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.

(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

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

Avogadri, Simone;Russo, Davide
2025-01-01

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.
2025
Inglese
Procedia Computer Science. 29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2025)
Flearmoy, Jonathan
270
Special Issue
263
272
online
Netherlands
Amsterdam
Elsevier
KES 2025: 29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Osaka, Japan, 10-12 September 2025
29th
Osaka, Japan
10-12 September 2025
internazionale
contributo
Settore IIND-03/B - Disegno e metodi dell'ingegneria industriale
Education; Teaching; Learning; Artificial Intelligence - AI; Large Language Model – LLM; Retrieval Augmented Generation – RAG; TRIZ; Systematic Innovation; Problem-Solving; Computer Aided Innovation – CAI
info:eu-repo/semantics/conferenceObject
2
Avogadri, Simone; Russo, Davide
1.4 Contributi in atti di convegno - Contributions in conference proceedings::1.4.01 Contributi in atti di convegno - Conference presentations
open
Non definito
273
(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
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/315805
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