Technology Acceptance Model (TAM), the research aims to understand how perceived ease of use, and perceived usefulness impact students' intention to use with attitude, and self-efficacy as mediators. Data collection employed a survey instrument distributed to a sample of 319 students from public and private higher education institutions. The survey measured participants' perceptions of AI ease of use, perceived usefulness, attitude towards AI, self-efficacy, and intention to use AI tools in their study. Statistical analysis utilized Partial Least Squares (PLS) to assess the relationships between the proposed variables and test the formulated hypotheses. The results of the hypothesis testing confirmed the positive influence of perceived ease of use and perceived usefulness on students' intention to use AI tools, aligning with TAM principles. Furthermore, the study revealed that attitude and self-efficacy act as mediating factors, bridging the gap between perceived ease of use and perceived usefulness and intention to use. These findings suggest that beyond just the technical aspects of AI, students' perceptions, attitudes, and confidence levels significantly influence their willingness to use AI in their study. The study's implications are significant for organizations implementing AI. By prioritizing the user-centered design of AI tools, emphasizing training and skill development to enhance perceived ease of use, and communicating the benefits of AI to address perceived usefulness, organizations can foster a more positive student attitude towards AI. Additionally, promoting a culture of learning and support can boost student's self-efficacy and ultimately encourage wider usage of AI tools within the organization.