Examining the determinants and perceptions of undergraduate students in the use of Artificial Intelligence (AI) chatbot - Kheow, Kar Lin; Seow, Yin Jeh (2024)
This study examines undergraduate students' behavioural intention to use AI chatbots, with a special focus on three critical aspects: trustworthiness, considered privacy risk, and perceived communication quality. Understanding the elements that affect students' acceptance of AI chatbots is essential as these technologies proliferate in educational settings. Based on the Technology Acceptance Model (TAM), expands on it by analysing the effects of perceived communication quality, perceived privacy risk, and trustworthiness on students' propensity to use AI chatbots. A well-organised Google Form questionnaire was used to collect data from 400 undergraduate students as part of a quantitative study strategy. The study analysed the data and tested the research hypotheses using descriptive, reliable, and inferential statistical analyses carried out using SPSS. The results show that behavioural intention significantly correlates with perceived privacy risk and trustworthiness, but not with perceived communication quality, which does not show a statistically significant correlation. As the survey shows, consumers' inclination to interact with AI technology mostly depends on trustworthiness, but privacy concerns continue to remain a significant obstacle to chatbot adoption. These discoveries have ramifications for the technology industry as well as for education. Theoretically, the study advances the TAM paradigm in research on AI adoption by offering a deeper comprehension of the variables affecting students' behavioural intention of AI technologies. The study guides how educators and developers might create AI chatbots that more effectively address privacy concerns and foster confidence to boost adoption. In conclusion, the study recognises its limitations, including the utilisation of closed-ended enquiries, and offers suggestions for future research aimed at delving further into these traits.