Avaliação da eficácia de grandes modelos de linguagem na geração de planos de estudo personalizados baseados nos estilos de aprendizagem Honey-Alonso.

Abstract

Personalized learning has become an increasingly relevant topic due to the growing application of digital technologies in educational contexts. In this scenario, Large Language Models (LLMs) have shown potential to support the development of study plans tailored to students' individual characteristics. This study investigates the use of LLMs in the creation of personalized study plans based on the learning styles defined by the Honey- Alonso Learning Styles Questionnaire (CHAEA). To achieve this objective, an exploratory research approach was conducted, supported by a literature review on learning styles, artificial intelligence, and Large Language Models. The proposed methodology includes the definition of educational scenarios, the development of a standardized model for study plan generation, and the establishment of criteria for evaluating the materials produced by the analyzed LLMs. This research seeks to contribute to the understanding of the potential applications of generative artificial intelligence in education, particularly in the context of personalized learning and support for the learning process, providing a foundation for future investigations into the use of these technologies as educational support tools.