A Pragmatic Approach to using LLMs
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Abstract
The advent of ChatGPT, and the plethora of similar large language models (LLMs) that followed it, has brought to the forefront aspects of artificial intelligence that have been discussed over the past seventy-five years or so. This paper posits that practitioners in the field of open and distance learning (ODL) provision should probably adopt a pragmatic approach to the utilisation of these new tools, similar to the ways in which ODL practitioners have embraced previous technologies. Reflecting on personal experience as well as current work in progress with the Commonwealth of Learning (COL), the paper argues that a cautious and critical engagement, based on gradual improvement is probably going to be more beneficial than non-engagement or any attempt at delayed perfection.
References
Adamopolou, E. and Moussiades, L. (2020) Chatbots: History, technology, and applications. Machine Learning with Applications, 2, 100006. https://doi.org/10.1016/j.mlwa.2020.100006. DOI: https://doi.org/10.1016/j.mlwa.2020.100006
Anderson, T. and Dron, J. (2011) Three Generations of Distance Education, IRRODL, 12(3), 80-97. https://doi.org/10.19173/irrodl.v12i3.890 DOI: https://doi.org/10.19173/irrodl.v12i3.890
Baidoo-Anu, D., and Owusu Ansah, L. (2023) Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning (January 25, 2023). Available at SSRN: https://ssrn.com/abstract=4337484 or http://dx.doi.org/10.2139/ssrn.4337484 DOI: https://doi.org/10.2139/ssrn.4337484
Bates. A. W. (u.d.) Teaching in a Digital Age – Second Edition. 11.4 Open pedagogy – Teaching in a Digital Age – Second Edition
Bates. A. W. (2022) Teaching in a Digital Age – Third Edition. https://pressbooks.bccampus.ca/teachinginadigitalagev3m/
Bates, A. W. (2024, April 26) What should universities do about AI for teaching and learning? https://www.tonybates.ca/2024/04/26/what-should-universities-do-about-ai-for-teaching-and-learning/
Beaven, T. (2018). ‘Dark reuse’: an empirical study of teachers’ OER engagement. Open Praxis, 10(4), 377-391. https://openpraxis.org/articles/10.5944/openpraxis.10.4.889 DOI: https://doi.org/10.5944/openpraxis.10.4.889
Bozkurt, A. and Keefer, J. (2017) Participatory learning culture and community formation in connectivist MOOCs. Interactive Learning Environments, 26(6), 776-788. https://doi.org/10.1080/10494820.2017.1412988 DOI: https://doi.org/10.1080/10494820.2017.1412988
Bozkurt, A. and Sharma, R. C. (2023) Generative AI and Prompt Engineering: The Art of Whispering to Let the Genie Out of the Algorithmic World. Asian Journal of Distance Education, 18(2). https://www.researchgate.net/profile/Aras-Bozkurt/publication/372650445_Generative_AI_and_Prompt_Engineering_The_Art_of_Whispering_to_Let_the_Genie_Out_of_the_Algorithmic_World/links/64c1af66c41fb852dd9d8ace/Generative-AI-and-Prompt-Engineering-The-Art-of-Whispering-to-Let-the-Genie-Out-of-the-Algorithmic-World.pdf
COL. (2023) Samoa pioneers AI-powered learner support. https://www.col.org/news/samoa-pioneers-ai-powered-learner-support/
COL. (2024). USP enhanced its Semester Zero programme with GPT-powered AI support. https://www.col.org/news/usp-enhanced-its-semester-zero-programme-with-gpt-powered-ai-support/
COL. (2025). From innovation to impact: AI-powered OER training equips Ghanaian educators. https://www.col.org/news/from-innovation-to-impact-ai-powered-oer-training-equips-ghanaian-educators/
Cooper, G. (2023) Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Generative Intelligence. J Sci Educ Technol 32, 444–452 (2023). https://doi.org/10.1007/s10956-023-10039-y DOI: https://doi.org/10.1007/s10956-023-10039-y
Du, H., Sun, Y., Jiang, H., Atiquil Islam, A. Y. M., and Gu, X. (2024) Exploring the effects of AI literacy in teacher learning: an empirical study. Humanities and Social Sciences Communications, 11, Article 559. https://doi.org/10.1057/s41599-024-03101-6 DOI: https://doi.org/10.1057/s41599-024-03101-6
Eke, D. O. (2023) ChatGPT and the rise of generative AI: Threat to academic integrity? Journal of Responsible Technology, 13. https://doi.org/10.1016/j.jrt.2023.100060 DOI: https://doi.org/10.1016/j.jrt.2023.100060
Farquhar, S., Kossen, J., Kuhn, L., and Gal, Y. (2024) Detecting hallucinations in large language models using semantic entropy. Nature, 630, 625-630. https://doi.org/10.1038/s41586-024-07421-0 DOI: https://doi.org/10.1038/s41586-024-07421-0
Garcia, M. B., Rosak-Szyrocka, J., Yilmaz, R., Metwally, A. H. S., Acut, D. P., Ofuso-Ampong, K., Erdogdu, F., Fung, C. Y., and Bozkurt, A. (2025) Rethinking Educational Assessment in the Age of Generative AI: Actionable Strategies to Mitigate Academic Dishonesty. https://www.researchgate.net/profile/Manuel-Garcia-33/publication/391606948_Rethinking_Educational_Assessment_in_the_Age_of_Generative_AI_Actionable_Strategies_to_Mitigate_Academic_Dishonesty/links/681f6a3fbfbe974b23c7d5c0/Rethinking-Educational-Assessment-in-the-Age-of-Generative-AI-Actionable-Strategies-to-Mitigate-Academic-Dishonesty.pdf DOI: https://doi.org/10.2139/ssrn.5250120
Grace, K., Stewart, H., Sandkühler, J. F., Thomas, S., Wenstein,-Raun, B., and Braunder, J. (2024) THOUSANDS OF AI AUTHORS ON THE FUTURE OF AI. arXiv. https://i-love-ai.com/wp-content/uploads/2024/12/2401.02843v2.pdf
Håkansson, A., and Phillips-Wren, G. (2024) Generative AI and Large Language Models - Benefits, Drawbacks, Future and Recommendations. Procedia Computer Science, 246, 5458-5468. https://doi.org/10.1016/j.procs.2024.09.689. DOI: https://doi.org/10.1016/j.procs.2024.09.689
Hegarty, B. (2015) Attributes of open pedagogy: a model for using open educational resources Educational Technology, July-August 2025, 3-13.
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S. Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., Weller, J., Kuhn, J., and Kasneci, G. (2023) ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 2023, 102274. https://doi.org/10.1016/j.lindif.2023.102274. DOI: https://doi.org/10.1016/j.lindif.2023.102274
Kaul, V., Enslin, S., and Gross, S. A. (2020) History of artificial intelligence in medicine. Gastrointestinal Endoscopy, 92 (4), pp. 807-812. https://doi.org/10.1016/j.gie.2020.06.040 DOI: https://doi.org/10.1016/j.gie.2020.06.040
Kesim, M., and ltinpulluk, H. (2015) A Theoretical Analysis of Moocs Types from a Perspective of Learning Theories. Procedia – Social and Behavioral Sciences, 186, 13 May 2025, 15-19. https://doi.org/10.1016/j.sbspro.2015.04.056 DOI: https://doi.org/10.1016/j.sbspro.2015.04.056
Kizilcec, R. (2024) To Advance AI Use in Education, Focus on Understanding Educators. Int J Artif Intell Educ 34, 12–19 (2024). https://doi.org/10.1007/s40593-023-00351-4 DOI: https://doi.org/10.1007/s40593-023-00351-4
Jebbari, M., Cherradi, B., Hamida, S., and Raihani, A. (2024). Identifying learning styles in MOOCs environment through machine learning predictive modeling. Educ Inf Technol 29, 20977–21014 (2024). https://doi.org/10.1007/s10639-024-12637-8 DOI: https://doi.org/10.1007/s10639-024-12637-8
Law, L. (2024) Application of generative artificial intelligence (GenAI) in language teaching and learning: A scoping literature review. Computers and Education Open, Volume 6, June 2024. https://doi.org/10.1016/j.caeo.2024.100174 DOI: https://doi.org/10.1016/j.caeo.2024.100174
Legg, C. and Hookway, C. (2014). "Pragmatism", The Stanford Encyclopedia of Philosophy (Winter 2024 Edition), Edward N. Zalta & Uri Nodelman (eds.), URL = <https://plato.stanford.edu/archives/win2024/entries/pragmatism/>.
Li, Y., Wu, Y,, and Chiu, T. K. F. (2025) How teacher presence affects student engagement with a generative artificial intelligence chatbot in learning designed with first principles of instruction. Journal of research on Technology in Education. https://doi.org/10.1080/15391523.2025.2493942 DOI: https://doi.org/10.1080/15391523.2025.2493942
Liu, H., Xue, W., Chen, Y., Chen, D., Zhao, X., Wang, K., Hou, L., Li, R., and Peng, W. (2024) A Survey on Hallucination in Large Vision-Language Models. https://arxiv.org/abs/2402.00253v2, https://doi.org/10.48550/arXiv.2402.00253
Linderoth, C., Hultén, M., and Stenliden, L. (2024) Competing visions of artificial intelligence in education—A heuristic analysis on sociotechnical imaginaries and problematizations in policy guidelines. Policy Futures in Education, 0(0). https://doi.org/10.1177/14782103241228900 DOI: https://doi.org/10.1177/14782103241228900
Madhan, M. and Mays, T. (2022). Structured Access to Curated Open Educational Resources Aligned to National School Curricula: An Experiment in the Commonwealth Member States in the Pacific Region. COL, PCF10.
Maholwald, K., Ivaniva, A. A,, Blank, I. A.; Kanwisher, N., Tenenbaum, J. B., and Fedorenko, E. (2024) Dissociating language and thought in large language models. Trends in Cognitive Sciences, 28(6), pp517-540. https://doi.org/10.1016/j.tics.2024.01.011 DOI: https://doi.org/10.1016/j.tics.2024.01.011
McGeary, B. (2025) Evaluating a Statewide OER Repository on the Hyku Platform: Value, Usability, Cost, and Administration. Journal of New Librarianship, 10(1), 1-21. https://doi.org/10.33011/newlibs/18/1 DOI: https://doi.org/10.33011/newlibs/18/1
Mohamed, A. and Misgra, S. (2024). Developing Policy Guidelines for Artificial Intelligence in Post-secondary Institutions. COL. http://hdl.handle.net/11599/5615
Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., and Grundy, S. (2023) ChatGPT versus engineering education assessment: a multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity. European Journal of Engineering Education, 48 (4), 559-614. https://doi.org/10.1080/03043797.2023.2213169 DOI: https://doi.org/10.1080/03043797.2023.2213169
Novikau, A. (2024) Online vs. Offline LLM Inference: Unlocking the Best of Both Worlds in Mobile Applications. International Journal of Science and Engineering Applications, 13(12), 5-8. https://ijsea.com/archive/volume13/volume13issue12.pdf#page=8
OER Africa. (2023, July 28) Three Ways Artificial Intelligence could change how we use Open Educational Resources (Blog). https://www.oerafrica.org/content/three-ways-artificial-intelligence-could-change-how-we-use-open-educational-resources
Paskevicius, M. (2024). Policy and Practice of Artificial Intelligence in Teaching and Learning at Post-secondary Educational Institutions in the Commonwealth. COL. http://hdl.handle.net/11599/5605
Perrault, R., and Clark, J. (2024) Artificial Intelligence Index Report 2024, Human-Centered Artificial Intelligence. United States of America. Retrieved from https://policycommons.net/artifacts/12089781/hai_ai-index-report-2024/12983534/ on 30 Apr 2024. CID: 20.500.12592/h70s46h.
Ratten, V., and Jones, P. (2023) Generative artificial intelligence (ChatGPT): Implications for management educators. The International Journal of Management Education, 21 (3). https://doi.org/10.1016/j.ijme.2023.100857 DOI: https://doi.org/10.1016/j.ijme.2023.100857
Smolansky, A., Cram, A., Raduescu, C., Zeivots, S., Huber, E., and Kizilcec, R. F. (2023) Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education. L@S '23: Proceedings of the Tenth ACM Conference on Learning @ ScaleJuly 2023Pages 378–382, https://doi.org/10.1145/3573051.3596191 DOI: https://doi.org/10.1145/3573051.3596191
Sevnarayan, K., and Potter, M-A., (2024) Generative Artificial Intelligence in distance education: Transformations, challenges, and impact on academic integrity and student voice. Journal of Applied Learning & Teaching, 7. https://doi.org/10.37074/jalt.2024.7.1.41 DOI: https://doi.org/10.37074/jalt.2024.7.1.41
Taylor, J. C. (2001) Fifth generation distance education. Instructional Design and Technology, 4(1), pp1-14. https://research.usq.edu.au/item/9x75x/fifth-generation-distance-education
Teachers.Institute. (2023, December 27) The Five generations of Distance Education: Evolution Through Technology. Blog. https://teachers.institute/open-and-distance-education/five-generations-distance-education-evolution-technology/
Tian, X.., Zhao, S., Wang, H., Chen, S., Peng, Y., Ji, Y., Zhao, H. and Li, X. (2025). Exploring the Potential of Offline RL for Reasoning in LLMs: A Preliminary Study. arXiv. https://arxiv.org/abs/2505.02142
UNESCO. (2023) Global Education Monitoring Report 2023. Technology in education: A TOOL on WHOSE TERMS? UNESCO. https://www.unesco.org/gem-report/en/technology
UNESCO. (2024a, 3 September) What you need to know about UNESCO's new AI competency frameworks for students and teachers. UNESCO News. What you need to know about UNESCO's new AI competency frameworks for students and teachers | UNESCO
UNESCO. (2024b) Global Education Monitoring Report 2024. Pacific: Technology in education: A TOOL ON WHOSE TERMS? UNESCO. https://www.unesco.org/gem-report/en/2024pacific
Yadav, A. B. (2023) Gen Ai-Driven Electronics: Innovations, Challenges and Future Prospects. 2023: International Congress on Models and Methods in Modern investigations (Poland). https://www.researchgate.net/profile/Archana-Yadav-28/publication/378825788_GEN_AI-DRIVEN_ELECTRONICS_INNOVATIONS_CHALLENGES_AND_FUTURE_PROSPECTS/links/65eb9aa6aaf8d548dcb441b1/GEN-AI-DRIVEN-ELECTRONICS-INNOVATIONS-CHALLENGES-AND-FUTURE-PROSPECTS.pdf
Yao, Y., Duan, J., Xu, K., Cai, Y. Sun, Z., & Zhang, Y. (2024). A survey on large language model (LLM) security and privacy: The Good, The Bad, and The Ugly. High-Confidence Computing, 4(2), 100211. https://www.sciencedirect.com/science/article/pii/S266729522400014X DOI: https://doi.org/10.1016/j.hcc.2024.100211
u, J. H. (2024) Integrating actionable analytics into learning design for MOOCs: a design-based research. Journal of Computing in Higher Education (2024). https://doi.org/10.1007/s12528-024-09413-5 DOI: https://doi.org/10.1007/s12528-024-09413-5
Walter, Y. (2024) Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational technology in Higher Education, 21, article 15. https://link.springer.com/article/10.1186/s41239-024-00448-3 DOI: https://doi.org/10.1186/s41239-024-00448-3
Williamson, B. (2024) The Social life of AI in Education. Int J Artif Intell Educ 34, 97–104. https://doi.org/10.1007/s40593-023-00342-5 DOI: https://doi.org/10.1007/s40593-023-00342-5
Zhang, Z., Aubrey, S., Huang, X.,, and Chiu, T. F. K. (2025). The role of generative AI and hybrid feedback in improving L2 writing skills: a comparative study. Innovation In Language Learning and Teaching, https://doi.org/10.1080/17501229.2025.2503890 DOI: https://doi.org/10.1080/17501229.2025.2503890
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