Abstract

Education 4.0 increasingly relies on generative artificial intelligence (GenAI) to personalize learning experiences and provide personalized tools that improve student engagement and comprehension. Its capacity for analyzing enormous volumes of data enables educators to design adaptable lessons that satisfy the various demands of students in a society that is becoming increasingly digitalized and interconnected. This study examines GenAI’s undergraduate intentions for enhanced learning from the planned behavior theory (PBT) perspective. Based on the convenience sampling technique, an online survey was conducted, and 122 undergraduates attending a Nigerian public university responded to the same. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze the data collected for measurement and structural model assessment. Evaluation of the measurement model revealed the reliability and validity of the factor loading and the constructs, while the structural model assessment was used to test the hypotheses, the effects of the paths, and the model’s predictive relevance. The result shows that attitudes toward GenAI do not influence its actual use among undergraduates but rather influence intention to use GenAI. Furthermore, the intention to use GenAI influences its actual use. In addition, perceived control concerning GenAI influences the intention to use and the actual use of GenAI. However, subjective norms concerning GenAI do not influence the intention to use GenAI. PBT core factors positively influence undergraduate intent to use GenAI, and behavioral intention influences the actual use of GenAI. This study stresses the need for motivating components like perceived behavioral control (PBC) in determining intention and actual use of GenAI.