Integration of Generative AI and Educational Repositories: Enhancing Pedagogical Effectiveness and Content Recommendation with LLaMA2

• Renan Zafalon da Silva Federal University of Pelotas http://orcid.org/0009-0009-6657-0958
• Paulo Cesar Ramos Pinho Federal University of Pelotas https://orcid.org/0000-0002-1847-6205
• Maria Isabel Giusti Moreira Southern Rio Grande Federal Institute https://orcid.org/0000-0001-9940-2138
• Raymundo Carlos Machado Ferreira Filho Southern Rio Grande Federal Institute https://orcid.org/0000-0001-7408-6124
• Tiago Thompsen Primo Federal University of Pelotas https://orcid.org/0000-0003-3870-097X

DOI: https://doi.org/10.5753/sbie.2024.244916

Abstract

This article presents the development of an educational recommendation system based on generative artificial intelligence (GenAI) integrated with the ProEdu repository. The system aims to personalize learning by suggesting content and learning paths tailored to the individual needs of students. Utilizing the LLaMA2 transformer model, the proposal addresses the integration of AI to enhance pedagogical effectiveness and student engagement. The applied methodology includes case studies and feedback analysis, allowing for continuous evaluation and refinement of the system. The results indicate significant potential in personalizing learning and improving academic outcomes.

Keywords: Artificial Intelligence, Repository, Recommendation System, Semantic Search

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