ChatGPT in higher education learning: Acceptance and use

Abstract

This paper examines the determinants that drive ChatGPT use in learning among Indonesian Higher Education Institutions (HEIs) students. A proposed model based on the unified theory of acceptance and use of technology model-2 (UTAUT2) was used in the context of the study. A pilot study was done prior to the main data collection to examine the reliability of the instrument. For the structural model assessment, 1117 responses were analyzed through Partial Least Square Structural Equation Modeling (PLS-SEM) and Importance-Performance Analysis (IPMA). Most hypotheses are confirmed by the significant results reported through the PLS-SEM. The strongest determinant of Behavioral Intention (BI) to use ChatGPT in learning was Facilitating Conditions (FC). ChatGPT use (GPTU) was most significantly predicted by BI. However, one hypothesis was not supported; the insignificant role of Effort Expectancy (EE) on BI was revealed. Through IPMA, FC had the most significant importance for BI, while BI was the most important determinant for GPTU. Besides, BI obtains the highest performance in the IPMA procedure. This study addresses a UTAUT model by evaluating ChatGPT acceptance and use among HEIs students in Indonesia. Findings could facilitate policymakers with insights into the determinants and initiate effective and efficient policies to improve artificial intelligence use in education, specifically ChatGPT.