AI Chatbots as Academic Assistants: Do Frequency and Perceived Usefulness Drive Learning Motivation?
DOI:
https://doi.org/10.31004/joecy.v5i2.3752Keywords:
AI chatbots, Cenderawasih University, economics students, frequency of use, learning motivationAbstract
The study purpose was to examine whether the frequency of using AI chatbots and students’ perceived usefulness of those chatbots are associated with learning motivation among economics undergraduates at Cenderawasih University.
Materials and methods. A quantitative explanatory, cross-sectional survey was administered to 89 economics students selected proportionally across semesters. Learning motivation was measured via indicators of interest in study, enthusiasm for assignments, satisfaction with learning, and consistency in study habits. After pilot testing and instrument refinement, data were analyzed using simple linear regression (overall utilization) and multiple regression (frequency and perceived usefulness), following normality, multicollinearity, and heteroscedasticity checks.
Results show a statistically significant model (F = 54.442, p < .001) explaining a substantial share of variance in learning motivation (R² = 0.559; Adjusted R² = 0.548). Perceived usefulness exerted a larger effect (β = 0.550) than frequency (β = 0.343), with both predictors highly significant (p < .001). The joint model of frequency and perceived usefulness predicted motivation robustly (p < .001), supporting all three hypotheses.
References
Brändle, M., Bahr, T., Arnold, J. B., & Zinn, B. (2025). A comparative study of epistemological beliefs and AI chatbot usage among early adopters and later users in higher education. 2022 IEEE Global Engineering Education Conference (EDUCON), 1–10. https://doi.org/10.1109/educon62633.2025.11016452
Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: a review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/access.2020.2988510
Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, 100118. https://doi.org/10.1016/j.caeai.2022.100118
Essel, H. B., Vlachopoulos, D., Tachie-Menson, A., Johnson, E. E., & Baah, P. K. (2022). The impact of a virtual teaching assistant (chatbot) on students’ learning in Ghanaian higher education. International Journal of Educational Technology in Higher Education, 19(1). https://doi.org/10.1186/s41239-022-00362-6
Eteng-Uket, S. (2025). The Impact of Artificial intelligence chatbots on Student Learning: A Quasi-Experimental Analysis of Learning Outcome and engagement. The Journal of Educators Online, 22(2). https://doi.org/10.9743/jeo.2025.22.2.4
Følstad, A., & Brandtzaeg, P. B. (2020). Users’ experiences with chatbots: findings from a questionnaire study. Quality and User Experience, 5(1). https://doi.org/10.1007/s41233-020-00033-2
Hanshaw, G., Vance, J., & Brewer, C. (2024). Exploring the effectiveness of AI course assistants on the student learning experience. Open Praxis, 16(4). https://doi.org/10.55982/openpraxis.16.4.719
Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial Intelligence in Education. Globethics Publications.
Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: Systematic literature review. International Journal of Educational Technology in Higher Education, 20(1), 56. https://doi.org/10.1186/s41239-023-00426-1
Mourabit, I. E., Andaloussi, S. J., Ouchetto, O., & Miyara, M. (2025). AI chatbots in Higher Education: Opportunities and challenges for personalized and mobile learning. International Journal of Interactive Mobile Technologies (iJIM), 19(12), 19–37. https://doi.org/10.3991/ijim.v19i12.54163
Nguyen, A., Kremantzis, M., Essien, A., Petrounias, I., & Hosseini, S. (2024). Editorial: Enhancing Student Engagement Through Artificial Intelligence (AI): Understanding the basics, opportunities, and challenges. Journal of University Teaching and Learning Practice, 21(06). https://doi.org/10.53761/caraaq92
Pappagallo, S. (2024). Chatbots in Education: A dual perspective on innovation and ethics. Journal of Digital Pedagogy, 3(1), 3–10. https://doi.org/10.61071/jdp.2420
Russell, S. J., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.
Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, 101860. https://doi.org/10.1016/j.cedpsych.2020.101860
Schunk, D. H., & DiBenedetto, M. K. (2020). Motivation and social cognitive theory. Contemporary Educational Psychology, 60, 101832. https://doi.org/10.1016/j.cedpsych.2019.101832
Segovia-García, N. (2024). Optimizing Student support. A review of the use of AI chatbots in higher education. European Public & Social Innovation Review, 9, 1–20. https://doi.org/10.31637/epsir-2024-324
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