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Generative artificial intelligence in education: From deceptive to disruptive

  • Marc Alier [1] Árbol académico ; Francisco José García-Peñalvo [2] Árbol académico ; Jorge D. Camba [3]
    1. [1] Universitat Politècnica de Catalunya

      Universitat Politècnica de Catalunya

      Barcelona, España

    2. [2] Universidad de Salamanca

      Universidad de Salamanca

      Salamanca, España

    3. [3] Purdue University

      Purdue University

      Township of Wabash, Estados Unidos

    Mostrar afiliaciones +
  • Localización: IJIMAI, ISSN-e 1989-1660, Vol. 8, Nº. 5, 2024, págs. 5-14
  • Idioma: inglés
  • DOI: 10.9781/ijimai.2024.02.011
  • Enlaces
  • Resumen

    • Generative Artificial Intelligence (GenAI) has emerged as a promising technology that can create original content, such as text, images, and sound. The use of GenAI in educational settings is becoming increasingly popular and offers a range of opportunities and challenges. This special issue explores the management and integration of GenAI in educational settings, including the ethical considerations, best practices, and opportunities. The potential of GenAI in education is vast. By using algorithms and data, GenAI can create original content that can be used to augment traditional teaching methods, creating a more interactive and personalized learning experience. In addition, GenAI can be utilized as an assessment tool and for providing feedback to students using generated content. For instance, it can be used to create custom quizzes, generate essay prompts, or even grade essays. The use of GenAI as an assessment tool can reduce the workload of teachers and help students receive prompt feedback on their work. Incorporating GenAI in educational settings also poses challenges related to academic integrity. With availability of GenAI models, students can use them to study or complete their homework assignments, which can raise concerns about the authenticity and authorship of the delivered work. Therefore, it is important to ensure that academic standards are maintained, and the originality of the student's work is preserved. This issue highlights the need for implementing ethical practices in the use of GenAI models and ensuring that the technology is used to support and not replace the student's learning experience

  • Referencias bibliográficas
    • V. Mahajan, “100+ Incredible ChatGPT Statistics & Facts in 2024,” 2023. [Online]. https://bit.ly/48M9fdX
    • P. H. Diamandis and S. Kotler, Abundance: The Future Is Better Than You Think (Exponential Technology Series). The Free Press, 2012.
    • F. J. García-Peñalvo and A. Vázquez-Ingelmo, “What do we mean by GenAI? A systematic mapping of the evolution, trends, and techniques involved...
    • R. R. Schaller, “Moore’s law: past, present, and future,” IEEE Spectrum, vol. 34, no. 6, pp. 52-59, 1997, doi: 10.1109/6.591665.
    • F. Rosenblatt, “The perceptron: A probabilistic model for information storage and organization in the brain,” Psychological Review, vol. 65,...
    • Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature, vol. 521, no. 7553, pp. 436-444, 2015, doi: 10.1038/nature14539.
    • A. Vaswani et al., “Attention is all you need,” in Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information...
    • D. Peral-García, J. Cruz-Benito, and F. J. García-Peñalvo, “Systematic literature review: Quantum machine learning and its applications,”...
    • W. X. Zhao et al., “A Survey of Large Language Models,” arXiv, 2023, Art no. arXiv:2303.18223v13, doi: 10.48550/arXiv.2303.18223. Y. Chang...
    • Z. Yang et al., “The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision),” arXiv, 2023, Art no. arXiv:2309.17421v2, doi: 10.48550/arXiv.2309.17421.
    • OpenAI, “GPT-4V(ision) System Card,” OpenAI, USA, 2023. [Online]. Available: https://bit.ly/3TOD21h
    • S. Yin, S. Bai, J. Huang, X. Chen, and Y. Zhang, “A Survey on Multimodal Large Language Models,” arXiv, 2023, Art no. arXiv:2306.13549v1,...
    • S. Bubeck et al., “Sparks of Artificial General Intelligence: Early experiments with GPT-4,” arXiv, 2023, Art no. arXiv:2303.12712v5, doi:...
    • V. Elliott, “Generative AI Learned Nothing From Web 2.0,” Wired, December 28, 2023. [Online]. Available: https://d66z.short.gy/BZ57XL
    • J. M. Flores-Vivar and F. J. García-Peñalvo, “Reflections on the ethics, potential, and challenges of artificial intelligence in the framework...
    • S. Altman, G. Brockman, and I. Sutskever, “Governance of superintelligence,” In: OpenAI, 2023. Available from: https://bit.ly/3q6NFjv.
    • F. A. Croitoru, V. Hondru, R. T. Ionescu, and M. Shah, “Diffusion Models in Vision: A Survey,” IEEE Transactions on Pattern Analysis and Machine...
    • T. B. Brown et al., “Language Models are Few-Shot Learners,” arXiv, 2020, Art no. arXiv:2005.14165v4 doi: 10.48550/arXiv.2005.14165.
    • OpenAI, “GPT-4 Technical Report,” arXiv, 2023, Art no. arXiv:2303.08774v4, doi: 10.48550/arXiv.2303.08774.
    • D. Patel and G. Wong, “GPT-4 Architecture, Infrastructure, Training Dataset, Costs, Vision, MoE. Demystifying GPT-4: The engineering tradeoffs...
    • T. Harris, “AI and The Future of Life,” 2023. [Online]. https://d66z.short.gy/LhQinU
    • C. Fourrier, “2023, year of open LLMs,” In: Hugging Face, 2023. [Online]. Available from: https://d66z.short.gy/vcHitF.
    • S. R.Bowman, “Eight Things to Know about Large Language Models,”arXiv, 2023, Art no. arXiv:2304.00612v1 doi: 10.48550/arXiv.2304.00612.
    • A. Radford, K. Narasimhan, T. Salimans, and I. Sutskever, “Improving Language Understanding by Generative Pre-Training,” OpenAI, USA, 2018....
    • A. Radford, J. Wu, R. Child, D. Luan, D. Amodei, and I. Sutskever, “Language Models are Unsupervised Multitask Learners,” OpenAI, USA, 2019....
    • J. Sevilla, L. Heim, A. Ho, T. Besiroglu, M. Hobbhahn, and P. Villalobos, “Compute Trends Across Three Eras of Machine Learning,” in 2022...
    • J. Wei et al., “Chain-of-Thought Prompting Elicits Reasoning in Large Language Models,” arXiv, 2023, Art no. arXiv:2201.11903v6, doi: 10.48550/arXiv.2201.11903.
    • M. Nye et al., “Show Your Work: Scratchpads for Intermediate Computation with Language Models,” arXiv, 2021, Art no. arXiv:2112.00114v1, doi:10.48550/arXiv.2112.00114.
    • J. Wei et al., “Emergent Abilities of Large Language Models,” arXiv, 2022, Art no. arXiv:2206.07682v2 doi: 10.48550/arXiv.2206.07682.
    • T. Kojima, S. S. Gu, M. Reid, Y. Matsuo, and Y. Iwasawa, “Large Language Models are Zero-Shot Reasoners,” arXiv, 2023, Art no. arXiv:2205.11916v4...
    • J. Zhou et al., “Instruction-Following Evaluation for Large Language Models,” arXiv, 2023, Art no. arXiv:2311.07911v1, doi: 10.48550/arXiv.2311.07911.
    • A. Srivastava et al., “Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models,” arXiv, 2023, Art no....
    • M. Abdou, A. Kulmizev, D. Hershcovich, S. Frank, E. Pavlick, and A. Søgaard, “Can Language Models Encode Perceptual Structure Without Grounding?...
    • J. Andreas, “Language Models as Agent Models,” in Findings of the Association for Computational Linguistics: EMNLP 2022, Y. Goldberg, Z. Kozareva,...
    • B. Z. Li, M. Nye, and J. Andreas, “Implicit Representations of Meaning in Neural Language Models,” arXiv, 2021, Art no. arXiv:2106.00737v1...
    • H. Levesque, E. Davis, L. Morgenstern, and T. i. c. o. t. p. o. k. r. a. reasoning., “The winograd schema challenge,” in Proceedings of the...
    • J. Hoffmann et al., “Training Compute-Optimal Large Language Models,”arXiv, 2022, Art no. arXiv:2203.15556v1, doi: 10.48550/arXiv.2203.15556.
    • R. Taori et al., “Alpaca: A Strong, Replicable Instruction-Following Model,” Stanford University, USA, 2023. [Online]. Available: https://bit.ly/444TrRx
    • H. Touvron et al., “LLaMA: Open and Efficient Foundation Language Models,” arXiv, 2023, Art no. arXiv:2302.13971v1, doi: 10.48550/arXiv.2302.13971.
    • S. Willinson, “Stanford Alpaca, and the Acceleration of On-Device Large Language Model Development,” In: Simon Willinson’s Blog, 2023. [Online]....
    • L. Zheng et al., “Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena,” arXiv, 2023, Art no. arXiv:2306.05685v4 doi: 10.48550/arXiv.2306.05685.
    • S. Pichai and D. Hassabis, “Our next-generation model: Gemini 1.5,” In: AI. 2024. [Online]. Available from: https://d66z.short.gy/cT19l1.
    • E. J. Hu et al., “LoRA: Low-Rank Adaptation of Large Language Models,”arXiv, 2021, Art no. arXiv:2106.09685v2, doi: 10.48550/arXiv.2106.09685.
    • T. Wang, J. Zhao, and W. V. Eaton, “LoRA Land: Fine-Tuned Open-Source LLMs that Outperform GPT-4,” In: Predibase, 2024. [Online]. Available...
    • N. Stephenson, The Diamond Age: Or, A Young Lady’s Illustrated Primer. Bantam Books, 1995.
    • N. Stephenson, Snowcrash. Bantam Books, 1992.
    • B. Srinivasan, The Network State: How To Start a New Country. USA: Amazon Kindle, 2022.
    • P. H. Diamandis and S. Kotler, The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and...
    • F. J. García-Peñalvo and J. García Carrasco, “Educational hypermedia resources facilitator,” Computers & Education, vol. 44, no. 3, pp....
    • F. J. García-Peñalvo and A. M. Seoane-Pardo, “An updated review of the concept of eLearning. Tenth anniversary,” Education in the Knowledge...
    • M. Sharples, M. Milrad, I. Arnedillo, and G. Vavoula, “Mobile Learning: Small devices, Big Issues,” in Technology Enhanced Learning: Principles...
    • C. J. Villagrá-Arnedo, F. J. Gallego-Durán, F. Llorens-Largo, R. SatorreCuerda, P. Compañ-Rosique, and R. Molina-Carmona, “Time-Dependent...
    • S. C. Cifuentes, S. G. García, M. P. Andrés-Sebastiá, J. D. Camba, and M. Contero, “Augmented Reality Experiences in Therapeutic Pedagogy:...
    • T. A. Urdan and C. C. Weggen, Corporate e-learning: Exploring a new frontier. San Francisco, USA: WR Hambrecht, 2000.
    • A. Anand and S. A. C. S. S. Eswaran, “A survey of open source learning management systems,” Annals: Computer Science Series, vol. 16, no....
    • C. López, F. García-Peñalvo, and P. Pernías, “Desarrollo de Repositorios de Objetos de Aprendizaje a través de la Reutilización de los Metadatos...
    • L. Castañeda and N. Selwyn, “More than tools? Making sense of the ongoing digitizations of higher education,” International Journal of Educational...
    • N. Selwyn, “Minding our language: why education and technology is full of bullshit … and what might be done about it†,” Learning, Media and...
    • A. Bartolomé, L. Castañeda, and J. Adell, “Personalisation in educational technology: the absence of underlying pedagogies,” International...
    • S. Papert, “Information Technology and Education: Computer Criticism vs. Technocentric Thinking,” Educational Researcher, vol. 16, no. 1,...
    • A. M. Seoane-Pardo, “Formalización de un modelo de formación online basado en el factor humano y la presencia docente mediante un lenguaje...
    • J. de Souza Zanirato Maia, A. P. Arantes Bueno, and J. R. Sato, “Applications of Artificial Intelligence Models in Educational Analytics and...
    • D. Amo-Filva, D. Fonseca, F. J. García-Peñalvo, M. Alier-Forment, and M. J. Casany-Guerrero, “Learning Analytics’ Privacy in the Fog and Edge...
    • D. Shin, “Embodying algorithms, enactive artificial intelligence and the extended cognition: You can see as much as you know about algorithm,”Journal...
    • T. Wang and E. C. K. Cheng, “An investigation of barriers to Hong Kong K-12 schools incorporating Artificial Intelligence in education,” Computers...
    • M. Alier-Forment and F. Llorens-Largo, “Cabalga el Cometa,” in EP31 Las Alucinaciones de ChatGPT con Faraón Llorens, 2023. [Online]. https://bit.ly/3ZCNBVT
    • F. J. García-Peñalvo, F. Llorens-Largo, and J. Vidal, “The new reality of education in the face of advances in generative artificial intelligence,”...
    • F. J. García-Peñalvo, “The perception of Artificial Intelligence in educational contexts after the launch of ChatGPT: Disruption or Panic?,”Education...
    • A. Bahrini et al., “ChatGPT: Applications, Opportunities, and Threats,” arXiv, 2023, Art no. arXiv:2304.09103v1, doi: 10.48550/arXiv.2304.09103.
    • J. Crawford, M. Cowling, and K. A. Allen, “Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial...
    • L. Henrickson and A. Meroño-Peñuela, “Prompting meaning: a hermeneutic approach to optimising prompt engineering with ChatGPT,” AI & SOCIETY,...
    • A. Nazir and Z. Wang, “A comprehensive survey of ChatGPT: Advancements, applications, prospects, and challenges,” Meta-Radiology, vol. 1,...
    • H. H. Thorp, “ChatGPT is fun, but not an author,” Science, vol. 379, no. 6630, p. 313, 2023, doi: 10.1126/science.adg7879.
    • Y. K. Dwivedi et al., ““So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative...
    • A. Iskender, “Holy or Unholy? Interview with Open AI’s ChatGPT,” European Journal of Tourism Research, vol. 34, 2023, Art no. 3414, doi: 10.54055/ejtr.v34i.3169.
    • E. P. H. Choi, J. J. Lee, M. H. Ho, J. Y. Y. Kwok, and K. Y. W. Lok, “Chatting or cheating? The impacts of ChatGPT and other artificial intelligence...
    • D. Gašević, G. Siemens, and S. Sadiq, “Empowering learners for the age of artificial intelligence,” Computers and Education: Artificial Intelligence,...
    • D. R. E. Cotton, P. A. Cotton, and J. R. Shipway, “Chatting and cheating: Ensuring academic integrity in the era of ChatGPT,” Innovations...
    • H. Lee, “The rise of ChatGPT: Exploring its potential in medical education,” Anatomical Sciences Education, vol. In Press, 2023, doi: 10.1002/ase.2270.
    • OpenAI, “Privacy policy” In: OpenAI, 2023. [Online]. Available from: https://d66z.short.gy/XyWACh.
    • F. Llorens-Largo and F. J. García-Peñalvo, “La inteligencia artificial en el gobierno universitario,” In: Universídad, 2023. [Online]. Available...
    • W. M. Lim, A. Gunasekara, J. L. Pallant, J. I. Pallant, and E. Pechenkina, “Generative AI and the future of education: Ragnarök or reformation?...
    • T. Wang, Y. Zhang, S. Qi, R. Zhao, Z. Xia, and J. Weng, “Security and Privacy on Generative Data in AIGC: A Survey,” arXiv, 2023, Art no....
    • M. Alier, M. J. Casañ Guerrero, D. Amo, C. Severance, and D. Fonseca, “Privacy and E-Learning: A Pending Task,” Sustainability, vol. 13, no....
    • E. Sabzalieva and A. Valentini, “ChatGPT and artificial intelligence in higher education: Quick start guide,” UNESCO and UNESCO International...
    • F. Llorens-Largo, J. Vidal, and F. J. García-Peñalvo, “Ya llegó, ya está aquí, y nadie puede esconderse: La inteligencia artificial generativa...
    • V. S. Sadasivan, A. Kumar, S. Balasubramanian, W. Wang, and S. Feizi, “Can AI-Generated Text be Reliably Detected?,” arXiv, 2024, Art no....
    • R. Topinka, “The software says my student cheated using AI. They say they’re innocent. Who do I believe?,” The Guardian, February 13th. [Online]....
    • F. J. García-Peñalvo, “Cómo afecta la inteligencia artificial generativa a los procesos de evaluación,” Cuadernos de Pedagogía, no. 549, 2024.
    • UNESCO, “Recommendation on the Ethics of Artificial Intelligence,” UNESCO, Paris, France, 2022. [Online]. Available: https://bit.ly/40MCNna
    • Y. Hu et al., “Artificial Intelligence Security: Threats and Countermeasures,” ACM Computing Surveys, vol. 55, no. 1, 2021, doi: 10.1145/3487890.
    • S. Khan, “How AI could save (not destroy) education,” In: TED2023, 2023. [Online]. Available from: https://d66z.short.gy/gp6isK.
    • M. Alier, M. J. Casañ, and D. Amo, “Smart Learning Applications: Leveraging LLMs for Contextualized and Ethical Educational Technology,” in...
    • M. Fernández Enguita, “Inteligencia aumentada y avanzada para aprender y enseñar,” Cuadernos de Pedagogía, no. 549, 2024.
    • A. García-Holgado, S. Marcos-Pablos, and F. J. García-Peñalvo, “Guidelines for performing Systematic Research Projects Reviews,” International...
    • F. J. García-Peñalvo, “Developing robust state-of-the-art reports: Systematic Literature Reviews,” Education in the Knowledge Society, vol....
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