Exploring intention of undergraduate students to embrace chatbots: from the vantage point of Lesotho

• Published in: International Journal of Educational Technology in Higher Education Vol. 21; no. 1; pp. 20 - 28
• Main Authors: Ayanwale, Musa Adekunle, Molefi, Rethabile Rosemary
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 22.03.2024; Springer Nature B.V; SpringerOpen
• Subjects: Artificial intelligence; Chatbots; College students; Compatibility; Computer Appl. in Social and Behavioral Sciences; Computer Science; Computers and Education; Diffusion theory; Diffusion theory of innovation; Education; Educational Objectives; Educational Technology; Higher Education; Humanities; Industry 4.0; Information Systems Applications (incl.Internet); Innovations; Intention; Law; Research Article; Statistics for Social Sciences; Students; Trust (Psychology); Undergraduate Students; Undergraduate study; Chatbots; Undergraduate students; Artificial intelligence; Diffusion theory of innovation
• ISSN: 2365-9440; 2365-9440
• DOI: 10.1186/s41239-024-00451-8

The increasing prevalence of Fourth Industrial Revolution (4IR) technologies has led to a surge in the popularity of AI application tools, particularly chatbots, in various fields, including education. This research explores the factors influencing undergraduate students' inclination to embrace AI application tools, specifically chatbots, for educational purposes. Using an expanded diffusion theory of innovation framework, the study investigates the relationship between relative advantages, compatibility, trialability, perceived trust, perceived usefulness, perceived ease of use, and behavioral intention. Using a 7-point scale, a questionnaire was given to 842 undergraduate students to collect data. The analysis, conducted using SmartPLS 4.0.9.2 software with a covariance-based structural equation model, produced significant findings. The study confirms hypotheses related to the relative advantages, compatibility, trialability, perceived usefulness, and perceived trust associated with chatbots. Notably, students who perceive the benefits of chatbots show a strong intention to use them for academic purposes. The perception of compatibility between students and chatbots positively influences adoption intention, highlighting the importance of compatibility. Additionally, students who have the opportunity to trial chatbots are more likely to use them, emphasizing the significance of trialability. Interestingly, the study did not establish direct relationships between perceived usefulness, perceived ease of use, and behavioral intention. This suggests the presence of other influential factors or dynamics in the adoption of chatbots for educational purposes. These findings offer practical insights for students and contribute to the theoretical understanding of the diffusion theory of innovation. Future research can further explore these insights to unravel the complexities of chatbot adoption and facilitate the broader adoption of AI tools in educational settings.