ConRec: An Ontology-Based Recommender System for Concept Coverage in Education Enhanced with a Gamified Chatbot Interface
Resumo
This paper presents an improvement to ConRec, an ontology-based recommender system designed to personalize learning by ensuring concept-level coverage of educational content. The system models students and learning objects using an ontology enriched with pedagogical metadata and SWRL inference rules. To enhance usability and engagement, a gamified chatbot interface was integrated into the system. The solution was evaluated in a real classroom with Computer Science undergraduates, demonstrating high satisfaction levels, increased student engagement, and improved effectiveness in supporting learning and clarifying conceptual doubts.Referências
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Belizário, Júnior, C. F. (2018). Reúso de conteúdo da web na recomendação personalizada de objetos de aprendizagem: uma abordagem baseada em um algoritmo genético, tecnologias da web semântica e uma ontologia. Master’s thesis, Universidade Federal de Uberlândia.
Belizário, Júnior, C. F. (2024). An Approach to the Personalized Learning Objects Recommendation Problem as a Set Covering Problem Using Ontologies and Metaheuristics. PhD thesis, Universidade Federal de Uberlândia.
Belizário Júnior, C. F. and Dorça, F. (2018). Uma abordagem para a criaçao e recomendaçao de objetos de aprendizagem usando um algoritmo genético, tecnologias da web semântica e uma ontologia. In Brazilian Symposium on Computers in Education, volume 29, pages 1533–1542, Fortaleza, CE. SBC.
Belizário Júnior, C. F., Dorça, F., Andrade, A. V., and Assis, L. P. (2020). Avanços na recomendação personalizada de objetos de aprendizagem através da utilização de meta-heurísticas clássicas associadas aos problemas de cobertura de conjuntos e de máxima cobertura: Uma análise experimental. In Brazilian Symposium on Computers in Education, volume 31, pages 1383–1392, Natal, RN. SBC.
Belizário Júnior, C. F., Dorça, F., Assis, L. P., and Andrade, A. V. (2024). Advances in personalised recommendation of learning objects based on the set covering problem using ontology. International Journal of Learning Technology, 19(1):25–57.
Belizário Júnior, C. F., Dorça, F. A., Assis, L., and Vivas, A. (2023). Solving the individualized instructional content delivery problem using ontology and metaheuristics on the set covering problem: An experimental analysis. In Anais do XXXIV Simpósio Brasileiro de Informática na Educação, pages 1202–1214. SBC.
Berners-Lee, T., Hendler, J., and Lassila, O. (2001). The semantic web. Scientific american, 284(5):34–43.
Christudas, B. C. L., Kirubakaran, E., and Thangaiah, P. R. J. (2018). An evolutionary approach for personalization of content delivery in e-learning systems based on learner behavior forcing compatibility of learning materials. Tel. and Inf., 35(3):520–533.
De Medio, C., Limongelli, C., Sciarrone, F., and Temperini, M. (2020). Moodlerec: A recommendation system for creating courses using the moodle e-learning platform. Computers in Human Behavior, 104:106168.
Falci, S. H., Dorça, F. A., Falci, D. H. M., and Vivas, A. (2019). A low complexity heuristic to solve a learning objects recommendation problem. In 2019 IEEE 19th ICALT, volume 19, pages 49–53. IEEE.
Felder, R. M., Silverman, L. K., et al. (1988). Learning and teaching styles in engineering education. Engineering education, 78(7):674–681.
Gomaa, Y., Moussa, S., Lahoud, C., and Abel, M.-H. (2024). Exploring recommender systems for assisting teachers in e-learning gamification. In Procedia Computer Science, volume 246, pages 2312–2321. Elsevier.
Graesser, A. C. (2016). Conversations with autotutor help students learn. International Journal of Artificial Intelligence in Education, 26(1):124–132.
Horrocks, I., Patel-Schneider, P. F., Boley, H., Tabet, S., Grosof, B., Dean, M., et al. (2004). Swrl: A semantic web rule language combining owl and ruleml. W3C Member submission, 21(79):1–31.
Joshi, A., Kale, S., Chandel, S., and Pal, D. K. (2015). Likert scale: Explored and explained. British journal of applied science & technology, 7(4):396–403.
Kingchang, T., Chatwattana, P., and Wannapiroon, P. (2024). Artificial intelligence chatbot platform: Ai chatbot platform for educational recommendations in higher education. International Journal of Information and Education Technology, 14(1):34–41.
Limongelli, C., Gasparetti, F., and Sciarrone, F. (2015). Wiki course builder: a system for retrieving and sequencing didactic materials from wikipedia. In 2015 Inter. Conf. on Inform. Tech. Based Higher Education and Training, pages 1–6. IEEE.
LTSC (2002). Standard for learning object metadata (ieee 1484.12.1). Learning Technology Standards Committee.
Mendes, T., Pereira, L., Baranda, V. R., de Oliveira Julio, A. M., and da Silva, R. L. d. S. (2019). Uso de sistemas de gamificação no combate a evasão de cursos de graduação da área de exatas. In Brazilian Symposium on Computers in Education-SBIE, volume 30, page 733.
Moreira, S., Sousa, T., Silva, W., and Marques, A. B. (2022). Uma experiência de gamificação no ensino com o ambiente classcraft: análise da motivação dos estudantes. In Simpósio Brasileiro de Informática na Educação (SBIE), pages 403–414. SBC.
Pereira, Júnior, C., Belizário, Júnior, C. F., Araújo, R. D., and Dorça, F. A. (2020). Personalized recommendation of learning objects through bio-inspired algorithms and semantic web technologies: an experimental analysis. In Anais do XXXI Simpósio Brasileiro de Informática na Educação, pages 1333–1342. SBC.
Ruan, S., Jiang, L., Xu, J., Tham, B. J.-K., Qiu, Z., Zhu, Y., Murnane, E. L., Brunskill, E., and Landay, J. A. (2019). Quizbot: A dialogue-based adaptive learning system for factual knowledge. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pages 1–13.
Tarus, J. K., Niu, Z., and Yousif, A. (2017). A hybrid knowledge-based recommender system for e-learning based on ontology and sequential pattern mining. Future Generation Computer Systems, 72:37–48.
Tilahun, S. L. and Ong, H. C. (2015). Prey-predator algorithm: a new metaheuristic algorithm for optimization problems. International Journal of Information Technology & Decision Making, 14(06):1331–1352.
Vanetti, M., Binaghi, E., Carminati, B., Carullo, M., and Ferrari, E. (2010). Content-based filtering in on-line social networks. In International Workshop on Privacy and Security Issues in Data Mining and Machine Learning, pages 127–140. Springer.
Belizário, Júnior, C. F. (2018). Reúso de conteúdo da web na recomendação personalizada de objetos de aprendizagem: uma abordagem baseada em um algoritmo genético, tecnologias da web semântica e uma ontologia. Master’s thesis, Universidade Federal de Uberlândia.
Belizário, Júnior, C. F. (2024). An Approach to the Personalized Learning Objects Recommendation Problem as a Set Covering Problem Using Ontologies and Metaheuristics. PhD thesis, Universidade Federal de Uberlândia.
Belizário Júnior, C. F. and Dorça, F. (2018). Uma abordagem para a criaçao e recomendaçao de objetos de aprendizagem usando um algoritmo genético, tecnologias da web semântica e uma ontologia. In Brazilian Symposium on Computers in Education, volume 29, pages 1533–1542, Fortaleza, CE. SBC.
Belizário Júnior, C. F., Dorça, F., Andrade, A. V., and Assis, L. P. (2020). Avanços na recomendação personalizada de objetos de aprendizagem através da utilização de meta-heurísticas clássicas associadas aos problemas de cobertura de conjuntos e de máxima cobertura: Uma análise experimental. In Brazilian Symposium on Computers in Education, volume 31, pages 1383–1392, Natal, RN. SBC.
Belizário Júnior, C. F., Dorça, F., Assis, L. P., and Andrade, A. V. (2024). Advances in personalised recommendation of learning objects based on the set covering problem using ontology. International Journal of Learning Technology, 19(1):25–57.
Belizário Júnior, C. F., Dorça, F. A., Assis, L., and Vivas, A. (2023). Solving the individualized instructional content delivery problem using ontology and metaheuristics on the set covering problem: An experimental analysis. In Anais do XXXIV Simpósio Brasileiro de Informática na Educação, pages 1202–1214. SBC.
Berners-Lee, T., Hendler, J., and Lassila, O. (2001). The semantic web. Scientific american, 284(5):34–43.
Christudas, B. C. L., Kirubakaran, E., and Thangaiah, P. R. J. (2018). An evolutionary approach for personalization of content delivery in e-learning systems based on learner behavior forcing compatibility of learning materials. Tel. and Inf., 35(3):520–533.
De Medio, C., Limongelli, C., Sciarrone, F., and Temperini, M. (2020). Moodlerec: A recommendation system for creating courses using the moodle e-learning platform. Computers in Human Behavior, 104:106168.
Falci, S. H., Dorça, F. A., Falci, D. H. M., and Vivas, A. (2019). A low complexity heuristic to solve a learning objects recommendation problem. In 2019 IEEE 19th ICALT, volume 19, pages 49–53. IEEE.
Felder, R. M., Silverman, L. K., et al. (1988). Learning and teaching styles in engineering education. Engineering education, 78(7):674–681.
Gomaa, Y., Moussa, S., Lahoud, C., and Abel, M.-H. (2024). Exploring recommender systems for assisting teachers in e-learning gamification. In Procedia Computer Science, volume 246, pages 2312–2321. Elsevier.
Graesser, A. C. (2016). Conversations with autotutor help students learn. International Journal of Artificial Intelligence in Education, 26(1):124–132.
Horrocks, I., Patel-Schneider, P. F., Boley, H., Tabet, S., Grosof, B., Dean, M., et al. (2004). Swrl: A semantic web rule language combining owl and ruleml. W3C Member submission, 21(79):1–31.
Joshi, A., Kale, S., Chandel, S., and Pal, D. K. (2015). Likert scale: Explored and explained. British journal of applied science & technology, 7(4):396–403.
Kingchang, T., Chatwattana, P., and Wannapiroon, P. (2024). Artificial intelligence chatbot platform: Ai chatbot platform for educational recommendations in higher education. International Journal of Information and Education Technology, 14(1):34–41.
Limongelli, C., Gasparetti, F., and Sciarrone, F. (2015). Wiki course builder: a system for retrieving and sequencing didactic materials from wikipedia. In 2015 Inter. Conf. on Inform. Tech. Based Higher Education and Training, pages 1–6. IEEE.
LTSC (2002). Standard for learning object metadata (ieee 1484.12.1). Learning Technology Standards Committee.
Mendes, T., Pereira, L., Baranda, V. R., de Oliveira Julio, A. M., and da Silva, R. L. d. S. (2019). Uso de sistemas de gamificação no combate a evasão de cursos de graduação da área de exatas. In Brazilian Symposium on Computers in Education-SBIE, volume 30, page 733.
Moreira, S., Sousa, T., Silva, W., and Marques, A. B. (2022). Uma experiência de gamificação no ensino com o ambiente classcraft: análise da motivação dos estudantes. In Simpósio Brasileiro de Informática na Educação (SBIE), pages 403–414. SBC.
Pereira, Júnior, C., Belizário, Júnior, C. F., Araújo, R. D., and Dorça, F. A. (2020). Personalized recommendation of learning objects through bio-inspired algorithms and semantic web technologies: an experimental analysis. In Anais do XXXI Simpósio Brasileiro de Informática na Educação, pages 1333–1342. SBC.
Ruan, S., Jiang, L., Xu, J., Tham, B. J.-K., Qiu, Z., Zhu, Y., Murnane, E. L., Brunskill, E., and Landay, J. A. (2019). Quizbot: A dialogue-based adaptive learning system for factual knowledge. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pages 1–13.
Tarus, J. K., Niu, Z., and Yousif, A. (2017). A hybrid knowledge-based recommender system for e-learning based on ontology and sequential pattern mining. Future Generation Computer Systems, 72:37–48.
Tilahun, S. L. and Ong, H. C. (2015). Prey-predator algorithm: a new metaheuristic algorithm for optimization problems. International Journal of Information Technology & Decision Making, 14(06):1331–1352.
Vanetti, M., Binaghi, E., Carminati, B., Carullo, M., and Ferrari, E. (2010). Content-based filtering in on-line social networks. In International Workshop on Privacy and Security Issues in Data Mining and Machine Learning, pages 127–140. Springer.
Publicado
24/11/2025
Como Citar
BELIZÁRIO JÚNIOR, Clarivando F.; DORÇA, Fabiano A.; ASSIS, Luciana; VIVAS, Alessandro; CATTELAN, Renan G.; SOUZA, Arthur H. de.
ConRec: An Ontology-Based Recommender System for Concept Coverage in Education Enhanced with a Gamified Chatbot Interface. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 36. , 2025, Curitiba/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 1121-1132.
DOI: https://doi.org/10.5753/sbie.2025.12799.
