A Cybernetic Perspective on Generative AI in Education: From Transmission to Coordination.
DOI:
https://doi.org/10.9781/ijimai.2024.02.008Keywords:
Education, Cybernetics, Generative AI, Human-Machine Communication, Large Language Models, Machine LearningAbstract
The recent sudden increase in the capabilities of Large Language Models (LLMs), and generative AI in general, has astonished education professionals and learners. In formulating a response to these developments, educational institutions are constrained by a lack of clarity concerning human-machine communication and its relationship to models of education. Ideas and models from the cybernetic tradition can help to fill this gap. Two paradigms are distinguished: (1) the transmission paradigm (combining the model of learning implied by the instruments and processes of formal education and the conduit model of communication), and (2) the coordination paradigm (combining the constructivist model of learning and the coordination model of communication). It is proposed that these paradigms have long coexisted in educational practice in a modus vivendi, which is disrupted by LLMs. If an LLM can pass an examination, then from within the transmission paradigm this can only understood as demonstrating that the LLM has indeed learned and understood the material being assessed. At the same time, we know that LLMs do not in fact have the capacity to learn and understand, but rather generate a simulacrum of intelligence. It is argued that this paradox prevents educational institutions from formulating a coherent response to generative AI systems. However, within the coordination paradigm the interactions of LLMs and education institutions can be more easily understood and can be situated in a conversational model of learning. These distinctions can help institutions, educational leaders, and teachers, to frame the complex and nuanced questions raised by GenAI, and to chart a course towards its effective use in education. More specifically, they indicate that to benefit fully from the capabilities of generative AI education institutions need to recognize the validity of the coordination paradigm and adapt their processes and instruments accordingly.
Downloads
References
F. García-Peñalvo and A. Vázquez-Ingelmo, “What Do We Mean by GenAI? A Systematic Mapping of The Evolution, Trends, and Techniques Involved in Generative AI”, International Journal of Interactive Multimedia and Artificial Intelligence, vol. 8, no. 4, p. 7, 2023, doi: 10.9781/ijimai.2023.07.006.
W. X. Zhao et al., “A Survey of Large Language Models”. arXiv, Sep. 11, 2023. Accessed: Sep. 28, 2023. [Online]. Available: http://arxiv.org/abs/2303.18223
E. Kasneci et al., “ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education”, Learning and individual differences, vol. 103, no. 102274, 2023.
S. Grassini, “Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings”, Education Sciences, vol. 13, no. 7, p. 692, Jul. 2023, doi: 10.3390/educsci13070692.
L. Yan et al., “Practical and Ethical Challenges of Large Language Models in Education: A Systematic Scoping Review”, British Journal of Educational Technology, vol. 55, no. 1, pp. 90–112, 2024, doi: 10.1111/ bjet.13370.
A. Caines et al., “On the application of Large Language Models for language teaching and assessment technology”. arXiv, Jul. 17, 2023. Accessed: Oct. 23, 2023. [Online]. Available: http://arxiv.org/abs/2307.08393
I. Drori et al., “From Human Days to Machine Seconds: Automatically Answering and Generating Machine Learning Final Exams”, in Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach CA USA: ACM, Aug. 2023, pp. 3947–3955. doi: 10.1145/3580305.3599827.
S. Moore, H. A. Nguyen, T. Chen, and J. Stamper, “Assessing the Quality of Multiple-Choice Questions Using GPT-4 and Rule-Based Methods”, presented at the European Conference on Technology Enhanced Learning, O. Viberg, I. Jivet, P. J. Muñoz-Merino, M. Perifanou, and T. Papathoma, Eds., in Lecture Notes in Computer Science, vol. 14200. Cham: Springer Nature Switzerland, 2023, pp. 229–245. doi: 10.1007/978-3-031-42682-7_16.
J. H. Choi, K. E. Hickman, A. Monahan, and D. B. Schwarcz, “ChatGPT Goes to Law School”, SSRN Journal, 2023, doi: 10.2139/ssrn.4335905.
D. Yan, M. Fauss, J. Hao, and W. Cui, “Detection of AI-generated Essays in Writing Assessments”, Psychological Test and Assessment Modeling, vol. 65, pp. 125-144, 2023.
Z. Liang, W. Yu, T. Rajpurohit, P. Clark, X. Zhang, and A. Kaylan, “Let GPT be a Math Tutor: Teaching Math Word Problem Solvers with Customized Exercise Generation”. arXiv, May 22, 2023. Accessed: Oct. 23, 2023. [Online]. Available: http://arxiv.org/abs/2305.14386
G. Zografos and L. Moussiades, “A GPT-Based Vocabulary Tutor.”, Springer Nature, 2023, pp. 270–280.
J. M. Markel, S. G. Opferman, J. A. Landay, and C. Piech, “GPTeach: Interactive TA Training with GPT-based Students”, in Proceedings of the Tenth ACM Conference on Learning @ Scale, Copenhagen Denmark: ACM, Jul. 2023, pp. 226–236. doi: 10.1145/3573051.3593393.
S. L. Fleming et al., “Assessing the Potential of USMLE-Like Exam Questions Generated by GPT-4”, Medical Education, preprint, Apr. 2023. doi: 10.1101/2023.04.25.23288588.
J. C. F. De Winter, “Can ChatGPT Pass High School Exams on English Language Comprehension?”, International Journal of Artificial Intelligence in Education, Sep. 2023, doi: 10.1007/s40593-023-00372-z.
M. S. Orenstrakh, O. Karnalim, C. A. Suárez, and M. Liut, “Detecting LLM-Generated Text in Computing Education: A Comparative Study for ChatGPT Cases”, arXiv preprint arXiv:2307.07411, 2023.
P. Denny, H. Khosravi, A. Hellas, J. Leinonen, and S. Sarsa, “Can We Trust AI-Generated Educational Content? Comparative Analysis of Human and AI-Generated Learning Resources”. arXiv, Jul. 03, 2023. Accessed: Oct. 23, 2023. [Online]. Available: http://arxiv.org/abs/2306.10509
S. Sarsa, P. Denny, A. Hellas, and J. Leinonen, “Automatic Generation of Programming Exercises and Code Explanations Using Large Language Models”, in Proceedings of the 2022 ACM Conference on International Computing Education Research - Volume 1, Lugano and Virtual Event Switzerland: ACM, Aug. 2022, pp. 27–43. doi: 10.1145/3501385.3543957.
A. Gilson et al., “How Does ChatGPT Perform on the United States Medical Licensing Examination? The Implications of Large Language Models for Medical Education and Knowledge Assessment”, JMIR Medical Education, vol. 9, no. 1, p. e45312, Feb. 2023, doi: 10.2196/45312.
W. Yeadon and D. P. Halliday, “Exploring Durham University Physics exams with Large Language Models”. arXiv, Jun. 27, 2023. Accessed: Oct. 23, 2023. [Online]. Available: http://arxiv.org/abs/2306.15609
Y. Kaneda et al., “Assessing the Performance of GPT-3.5 and GPT-4 on the 2023 Japanese Nursing Examination”, Cureus, Aug. 2023, doi: 10.7759/cureus.42924.
J. M. Markel, S. G. Opferman, J. A. Landay, and C. Piech, “GPTeach: Interactive TA Training with GPT-based Students”, in Proceedings of the Tenth ACM Conference on Learning @ Scale, Copenhagen Denmark: ACM, Jul. 2023, pp. 226–236. doi: 10.1145/3573051.3593393.
Duolingo team, “Introducing Duolingo Max, a learning experience powered by GPT-4”, Duolingo Blog. Accessed: Oct. 23, 2023. [Online]. Available: https://blog.duolingo.com/duolingo-max/
S. Kahn, “Harnessing GPT-4 so that all students benefit. A nonprofit approach for equal access”, Kahn Academy. [Online]. Available: https://blog.khanacademy.org/harnessing-ai-so-that-all-students-benefit-anonprofit-approach-for-equal-access/
A. Varma, C. Dawkins, and K. Chaudhuri, “Artificial intelligence and people management: A critical assessment through the ethical lens”, Human Resource Management Review, vol. 33, no. 1, p. 100923, Mar. 2023, doi: 10.1016/j.hrmr.2022.100923.
R. González-Sendino, E. Serrano, J. Bajo, and P. Novais, “A Review of Bias and Fairness in Artificial Intelligence”, International Journal of Interactive Multimedia and Artificial Intelligence, vol. In press, no. In press, p. 1, 2023, doi: 10.9781/ijimai.2023.11.001.
A. J. López Rivero, M. E. Beato, C. Muñoz Martínez, and P. G. Cortiñas Vázquez, “Empirical Analysis of Ethical Principles Applied to Different AI Uses Cases”, International Journal of Interactive Multimedia and Artificial Intelligence, vol. 7, no. 7, p. 105, 2022, doi: 10.9781/ijimai.2022.11.006.
E. R. Kahu, “Framing student engagement in higher education”, Studies in Higher Education, vol. 38, no. 5, pp. 758–773, Jun. 2013, doi: 10.1080/03075079.2011.598505.
J. Girard and J. Girard, “Defining knowledge management: Toward an applied compendium”, vol. 3, no. 1, 2015.
E. V. Glasersfeld, Radical Constructivism: A Way of Knowing and Learning. Falmer Press, 1996.
G. Biesta, “Freeing teaching from learning: Opening up existential possibilities in educational relationships”, Studies in Philosophy and Education, vol. 34, no. 3, pp. 229–243, 2015.
N. Bremner, N. Sakata, and L. Cameron, “The outcomes of learnercentred pedagogy: A systematic review”, International Journal of Educational Development, vol. 94, no. article 102649, Oct. 2022, doi: 10.1016/j.ijedudev.2022.102649.
M. J. Reddy, “The Conduit Metaphor: A Case of Frame Conflict in Our Language about Language”, Metaphor and thought, vol. 2, pp. 285–324, 1979.
C. E. Shannon, “A mathematical theory of communication”, The Bell system technical journal, vol. 27, no. 3, pp. 379–423, 1948.
K. Krippendorff, On Communication. New York: Routedge, 2009.
G. J. Booth et al., “Competency-Based Assessments: Leveraging Artificial Intelligence to Predict Subcompetency Content”, Academic Medicine, vol. 98, no. 4, pp. 497–504, Apr. 2023, doi: 10.1097/ACM.0000000000005115.
W. Wang, X. Lin, F. Feng, X. He, and T.-S. Chua, “Generative Recommendation: Towards Next-generation Recommender Paradigm”. arXiv, Apr. 07, 2023. Accessed: Feb. 01, 2024. [Online]. Available: http://arxiv.org/abs/2304.03516
M. H. Jarrahi, D. Askay, A. Eshraghi, and P. Smith, “Artificial intelligence and knowledge management: A partnership between human and AI”, Business Horizons, vol. 66, no. 1, pp. 87–99, Jan. 2023, doi: 10.1016/j.bushor.2022.03.002.
U. Maturana and F. Varela, The Tree of Knowledge. Boston MA: Shambala, 1987.
U. Cress and J. Kimmerle, “Co-constructing knowledge with generative AI tools: Reflections from a CSCL perspective”, International Journal of Computer-Supported Collaborative Learning, vol. 18, no. 4, pp. 607–614, Dec. 2023, doi: 10.1007/s11412-023-09409-w.
I. Molenaar, “The concept of hybrid human-AI regulation: Exemplifying how to support young learners” self-regulated learning”, Computers and Education: Artificial Intelligence, vol. 3, p. 100070, Jan. 2022, doi: 10.1016/j.caeai.2022.100070.
D. E. Salinas-Navarro, E. Vilalta-Perdomo, R. Michel-Villarreal, and L. Montesinos, “Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment”, Education Sciences, vol. 14, no. 1, p. 83, Jan. 2024, doi: 10.3390/educsci14010083.
W. Yeadon, O.-O. Inyang, A. Mizouri, A. Peach, and C. P. Testrow, “The death of the short-form physics essay in the coming AI revolution”, Physics Education, vol. 58, no. 3, p. 035027, May 2023, doi: 10.1088/1361-6552/acc5cf.
S. C. Shelmerdine, H. Martin, K. Shirodkar, S. Shamshuddin, and J. R. Weir-McCall, “Can artificial intelligence pass the Fellowship of the Royal College of Radiologists examination? Multi-reader diagnostic accuracy study”, BMJ, p. e072826, Dec. 2022, doi: 10.1136/bmj-2022-072826.
M. Kelloniemi and V. Koljonen, “AI did not pass Finnish plastic surgery written board examination”, Journal of Plastic, Reconstructive & Aesthetic Surgery, p. S1748681523005983, Oct. 2023, doi: 10.1016/j.bjps.2023.10.059.
M. R. Das, “Not smarter than a 6th grader: ChatGPT fails Singapore’s 6th-grade maths and science exams”, Firstpost. Accessed: Oct. 30, 2023. [Online]. Available: https://www.firstpost.com/world/chatgpt-failssingapore-6th-grade-maths-and-science-exams-12189482.html
M. Eulerich, A. Sanatizadeh, H. Vakilzadeh, and D. A. Wood, “Can Artificial Intelligence Pass Accounting Certification Exams? ChatGPT: CPA, CMA, CIA, and EA?”, SSRN Journal, 2023, doi: 10.2139/ssrn.4452175.
M. Sharples, “Automated Essay Writing: An AIED Opinion”, International Journal of Artificial Intelligence in Education, vol. 32, no. 4, pp. 1119–1126, Dec. 2022, doi: 10.1007/s40593-022-00300-7.
N. Tiku, “The Google engineer who thinks the company’s AI has come to life,” Washington Post. Accessed: Feb. 16, 2024. [Online]. Available: https://www.washingtonpost.com/technology/2022/06/11/google-ailamda-blake-lemoine/
D. Griffiths, “Artificial Intelligence Seen Through the Lens of Bateson’s Ecology of Mind”, International Journal of Interactive Multimedia and Artificial Intelligence, vol. 7, no. 1, pp. 62–70, 2021, doi: 10.9781/ ijimai.2021.08.004.
G. Bateson, Steps to an Ecology of Mind (first published 1972). Chicago and London: The University Of Chicago Press, 1987.
G. Bateson and M. C. Bateson, Angels fear: Towards an epistemology of the sacred (first published 1987), no. 1. Hampton Press, 2005. doi: 10.1016/0732-118x(90)90037-3.
F. J. Varela, E. Thompson, and E. Rosch, The Embodied Mind. Cambridge, MA: MIT Press, 1993.
B. Cantwell-Smith, The promise of artificial intelligence: Reckoning and judgment. MIT Press, 2019.
F. H. Bradley, Appearance and Reality, A Metaphysical Essay. Allen and Unwin, 1893.
J. Baudrillard, Simulacra and Simulation translated by Sheila Faria Glaser. Ann Arbor: University of Michigan Press, 1994.
L. Zapponi, R. Nieri, V. Zaffaroni-Caorsi, N. M. Pugno, and V. Mazzoni, “Vibrational calling signals improve the efficacy of pheromone traps to capture the brown marmorated stink bug”, Journal of Pest Science, vol. 96, no. 2, pp. 587–597, Mar. 2023, doi: 10.1007/s10340-022-01533-0.
Χ. Λ. (Christina Linardaki), “Artificial Intelligence vs. Human Intelligence: The case of poetry”, Academia Letters, Jan. 2021, Accessed: Sep. 08, 2023. [Online]. Available: https://www.academia.edu/49359147/Artificial_Intelligence_vs_Human_Intelligence_The_case_of_poetry
W. S. McCulloch, Embodiments of Mind. Cambridge, MA: MIT Press, 1988.
“War of the chatbots: Bard, Bing Chat, ChatGPT, Ernie and beyond. The new AI gold rush and its impact on higher education”, Journal of Applied Learning and Teaching, vol. 6, no. 1, Apr. 2023, doi: 10.37074/jalt.2023.6.1.23.
TutorAI, “Learn anything”. Accessed: Oct. 31, 2023. [Online]. Available: https://www.tutorai.me/
Formative, “Formative AI”. Accessed: Oct. 31, 2023. [Online]. Available: https://en-gb.formative.com/ai-powered
jenni, “Supercharge Your Next Research Paper”. Accessed: Oct. 31, 2023. [Online]. Available: https://jenni.ai/
CourseAI, “Our AI Course Creator tool streamlines the process of creating online courses and empowers financial independence using AI technology.”, CourseAI. Accessed: Oct. 31, 2023. [Online]. Available: https://courseai.com/
Taskade, “AI Educational Game Generator”. Accessed: Oct. 31, 2023. [Online]. Available: https://www.taskade.com/generate/education/educational-game
J. de Souza Zanirato Maia, A. P. A. Bueno, and J. R. Sato, “Applications of Artificial Intelligence Models in Educational Analytics and Decision Making: A Systematic Review”, World, vol. 4, no. 2, Art. no. 2, Jun. 2023, doi: 10.3390/world4020019.
Tribal, “How AI is assisting students teachers and administrators today”. Accessed: Oct. 31, 2023. [Online]. Available: https://www.tribalgroup.com/blog/how-ai-is-assisting-students-teachers-and-administratorstoday
G. Pask, “Conversational techniques in the study and practice of education”, British Journal of Educational Technology, no. 46, pp. 12–25, 1976.
G. Pask, B. C. E. Scott, and D. Kallikourdis, “A theory of conversations and individuals (Exemplified by the Learning Process on CASTE)”, International Journal of Man-Machine Studies, vol. 5, no. 4, pp. 443–566, Oct. 1973, doi: 10.1016/S0020-7373(73)80002-1.
D. Laurillard, Rethinking University Teaching: a framework for the effective use of educational technology. London: Routledge, 1993.
D. C. Dennett, “The Problem With Counterfeit People”, The Atlantic. Accessed: Oct. 24, 2023. [Online]. Available: https://www.theatlantic.com/technology/archive/2023/05/problem-counterfeit-people/674075/
European Writers Council, “Analysis: The success of Generative AI in the book sector is based on theft”. Accessed: Oct. 30, 2023. [Online]. Available: https://europeanwriterscouncil.eu/gai-is-based-on-theft/
L. Lucy and D. Bamman, “Gender and Representation Bias in GPT-3 Generated Stories”, in Proceedings of the Third Workshop on Narrative Understanding, Virtual: Association for Computational Linguistics, Jun. 2021, pp. 48–55. doi: 10.18653/v1/2021.nuse-1.5.
V. Turk, “How AI reduces the world to stereotypes”, Rest of World. Accessed: Oct. 24, 2023. [Online]. Available: https://restofworld.org/2023/ai-image-stereotypes/
P. Guleria and M. Sood, “Explainable AI and machine learning: performance evaluation and explainability of classifiers on educational data mining inspired career counseling”, Education and Information Technology, vol. 28, no. 1, pp. 1081–1116, Jan. 2023, doi: 10.1007/s10639- 022-11221-2.
Downloads
Published
-
Abstract234
-
PDF593
Submit Article
Information
