Unleashing the Determinants of Adoption of ChatGPT in Medical Education: A Student Perspective

Authors: Puneet Kumar Gupta, Sonam Maheshwari, Reena Pal

DOI: 10.18231/j.ijfcm.11419.1758619569

Keywords: ChatGPT, UTAUT2, medical education, technology acceptance, SmartPLS

Abstract: Background: ChatGPT is a powerful AI tool with conversational capabilities, in the setting of writing, learning, and assessment solving. Objective: The crux of the proposed study is to develop a predictive model based on an established theory of technology adoption to understand the determinants leading to medical students' acceptance and use of ChatGPT. Materials and Methods: The study selected seven key predictors to construct the model, which focused on students' behavioral intentions and actual usage of ChatGPT. Data analysis employed the partial-least squares method of structural equation modeling, demonstrating the reliability and validity of the proposed model. Findings: The findings are based on self-reported data from 353 students from a government medical college of Uttarakhand. Remarkably, nine out of ten hypotheses were confirmed, revealing significant insights into the factors driving students' intentions to use ChatGPT. Habit emerged as the most dominant determinant of behavioral intention, afterward performance expectancy and hedonic motivation. Moreover, the influencing determinant of actual usage behavior was behavioral intention, complemented by personal innovativeness. Conclusion: The research underlines the urgency for further investigation into the integration of AI tools in learning, signifying the potential transformative impact of AI in education.