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

• Autores: Musa Adekunle Ayanwale, Rethabile Rosemary Molef
• Localización: International Journal of Educational Technology in Higher Education, ISSN 2365-9440, Nº. 21, 2024
• Idioma: inglés
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• Dialnet Métricas: 2 Citas
• Resumen

  • 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 felds, including education. This research explores the factors infuencing undergraduate students’ inclination to embrace AI application tools, specifcally chatbots, for educational purposes. Using an expanded difusion 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 signifcant fndings.

    The study confrms hypotheses related to the relative advantages, compatibility, trialability, perceived usefulness, and perceived trust associated with chatbots. Notably, students who perceive the benefts of chatbots show a strong intention to use them for academic purposes. The perception of compatibility between students and chatbots positively infuences adoption intention, highlighting the importance of compatibility. Additionally, students who have the opportunity to trial chatbots are more likely to use them, emphasizing the signifcance 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 infuential factors or dynamics in the adoption of chatbots for educational purposes. These fndings ofer practical insights for students and contribute to the theoretical understanding of the difusion 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.