Sistema Adaptativo Educacional Baseado na Combinação de Dimensões da Aprendizagem
Resumo
Sistemas adaptativos educacionais personalizam a aprendizagem conforme características dos estudantes. Entretanto, muitas abordagens priorizam o desempenho acadêmico e pouco exploram outras dimensões. Esta pesquisa investiga como dimensões cognitivas, metacognitivas e afetivas influenciam a personalização de trilhas adaptativas. Um modelo baseado em lógica fuzzy integra desempenho, dificuldade percebida e autoconfiança para recomendar trilhas de Reforço, Regular ou Desafio. A pesquisa compreende mapeamento da literatura e avaliações em cursos de Robótica com Arduino e Fundamentos de IA Generativa. Os resultados indicam a viabilidade e o potencial da abordagem multidimensional para personalizar a aprendizagem.
Palavras-chave:
Sistemas Adaptativos Educacionais, Lógica Fuzzy, Personalização da Aprendizagem
Referências
Al Duhayyim, M. and Newbury, P. (2018). “Concept-based and Fuzzy Adaptive E-learning”. In Proceedings of the 3rd International Conference on Information and Education Innovations (ICIEI 2018), pp. 49–56. ACM. DOI: 10.1145/3234825.3234832.
Ezzaim, A., Dahbi, A., Haidine, A., Aqqal, A. (2024). “Development, Implementation, and Evaluation of a Machine Learning-Based Multi-Factor Adaptive E-Learning System”. IAENG International Journal of Computer Science, 51(9), 1250–1271.
Flavell, J. H. (1979). “Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry”. American Psychologist, 34(10), 906–911. DOI: 10.1037/0003-066X.34.10.906.
Ghergulescu, I., Flynn, C., O'Sullivan, C., van Heck, I. and Slob, M. (2021). “A Conceptual Framework for Extending Domain Model of AI-enabled Adaptive Learning with Sub-skills Modelling”. In: Proceedings of the 13th International Conference on Computer Supported Education (CSEDU 2021), vol. 1, pp. 116–123. DOI: 10.5220/0010451201160123.
Hwang, G.-J., Sung, H.-Y., Chang, S.-C., and Huang, X.-C. (2020). “A fuzzy expert system-based adaptive learning approach to improving students’ learning performances by considering affective and cognitive factors”. Computers and Education: Artificial Intelligence, 1, 100003. DOI: 10.1016/j.caeai.2020.100003.
Panadero, E. (2017). “A review of self-regulated learning: Six models and four directions for research”. Frontiers in Psychology, 8, 422. DOI: 10.3389/fpsyg.2017.00422.
Szczepański, M. and Marciniak, J. (2023). “Application of a Fuzzy Controller in Adaptive E-Learning Content Used to Evaluate Student Activity”. Procedia Computer Science, 225, 2526–2535. DOI: 10.1016/j.procs.2023.10.244.
Wang, S., Christensen, C., McBride, E. A., Kelly, H., Cui, W., Tong, R., Shear, L., Yarnall, L. and Feng, M. (2020). “Identifying Gaps in Use of and Research on Adaptive Learning Systems”. In: International Conference on Computer Supported Education, pp. 118-124. DOI: 10.5220/0009590701180124.
Ezzaim, A., Dahbi, A., Haidine, A., Aqqal, A. (2024). “Development, Implementation, and Evaluation of a Machine Learning-Based Multi-Factor Adaptive E-Learning System”. IAENG International Journal of Computer Science, 51(9), 1250–1271.
Flavell, J. H. (1979). “Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry”. American Psychologist, 34(10), 906–911. DOI: 10.1037/0003-066X.34.10.906.
Ghergulescu, I., Flynn, C., O'Sullivan, C., van Heck, I. and Slob, M. (2021). “A Conceptual Framework for Extending Domain Model of AI-enabled Adaptive Learning with Sub-skills Modelling”. In: Proceedings of the 13th International Conference on Computer Supported Education (CSEDU 2021), vol. 1, pp. 116–123. DOI: 10.5220/0010451201160123.
Hwang, G.-J., Sung, H.-Y., Chang, S.-C., and Huang, X.-C. (2020). “A fuzzy expert system-based adaptive learning approach to improving students’ learning performances by considering affective and cognitive factors”. Computers and Education: Artificial Intelligence, 1, 100003. DOI: 10.1016/j.caeai.2020.100003.
Panadero, E. (2017). “A review of self-regulated learning: Six models and four directions for research”. Frontiers in Psychology, 8, 422. DOI: 10.3389/fpsyg.2017.00422.
Szczepański, M. and Marciniak, J. (2023). “Application of a Fuzzy Controller in Adaptive E-Learning Content Used to Evaluate Student Activity”. Procedia Computer Science, 225, 2526–2535. DOI: 10.1016/j.procs.2023.10.244.
Wang, S., Christensen, C., McBride, E. A., Kelly, H., Cui, W., Tong, R., Shear, L., Yarnall, L. and Feng, M. (2020). “Identifying Gaps in Use of and Research on Adaptive Learning Systems”. In: International Conference on Computer Supported Education, pp. 118-124. DOI: 10.5220/0009590701180124.
Publicado
13/10/2026
Como Citar
GRION, Renan; MORAES, Laura O..
Sistema Adaptativo Educacional Baseado na Combinação de Dimensões da Aprendizagem. In: TRILHA DO CONSÓRCIO DE TESES - CONFERÊNCIA LATINO-AMERICANA DA TECNOLOGIAS DE APRENDIZAGEM (LACLO), 21. , 2026, Rio de Janeiro/RJ.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
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p. 439-446.
