Inteligencia artificial generativa y educación
Un análisis desde múltiples perspectivas
Resumen En la intersección entre la tecnología avanzada y la pedagogía, la Inteligencia Artificial Generativa (IAGen) está provocando, como poco, el replanteamiento de los paradigmas educativos tradicionales. Después de un año frenético en el avance de la IAGen, especialmente tras la aparición en escena de ChatGPT, se quiere explorar el impacto de la IAGen en el sector educativo, analizado desde las perspectivas de cuatro colectivos clave: profesorado, estudiantado, perfiles de toma de decisiones e ingenieros/as de software. Durante 2023 y lo que llevamos de 2024 se han realizado revisiones de literatura, entrevistas, encuestas, formaciones y observaciones directas de cómo se percibe la IAGen por personas que representan a los colectivos anteriormente mencionados dentro del contexto educativo. Se destaca cómo la IAGen ofrece oportunidades sin precedentes para, entre otros aspectos, personalizar el aprendizaje, mejorar la calidad de los recursos educativos u optimizar los procesos administrativos y de evaluación. Sin embargo, la IAGen aplicada a la educación tiene otra cara menos amable que se relaciona con recelos y desconfianzas, debidas, en muchas ocasiones a una falta de alfabetización en aspectos relacionados con la IA en general, pero bien fundamentados en otras ocasiones por las lagunas existentes en cuanto a aspectos legislativos, éticos, de seguridad o de influencia medioambiental. Este análisis revela que, aunque la IAGen tiene el potencial de transformar significativamente la educación, su implementación exitosa requiere un enfoque colaborativo y transversal que involucre a todos los actores del ecosistema educativo. A medida que exploramos este nuevo horizonte, es imperativo considerar las implicaciones éticas y garantizar que la tecnología se utilice de manera que signifique un beneficio para la sociedad en general, sin obviar los riesgos y retos que ya existen o que ineludiblemente aparecerán con el desarrollo acelerado de estas tecnologías tan extremadamente potentes.
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Alier, M., Casañ, M. J., & Amo, D. (2024). Smart Learning Applications: Leveraging LLMs for Contextualized and Ethical Educational Technology. In Proceedings TEEM 2023: Eleventh International Conference on Technological Ecosystems for Enhancing Multiculturality. Bragança, Portugal, October 25–27, 2023. Springer.
Alier, M., García-Peñalvo, F. J., & Camba, J. D. (2024). Generative Artificial Intelligence in Education: From Deceptive to Disruptive. International Journal of Interactive Multimedia and Artificial Intelligence, 8(5), 5-14. https://doi.org/10.9781/ijimai.2024.02.011
Álvarez, D. (2023). Inteligencia Artificial en Educación: Oportunidades y Desafíos para el Aula del s.XXI SIMO Educación 2023, Madrid, España. https://bit.ly/3QLGBlG
Amo-Filva, D., Fonseca, D., Vernet, D., Torres, E., Muñoz Pastor, P., Caballero, V., Fernandez, E., Alier, M., García-Peñalvo, F. J., García-Holgado, A., Llorens-Largo, F., Molina-Carmona, R., Conde, M. Á., & Hernández-García, Á. (2023). Usos y desusos del modelo GPT-3 entre estudiantes de grados de ingeniería. In J. A. Cruz Lemus, N. Medina Medina, & M. J. Rodríguez Fórtiz (Eds.), Actas de las XXIX Jornadas sobre la Enseñanza Universitaria de la Informática - JENUI 2023 (Granada, España, 5-7 de julio de 2023) (Vol. 8, pp. 415-418).
Aoun, J. E. (2018). Robot-Proof. Higher Education in the Age of Artificial Intelligence. The MIT Press.
Bandi, A., Adapa, P. V., & Kuchi, Y. E. (2023). The Power of Generative AI: A Review of Requirements, Models, Input–Output Formats, Evaluation Metrics, and Challenges. Future Internet, 15(8), Article 260. https://doi.org/10.3390/fi15080260
Bartlett, K. A., & Camba, J. D. (2024). Generative Artificial Intelligence in Product Design Education: Navigating Concerns of Originality and Ethics. International Journal of Interactive Multimedia and Artificial Intelligence, 8(5), 55-64. https://doi.org/10.9781/ijimai.2024.02.006
Berthelot, A., Jay, M., Lefevre, L., & Caron, E. (2023). Estimating the environmental impact of Generative-AI services using an LCA-based methodology. Portail INRIA.HAL.SCIENCE, Article hal-04346102. https://inria.hal.science/hal-04346102
Biderman, S., & Raff, E. (2022). Fooling MOSS Detection with Pretrained Language Models. In CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management (Atlanta, GA, USA, October 17 - 21, 2022) (pp. 2933–2943). ACM. https://doi.org/10.1145/3511808.3557079
Bozkurt, A. (2023). Generative artificial intelligence (AI) powered conversational educational agents: The inevitable paradigm shift. Asian Journal of Distance Education, 18(1), 198-204. https://doi.org/10.5281/zenodo.7716416
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., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., & Amodei, D. (2020). Language Models are Few-Shot Learners. arXiv, Article arXiv:2005.14165v4 https://doi.org/10.48550/arXiv.2005.14165
Casal-Otero, L., Catala, A., Fernández-Morante, C., Taboada, M., Cebreiro, B., & Barro, S. (2023). AI literacy in K-12: a systematic literature review. International Journal of STEM Education, 10(1), Article 29. https://doi.org/10.1186/s40594-023-00418-7
Chien, A. A., Lin, L., Nguyen, H., Rao, V., Sharma, T., & Wijayawardana, R. (2023). Reducing the Carbon Impact of Generative AI Inference (today and in 2035). In HotCarbon '23: Proceedings of the 2nd Workshop on Sustainable Computer Systems (Boston, MA, USA, 9 July 2023) (pp. Article 11). Association for Computing Machinery. https://doi.org/10.1145/3604930.3605705
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
Conde, M. Á., Rodríguez-Sedano, F. J., Fernández-Llamas, C., Gonçalves, J., Lima, J., & García-Peñalvo, F. J. (2021). Fostering STEAM through Challenge Based Learning, Robotics and Physical Devices: A systematic mapping literature review. Computer Application in Engineering Education, 29, 46-65. https://doi.org/10.1002/cae.22354
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. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228-239. 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 artificial intelligence (AI). Journal of University Teaching and Learning Practice, 20(3). https://doi.org/10.53761/1.20.3.02
de Souza Zanirato Maia, J., Arantes Bueno, A. P., & Sato, J. R. (2023). Applications of Artificial Intelligence Models in Educational Analytics and Decision Making: A Systematic Review. World, 4(2), 288-313. https://doi.org/10.3390/world4020019
Denny, P., Prather, J., Becker, B. A., Finnie-Ansley, J., Hellas, A., Leinonen, J., Luxton-Reilly, A., Reeves, B. N., Santos, E. A., & Sarsa, S. (2024). Computing Education in the Era of Generative AI. Communications of the ACM, 67(2), 56–67. https://doi.org/10.1145/3624720
Duarte, F. (2024, March 27th). Number of ChatGPT Users (Apr 2024). https://bit.ly/3NWOEvH
Evans, O., Wale-Awe, O. I., Emeka, O., Ayoola, O. O., Alenoghena, R., & Adeniji, S. (2023). ChatGPT impacts on access-efficiency, employment, education and ethics: The socio-economics of an AI language model. Bizecons Quarterly, 16. https://d66z.short.gy/23XlQI
Fernández Enguita, M. (2024). Inteligencia aumentada y avanzada para aprender y enseñar. Cuadernos de Pedagogía(549).
Flores-Vivar, J. M., & García-Peñalvo, F. J. (2023). 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
Fonseca-Escudero, D., García-Peñalvo, F. J., Llorens-Largo, F., & Molina-Carmona, R. (2023, 18-20 de octubre de 2023). ¡Qué viene la IA! ¿Estoy preparada/o? VII Congreso Internacional sobre Innovación, Aprendizaje y Cooperación, CINAIC 2023, Universidad Politécnica de Madrid, Madrid, España. https://doi.org/10.5281/zenodo.10050857
Gallent-Torres, C., & Comas-Forgas, R. (2024). La llama de Prometeo: IA e integridad académica. Cuadernos de Pedagogía(549).
García San Martín, M. J. (2024). ¿Qué lugar ocupa la IA en las competencias digitales de los docentes? Cuadernos de Pedagogía(549).
García-Peñalvo, F. J. (2018). Ecosistemas tecnológicos universitarios. In J. Gómez (Ed.), UNIVERSITIC 2017. Análisis de las TIC en las Universidades Españolas (pp. 164-170). Crue Universidades Españolas.
García-Peñalvo, F. J. (2023a, 18-20 de octubre). Discusión abierta sobre beneficios, riesgos y retos de la Inteligencia Artificial Generativa VII Edición del Congreso Internacional sobre Innovación, Aprendizaje y Cooperación, CINAIC 2023, Universidad Politécnica de Madrid, Madrid, España. https://doi.org/10.5281/zenodo.10029703
García-Peñalvo, F. J. (2023b, 4 de diciembre). La era de la inteligencia artificial generativa en educación 4º Congreso de Educación, Innovación, Normalismo y Neuroeducación (CEINN 2023), Ciudad de México, México. https://doi.org/10.5281/zenodo.10255745
García-Peñalvo, F. J. (2023c). 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. (2023d). Using ChatGPT for discovering conceptual classes in object-oriented modeling. In C. Nerantzi, S. Abegglen, M. Karatsiori, & A. M. Arboleda (Eds.), 101 creative ideas to use AI in education, A crowdsourced collection. https://bit.ly/48D87dq
García-Peñalvo, F. J. (2024a). Cómo afecta la inteligencia artificial generativa a los procesos de evaluación. Cuadernos de Pedagogía(549).
García-Peñalvo, F. J. (2024b, 13 de marzo). Escenarios de innovación educativa con Inteligencia Artificial Generativa XIII Jornadas de Innovación Docente de la UNED, Facultad de Educación de la UNED, Madrid, España. https://doi.org/10.5281/zenodo.10808874
García-Peñalvo, F. J. (2024c, 24 January). Generative Artificial Intelligence in Higher Education: A 360° Perspective IFE Conference Special Event; Artificial Intelligence in Education Summit, Tecnológico de Monterrey, Monterrey, México. https://doi.org/10.5281/zenodo.10499828
García-Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2024). The new reality of education in the face of advances in generative artificial intelligence. RIED: revista iberoamericana de educación a distancia, 27(1), 9–39. https://doi.org/10.5944/ried.27.1.37716
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, 8(4), 7-16. https://doi.org/10.9781/ijimai.2023.07.006
Garmpis, S., Maragoudakis, M., & Garmpis, A. (2022). Assisting Educational Analytics with AutoML Functionalities. Computers, 11(6). https://doi.org/10.3390/computers11060097
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
Ghosh, B. (2023). The Rise of Small Language Models— Efficient & Customizable. Medium. https://bit.ly/47pZktn
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
Griffiths, D., Frías-Martínez, E., Tlili, A., & Burgos, D. (2024). A Cybernetic Perspective on Generative AI in Education: From Transmission to Coordination. International Journal of Interactive Multimedia and Artificial Intelligence, 8(5), 15-24. https://doi.org/10.9781/ijimai.2024.02.008
Grush, A. (2023, November 16). Bing Chat is now Microsoft Copilot: What's new and is it better than ChatGPT? Android Authority. https://d66z.short.gy/RqJxf3
Gupta, M., Akiri, C., Aryal, K., Parker, E., & Praharaj, L. (2023). From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy. IEEE Access, 11, 80218-80245. https://doi.org/10.1109/ACCESS.2023.3300381
Hannan, E., & Liu, S. (2023). AI: new source of competitiveness in higher education. Competitiveness Review: An International Business Journal, 33(2), 265-279. https://doi.org/10.1108/CR-03-2021-0045
Held, W., Harris, C., Best, M., & Yang, D. (2023). A Material Lens on Coloniality in NLP. arXiv, Article arXiv:2311.08391v1. https://doi.org/10.48550/arXiv.2311.08391
Hodges, C. B., & Kirschner, P. A. (2024). Innovation of Instructional Design and Assessment in the Age of Generative Artificial Intelligence. TechTrends, 68(1), 195-199. https://doi.org/10.1007/s11528-023-00926-x
Huang, A. Y. Q., Lu, O. H. T., & Yang, S. J. H. (2023). Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Computers & Education, 194, Article 104684. https://doi.org/10.1016/j.compedu.2022.104684
Hyun Baek, T., & Kim, M. (2023). Is ChatGPT scary good? How user motivations affect creepiness and trust in generative artificial intelligence. Telematics and Informatics, 83, Article 102030. https://doi.org/10.1016/j.tele.2023.102030
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
Kartal, G. (2023). Contemporary Language Teaching and Learning with ChatGPT. Contemporary Research in Language and Linguistics, 1(1), 59-70.
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
Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y.-S., Kay, J., Knight, S., Martinez-Maldonado, R., Sadiq, S., & Gašević, D. (2022). Explainable Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 3, Article 100074. https://doi.org/10.1016/j.caeai.2022.100074
Kranzberg, M. (1986). Technology and History: “Kranzberg's Laws”. Technology and Culture, 27(3), 544-560. https://doi.org/10.2307/3105385
Kurzweil, R. (2001, March 7, 2001). The Law of Accelerating Returns. The Kurzweil Library + collections. Tracking breakthroughs in tech, science, and world progress. https://bit.ly/45kyYrH
Leal Filho, W., Ribeiro, P. C. C., Mazutti, J., Lange Salvia, A., Bonato Marcolin, C., Lima Silva Borsatto, J. M., Sharifi, A., Sierra, J., Luetz, J., Pretorius, R., & Viera Trevisan, L. (2024). Using artificial intelligence to implement the UN sustainable development goals at higher education institutions. International Journal of Sustainable Development & World Ecology, In Press. https://doi.org/10.1080/13504509.2024.2327584
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
Li, J., Chen, J., Ren, R., Cheng, X., Zhao, W. X., Nie, J.-Y., & Wen, J.-R. (2024). The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models. arXiv, Article arXiv:2401.03205v1. https://doi.org/10.48550/arXiv.2401.03205
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
Llorens-Largo, F. (2019, 13/02). Las tecnologías en la educación: características deseables, efectos perversos. Universídad. https://bit.ly/3SxO72D
Llorens-Largo, F., & García-Peñalvo, F. J. (2023, 5 de diciembre). La inteligencia artificial en el gobierno universitario. Universídad. https://bit.ly/46SSxbG
Llorens-Largo, F., Vidal, J., & García-Peñalvo, F. J. (2023). Ya llegó, ya está aquí, y nadie puede esconderse: La inteligencia artificial generativa en educación. Aula Magna 2.0. https://bit.ly/3tcq5Uh
Long, D., & Magerko, B. (2020). What is AI Literacy? Competencies and Design Considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA, April 25 - 30, 2020) (pp. 1–16). Association for Computing Machinery. https://doi.org/10.1145/3313831.3376727
Lytras, M. D. (2023). An Integrated Transformative Learning Strategy at National Level: Bold Initiatives Toward Vision 2030 in Saudi Arabia. In M. D. Lytras (Ed.), Active and Transformative Learning in STEAM Disciplines (pp. 281-296). Emerald Publishing Limited. https://doi.org/10.1108/978-1-83753-618-420231014
Mahajan, V. (2023, October 13th). 100+ Incredible ChatGPT Statistics & Facts in 2024. https://bit.ly/48M9fdX
Marina, J. A. (2020). Proyecto Centauro. Ediciones KHAF.
Martínez-Arboleda, A. (2024). The Futures of Higher Education in the Age of Artificial Intelligence 3rd Online Debate on the Future of Education, Metropolitan College, Greece. https://d66z.short.gy/NWW7F5
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
McIntosh, T. R., Susnjak, T., Liu, T., Watters, P., & Halgamuge, M. N. (2023). From Google Gemini to OpenAI Q* (Q-Star): A Survey of Reshaping the Generative Artificial Intelligence (AI) Research Landscape. arXiv, Article arXiv:2312.10868v1. https://doi.org/10.48550/arXiv.2312.10868
Mustak, M., Salminen, J., Mäntymäki, M., Rahman, A., & Dwivedi, Y. K. (2023). Deepfakes: Deceptions, mitigations, and opportunities. Journal of Business Research, 154, Article 113368. https://doi.org/10.1016/j.jbusres.2022.113368
Nerantzi, C., Abegglen, S., Karatsiori, M., & Arboleda, A. M. (Eds.). (2023). 101 creative ideas to use AI in education, A crowdsourced collection. https://doi.org/10.5281/zenodo.8355454.
OpenAI. (2023a). GPT-4 Technical Report. arXiv, Article arXiv:2303.08774v4. https://doi.org/10.48550/arXiv.2303.08774
OpenAI. (2023b). GPT-4V(ision) System Card. OpenAI. https://bit.ly/3TOD21h
Patel, D., & Wong, G. (2023, July 10th). GPT-4 Architecture, Infrastructure, Training Dataset, Costs, Vision, MoE. Demystifying GPT-4: The engineering tradeoffs that led OpenAI to their architecture. https://bit.ly/3SbiU8r
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
Pearce, J., & Chiavaroli, N. (2023). Rethinking assessment in response to generative artificial intelligence. Medical Education, 57(10), 889-891. https://doi.org/10.1111/medu.15092
Pedreño Muñoz, A., González Gosálbez, R., Mora Illán, T., Pérez Fernández, E. d. M., Ruiz Sierra, J., & Torres Penalva, A. (2024). La inteligencia artificial en las universidades: Retos y oportunidades. Grupo 1 Million Bot. https://d66z.short.gy/izakDX
Pichai, S., & Hassabis, D. (2024). Our next-generation model: Gemini 1.5. AI. https://d66z.short.gy/cT19l1
Prem, E. (2023). From ethical AI frameworks to tools: a review of approaches. AI and Ethics, 3(3), 699-716. https://doi.org/10.1007/s43681-023-00258-9
Qin, L., Chen, Q., Zhou, Y., Chen, Z., Li, Y., Liao, L., Li, M., Che, W., & Yu, P. S. (2024). Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers. arXiv, Article arXiv:2404.04925v1. https://doi.org/10.48550/arXiv.2404.04925
Sabzalieva, E., & Valentini, A. (2023). ChatGPT and artificial intelligence in higher education: Quick start guide (ED/HE/IESALC/IP/2023/12). UNESCO and UNESCO International Institute for Higher Education in Latin America and the Caribbean (IESALC). https://bit.ly/3oeYm2f
Sadasivan, V. S., Kumar, A., Balasubramanian, S., Wang, W., & Feizi, S. (2024). Can AI-Generated Text be Reliably Detected? arXiv, Article arXiv:2303.11156v3. 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
Santana, C. (2023). Lo que OpenAI NO quería que supieras sobre GPT4 - (De los MoEs a Mixtral). https://bit.ly/3tK52Zk
Sarkar, S. (2023). AI Industry Analysis: 50 Most Visited AI Tools and Their 24B+ Traffic Behavior. Writerbuddy. https://bit.ly/3TUVtBK
Shen, S., Hou, L., Zhou, Y., Du, N., Longpre, S., Wei, J., Chung, H. W., Zoph, B., Fedus, W., Chen, X., Vu, T., Wu, Y., Chen, W., Webson, A., Li, Y., Zhao, V., Yu, H., Keutzer, K., Darrell, T., & Zhou, D. (2023). Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models. arXiv, Article arXiv:2305.14705v2. https://doi.org/10.48550/arXiv.2305.14705
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
Tyton Partners. (2023). GenAI in Higher Education: Fall 2023 update time for class study. Tyton Partners. https://d66z.short.gy/xdMnMZ
Vardi, G. (2023). On the Implicit Bias in Deep-Learning Algorithms. Communications of the ACM, 66(6), 86–93. https://doi.org/10.1145/3571070
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
Vázquez-Ingelmo, A., García-Peñalvo, F. J., & Therón, R. (2022). MetaViz – A graphical meta-model instantiator for generating information dashboards and visualizations. Journal of King Saud University - Computer and Information Sciences, 34(10), 9977-9990. https://doi.org/10.1016/j.jksuci.2022.09.015
Verma, G., Campbell, T., Melville, W., & Park, B.-Y. (2023). Navigating Opportunities and Challenges of Artificial Intelligence: ChatGPT and Generative Models in Science Teacher Education. Journal of Science Teacher Education, 34(8), 793-798. https://doi.org/10.1080/1046560X.2023.2263251
wael Al-khatib, A. (2023). Drivers of generative artificial intelligence to fostering exploitative and exploratory innovation: A TOE framework. Technology in Society, 75, Article 102403. https://doi.org/10.1016/j.techsoc.2023.102403
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
Yan, L., Martinez-Maldonado, R., & Gasevic, D. (2024). Generative Artificial Intelligence in Learning Analytics: Contextualising Opportunities and Challenges through the Learning Analytics Cycle. In LAK '24: Proceedings of the 14th Learning Analytics and Knowledge Conference (Kyoto Japan, March 18 - 22, 2024) (pp. 101–111). ACM. https://doi.org/10.1145/3636555.3636856
Yang, Z., Li, L., Lin, K., Wang, J., Lin, C.-C., Liu, Z., & Wang, L. (2023). The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision). arXiv, Article arXiv:2309.17421v2. https://doi.org/10.48550/arXiv.2309.17421
Zapata-Ros, M. (2023). Inteligencia Artificial y Educación ¿dónde estamos? RED. El aprendizaje en la Sociedad del Conocimiento. https://red.hypotheses.org/2607
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., Liu, P., Nie, J.-Y., & Wen, J.-R. (2023). A Survey of Large Language Models. arXiv, Article arXiv:2303.18223v13. https://doi.org/10.48550/arXiv.2303.18223
Zhong, X., & Zhan, Z. (2024). An intelligent tutoring system for programming education based on informative tutoring feedback: system development, algorithm design, and empirical study. Interactive Technology and Smart Education, In Press. https://doi.org/10.1108/ITSE-09-2023-0182
Alier, M., García-Peñalvo, F. J., & Camba, J. D. (2024). Generative Artificial Intelligence in Education: From Deceptive to Disruptive. International Journal of Interactive Multimedia and Artificial Intelligence, 8(5), 5-14. https://doi.org/10.9781/ijimai.2024.02.011
Álvarez, D. (2023). Inteligencia Artificial en Educación: Oportunidades y Desafíos para el Aula del s.XXI SIMO Educación 2023, Madrid, España. https://bit.ly/3QLGBlG
Amo-Filva, D., Fonseca, D., Vernet, D., Torres, E., Muñoz Pastor, P., Caballero, V., Fernandez, E., Alier, M., García-Peñalvo, F. J., García-Holgado, A., Llorens-Largo, F., Molina-Carmona, R., Conde, M. Á., & Hernández-García, Á. (2023). Usos y desusos del modelo GPT-3 entre estudiantes de grados de ingeniería. In J. A. Cruz Lemus, N. Medina Medina, & M. J. Rodríguez Fórtiz (Eds.), Actas de las XXIX Jornadas sobre la Enseñanza Universitaria de la Informática - JENUI 2023 (Granada, España, 5-7 de julio de 2023) (Vol. 8, pp. 415-418).
Aoun, J. E. (2018). Robot-Proof. Higher Education in the Age of Artificial Intelligence. The MIT Press.
Bandi, A., Adapa, P. V., & Kuchi, Y. E. (2023). The Power of Generative AI: A Review of Requirements, Models, Input–Output Formats, Evaluation Metrics, and Challenges. Future Internet, 15(8), Article 260. https://doi.org/10.3390/fi15080260
Bartlett, K. A., & Camba, J. D. (2024). Generative Artificial Intelligence in Product Design Education: Navigating Concerns of Originality and Ethics. International Journal of Interactive Multimedia and Artificial Intelligence, 8(5), 55-64. https://doi.org/10.9781/ijimai.2024.02.006
Berthelot, A., Jay, M., Lefevre, L., & Caron, E. (2023). Estimating the environmental impact of Generative-AI services using an LCA-based methodology. Portail INRIA.HAL.SCIENCE, Article hal-04346102. https://inria.hal.science/hal-04346102
Biderman, S., & Raff, E. (2022). Fooling MOSS Detection with Pretrained Language Models. In CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management (Atlanta, GA, USA, October 17 - 21, 2022) (pp. 2933–2943). ACM. https://doi.org/10.1145/3511808.3557079
Bozkurt, A. (2023). Generative artificial intelligence (AI) powered conversational educational agents: The inevitable paradigm shift. Asian Journal of Distance Education, 18(1), 198-204. https://doi.org/10.5281/zenodo.7716416
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., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., & Amodei, D. (2020). Language Models are Few-Shot Learners. arXiv, Article arXiv:2005.14165v4 https://doi.org/10.48550/arXiv.2005.14165
Casal-Otero, L., Catala, A., Fernández-Morante, C., Taboada, M., Cebreiro, B., & Barro, S. (2023). AI literacy in K-12: a systematic literature review. International Journal of STEM Education, 10(1), Article 29. https://doi.org/10.1186/s40594-023-00418-7
Chien, A. A., Lin, L., Nguyen, H., Rao, V., Sharma, T., & Wijayawardana, R. (2023). Reducing the Carbon Impact of Generative AI Inference (today and in 2035). In HotCarbon '23: Proceedings of the 2nd Workshop on Sustainable Computer Systems (Boston, MA, USA, 9 July 2023) (pp. Article 11). Association for Computing Machinery. https://doi.org/10.1145/3604930.3605705
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
Conde, M. Á., Rodríguez-Sedano, F. J., Fernández-Llamas, C., Gonçalves, J., Lima, J., & García-Peñalvo, F. J. (2021). Fostering STEAM through Challenge Based Learning, Robotics and Physical Devices: A systematic mapping literature review. Computer Application in Engineering Education, 29, 46-65. https://doi.org/10.1002/cae.22354
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. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228-239. 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 artificial intelligence (AI). Journal of University Teaching and Learning Practice, 20(3). https://doi.org/10.53761/1.20.3.02
de Souza Zanirato Maia, J., Arantes Bueno, A. P., & Sato, J. R. (2023). Applications of Artificial Intelligence Models in Educational Analytics and Decision Making: A Systematic Review. World, 4(2), 288-313. https://doi.org/10.3390/world4020019
Denny, P., Prather, J., Becker, B. A., Finnie-Ansley, J., Hellas, A., Leinonen, J., Luxton-Reilly, A., Reeves, B. N., Santos, E. A., & Sarsa, S. (2024). Computing Education in the Era of Generative AI. Communications of the ACM, 67(2), 56–67. https://doi.org/10.1145/3624720
Duarte, F. (2024, March 27th). Number of ChatGPT Users (Apr 2024). https://bit.ly/3NWOEvH
Evans, O., Wale-Awe, O. I., Emeka, O., Ayoola, O. O., Alenoghena, R., & Adeniji, S. (2023). ChatGPT impacts on access-efficiency, employment, education and ethics: The socio-economics of an AI language model. Bizecons Quarterly, 16. https://d66z.short.gy/23XlQI
Fernández Enguita, M. (2024). Inteligencia aumentada y avanzada para aprender y enseñar. Cuadernos de Pedagogía(549).
Flores-Vivar, J. M., & García-Peñalvo, F. J. (2023). 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
Fonseca-Escudero, D., García-Peñalvo, F. J., Llorens-Largo, F., & Molina-Carmona, R. (2023, 18-20 de octubre de 2023). ¡Qué viene la IA! ¿Estoy preparada/o? VII Congreso Internacional sobre Innovación, Aprendizaje y Cooperación, CINAIC 2023, Universidad Politécnica de Madrid, Madrid, España. https://doi.org/10.5281/zenodo.10050857
Gallent-Torres, C., & Comas-Forgas, R. (2024). La llama de Prometeo: IA e integridad académica. Cuadernos de Pedagogía(549).
García San Martín, M. J. (2024). ¿Qué lugar ocupa la IA en las competencias digitales de los docentes? Cuadernos de Pedagogía(549).
García-Peñalvo, F. J. (2018). Ecosistemas tecnológicos universitarios. In J. Gómez (Ed.), UNIVERSITIC 2017. Análisis de las TIC en las Universidades Españolas (pp. 164-170). Crue Universidades Españolas.
García-Peñalvo, F. J. (2023a, 18-20 de octubre). Discusión abierta sobre beneficios, riesgos y retos de la Inteligencia Artificial Generativa VII Edición del Congreso Internacional sobre Innovación, Aprendizaje y Cooperación, CINAIC 2023, Universidad Politécnica de Madrid, Madrid, España. https://doi.org/10.5281/zenodo.10029703
García-Peñalvo, F. J. (2023b, 4 de diciembre). La era de la inteligencia artificial generativa en educación 4º Congreso de Educación, Innovación, Normalismo y Neuroeducación (CEINN 2023), Ciudad de México, México. https://doi.org/10.5281/zenodo.10255745
García-Peñalvo, F. J. (2023c). 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. (2023d). Using ChatGPT for discovering conceptual classes in object-oriented modeling. In C. Nerantzi, S. Abegglen, M. Karatsiori, & A. M. Arboleda (Eds.), 101 creative ideas to use AI in education, A crowdsourced collection. https://bit.ly/48D87dq
García-Peñalvo, F. J. (2024a). Cómo afecta la inteligencia artificial generativa a los procesos de evaluación. Cuadernos de Pedagogía(549).
García-Peñalvo, F. J. (2024b, 13 de marzo). Escenarios de innovación educativa con Inteligencia Artificial Generativa XIII Jornadas de Innovación Docente de la UNED, Facultad de Educación de la UNED, Madrid, España. https://doi.org/10.5281/zenodo.10808874
García-Peñalvo, F. J. (2024c, 24 January). Generative Artificial Intelligence in Higher Education: A 360° Perspective IFE Conference Special Event; Artificial Intelligence in Education Summit, Tecnológico de Monterrey, Monterrey, México. https://doi.org/10.5281/zenodo.10499828
García-Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2024). The new reality of education in the face of advances in generative artificial intelligence. RIED: revista iberoamericana de educación a distancia, 27(1), 9–39. https://doi.org/10.5944/ried.27.1.37716
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, 8(4), 7-16. https://doi.org/10.9781/ijimai.2023.07.006
Garmpis, S., Maragoudakis, M., & Garmpis, A. (2022). Assisting Educational Analytics with AutoML Functionalities. Computers, 11(6). https://doi.org/10.3390/computers11060097
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
Ghosh, B. (2023). The Rise of Small Language Models— Efficient & Customizable. Medium. https://bit.ly/47pZktn
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
Griffiths, D., Frías-Martínez, E., Tlili, A., & Burgos, D. (2024). A Cybernetic Perspective on Generative AI in Education: From Transmission to Coordination. International Journal of Interactive Multimedia and Artificial Intelligence, 8(5), 15-24. https://doi.org/10.9781/ijimai.2024.02.008
Grush, A. (2023, November 16). Bing Chat is now Microsoft Copilot: What's new and is it better than ChatGPT? Android Authority. https://d66z.short.gy/RqJxf3
Gupta, M., Akiri, C., Aryal, K., Parker, E., & Praharaj, L. (2023). From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy. IEEE Access, 11, 80218-80245. https://doi.org/10.1109/ACCESS.2023.3300381
Hannan, E., & Liu, S. (2023). AI: new source of competitiveness in higher education. Competitiveness Review: An International Business Journal, 33(2), 265-279. https://doi.org/10.1108/CR-03-2021-0045
Held, W., Harris, C., Best, M., & Yang, D. (2023). A Material Lens on Coloniality in NLP. arXiv, Article arXiv:2311.08391v1. https://doi.org/10.48550/arXiv.2311.08391
Hodges, C. B., & Kirschner, P. A. (2024). Innovation of Instructional Design and Assessment in the Age of Generative Artificial Intelligence. TechTrends, 68(1), 195-199. https://doi.org/10.1007/s11528-023-00926-x
Huang, A. Y. Q., Lu, O. H. T., & Yang, S. J. H. (2023). Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Computers & Education, 194, Article 104684. https://doi.org/10.1016/j.compedu.2022.104684
Hyun Baek, T., & Kim, M. (2023). Is ChatGPT scary good? How user motivations affect creepiness and trust in generative artificial intelligence. Telematics and Informatics, 83, Article 102030. https://doi.org/10.1016/j.tele.2023.102030
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
Kartal, G. (2023). Contemporary Language Teaching and Learning with ChatGPT. Contemporary Research in Language and Linguistics, 1(1), 59-70.
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
Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y.-S., Kay, J., Knight, S., Martinez-Maldonado, R., Sadiq, S., & Gašević, D. (2022). Explainable Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 3, Article 100074. https://doi.org/10.1016/j.caeai.2022.100074
Kranzberg, M. (1986). Technology and History: “Kranzberg's Laws”. Technology and Culture, 27(3), 544-560. https://doi.org/10.2307/3105385
Kurzweil, R. (2001, March 7, 2001). The Law of Accelerating Returns. The Kurzweil Library + collections. Tracking breakthroughs in tech, science, and world progress. https://bit.ly/45kyYrH
Leal Filho, W., Ribeiro, P. C. C., Mazutti, J., Lange Salvia, A., Bonato Marcolin, C., Lima Silva Borsatto, J. M., Sharifi, A., Sierra, J., Luetz, J., Pretorius, R., & Viera Trevisan, L. (2024). Using artificial intelligence to implement the UN sustainable development goals at higher education institutions. International Journal of Sustainable Development & World Ecology, In Press. https://doi.org/10.1080/13504509.2024.2327584
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
Li, J., Chen, J., Ren, R., Cheng, X., Zhao, W. X., Nie, J.-Y., & Wen, J.-R. (2024). The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models. arXiv, Article arXiv:2401.03205v1. https://doi.org/10.48550/arXiv.2401.03205
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
Llorens-Largo, F. (2019, 13/02). Las tecnologías en la educación: características deseables, efectos perversos. Universídad. https://bit.ly/3SxO72D
Llorens-Largo, F., & García-Peñalvo, F. J. (2023, 5 de diciembre). La inteligencia artificial en el gobierno universitario. Universídad. https://bit.ly/46SSxbG
Llorens-Largo, F., Vidal, J., & García-Peñalvo, F. J. (2023). Ya llegó, ya está aquí, y nadie puede esconderse: La inteligencia artificial generativa en educación. Aula Magna 2.0. https://bit.ly/3tcq5Uh
Long, D., & Magerko, B. (2020). What is AI Literacy? Competencies and Design Considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA, April 25 - 30, 2020) (pp. 1–16). Association for Computing Machinery. https://doi.org/10.1145/3313831.3376727
Lytras, M. D. (2023). An Integrated Transformative Learning Strategy at National Level: Bold Initiatives Toward Vision 2030 in Saudi Arabia. In M. D. Lytras (Ed.), Active and Transformative Learning in STEAM Disciplines (pp. 281-296). Emerald Publishing Limited. https://doi.org/10.1108/978-1-83753-618-420231014
Mahajan, V. (2023, October 13th). 100+ Incredible ChatGPT Statistics & Facts in 2024. https://bit.ly/48M9fdX
Marina, J. A. (2020). Proyecto Centauro. Ediciones KHAF.
Martínez-Arboleda, A. (2024). The Futures of Higher Education in the Age of Artificial Intelligence 3rd Online Debate on the Future of Education, Metropolitan College, Greece. https://d66z.short.gy/NWW7F5
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
McIntosh, T. R., Susnjak, T., Liu, T., Watters, P., & Halgamuge, M. N. (2023). From Google Gemini to OpenAI Q* (Q-Star): A Survey of Reshaping the Generative Artificial Intelligence (AI) Research Landscape. arXiv, Article arXiv:2312.10868v1. https://doi.org/10.48550/arXiv.2312.10868
Mustak, M., Salminen, J., Mäntymäki, M., Rahman, A., & Dwivedi, Y. K. (2023). Deepfakes: Deceptions, mitigations, and opportunities. Journal of Business Research, 154, Article 113368. https://doi.org/10.1016/j.jbusres.2022.113368
Nerantzi, C., Abegglen, S., Karatsiori, M., & Arboleda, A. M. (Eds.). (2023). 101 creative ideas to use AI in education, A crowdsourced collection. https://doi.org/10.5281/zenodo.8355454.
OpenAI. (2023a). GPT-4 Technical Report. arXiv, Article arXiv:2303.08774v4. https://doi.org/10.48550/arXiv.2303.08774
OpenAI. (2023b). GPT-4V(ision) System Card. OpenAI. https://bit.ly/3TOD21h
Patel, D., & Wong, G. (2023, July 10th). GPT-4 Architecture, Infrastructure, Training Dataset, Costs, Vision, MoE. Demystifying GPT-4: The engineering tradeoffs that led OpenAI to their architecture. https://bit.ly/3SbiU8r
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
Pearce, J., & Chiavaroli, N. (2023). Rethinking assessment in response to generative artificial intelligence. Medical Education, 57(10), 889-891. https://doi.org/10.1111/medu.15092
Pedreño Muñoz, A., González Gosálbez, R., Mora Illán, T., Pérez Fernández, E. d. M., Ruiz Sierra, J., & Torres Penalva, A. (2024). La inteligencia artificial en las universidades: Retos y oportunidades. Grupo 1 Million Bot. https://d66z.short.gy/izakDX
Pichai, S., & Hassabis, D. (2024). Our next-generation model: Gemini 1.5. AI. https://d66z.short.gy/cT19l1
Prem, E. (2023). From ethical AI frameworks to tools: a review of approaches. AI and Ethics, 3(3), 699-716. https://doi.org/10.1007/s43681-023-00258-9
Qin, L., Chen, Q., Zhou, Y., Chen, Z., Li, Y., Liao, L., Li, M., Che, W., & Yu, P. S. (2024). Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers. arXiv, Article arXiv:2404.04925v1. https://doi.org/10.48550/arXiv.2404.04925
Sabzalieva, E., & Valentini, A. (2023). ChatGPT and artificial intelligence in higher education: Quick start guide (ED/HE/IESALC/IP/2023/12). UNESCO and UNESCO International Institute for Higher Education in Latin America and the Caribbean (IESALC). https://bit.ly/3oeYm2f
Sadasivan, V. S., Kumar, A., Balasubramanian, S., Wang, W., & Feizi, S. (2024). Can AI-Generated Text be Reliably Detected? arXiv, Article arXiv:2303.11156v3. 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
Santana, C. (2023). Lo que OpenAI NO quería que supieras sobre GPT4 - (De los MoEs a Mixtral). https://bit.ly/3tK52Zk
Sarkar, S. (2023). AI Industry Analysis: 50 Most Visited AI Tools and Their 24B+ Traffic Behavior. Writerbuddy. https://bit.ly/3TUVtBK
Shen, S., Hou, L., Zhou, Y., Du, N., Longpre, S., Wei, J., Chung, H. W., Zoph, B., Fedus, W., Chen, X., Vu, T., Wu, Y., Chen, W., Webson, A., Li, Y., Zhao, V., Yu, H., Keutzer, K., Darrell, T., & Zhou, D. (2023). Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models. arXiv, Article arXiv:2305.14705v2. https://doi.org/10.48550/arXiv.2305.14705
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
Tyton Partners. (2023). GenAI in Higher Education: Fall 2023 update time for class study. Tyton Partners. https://d66z.short.gy/xdMnMZ
Vardi, G. (2023). On the Implicit Bias in Deep-Learning Algorithms. Communications of the ACM, 66(6), 86–93. https://doi.org/10.1145/3571070
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
Vázquez-Ingelmo, A., García-Peñalvo, F. J., & Therón, R. (2022). MetaViz – A graphical meta-model instantiator for generating information dashboards and visualizations. Journal of King Saud University - Computer and Information Sciences, 34(10), 9977-9990. https://doi.org/10.1016/j.jksuci.2022.09.015
Verma, G., Campbell, T., Melville, W., & Park, B.-Y. (2023). Navigating Opportunities and Challenges of Artificial Intelligence: ChatGPT and Generative Models in Science Teacher Education. Journal of Science Teacher Education, 34(8), 793-798. https://doi.org/10.1080/1046560X.2023.2263251
wael Al-khatib, A. (2023). Drivers of generative artificial intelligence to fostering exploitative and exploratory innovation: A TOE framework. Technology in Society, 75, Article 102403. https://doi.org/10.1016/j.techsoc.2023.102403
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
Yan, L., Martinez-Maldonado, R., & Gasevic, D. (2024). Generative Artificial Intelligence in Learning Analytics: Contextualising Opportunities and Challenges through the Learning Analytics Cycle. In LAK '24: Proceedings of the 14th Learning Analytics and Knowledge Conference (Kyoto Japan, March 18 - 22, 2024) (pp. 101–111). ACM. https://doi.org/10.1145/3636555.3636856
Yang, Z., Li, L., Lin, K., Wang, J., Lin, C.-C., Liu, Z., & Wang, L. (2023). The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision). arXiv, Article arXiv:2309.17421v2. https://doi.org/10.48550/arXiv.2309.17421
Zapata-Ros, M. (2023). Inteligencia Artificial y Educación ¿dónde estamos? RED. El aprendizaje en la Sociedad del Conocimiento. https://red.hypotheses.org/2607
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., Liu, P., Nie, J.-Y., & Wen, J.-R. (2023). A Survey of Large Language Models. arXiv, Article arXiv:2303.18223v13. https://doi.org/10.48550/arXiv.2303.18223
Zhong, X., & Zhan, Z. (2024). An intelligent tutoring system for programming education based on informative tutoring feedback: system development, algorithm design, and empirical study. Interactive Technology and Smart Education, In Press. https://doi.org/10.1108/ITSE-09-2023-0182
García-Peñalvo, F. J. (2024). Inteligencia artificial generativa y educación: Un análisis desde múltiples perspectivas. Education in the Knowledge Society (EKS), 25, e31942. https://doi.org/10.14201/eks.31942
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