Anàlisi dels arguments dels candidats a docents sobre la integració de la IA a l'educació mitjançant diferents chatbots

Autors/ores

DOI:

https://doi.org/10.1344/der.2024.45.68-83

Paraules clau:

IA en educació, Anàlisi de l’argumentació, chatbot, impacte de la IA, mètode de Toulmin, exploració espacial negativa

Resum

El paper creixent de la Intel·ligència Artificial (IA) en l'educació planteja discussions crucials sobre les seves implicacions per a l'ensenyament i l'aprenentatge. Aquest estudi qualitatiu examina les perspectives argumentatives de 118 candidats a docents de la Universitat d'Iğdır respecte a la integració de la IA en les pràctiques educatives. Utilitzant el model de Toulmin (1958), analitzem els seus arguments, que abasten afirmacions, evidències, garanties, suports, refutacions i conclusions, per determinar la seva postura sobre la integració pedagògica de la IA. Emprant quatre xatbots de IA diferents —GPT-4, Gemini-AI, Claude 3 Haiku i Mistral AI—, la recerca desxifra les corrents temàtiques dins d'aquestes dimensions. A més, es realitza una nova contribució metodològica a través de l'"exploració de l'espai negatiu", centrant-se en els temes no esmentats per identificar biaixos i suposicions latents en l'argumentació. El doble enfocament analític de l'estudi, que combina la identificació de temes impulsada per la IA i l'exploració de l'espai negatiu, ha resultat en una comprensió enriquida del contingut. Els resultats claus suggereixen una percepció matissada entre els participants: tot i que es reconeix els xatbots de IA per millorar l'eficiència educativa i possibilitar l'aprenentatge personalitzat, persisteixen les preocupacions respecte a la disminució de la interacció humana, l'erosió potencial de les habilitats de pensament crític i l'ús ètic. Les anàlisis també destaquen la necessitat d'una implementació equilibrada de la IA que recolzi i no reemplaci els mètodes educatius tradicionals. Aquesta investigació contribueix al debat continu sobre la integració efectiva de la IA en l'educació i advoca per una adopció pedagògica responsable de les tecnologies de IA.

           

Referències

Aldağ, H. (2005). The effects of textual and graphical-textual argumentation software as cognitive tools on development of argumentation skills [Unpublished doctoral dissertation]. Adana.

Baker, R., & Siemens, G. (2014). Educational data mining and learning analytics. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (2nd ed., pp. 443-464). Cambridge University Press. https://doi.org/10.1017/CBO9781139519526.016

Bibauw, S., François, T., & Desmet, P. (2019). Discussing with a computer to practice a foreign language: Research synthesis and conceptual framework of dialogue-based CALL. Computer Assisted Language Learning, 32(8), 827–877. https://doi.org/10.1080/09588221.2018.1535508

Duschl, R., & Osborne, J. (2002). Supporting and promoting argumentation discourse in science education. Studies in Science Education, 38, 39-72. https://doi.org/10.1080/03057260208560187

Eisenhardt, K.M. (1989). Building theories from case study research. Academy of Management Review, 14 (4), 532-550. https://doi.org/10.2307/258557

Eisenhardt, K.M. & Graebner, M.E. (2007). Theory building from cases: Opportunities and challenges, Academy of Management Journal, 50 (1), 25-32

Erduran, S., Simon, S., & Osborne, J. (2004). TAPping into argumentation: Developments in the application of Toulmin’s argument pattern for studying science discourse. Science Education, 88, 915-933. https://doi.org/10.1002/sce.20012

Fahimirad, M., & Kotamjani, S. S. (2018). A review on application of artificial intelligence in teaching and learning in educational contexts. International Journal of Learning and Development, 8(4), 106-118. https://doi.org/10.5296/ijld.v8i4.14057

Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2023). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International. Advance online publication. https://doi.org/10.1080/14703297.2023.2195846

Følstad, A., & Brandtzæg, P. B. (2017). Chatbots and the new world of HCI. Interactions, 24(4), 38–42. https://doi.org/10.1145/3085558

Guo, K., Wang, J., & Chu, S. K. W. (2022). Using chatbots to scaffold EFL students’ argumentative writing. Assessing Writing, 54, 100666. https://doi.org/10.1016/j.asw.2022.100666

Guo, K., Zhong, Y., Li, D., & Chu, S. K. W. (2023). Effects of chatbot-assisted in-class debates on students’ argumentation skills and task motivation. Computers & Education, 203, 104862. https://doi.org/10.1016/j.compedu.2023.104862

Harwood, T. G., & Garry, T. (2003). An overview of content analysis. The Marketing Review, 3(4), 479-498. https://doi.org/10.1362/146934703771910080

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. https://doi.org/10.58863/20.500.12424/4276068

Hwang, G., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of artificial intelligence in education. Computers & Education: Artificial Intelligence, 1, [100001]. https://doi.org/10.1016/j.caeai.2020.100001

Jiménez-Aleixandre, M. P., & Erduran, S. (2007). Argumentation in science education: An overview. In S. Erduran & M. P. Jiménez-Aleixandre (Eds.), Argumentation in Science Education (pp. 3-28). Springer Science + Business Media B.V. https://doi.org/10.1007/1-4020-6051-6_1

Kim, H., Yang, H., Shin, D., & Lee, J. H. (2022). Design principles and architecture of a second language learning chatbot. Language Learning & Technology, 26(1), 1-18. http://hdl.handle.net/10125/73463

Kooli, C. (2023). Chatbots in Education and Research: A Critical Examination of Ethical Implications and Solutions. Sustainability, 15(7), 5614. https://doi.org/10.3390/su15075614

Malik, R., Shrama, A., Trivedi, S., & Mishra, R. (2021). Adoption of chatbots for learning among university students: Role of perceived convenience and enhanced performance. International Journal of Emerging Technologies in Learning (iJET), 16(18), 200-212. https://doi.org/10.3991/ijet.v16i18.24315

Merriam, S. B. (1998). Qualitative research and case study applications in education. Jossey-Bass.

Mhlanga, D. (2023). Open AI in education, the responsible and ethical use of ChatGPT towards lifelong learning. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.4354422

Nussbaum, E. M. (2011). Argumentation, Dialogue Theory, and Probability Modeling: Alternative Frameworks for Argumentation Research in Education. Educational Psychologist, 46(2), 84–106. https://doi.org/10.1080/00461520.2011.558816

Qadir, J. (2022). Engineering education in the era of ChatGPT: Promise and pitfalls of generative AI for education. TechRxiv. https://doi.org/10.36227/techrxiv.21789434.v1

Sandu, N., & Gide, E. (2019, September). Adoption of AI-Chatbots to enhance student learning experience in higher education in India. In 2019 18th International Conference on Information Technology Based Higher Education and Training (ITHET) (pp. 1-5). IEEE. https://doi.org/10.1109/ITHET46829.2019.8937382

Smutny, P., & Schreiberova, P. (2020). Chatbots for learning: A review of educational chatbots for the Facebook Messenger. Computers & Education, 151. https://doi.org/10.1016/j.compedu.2020.103862

Su, Y., Lin, Y., & Lai, C. (2023). Collaborating with ChatGPT in argumentative writing classrooms. Assessing Writing, 57, 100752. https://doi.org/10.1016/j.asw.2023.100752

Suri, H. (2011). Purposeful sampling in qualitative research synthesis. Qualitative Research Journal, 11(2), 63-75. https://doi.org/10.3316/QRJ1102063

Tamayo, P. R. V., Herrero, A. M., Martín, J., Navarro, C., & Tránchez, J. M. (2020). Design of a chatbot as a distance learning assistant. Open Praxis, 12(1), 145. https://doi.org/10.5944/openpraxis.12.1.1063

Toulmin, S. (1958). The Uses of Argument. Cambridge University Press.

Walton, D. (2006). Examination dialogue: An argumentation framework for critically questioning an expert opinion. Journal of Pragmatics, 38(5), 745-777. https://doi.org/10.1016/j.pragma.2005.01.016

Wambsganss, T., Guggisberg, S., & Söllner, M. (2021). ArgueBot: A conversational agent for adaptive argumentation feedback. In Innovation Through Information Systems (pp. 267-282). Springer. https://doi.org/10.1007/978-3-030-85868-4_18

Weller, M. (2021). 25 Years of Ed Tech. Athabasca University Press.

Yin, R. K. (1999). Enhancing the quality of case studies in health services research. Health Services Research, 34 (5 Pt 2), 1209-1224. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1089060/

Yin, R. K. (2014). Case study research: Design and methods (5th ed.). Sage.

Descàrregues

Publicades

2024-07-01