2024-09-242024-09-242023-12-13https://repositorio.ifal.edu.br/handle/123456789/738In the globalized world in which we live, the amount of accessible information has become infinite in content, modality and forms of access. The process of choosing among so many options becomes humanly difficult, which is why forms of filters have emerged both in online search engines and in textual and multimedia content hosting platforms. The study of students' best learning possibilities is a field present within the issues of Educational Psychology. Recommender systems began to gain space within the scope of education due to the possibility of bringing advantages to students in different aspects. The departure of high school students to professional technical education at a technical level or higher becomes a challenge, given that choosing an area of activity implies a choice that will have repercussions throughout their lives. The general objective of the research is to propose a recommendation system model for choosing courses to help students make better decisions based on extrinsic and intrinsic characteristics of the student. The research will use data from students' entire basic education records and a profile questionnaire based on the RIASEC model. The recommendation system will use content-based filtering and collaborative filtering algorithms. As future work, we intend to implement the model for the development of a tool for application with two levels of students: (1) they are attending high school; and (2) students who completed high school more than 1 year ago. With the results of the application, it will be possible to determine the level of effectiveness of the proposed solution.ptAttribution-ShareAlike 3.0 BrazilEducaçãoEnsino a Distânciasistemas de recomendaçãoEnsino técnicoInteligência ArtificialEducationDistance learningRecommendation systemsTechnical educationArtificial intelligenceTrabalho de Conclusão de CursoCIENCIAS HUMANAS