La nueva realidad de la educación ante los avances de la inteligencia artificial generativa
Open accessAbstract
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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 72 · Cited by 238
Research works printed but not linked: 48
- Agarwal, G. (2023). AI Tool Master List. https://doi.org/10.1007/s43681-022- 00147-7 · DOI
- Ali, S., DiPaola, D. y Breazeal, C. (2021). What are GANs?: Introducing Generative Adversarial Networks to Middle School Students. En Proceedings of the 35th AAAI Conference on Artificial Intelligence, AAAI 2021 (pp. 15472-15479). https:// doi.org/10.1609/aaai.v35i17.17821 · DOI
- Ali, S., DiPaola, D., Lee, I., Sindato, V., Kim, G., Blumofe, R. y 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 · DOI
- 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 · DOI · Paper page
- Chng, E., Tan, A. L. y 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 · DOI
- Crespo Artiaga, D., Ruiz Martínez, P. M., Claver Iborra, J. M., Fernández Martínez, A. y 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
- Devlin, J., Chang, M.-W., Lee, K. y 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 · DOI · Paper page
- 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 · DOI · Paper page
- Finnie-Ansley, J., Denny, P., Luxton-Reilly, A., Santos, E. A., Prather, J. y Becker, B. A. (2023). My AI Wants to Know if This Will Be on the Exam: Testing OpenAI's Codex on CS2 Programming Exercises. En ACE '23: Proceedings of the 25th Australasian Computing Education Conference (pp. 97-104). ACM. https:// doi.org/10.1145/3576123.3576134 · DOI · Paper page
- Flores-Vivar, J. M. y García-Peñalvo, F. J. (2023a). La vida algorítmica de la educación: Herramientas y sistemas de inteligencia artificial para el aprendizaje en línea. En G. Bonales Daimiel y J. Sierra Sánchez (Eds.), Desafíos y retos de las redes sociales en el ecosistema de la comunicación, (Vol. 1, pp. 109-121).
- Flores-Vivar, J. M. y 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 · DOI
- García Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2024). The new reality of education in the face of advances in generative artificial intelligence. [La nueva realidad de la educación ante los avances de la inteligencia artificial generativa]. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), pp. 9-39. https://doi.org/10.5944/ried.27.1.37716 Knowledge Society, 23, Article e28600. https://doi.org/10.14201/eks.28600 · DOI
- García-Peñalvo, F. J. y 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. y 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 · DOI · Paper page
- Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A. y Bengio, Y. (2020). Generative adversarial networks. Commun. ACM, 63(11), 139-144. https:// doi.org/10.1145/3422622 · DOI · Paper page
- Gruetzemacher, R. y 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 · DOI
- Gubareva, R. y Lopes, R. P. (2020). Virtual Assistants for Learning: A Systematic Literature Review. En H. Chad Lane, S. Zvacek, y 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 · DOI
- 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 · DOI · Paper page
- García Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2024). The new reality of education in the face of advances in generative artificial intelligence. [La nueva realidad de la educación ante los avances de la inteligencia artificial generativa]. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), pp. 9-39. https://doi.org/10.5944/ried.27.1.37716 Informatics Europe (2023). AI in Informatics Education (Position paper by Informatics Europe and the National Informatics Associations). Informatics Europe.
- Johinke, R., Cummings, R. y 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 · DOI
- 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 · DOI
- Khan, R. A., Jawaid, M., Khan, A. R. y 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 · DOI · Paper page
- Kingma, D. P. y Welling, M. (2022). Auto- Encoding Variational Bayes. arXiv, Article arXiv:1312.6114v11. https://doi. org/10.48550/arXiv.1312.6114 · DOI · Paper page
- Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepano, C., Madriaga, M., Aggabao, R., Diaz- Candido, G., Maningo, J. y 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 · DOI · Paper page
- Lyu, Z., Ali, S. y Breazeal, C. (2022). Introducing Variational Autoencoders to High School Students. En Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022 (pp. 12801- 12809). https://doi.org/10.1609/aaai. v36i11.21559 · DOI
- García Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2024). The new reality of education in the face of advances in generative artificial intelligence. [La nueva realidad de la educación ante los avances de la inteligencia artificial generativa]. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), pp. 9-39. https://doi.org/10.5944/ried.27.1.37716
- 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 · DOI · Paper page
- Muscanell, N. y Robert, J. (2023). EDUCAUSE QuickPoll Results: Did ChatGPT Write This Report? EDUCASE Review. https://bit.ly/44o0uWj
- Nemorin, S., Vlachidis, A., Ayerakwa, H. M. y 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/10.1080/1743988 4.2022.2095568 · DOI · Paper page
- 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 · DOI
- Ng, D. T. K., Lee, M., Tan, R. J. Y., Hu, X., Downie, J. S. y 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. h t t p s : / / d o i . o r g / 1 0 . 4 8 5 5 0 / arXiv.2303.08774 · DOI · Paper page
- Pataranutaporn, P., Leong, J., Danry, V., Lawson, A. P., Maes, P. y Sra, M. (2022). AI-Generated Virtual Instructors Based on Liked or Admired People Can Improve Motivation and Foster Positive Emotions for Learning. En Proceedings of 2022 IEEE Frontiers in Education Conference (FIE) (Uppsala, Sweden, 08-11 October 2022). IEEE. https://doi.org/10.1109/ FIE56618.2022.9962478 · DOI
- Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W. y 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.
- Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3(3), 417-424. https://doi.org/10.1017/ S0140525X00005756 · DOI · Paper page
- 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 · DOI
- Thatcher, J., Wright, R. T., Sun, H., Zagenczyk, T. J. y 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 · DOI
- 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 · DOI · Paper page
- Thurzo, A., Strunga, M., Urban, R., Surovková, J. y 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 · DOI
- 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. y Lample, G. (2023). LLaMA: Open and Efficient Foundation Language Models. arXiv, Article arXiv:2302.13971v1. h t t p s : / / d o i . o r g / 1 0 . 4 8 5 5 0 / arXiv.2302.13971 · DOI · Paper page
- En 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 · DOI
- Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L. y Polosukhin, I. (2017). Attention is all you need. En 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. y 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 · DOI
- Yilmaz, R., Yurdugül, H., Karaoğlan Yilmaz, F. G., Şahiṅ, M., Sulak, S., Aydin, F., Tepgeç, M., Müftüoğlu, C. T. y 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 · DOI
- Zhang, L., Basham, J. D. y 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 · DOI
- Zhang, R., Han, J., Liu, C., Gao, P., Zhou, A., Hu, X., Yan, S., Lu, P., Li, H. y 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 · DOI
- 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. y Levy, O. (2023). LIMA: Less Is More for Alignment. arXiv, Article arXiv:2305.11206v1. https://doi. org/10.48550/arXiv.2305.11206 · DOI · Paper page
- García Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2024). The new reality of education in the face of advances in generative artificial intelligence. [La nueva realidad de la educación ante los avances de la inteligencia artificial generativa]. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), pp. 9-39. https://doi.org/10.5944/ried.27.1.37716
- Authors
- García Peñalvo, F. J., Llorens-Largo, F., & Vidal, J.
- Affiliations
- Universidad de León (MX)
- Venue
- RIED-Revista Iberoamericana de Educación a Distancia
- Published
- 2023-07-07
- Volume
- 27
- Issue
- 1
- Pages
- 9-39
- ISSN
- 1138-2783 (ISSN-L)
- 1390-3306
- OpenAlex
- W4389737189
- Cited by
- 238
- References
- 72
- Citations by year
- 2026: 73 · 2025: 90 · 2024: 71 · 2023: 4
- FWCI
- 55.85
- Type
- journal article
- Language
- es
- Open access
- diamond
- doi.org
- Locations
- RIED Revista Iberoamericana de Educación a Distancia (publishedVersion, cc-by)
- Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- generative AI, ChatGPT, artificial intelligence in education, teaching-learning process, large language models, AI limitations, algorithmic bias, teacher practices, educational technology adoption
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review