La nueva realidad de la educación ante los avances de la inteligencia artificial generativa
DOI:
https://doi.org/10.5944/ried.27.1.37716Palabras clave:
inteligencia artificial, inteligencia artificial generativa, ChatGPT, educaciónResumen
Cada vez es más común interactuar con productos que parecen “inteligentes”, aunque quizás la etiqueta “inteligencia artificial” haya sido sustituida por otros eufemismos. Desde noviembre de 2022, con la aparición de la herramienta ChatGPT, ha habido un aumento exponencial en el uso de la inteligencia artificial en todos los ámbitos. Aunque ChatGPT es solo una de las muchas tecnologías generativas de inteligencia artificial, su impacto en los procesos de enseñanza y aprendizaje ha sido notable. Este artículo reflexiona sobre las ventajas, inconvenientes, potencialidades, límites y retos de las tecnologías generativas de inteligencia artificial en educación, con el objetivo de evitar los sesgos propios de las posiciones extremistas. Para ello, se ha llevado a cabo una revisión sistemática tanto de las herramientas como de la producción científica que ha surgido en los seis primeros meses desde la aparición de ChatGPT. La inteligencia artificial generativa es extremadamente potente y mejora a un ritmo acelerado, pero se basa en lenguajes de modelo de gran tamaño con una base probabilística, lo que significa que no tienen capacidad de razonamiento ni de comprensión y, por tanto, son susceptibles de contener fallos que necesitan ser contrastados. Por otro lado, muchos de los problemas asociados con estas tecnologías en contextos educativos ya existían antes de su aparición, pero ahora, debido a su potencia, no podemos ignorarlos solo queda asumir cuál será nuestra velocidad de respuesta para analizar e incorporar estas herramientas a nuestra práctica docente.
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https://revistas.uned.es/index.php/ried/article/view/37716/27872
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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
