Abstract

The invention of ChatGPT in late 2022 has contributed to the increasing use of generative artificial intelligence chatbots as a regular action in educational institutions. The aim of this study is to investigate the Impact of Enablers & Disablers on Students' Switching Intention from Generative AI Chatbots (ChatGPT) using the Push and Pull Theory. The Push and Pull Theory is appropriate for this research as it provides a basic approach to detailing factors that will motivate or demotivate a subject matter to switch away from the use of a product. Data was collected between April 2024 and May 2024. Survey data were collected from 224 students across various study levels starting from high school to doctoral level in Saudi Arabia, in which 207 responses were valid, having filtered data based to only respondents that have used generative AI chatbot tool in learning and data with standard deviation above zero. The data were analyzed using SPSS and proposed relationships were assessed using SMART-PLS structural equation modeling tool. To ensure the absence of common method bias (CMB), several tests were examined by the authors including Harman’s test, inner and outer VIF assessment, and marker variable. Concluding no existence of CMB. The study found a positive significant impact of perceived risk, and less social interaction on switching intention. If there is continuously less interaction between students and tutors and there are associated risks with using generative chatbot, students intend to switch away from using this tool. The analysis also revealed that information quality of generative AI chatbot, trust in generative AI chatbot and anthropomorphism characteristics of generative AI chatbot are not enough factors that would make students not to switch away from using the tool if the risks associated with its use are high and the relationship amongst students and teachers will be impacted by the continuous usage of generative AI Chatbot in education. The relevancy of the research stems from the scarcity of research on post-adoption of generative AI chatbot. There is need to identify the factors that will make students switch from using generative AI chatbot in relation to its associated risks, impact on social interaction and quality of information it generates to students. For educational institutions, it highlights the need for continuous emphasis on promoting an amicable environment where students and tutors’ relationship is promoted more over the use of social human-computer interactive technology. The study extends the literature on the use of generative AI chatbot, revealing key factors driving students to learn in an era of high human-robot interaction.

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