EduRag
Una proposta per usare l’intelligenza artificiale in ambito educativo
DOI:
https://doi.org/10.4454/graphos.112Keywords:
LLMs, RAG, Artificial intelligence, Prompt engineering, EduRagAbstract
This article explores the relationship between artificial intelligence and education, focusing on Large Language Models and the opportunities and challenges these tools present. After analysing the architectures that have enabled their success, such as the Transformer, the issues related to the transparency and reliability of the generated responses are examined, with particular attention to the phenomenon of model "hallucinations." Strategies to mitigate these challenges, such as Chain of Thought and Retrieval-Augmented Generation, are then illustrated, which improve the transparency and reliability of LLMs. The EduRag project represents a practical application of these strategies, demonstrating how AI can be effectively used in the educational field to support learning and promote the use of reliable sources. Finally, possible future scenarios are outlined in which AI will play a central role in education, with increasingly personalized, interactive, and multimodal tools capable of enhancing the educational experience through deeper integration with language, writing, and other forms of human interaction.
References
Beard, G. M. (1881). American Nervousness.
Carr, N. (2011). Internet ci rende stupidi? Come la rete sta cambiando il nostro cervello. Raffaello Cortina (ed. or. 2010).
Chen, Y., Fu, Q., Yuan, Y., Wen, Z., Fan, G., Liu, D., Zhang, D., Li, Z., & Xiao, Y. (2023). Hallucination Detection: Robustly Discerning Reliable Answers in Large Language Models. Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 245–255. CIKM ’23: The 32nd ACM International Conference on Information and Knowledge Management. https://doi.org/10.1145/3583780.3614905
Giliberto, J. (2013, settembre 17). Storia. Quando la paura del treno scatena rivolte e sabotaggi. È il 1830. Correnti. https://jacopogiliberto.blog.ilsole24ore.com/2013/09/17/tav-quando-la-paura-del-treno-scatena-rivolte-sabotaggi/
Gori, M. (2003). Introduzione alle reti neurali artificiali. Mondo digitale, 2(8), 4–20.
Howard, R. (Regista). (2002, gennaio 4). A Beautiful Mind [Bi-ography, Drama, Mystery]. Universal Pictures, Dreamworks Pic-tures, Imagine Entertainment.
Johnson, J., Douze, M., & Jégou, H. (2017). Billion-scale similarity search with GPUs (arXiv:1702.08734). arXiv. https://doi.org/10.48550/arXiv.1702.08734
LangChain. (2024, settembre 15). https://www.langchain.com/
Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W., Rocktäschel, T., Riedel, S., & Kiela, D. (2021). Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (arXiv:2005.11401). arXiv. https://doi.org/10.48550/arXiv.2005.11401
McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (1955). A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine, 27(4), 12–12.
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient Es-timation of Word Representations in Vector Space (arXiv:1301.3781). arXiv. https://doi.org/10.48550/arXiv.1301.3781
Naveed, H., Khan, A. U., Qiu, S., Saqib, M., Anwar, S., Usman, M., Akhtar, N., Barnes, N., & Mian, A. (2023). A Comprehensive Over-view of Large Language Models. https://doi.org/10.48550/ARXIV.2307.06435
Neelakantan, A., Xu, T., Puri, R., Radford, A., Han, J. M., Tworek, J., Yuan, Q., Tezak, N., Kim, J. W., Hallacy, C., Heidecke, J., Shyam, P., Power, B., Nekoul, T. E., Sastry, G., Krueger, G., Schnurr, D., Such, F. P., Hsu, K., … Weng, L. (2022). Text and Code Embeddings by Con-trastive Pre-Training (arXiv:2201.10005). arXiv. https://doi.org/10.48550/arXiv.2201.10005
Numerico, T. (2021). Big data e algoritmi: Prospettive critiche. Carocci.
Parlamento Europeo e Consiglio dell’Unione Europea. (2024). Regolamento (UE) 2024/1689 relativo all’intelligenza artificiale (AI Act). https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence
Ramshaw, L., & Marcus, M. (1995). Text chunking using trans-formation-based learning. Third workshop on very large corpora. https://aclanthology.org/W95-0107
Schulhoff, S., Ilie, M., Balepur, N., Kahadze, K., Liu, A., Si, C., Li, Y., Gupta, A., Han, H., Schulhoff, S., Dulepet, P. S., Vidyadhara, S., Ki, D., Agrawal, S., Pham, C., Kroiz, G., Li, F., Tao, H., Srivastava, A., … Res-nik, P. (2024). The Prompt Report: A Systematic Survey of Prompt-ing Techniques. https://doi.org/10.48550/ARXIV.2406.06608
Skinner, B. F. (1961). Teaching Machines. Scientific American, 205(5), 90–106.
Spitzer, M. (2013). Demenza digitale: Come la nuova tecnologia ci rende stupidi. Garzanti (ed. or. 2012).
Streamlit. (2024, settembre 15). https://streamlit.io/
Toosi, A., Bottino, A. G., Saboury, B., Siegel, E., & Rahmim, A. (2021). A brief history of AI: How to prevent another winter (a critical review). PET clinics, 16(4), 449–469.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017). Attention Is All You Need (arXiv:1706.03762). arXiv. https://doi.org/10.48550/arXiv.1706.03762
Vespignani, A., & Rijtano, R. (2019). L’algoritmo e l’oracolo: Co-me la scienza predice il futuro e ci aiuta a cambiarlo (p. 197). Il Saggiatore.
Vygotskij, L. S. (1934). Pensiero e linguaggio (L. Mecacci, A c. Di). La Terza e figli (Ed. italiana 1990).
Wei, J., Wang, X., Schuurmans, D., Bosma, M., Xia, F., Chi, E., Le, Q. V., & Zhou, D. (2022). Chain-of-thought prompting elicits rea-soning in large language models. Advances in neural information processing systems, 35, 24824–24837.
Yao, S., Yu, D., Zhao, J., Shafran, I., Griffiths, T., Cao, Y., & Nara-simhan, K. (2024). Tree of thoughts: Deliberate problem solving with large language models. Advances in Neural Information Pro-cessing Systems, 36. https://proceedings.neurips.cc/paper_files/paper/2023/hash/271db9922b8d1f4dd7aaef84ed5ac703-Abstract-Conference.html
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Daniele Dragoni, Italiano
This work is licensed under a Creative Commons Attribution 4.0 International License.
Edizioni ETS s.r.l. LUNGARNO MEDICEO 16 - 56127 - PISA