La nueva realidad de la educación ante los avances de la inteligencia artificial generativa

  1. Francisco José García-Peñalvo 1
  2. Faraón Llorens-Largo 2
  3. Javier Vidal 3
  1. 1 Universidad de Salamanca (España)
  2. 2 Universidad de Alicante (España)
  3. 3 Universidad de León (España)
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Revue:
RIED: revista iberoamericana de educación a distancia

ISSN: 1138-2783

Année de publication: 2024

Titre de la publication: Tendencias en la Educación Digital

Volumen: 27

Número: 1

Pages: 9-39

Type: Article

DIALNET GOOGLE SCHOLAR lock_openAccès ouvert editor

D'autres publications dans: RIED: revista iberoamericana de educación a distancia

Résumé

It is increasingly common to interact with products that seem “intelligent”, although the label “artificial intelligence” may have been replaced by other euphemisms. Since November 2022, with the emergence of the ChatGPT tool, there has been an exponential increase in the use of artificial intelligence in all areas. Although ChatGPT is just one of many generative artificial intelligence technologies, its impact on teaching and learning processes has been significant. This article reflects on the advantages, disadvantages, potentials, limits, and challenges of generative artificial intelligence technologies in education to avoid the biases inherent in extremist positions. To this end, a systematic review has been carried out of both the tools and the scientific production that has emerged in the six months since the appearance of ChatGPT. Generative artificial intelligence is extremely powerful and improving at an accelerated pace, but it is based on large language models with a probabilistic basis, which means that they have no capacity for reasoning or comprehension and are therefore susceptible to containing errors that need to be contrasted. On the other hand, many of the problems associated with these technologies in educational contexts already existed before their appearance, but now, due to their power, we cannot ignore them, and we must assume what our speed of response will be to analyse and incorporate these tools into our teaching practice

Références bibliographiques

  • Adiwardana, D. (2020, January 28th). Towards a Conversational Agent that Can Chat About…Anything. Google. http://bit.ly/3YAYGpm
  • Agarwal, G. (2023). AI Tool Master List. https://doi.org/10.1007/s43681-022-00147-7
  • Ali, S., DiPaola, D., & Breazeal, C. (2021). What are GANs?: Introducing Generative Adversarial Networks to Middle School Students. In Proceedings of the 35th AAAI Conference on Artificial Intelligence, AAAI 2021 (pp. 15472-15479). https://doi.org/10.1609/aaai.v35i17.17821
  • Ali, S., DiPaola, D., Lee, I., Sindato, V., Kim, G., Blumofe, R., & Breazeal, C. (2021). Children as creators, thinkers and citizens in an AI-driven future. Computers and Education: Artificial Intelligence, 2, Article 100040. https://doi.org/10.1016/j.caeai.2021.100040
  • Alier-Forment, M., & Llorens-Largo, F. (2023). EP-31 Las Alucinaciones de ChatGPT con Faraón Llorens In Cabalga el Cometa. https://bit.ly/3ZCNBVT
  • Alonso, C. (2023, 19 de abril). ¡Ojo con ChatGPT, que es un charlatán mentirosillo! El futuro está por hackear. https://bit.ly/44dEbCk
  • Arora, A., & Arora, A. (2022). Generative adversarial networks and synthetic patient data: current challenges and future perspectives. Future Healthcare Journal, 9(2), 190-193. https://doi.org/10.7861/fhj.2022-0013
  • Bozkurt, A., Xiao, J., Lambert, S., Pazurek, A., Crompton, H., Koseoglu, S., Farrow, R., Bond, M., Nerantzi, C., Honeychurch, S., Bali, M., Dron, J., Mir, K., Stewart, B., Costello, E., Mason, J., Stracke, C. M., Romero-Hall, E., Koutropoulos, A., … Jandrić, P. (2023). Speculative futures on ChatGPT and generative artificial intelligence (AI): A collective reflection from the educational landscape. Asian Journal of Distance Education, 18(1), 53-130. https://doi.org/10.5281/zenodo.7636568
  • Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., … Amodei, D. (2020). Language Models are Few-Shot Learners. arXiv. https://doi.org/10.48550/arXiv.2005.14165
  • Chng, E., Tan, A. L., & Tan, S. C. (2023). Examining the Use of Emerging Technologies in Schools: a Review of Artificial Intelligence and Immersive Technologies in STEM Education. Journal for STEM Education Research, In Press. https://doi.org/10.1007/s41979-023-00092-y
  • Choi, E. P. H., Lee, J. J., Ho, M. H., Kwok, J. Y. Y., & Lok, K. Y. W. (2023). Chatting or cheating? The impacts of ChatGPT and other artificial intelligence language models on nurse education. Nurse Education Today, 125, Article 105796. https://doi.org/10.1016/j.nedt.2023.105796
  • Chomsky, N., Roberts, I., & Watumull, J. (2023, March 8th). The False Promise of ChatGPT. The New York Times. http://bit.ly/3GycXfx
  • Coeckelbergh, M. (2023). La filosofía política de la inteligencia artificial. Una introducción. Cátedra.
  • Collins, E., & Ghahramani, Z. (2021, May 18th). LaMDA: our breakthrough conversation technology. Google. http://bit.ly/3I5udIZ
  • Cooper, G. (2023). Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence. Journal of Science Education and Technology, 32, 444-452. https://doi.org/10.1007/s10956-023-10039-y
  • Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, In Press. https://doi.org/10.1080/14703297.2023.2190148
  • Crawford, J., Cowling, M., & Allen, K. A. (2023). Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artifiicial intelligence (AI). Journal of University Teaching and Learning Practice, 20(3). https://doi.org/10.53761/1.20.3.02
  • Crespo Artiaga, D., Ruiz Martínez, P. M., Claver Iborra, J. M., Fernández Martínez, A., & Llorens Largo, F. (Eds.). (2023). UNIVERSITIC 2022. Análisis de la madurez digital de las universidades españolas en 2022. Crue Universidades Españolas. https://bit.ly/3n60tp3
  • Dennett, D. (2017). De las bacterias a Bach. La evolución de la mente. Pasado & Presente.
  • Devlin, J., & Chang, M.-W. (2018, November 2nd). Open Sourcing BERT: State-of-the-Art Pre-training for Natural Language Processing. Google. http://bit.ly/3Ebwrpi
  • Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint, Article 1810.04805. https://doi.org/10.48550/arXiv.1810.04805
  • Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, Article 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
  • Ebrahimi, Y. (2023). 1000 AI collection tools. http://bit.ly/3YOjkSK
  • European University Association (2023). Artificial intelligence tools and their responsible use in higher education learning and teaching. European University Association. https://bit.ly/3Hq2ROf
  • Finnie-Ansley, J., Denny, P., Luxton-Reilly, A., Santos, E. A., Prather, J., & Becker, B. A. (2023). My AI Wants to Know if This Will Be on the Exam: Testing OpenAI's Codex on CS2 Programming Exercises. In ACE '23: Proceedings of the 25th Australasian Computing Education Conference (pp. 97-104). ACM. https://doi.org/10.1145/3576123.3576134
  • Flores-Vivar, J. M., & García-Peñalvo, F. J. (2023a). La vida algorítmica de la educación: Herramientas y sistemas de inteligencia artificial para el aprendizaje en línea. In G. Bonales Daimiel & J. Sierra Sánchez (Eds.), Desafíos y retos de las redes sociales en el ecosistema de la comunicación, (Vol. 1, pp. 109-121). McGraw-Hill.
  • Flores-Vivar, J. M., & García-Peñalvo, F. J. (2023b). Reflections on the ethics, potential, and challenges of artificial intelligence in the framework of quality education (SDG4). Comunicar, 31(74), 35-44. https://doi.org/10.3916/C74-2023-03
  • García-Peñalvo, F. J. (2022). Developing robust state-of-the-art reports: Systematic Literature Reviews. Education in the Knowledge Society, 23, Article e28600. https://doi.org/10.14201/eks.28600
  • García-Peñalvo, F. J. (2023). The perception of Artificial Intelligence in educational contexts after the launch of ChatGPT: Disruption or Panic? Education in the Knowledge Society, 24, Article e31279. https://doi.org/10.14201/eks.31279
  • García-Peñalvo, F. J., & Vázquez-Ingelmo, A. (2023). 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, In Press.
  • Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64-71. https://doi.org/10.1007/s11528-014-0822-x
  • Gašević, D., Siemens, G., & Sadiq, S. (2023). Empowering learners for the age of artificial intelligence. Computers and Education: Artificial Intelligence, 4, Article 100130. https://doi.org/10.1016/j.caeai.2023.100130
  • Gates, B. (2023, March 21). The Age of AI has begun. GatesNotes. http://bit.ly/3nZjFF4
  • Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2023). 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, 9, Article e45312. https://doi.org/10.2196/45312
  • Gobierno de España (2020). ENIA: Estrategia Nacional de Inteligencia Artificial. Ministerio de Asuntos Económicos y Transformación Digital. https://bit.ly/3oHHUb0
  • Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2020). Generative adversarial networks. Commun. ACM, 63(11), 139-144. https://doi.org/10.1145/3422622
  • Grant, M. J., & Booth, A. (2009). A typology of reviews: an analysis of 14 review types and associated methodologies. Health Information and Libraries Journal, 26(2), 91-108. https://doi.org/10.1111/j.1471-1842.2009.00848.x
  • Gruetzemacher, R., & Paradice, D. (2022). Deep Transfer Learning & Beyond: Transformer Language Models in Information Systems Research. ACM Computing Surveys, 54(10s). https://doi.org/10.1145/3505245
  • Gubareva, R., & Lopes, R. P. (2020). Virtual Assistants for Learning: A Systematic Literature Review. In H. Chad Lane, S. Zvacek, & J. Uhomoibhi (Eds.), Proceedings of the 12th International Conference on Computer Supported Education (CSEDU 2020) (Online, May 2 - 4, 2020) (Vol. 1, pp. 97-103). SCITEPRESS. https://doi.org/10.5220/0009417600970103
  • Hazzan, O. (2023, January 23). ChatGPT in Computer Science Education. BLOG@ACM. http://bit.ly/3WYTxpv
  • Hoffmann, J., Borgeaud, S., Mensch, A., Buchatskaya, E., Cai, T., Rutherford, E., de las Casas, D., Hendricks, L. A., Welbl, J., Clark, A., Hennigan, T., Noland, E., Millican, K., Driessche, G. v. d., Damoc, B., Guy, A., Osindero, S., Simonyan, K., Elsen, E., … Sifre, L. (2022). Training Compute-Optimal Large Language Models. arXiv, Article arXiv:2203.15556v1. https://doi.org/10.48550/arXiv.2203.15556
  • Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2022). Ethics of AI in Education: Towards a Community-Wide Framework. International Journal of Artificial Intelligence in Education, 32, 504-526. https://doi.org/10.1007/s40593-021-00239-1
  • Informatics Europe (2023). AI in Informatics Education (Position paper by Informatics Europe and the National Informatics Associations). Informatics Europe.
  • Iskender, A. (2023). Holy or Unholy? Interview with Open AI’s ChatGPT. European Journal of Tourism Research, 34, Article 3414. https://doi.org/10.54055/ejtr.v34i.3169
  • Johinke, R., Cummings, R., & Di Lauro, F. (2023). Reclaiming the technology of higher education for teaching digital writing in a post-pandemic world. Journal of University Teaching and Learning Practice, 20(2), Article 01. https://doi.org/10.53761/1.20.02.01
  • Karaali, G. (2023). Artificial Intelligence, Basic Skills, and Quantitative Literacy. Numeracy, 16(1), Article 9. https://doi.org/10.5038/1936-4660.16.1.1438
  • Karras, T., Laine, S., & Aila, T. (2021). A Style-Based Generator Architecture for Generative Adversarial Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(12), 4217-4228. https://doi.org/10.1109/TPAMI.2020.2970919
  • Khan, R. A., Jawaid, M., Khan, A. R., & Sajjad, M. (2023). ChatGPT-Reshaping medical education and clinical management. Pakistan Journal of Medical Sciences, 39(2), 605-607. https://doi.org/10.12669/pjms.39.2.7653
  • Kingma, D. P., & Welling, M. (2022). Auto-Encoding Variational Bayes. arXiv, Article arXiv:1312.6114v11. https://doi.org/10.48550/arXiv.1312.6114
  • Kirchner, J. H., Ahmad, L., Aaronson, S., & Leike, J. (2023, January 31). New AI classifier for indicating AI-written text. https://bit.ly/3rbXJYI
  • Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepano, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., & Tseng, V. (2023). Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models. PLOS Digital Health, 2(2), Article e0000198. https://doi.org/10.1371/journal.pdig.0000198
  • Kurian, T. (2023, March 14th). The next generation of AI for developers and Google Workspace. The Keyword. http://bit.ly/3mUo0sx
  • Lee, H. (2023). The rise of ChatGPT: Exploring its potential in medical education. Anatomical sciences education, In Press. https://doi.org/10.1002/ase.2270
  • Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. International Journal of Management Education, 21(2), Article 100790. https://doi.org/10.1016/j.ijme.2023.100790
  • Liu, Y., Han, T., Ma, S., Zhang, J., Yang, Y., Tian, J., He, H., Li, A., He, M., Liu, Z., Wu, Z., Zhu, D., Li, X., Qiang, N., Shen, D., Tianming Liu, & Ge, B. (2023). Summary of ChatGPT/GPT-4 Research and Perspective Towards the Future of Large Language Models. arXiv, Article arXiv:2304.01852v3. https://doi.org/10.48550/arXiv.2304.01852
  • Llorens-Largo, F. (2019, 13/02/2019). Las tecnologías en la educación: características deseables, efectos perversos. Universídad. https://bit.ly/3SxO72D
  • Lyu, Z., Ali, S., & Breazeal, C. (2022). Introducing Variational Autoencoders to High School Students. In Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022 (pp. 12801-12809). https://doi.org/10.1609/aaai.v36i11.21559
  • Maslej, N., Fattorini, L., Brynjolfsson, E., Etchemendy, J., Ligett, K., Lyons, T., Manyika, J., Ngo, H., Niebles, J. C., Parli, V., Shoham, Y., Wald, R., Jack Clark, & Perrault, R. (2023). The AI Index 2023 Annual Report. http://bit.ly/3KBVCFa
  • Masters, K. (2023). Ethical use of artificial intelligence in health professions education: AMEE Guide No. 158. Medical Teacher, 45(6), 574-584. https://doi.org/10.1080/0142159X.2023.2186203
  • Mbakwe, A. B., Lourentzou, I., Celi, L. A., Mechanic, O. J., & Dagan, A. (2023). ChatGPT passing USMLE shines a spotlight on the flaws of medical education. PLOS digital health, 2(2), Article e0000205. https://doi.org/10.1371/journal.pdig.0000205
  • Meyer, B. (2022, December 23). What Do ChatGPT and AI-based Automatic Program Generation Mean for the Future of Software. BLOG@CACM. https://bit.ly/3LyAJLj
  • Muscanell, N., & Robert, J. (2023). EDUCAUSE QuickPoll Results: Did ChatGPT Write This Report? EDUCASE Review. https://bit.ly/44o0uWj
  • Nemorin, S., Vlachidis, A., Ayerakwa, H. M., & Andriotis, P. (2023). AI hyped? A horizon scan of discourse on artificial intelligence in education (AIED) and development. Learning, Media and Technology, 48(1), 38-51. https://doi.org/10.1080/17439884.2022.2095568
  • Neubauer, A. C. (2021). The future of intelligence research in the coming age of artificial intelligence – With a special consideration of the philosophical movements of trans- and posthumanism. Intelligence, 87, Article 101563. https://doi.org/10.1016/j.intell.2021.101563
  • Ng, D. T. K., Lee, M., Tan, R. J. Y., Hu, X., Downie, J. S., & Chu, S. K. W. (2022). A review of AI teaching and learning from 2000 to 2020. Education and Information Technologies, In Press. https://doi.org/10.1007/s10639-022-11491-w
  • OpenAI. (2023). GPT-4 Technical Report. arXiv, Article arXiv:2303.08774v3. https://doi.org/10.48550/arXiv.2303.08774
  • Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, Article n71. https://doi.org/10.1136/bmj.n71
  • Pataranutaporn, P., Leong, J., Danry, V., Lawson, A. P., Maes, P., & Sra, M. (2022). AI-Generated Virtual Instructors Based on Liked or Admired People Can Improve Motivation and Foster Positive Emotions for Learning. In Proceedings of 2022 IEEE Frontiers in Education Conference (FIE) (Uppsala, Sweden, 08-11 October 2022). IEEE. https://doi.org/10.1109/FIE56618.2022.9962478
  • Pavlik, J. V. (2023). Collaborating With ChatGPT: Considering the Implications of Generative Artificial Intelligence for Journalism and Media Education. Journalism and Mass Communication Educator, 78(1), 84-93. https://doi.org/10.1177/10776958221149577
  • Perkins, M. (2023). Academic Integrity considerations of AI Large Language Models in the post-pandemic era: ChatGPT and beyond. Journal of University Teaching and Learning Practice, 20(2), Article 07. https://doi.org/10.53761/1.20.02.07
  • Pichai, S. (2023, February 6th). An important next step on our AI journey. Google. http://bit.ly/3YZj9E2
  • Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2020). Exploring the limits of transfer learning with a unified text-to-text transformer. Journal of Machine Learning Research, 21(140), 1-67.
  • 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), 1-22. https://doi.org/10.37074/jalt.2023.6.1.9
  • Sabzalieva, E., & Valentini, A. (2023). ChatGPT e inteligencia artificial en la educación superior: Guía de inicio rápido (ED/HE/IESALC/IP/2023/12). UNESCO e Instituto Internacional de la UNESCO para la Educación Superior en América Latina y el Caribe. https://bit.ly/3oeYm2f
  • Sadasivan, V. S., Kumar, A., Balasubramanian, S., Wang, W., & Feizi, S. (2023). Can AI-Generated Text be Reliably Detected? arXiv, Article arXiv:2303.11156v1. https://doi.org/10.48550/arXiv.2303.11156
  • Sallam, M. (2023). ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns. Healthcare, 11(6), Article 887. https://doi.org/10.3390/healthcare11060887
  • Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3(3), 417-424. https://doi.org/10.1017/S0140525X00005756
  • Sivasubramanian, S. (2023, April 13th). Announcing New Tools for Building with Generative AI on AWS. AWS. https://bit.ly/3mziFXM
  • Šlapeta, J. (2023). Are ChatGPT and other pretrained language models good parasitologists? Trends in parasitology, 39(5), 314-316. https://doi.org/10.1016/j.pt.2023.02.006
  • Taori, R., Gulrajani, I., Zhang, T., Dubois, Y., Li, X., Guestrin, C., Liang, P., & Hashimoto, T. B. (2023). Alpaca: A Strong, Replicable Instruction-Following Model. Stanford University. https://bit.ly/444TrRx
  • Thatcher, J., Wright, R. T., Sun, H., Zagenczyk, T. J., & Klein, R. (2018). Mindfulness in Information Technology Use: Definitions, Distinctions, and a New Measure. MIS Quarterly, 42(3), 831-847. https://doi.org/10.25300/MISQ/2018/11881
  • Thoppilan, R., Freitas, D. D., Hall, J., Shazeer, N., Kulshreshtha, A., Cheng, H.-T., Jin, A., Bos, T., Baker, L., Du, Y., Li, Y., Lee, H., Zheng, H. S., Ghafouri, A., Menegali, M., Huang, Y., Krikun, M., Lepikhin, D., Qin, J., … Le, Q. (2022). LaMDA: Language Models for Dialog Applications. arXiv, Article arXiv:2201.08239v3. https://doi.org/10.48550/arXiv.2201.08239
  • Thorp, H. H. (2023). ChatGPT is fun, but not an author. Science, 379(6630), 313. https://doi.org/10.1126/science.adg7879
  • Thurzo, A., Strunga, M., Urban, R., Surovková, J., & Afrashtehfar, K. I. (2023). Impact of Artificial Intelligence on Dental Education: A Review and Guide for Curriculum Update. Education Sciences, 13(2), Article 150. https://doi.org/10.3390/educsci13020150
  • Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(1), Article 15. https://doi.org/10.1186/s40561-023-00237-x
  • Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., Rodriguez, A., Joulin, A., Grave, E., & Lample, G. (2023). LLaMA: Open and Efficient Foundation Language Models. arXiv, Article arXiv:2302.13971v1. https://doi.org/10.48550/arXiv.2302.13971
  • Turing, A. M. (1950). Computing machinery and intelligence. Mind, 59(236), 433-460. https://doi.org/10.1093/mind/LIX.236.433
  • UNESCO. (2019). Beijing Consensus on Artificial Intelligence and Education. International Conference on¬ Artificial Intelligence and Education, Planning Education in the AI Era: Lead the Leap, Beijing, China. ¬https://bit.ly/3n7wBIK
  • UNESCO. (2021). Inteligencia artificial y educación: Guía para las personas a cargo de formular políticas. UNESCO. https://bit.ly/3Hl93Hj
  • UNESCO. (2022). Recomendación sobre la ética de la inteligencia artificial. UNESCO. https://bit.ly/3nc3Yu1
  • van der Zant, T., Kouw, M., & Schomaker, L. (2013). Generative artificial intelligence. In V. C. Müller (Ed.), Philosophy and Theory of Artificial Intelligence (107-120). Springer-Verlag. https://doi.org/10.1007/978-3-642-31674-6_8
  • Vartiainen, H., & Tedre, M. (2023). Using artificial intelligence in craft education: crafting with text-to-image generative models. Digital Creativity, 34(1), 1-21. https://doi.org/10.1080/14626268.2023.2174557
  • Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017). Attention is all you need. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA (pp. 5998-6008).
  • Vázquez-Ingelmo, A., García-Peñalvo, F. J., & Therón, R. (2021). Towards a Technological Ecosystem to Provide Information Dashboards as a Service: A Dynamic Proposal for Supplying Dashboards Adapted to Specific Scenarios. Applied Sciences, 11(7), Article 3249. https://doi.org/10.3390/app11073249
  • Wang, T., & Cheng, E. C. K. (2021). An investigation of barriers to Hong Kong K-12 schools incorporating Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 2, Article 100031. https://doi.org/10.1016/j.caeai.2021.100031
  • Yang, J., Jin, H., Tang, R., Han, X., Feng, Q., Jiang, H., Yin, B., & Hu, X. (2023). Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond. arXiv, Article arXiv:2304.13712v2. https://doi.org/10.48550/arXiv.2304.13712
  • Yilmaz, R., Yurdugül, H., Karaoğlan Yilmaz, F. G., Şahi̇n, M., Sulak, S., Aydin, F., Tepgeç, M., Müftüoğlu, C. T., & Ömer, O. (2022). Smart MOOC integrated with intelligent tutoring: A system architecture and framework model proposal. Computers and Education: Artificial Intelligence, 3, Article 100092. https://doi.org/10.1016/j.caeai.2022.100092
  • Zhang, L., Basham, J. D., & Yang, S. (2020). Understanding the implementation of personalized learning: A research synthesis. Educational Research Review, 31, Article 100339. https://doi.org/10.1016/j.edurev.2020.100339
  • Zhang, R., Han, J., Liu, C., Gao, P., Zhou, A., Hu, X., Yan, S., Lu, P., Li, H., & Qiao, Y. (2023). LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention. arXiv, Article arXiv:2303.16199v2. https://doi.org/10.48550/arXiv.2303.16199
  • Zhao, W. X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., Du, Y., Yang, C., Chen, Y., Chen, Z., Jiang, J., Ren, R., Li, Y., Tang, X., Liu, Z., … Wen, J.-R. (2023). A Survey of Large Language Models. arXiv, Article arXiv:2303.18223v10. https://doi.org/10.48550/arXiv.2303.18223
  • Zhou, C., Liu, P., Xu, P., Iyer, S., Sun, J., Mao, Y., Ma, X., Efrat, A., Yu, P., Yu, L., Zhang, S., Ghosh, G., Lewis, M., Zettlemoyer, L., & Levy, O. (2023). LIMA: Less Is More for Alignment. arXiv, Article arXiv:2305.11206v1. https://doi.org/10.48550/arXiv.2305.11206
La source de données: Dialnet