Investigating student acceptance of an academic advising chatbot in higher education institutions

The study explores factors affecting university students’ behavioural intentions in adopting an academic advising chatbot. The study focuses on functional, socio emotional, and relational factors affecting students’ acceptance of an AI-driven aca demic advising chatbot. The research is based on a co...

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Bibliographic Details
Main Author: Bilquise, Ghazala (author)
Other Authors: Ibrahim, Samar (author), M. Salhieh, Sa’Ed (author)
Published: 2023
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Online Access:https://bspace.buid.ac.ae/handle/1234/3113
https://doi.org/10.1007/s10639-023-12076-x.
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Summary:The study explores factors affecting university students’ behavioural intentions in adopting an academic advising chatbot. The study focuses on functional, socio emotional, and relational factors affecting students’ acceptance of an AI-driven aca demic advising chatbot. The research is based on a conceptual model derived from several constructs of traditional technology acceptance models, TAM, UTAUT, the latest AI-driven self-service technologies models, the Service Robot Acceptance (sRAM) model, and the intrinsic motivation Self Determination Theory (SDT) model. The proposed conceptual model has been tailored to an educational con text. A questionnaire Survey of Non-purposive sampling technique was applied to collect data points from 207 university students from two major universities in the UAE. Subsequently, PLS-SEM causal modelling was applied for hypothesis testing. The results revealed that the functional elements, perceived ease of use and social influence significantly affect behavioural intention for chatbots’ acceptance. How ever, perceived usefulness, autonomy, and trust did not show significant evidence of influence on the acceptance of an advising chatbot. The study reviews chatbot literature and presents recommendations for educational institutions to implement AI-driven chatbots effectively for academic advising. It is one of the first studies that assesses and examines factors that impact the willingness of higher education students to accept AI-driven academic advising chatbots. This study presents sev eral theoretical contributions and practical implications for successful deployment of service-oriented chatbots for academic advising in the educational sector.