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LearnAIng: Generative Artificial Intelligence to boost teaching and training in technical field

Contributo in Atti di convegno
Data di Pubblicazione:
2025
Citazione:
(2025). LearnAIng: Generative Artificial Intelligence to boost teaching and training in technical field . In PROCEDIA COMPUTER SCIENCE. Retrieved from https://hdl.handle.net/10446/315805
Abstract:
Generative Artificial Intelligence is revolutionizing the field of education, offering innovative tools to support students in the learning process and teachers in their activities. This paper presents an AI-powered software developed to support the teaching of systematic innovation courses, following TRIZ methodology, through the integration of Large Language Models (LLMs), Retrieval Augmented Generation (RAG) techniques and the access to patent source. The article describes the methodology implemented and the results of an experimental phase conducted on a large sample of students. The analysis shows how the use of AI in technical Problem-Solving enhances a more structured approach but at the same time is more effective in stimulating creativity and lateral thinking, reducing psychological inertia and boosting Technology Transfer. The findings highlight significant improvements over traditional didactics methods, both in learning effectiveness and instructional support.
Tipologia CRIS:
1.4.01 Contributi in atti di convegno - Conference presentations
Elenco autori:
Avogadri, Simone; Russo, Davide
Autori di Ateneo:
AVOGADRI Simone
RUSSO Davide
Link alla scheda completa:
https://aisberg.unibg.it/handle/10446/315805
Link al Full Text:
https://aisberg.unibg.it/retrieve/handle/10446/315805/922838/KES25+-+Avogadri,+Russo.pdf
Titolo del libro:
Procedia Computer Science. 29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2025)
Pubblicato in:
PROCEDIA COMPUTER SCIENCE
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Settore IIND-03/B - Disegno e metodi dell'ingegneria industriale
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