Abstracts
Résumé
Dans cet article, nous réfléchissons aux événements et expériences entourant l’utilisation de ChatGPT et d’autres outils d’intelligence artificielle générative (IAg) pour soutenir l’apprentissage étudiant. La théorie de l’autodétermination est utilisée pour structurer nos réflexions, ce qui nous permet de comprendre comment ChatGPT peut améliorer ou diminuer l’automotivation des étudiants et étudiantes, tout en soutenant leurs besoins psychologiques. En nous inspirant de nos expériences et de la littérature émergente, nous proposons des principes directeurs pour les professeurs et professeures afin de renforcer les avantages motivationnels de ChatGPT et de l’IAg, tout en minimisant leurs impacts négatifs.
Mots-clés :
- IA générative,
- ChatGPT,
- réflexions pédagogiques,
- théorie de l’autodétermination,
- soutien des besoins par le numérique
Abstract
In this paper, we reflect on classroom events and experiences surrounding the use of ChatGPT and other generative AI (GenAI) tools to support students’ learning. Self-determination theory is used as a lens to structure our reflections, allowing us to understand the ways in which ChatGPT can enhance or diminish students’ self-motivation by supporting or thwarting their basic psychological needs. Drawing on our experiences, as well as on findings from the emerging literature, we propose guiding principles for educators to enhance the motivational benefits of ChatGPT and GenIA while minimizing their negative impacts.
Keywords:
- Generative AI,
- ChatGPT,
- pedagogical reflections,
- self-determination theory,
- digital needs support
Appendices
Références
- AI for Education. (s.d.a). Guide pour les étudiants : dois-je utiliser l’IA? [version française de A guide for students: Should I use AI?]. https://aiforeducation.io/...
- AI for Education. (s.d.b). Prompt framework for students: The five “S” model. Récupéré le 16 mars 2025 de https://aiforeducation.io/...
- Anwar, I. (2023, 18 juillet). The future of innovation: AI powered design sprints [billet de blogue]. AltLabs Insights. https://altlabs.co.uk/...
- Boguslawski, S., Deer, R. et Dawson, M. G. (2025). Programming education and learner motivation in the age of generative AI: Student and educator perspectives. Information and Learning Sciences, 126(1/2), 91-109. https://doi.org/10.1108/ils-10-2023-0163
- Chiu, T. (2023). The impact of generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 32(10), 6187-6203. https://doi.org/gtdg8h
- Chiu, T. (2024). A classification tool to foster self-regulated learning with generative artifcial intelligence by applying self-determination theory: A case of ChatGPT. Educational Technology Research and Development, 72, 2401-2416. https://doi.org/gtw76w
- Chiu, T., Moorhouse, B. et Chai, C. (2023). Teacher support and student motivation to learn with artificial intelligence (AI) based chatbot. Interactive Learning Environments, 32(7), 3240-3256. https://doi.org/grv9s8
- Deci, E. L. et Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and self-determination of behavior. Psychological Inquiry, 11(4), 227-268. https://doi.org/bfn2hn
- Deci, E. L. et Ryan, R. M. (2015). Self-determination theory. Dans J. D. Wright (dir.), International encyclopedia of the social & behavioral sciences (2e éd., p. 486-491). Elsevier. https://doi.org/cq45
- Deci, E. L., Vallerand, R. J., Pelletier, L. G. et Ryan, R. M. (1991). Motivation and education: The self-determination perspective. Educational Psychologist, 26(3-4), 325-346. https://doi.org/dk7ttj
- Delaby, M., Bailleul, M. et Desombre, C. (2022). L’étayage comme réponse aux besoins des élèves d’unité d’enseignement : contrôlé ou en lâcher prise? Carrefours de l’Éducation, 54(2), 145-159. https://doi.org/10.3917/cdle.054.0145
- Dell’Acqua, F., McFowland, E., III, Mollick, E., Lifshitz-Assaf, H., Kellogg, K. C., Rajendran, S., Krayer, L, Candelon, F. et Lakhani, K. R. (2023). Navigating the jagged technological frontier: Field experimental evidence of the effects of AI on knowledge worker productivity and quality (document de travail no 24-013). Harvard Business School. https://hbs.edu/...
- Guay, F. (2022). Applying self-determination theory to education: Regulations types, psychological needs, and autonomy supporting behaviors. Canadian Journal of School Psychology, 37(1), 75-92. https://doi.org/grr27g
- Hasanein, A. et Sobaih, A. (2023). Drivers and consequences of ChatGPT use in higher education: Key stakeholder perspectives. European Journal of Investigation in Health, Psychology and Education, 13(11), 2599-2614. https://doi.org/10.3390/ejihpe13110181
- Heaven, W. D. (2023, 6 avril). ChatGPT is going to change education, not destroy it. MIT Technology Review. https://technologyreview.com/...
- Howard, J. L., Bureau, J. S., Guay, F., Chong, J. X. Y. et Ryan, R. M. (2021). Student motivation and associated outcomes: A meta-analysis from self-determination theory. Perspectives on Psychological Science, 16(6), 1300-1323. https://doi.org/gh5s57
- Hyde, B. (2024). Teacher reflection as a research method: Using phenomenology to reflect on classroom events. International Journal of Research & Method in Education. https://doi.org/n8mw
- Innovation Training. (2023). The design sprint with AI. Récupéré le 16 mars 2025 de https://innovationtraining.org/...
- Jabagi, N., Croteau, A.-M., Audebrand, L. et Marsan, J. (2019). Gig-workers’ motivation: Thinking beyond carrots and sticks. Journal of Managerial Psychology, 34(4), 192-213. https://doi.org/10.1108/JMP-06-2018-0255
- Kremer, J., Moran, A., Walker, G. et Craig, C. (2013). Self-efficacy and perceived competence in key concepts in sport psychology. Sage.
- Lee, M. K. et Baykal, S. (2017). Algorithmic mediation in group decisions: Fairness perceptions of algorithmically mediated vs. discussion-based social division. Dans S. Poltrock et C.P. Lee (prés.), CSCW ‘17: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (p. 1035–1048). ACM. https://doi.org/gfvdzr
- Leroux, J. (2014). Évaluer pour faire apprendre. Dans L. Ménard et L. St-Pierre (dir.), Se former à la pédagogie de l’enseignement supérieur (p. 333-355). Chenelière.
- Lo, C. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), article 410. https://doi.org/10.3390/educsci13040410
- Molenaar, I., de Mooij, S., Azevedo, R., Bannert, M., Järvelä, S. et Gašević, D. (2023). Measuring self-regulated learning and the role of AI: Five years of research using multimodal multichannel data. Computers in Human Behavior, 139, article 107540. https://doi.org/10.1016/j.chb.2022.107540
- Murtaza, M., Ahmed, Y., Shamsi, J., Sherwani, F. et Usman, M. (2022). AI-based personalized e-learning systems: Issues, challenges, and solutions. IEEE Access, 10, 81323-81342. https://doi.org/10.1109/ACCESS.2022.3193938
- Neumann, M., Rauschenberger, M. et Schön, E.-M. (2023). We need to talk about ChatGPT: The future of AI and higher education. Dans Proceedings of 2023 IEEE/ACM 5th International Workshop on Software Engineering Education for the Next Generation (SEENG) (p. 29-32). IEEE. https://doi.org/10.1109/SEENG59157.2023.00010
- Newman, D. T., Fast, N. J. et Harmon, D. J. (2020). When eliminating bias isn’t fair: Algorithmic reductionism and procedural justice in human resource decisions. Organizational Behavior and Human Decision Processes, 160, 149–167. https://doi.org/10.1016/j.obhdp.2020.03.008
- Nie, Y. et Lau, S. (2009). Complementary roles of care and behavioral control in classroom management: The self-determination theory perspective. Contemporary Educational Psychology, 34(3), 185-194. https://doi.org/10.1016/j.cedpsych.2009.03.001
- Niemiec, C. P. et Ryan, R. M. (2009). Autonomy, competence, and relatedness in the classroom. Theory and Research in Education, 7(2), 133-144. https://doi.org/bmwfzs
- Ryan, R. M. et Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1) 68-78. https://doi.org/c48g8h
- Ryan, R. M. et Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Press.
- Ryan, R. M. et Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, article 101860. https://doi.org/10.1016/j.cedpsych.2020.101860
- Schuetzler, R., Giboney, J., Wells, T. M., Richardson, B., Meservy, T., Sutton, C., Posey, C., Steffen, J. et Hughes, A. (2024). Student interaction with generative AI: An exploration of an emergent information-search process. Dans T. X. Bui (dir.), Proceedings of the 57th Hawaii International Conference on System Sciences (p. 7500-7509). https://aisel.aisnet.org/...
- UNESCO. (2023). ChatGPT and artificial intelligence in higher education: Quick start guide. https://unesdoc.unesco.org/...
- World Economic Forum. (2023). The Future of Jobs report 2023. https://weforum.org/...
- Wu, T.-T., Lee, H.-Y., Li, P.-H., Huang, C.-N. et Huang, Y.-N. (2023). Promoting self-regulation progress and knowledge construction in blended learning via ChatGPT-based learning aid. Journal of Educational Computing Research, 61(8), 3-31. https://doi.org/mkr3
- Xia, Q., Chiu, T., Chai, C. et Xie, K. (2023). The mediating effects of needs satisfaction on the relationships between prior knowledge and self-regulated learning through artificial intelligence chatbot. British Journal of Educational Technology, 54(4), 967-986. https://doi.org/10.1111/bjet.13305

