University Students' Interactions with ChatGPT: An Investigation in terms of CoI, Motivation, and Learning Strategies
DOI:
https://doi.org/10.46328/ijte.5419Keywords:
Chatbot, community of inquiry, motivation, students’ learning strategies.Abstract
The research aims to investigate the effects of ChatGPT in the context of the Community of Inquiry framework, Motivation, and Students’ learning strategies. In the study, there are two instructional methods. One group was included in open inquiry + lecturing, and the other was included in ChatGPT as a teaching assistant method. Both groups participated in a four-week instruction process consisting of two hours each. According to CoI index measurements, there is a significant difference in favor of males, but there is no differentiation in Motivation and Learning strategies measurements according to gender. There is a difference in favor of ChatGPT as a teaching assistant method regarding teaching presence, cognitive presence, and CoI index total score. There is a difference in favor of the ChatGPT as a teaching assistant method in terms of motivation. However, there is no differentiation in terms of learning strategies used by students.
References
Açıkgöz, K. Ü. (2006). Active learning (8th ed.). Izmir: Biliş publications.
Alshorman, S. M. (2024). The readiness to use aı in teaching science: science teachers' perspectives. Journal of Baltic Science Education, 23(3), 432-448.
Bayram, Z., Oskay, Ö. Ö., Erdem, E., Özgür, S. D., & Şen, Ş. (2013). Effect of inquiry based learning method on students' motivation. Procedia-Social and Behavioral Sciences, 106, 988-996.
Büyüköztürk, Ş., Akgün, Ö. E., Özkahveci, Ö., & Demirel, F. (2004). The validity and reliability study of the Turkish version of the Motivated Strategies for Learning Questionnaire. Educational Sciences: Theory & Practice, 4(2), 231-237.
Cabellos, B., De Aldama, C., & Pozo, J. I. (2024). University teachers' beliefs about the use of generative artificial intelligence for teaching and learning. Frontiers in Psychology, 15, 1468900. https://doi.org/10.3389/fpsyg.2024.1468900
Chaves, M. (2022). The community of inquiry instructional strategies impact on student satisfaction on remote learning. Recoletos Multidisciplinary Research Journal, 10(1), 191-204. https://doi.org/10.32871/rmrj2210.01.14
Chien-Liang, L. I. N., Tian-Yun, L. I. N., Shi-En, L. I. N., & Yu-Chen, L. I. N. (2024, November). A Study on High School Students' Continuance Intention to Use ChatGPT for Learning Assistance: An Exploration Based on Self-Determination Theory. In International Conference on Computers in Education.
Daher, W., & Hussein, A. (2024). Higher Education Students' Perceptions of GenAI Tools for Learning. Information (2078-2489), 15(7). https://doi.org/10.3390/info15070416
Duban, N. (2008). Conducting science and technology course through inquiry-based learning approach in primary education: An action research. (Unpublished doctoral dissertation). Anadolu University, Eskisehir.
Esiyok, E., Gokcearslan, S., & Kucukergin, K. G. (2024). Acceptance of Educational Use of AI Chatbots in the Context of Self-Directed Learning with Technology and ICT Self-Efficacy of Undergraduate Students. International Journal of Human-Computer Interaction, 1-10. https://doi.org/10.1080/10447318.2024.2303557
Freankel, J.R. & Wallen, N. E. (2009). How to design and evaluate research in education. (7th. ed.). New York: McGraw-Hill.
Garrison, D. R. (2007). Online Community of Inquiry Review: Social, Cognitive and Teaching Presence Issues. Journal of Asynchronous Learning Networks, 11(1), 61-72. https://doi.org/10.24059/olj.v11i1.1737
Garrison, D. R. (2007). Online community of inquiry review: Social, cognitive, and teaching presence issues. Journal of Asynchronous Learning Networks,11(1), 61-72. https://doi.org/10.24059/olj.v11i1.1737
Garrison, D. R., Anderson, T., & Archer, W. (1999). Critical inquiry in a text-based environment: Computer conferencing in higher education. The internet and higher education, 2(2-3), 87-105. https://doi.org/10.1016/S1096-7516(00)00016-6
Garrison, D. R., Anderson, T., & Archer, W. (2010). The first decade of the community of inquiry framework: A retrospective. The internet and higher education, 13(1-2), 5-9. https://doi.org/10.1016/j.iheduc.2009.10.003
Garrison, D. R., Cleveland-Innes, M., & Fung, T. S. (2010). Exploring causal relationships among teaching, cognitive and social presence: Student perceptions of the community of inquiry framework. The internet and higher education, 13(1-2), 31-36. https://doi.org/10.1016/j.iheduc.2009.10.002
Gnambs, T., & Appel, M. (2019). Are robots becoming unpopular? Changes in attitudes towards autonomous robotic systems in Europe. Computers in human behavior, 93, 53-61. https://doi.org/10.1016/j.chb.2018.11.045
Günbatar (2024). Artificial intelligence, scientific research and honesty. Artificial Intelligence Literacy Ankara: Anı publishing.
Günbatar, M. S., & Güyer, T. (2017). Effects of inquiry types on states related to community of inquiry in online learning environments: An explanatory case study. Contemporary Educational Technology, 8(2), 158-175.
Hajam, K. B., & Gahir, S. (2024). Unveiling the attitudes of university students toward artificial intelligence. Journal of Educational Technology Systems, 52(3), 335-345. https://doi.org/10.1177/00472395231225920
King, M.R. & chatGPT (2023). A Conversation on Artificial Intelligence, Chatbots, and Plagiarism in Higher Education. Cellular and Molecular Bioengineering. 16(1), 1-2. 10.1007/s12195-022-00754-8. https://doi.org/10.1007/s12195-022-00754-8
Kotsis, K. T. (2024). ChatGPT as teacher assistant for physics teaching. EIKI Journal of Effective Teaching Methods, 2(4). https://orcid.org/0000-0003-1548-0134
Kovanović, V., Joksimović, S., Poquet, O., Hennis, T., de Vries, P., Hatala, M., ... & Gašević, D. (2019). Examining communities of inquiry in Massive Open Online Courses: The role of study strategies. The Internet and Higher Education, 40, 20-43. https://doi.org/10.1016/j.iheduc.2018.09.001
Lai, C. Y., Cheung, K. Y., & Chan, C. S. (2023). Exploring the role of intrinsic motivation in ChatGPT adoption to support active Learning: An extension of the technology acceptance model. Computers and Education: Artificial Intelligence, 5, 100178. https://doi.org/10.1016/j.caeai.2023.100178
Lestari, K. (2023). Motivation of learning english: a case study of junior high school students. Education and Human Development Journal, 8(2), 41-48. https://doi.org/10.33086/ehdj.v8i2.4973
Li, P. H., Lee, H. Y., Lin, C. J., Wang, W. S., & Huang, Y. M. (2025). InquiryGPT: Augmenting ChatGPT for Enhancing Inquiry-Based Learning in STEM Education. Journal of Educational Computing Research, 62(8), 2157-2186. https://doi.org/10.1177/07356331241289824
Lim, B. R. (2001). Guidelines for designing inquiry-based learning on the Web: Online professional development of educators (Unpublished doctoral dissertation). Indiana University, Bloomington.
Liu, G. L., Zou, M. M., Soyoof, A., & Chiu, M. M. (2024). Untangling the Relationship Between AI- Mediated Informal Digital Learning of English (AI-IDLE), Foreign Language Enjoyment and the Ideal L2 Self: Evidence From Chinese University EFL Students. European Journal of Education, e12846. https://doi.org/10.1111/ejed.12846
McKeachie, W. J., Pintrich, P.R., Lin, Y.G., & Smith,D. (1986). Teaching and learning in the college classroom: A review of the research literature. Ann Arbor, MI: National Center for Research to Improve Postsecondary Teaching and Learning, The University of Michigan.
Neroni, J., Meijs, C., Gijselaers, H. J., Kirschner, P. A., & de Groot, R. H. (2019). Learning strategies and academic performance in distance education. Learning and individual differences, 73, 1-7. https://doi.org/10.1016/j.lindif.2019.04.007
Öztürk, E. (2012). Adaptation of the Research Community Scale to Turkish: Validity and Reliability Study. İlköğretim Online, 11(2), 408-422.
Shea, P. & Bidjerano, T. (2012). Learning presence as a moderator in the community of inquiry model. Computers & Education (59), 316-326. https://doi.org/10.1016/j.compedu.2012.01.011
Pintrich, P. R. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ).
Punar Özçelik, N., & Yangın Ekşi, G. (2024). Cultivating writing skills: The role of ChatGPT as a learning assistant-a case study. Smart Learning Environments, 11(1), 10. https://doi.org/10.1186/s40561-024-00296-8
Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?. Journal of Applied Learning and Teaching, 6(1), 342-363. https://doi.org/10.37074/jalt.2023.6.1.9
Saklaki, A., & Gardikiotis, A. (2024). Exploring Greek Students' Attitudes Toward Artificial Intelligence: Relationships with AI Ethics, Media, and Digital Literacy. Societies, 14(12), 248. https://doi.org/10.3390/soc14120248
Slamet, J. (2024). Potential of ChatGPT as a digital language learning assistant: EFL teachers' and students' perceptions. Discover Artificial Intelligence, 4(1), 46. https://doi.org/10.1007/s44163-024-00143-2
Spronken-Smith, R., Bullard, J., Ray, W., Roberts, C., & Keiffer, A. (2008). Where Might Sand Dunes be on Mars? Engaging Students through Inquiry-based Learning in Geography. Journal of Geography in Higher Education, 32(1), 71-86. https://doi.org/10.1080/03098260701731520
Stenbom, S. (2018). A systematic review of the Community of Inquiry survey. The Internet and Higher Education, 39, 22-32. https://doi.org/10.1016/j.iheduc.2018.06.001
Sun, L., & Zhou, L. (2024). Generative artificial intelligence attitude analysis of undergraduate students and their precise improvement strategies: A differential analysis of multifactorial influences. Education and Information Technologies, 1-36. https://doi.org/10.1007/s10639-024-13236-3
Turing, A.M. (2009). Computing Machinery and Intelligence (pp 23-66). Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer Robert Epstein, Gary Roberts & Grace Beber (editors). USA: Springer Publishing:
Wang, X., Li, L., Tan, S. C., Yang, L., & Lei, J. (2023). Preparing for AI-enhanced education: Conceptualizing and empirically examining teachers' AI readiness. Computers in Human Behavior, 146, 107798. https://doi.org/10.1016/j.chb.2023.107798
Wang, X., Liu, Q., Pang, H., Tan, S. C., Lei, J., Wallace, M. P., & Li, L. (2023). What matters in AI-supported Learning: A study of human-AI interactions in language learning using cluster analysis and epistemic network analysis. Computers & Education, 194, 104703. https://doi.org/10.1016/j.compedu.2022.104703
Yu, S. C., Huang, Y. M., & Wu, T. T. (2024). Tool, Threat, Tutor, Talk, and Trend: College Students' Attitudes toward ChatGPT. Behavioral Sciences, 14(9), 755. https://doi.org/10.3390/bs14090755
Zhai, X. (2023). Chatgpt and AI: The game changer for education. Zhai, X.(2023). ChatGPT: Reforming Education on Five Aspects. Shanghai Education, 16-17.
Zhang, W. (2023). Literature review of community of inquiry model in China and abroad., Proceedings of the 4th International Conference on Language, Art and Cultural Exchange (ICLACE 2023). 20-28. https://doi.org/10.2991/978-2-38476-094-7_4
Zydney, J. M., deNoyelles, A., & Seo, K. K.-J. (2012). Creating a community of inquiry in online environments: An exploratory study on the effect of a protocol on interactions within asynchronous discussions. Computers & Education(58), 77-87. https://doi.org/10.1016/j.compedu.2011.07.009
Downloads
Published
Issue
Section
License
Copyright (c) 2026 International Journal of Technology in Education
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Articles may be used for research, teaching, and private study purposes. Authors alone are responsible for the contents of their articles. The journal owns the copyright of the articles. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of the research material.
The author(s) of a manuscript agree that if the manuscript is accepted for publication in the International Journal of Technology in Education (IJTE), the published article will be copyrighted using a Creative Commons “Attribution 4.0 International” license. This license allows others to freely copy, distribute, and display the copyrighted work, and derivative works based upon it, under certain specified conditions.
Authors are responsible for obtaining written permission to include any images or artwork for which they do not hold copyright in their articles, or to adapt any such images or artwork for inclusion in their articles. The copyright holder must be made explicitly aware that the image(s) or artwork will be made freely available online as part of the article under a Creative Commons “Attribution 4.0 International” license.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
