Modeling Student Loyalty in the Age of Generative AI: A Structural Equation Analysis of ChatGPT’s Role in Higher Education

Abstract

Lately, there has been a notable surge in the use of AI-driven dialogue systems like ChatGPT-3.5 within the realm of education. Understanding the factors that are associated with student engagement in these digital platforms is crucial for maximizing their potential and long-term efficacy. This study aims to systematically identify the key drivers behind university students’ loyalty to ChatGPT. Data gathered from university participants was analyzed using structural equation modeling. The findings indicate that novelty value is positively associated with both task attraction and hedonic value. Perceived intelligence shows significant associations with knowledge acquisition, task attraction, and hedonic value. Moreover, knowledge acquisition is positively related to task attraction and hedonic value, while creepiness is negatively related to them. Both task attraction and hedonic value demonstrate significant relationships with satisfaction and loyalty, with trust also positively associated with satisfaction. These insights provide a clearer understanding of what motivates university students to engage with AI conversational platforms like ChatGPT. This information is invaluable for stakeholders aiming to augment the adoption and effective use of such tools in educational contexts.