Abstract
Bayesian Networks have been related to education for several years due to the advantages that this technique offers. Building a Bayesian Network (BN) in the educational domain is laborious. The objective of this study is to define a methodology to develop BNs to be implemented them in an Intelligent Tutoring Systems based on ontologies and experts’ knowledge. Also, establish a method for building automatically BN qualitative part. The main contributions of our work are the methodology to build BNs based on experts’ knowledge, the formalization of ontologies, and the process of construct BN qualitative part. The resulted BNs are useful to infer and diagnose students’ knowledge. This inference will be helpful to decide what are concepts need to be reinforce.
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References
Almashaykhi, A.M.O.: Domain ontology for programming languages. J. Comput. Model. 2(4), 75–91 (2012)
Cataldi, Z., Lage, F.J.: Modelado del estudiante en sistemas tutores inteligentes. Revista Iberoamericana de Tecnologia en Educación y Educación en Tecnología 5, 29–38 (2010)
Conati, C., Gertner, A., Vanlehn, K.: Using Bayesian networks to manage uncertainty in student modeling. User Model. User-Adap. Inter. 12(4), 371–417 (2002)
Conejo, R., Millán, E., Pérez, J., Trella, M.: Modelado del alumno: un enfoque bayesiano. Revista Iberoamericana de Inteligencia Artificial 12, 50–58 (2001)
Ding, Z., Peng, Y.: A probabilistic extension to ontology language OWL. In: Proceedings of the 37th Annual Hawaii International Conference on System Sciences, pp. 1–10 (2004)
Fernández-López, M., Gómez-Pérez, A., Juristo, N.: Methontology: from ontological art towards ontological engineering. Assessment SS-97-06, pp. 33–40 (1997)
Khodeir, N., Wanas, N., Hegazy, N., Darwish, N.: Bayesian based student knowledge modeling in intelligent tutoring systems. In: Proceedings of the 2012 6th IEEE International Conference on E-Learning in Industrial Electronics, ICELIE 2012, pp. 12–17 (2012)
Madsen, A.L., Lohse, N.: Diagnostic Models Using Expert Knowledge (2015)
Mendes, E.: Knowledge representation using Bayesian networks — a case study in Web effort estimation. In: Proceedings of the World Congress on Information and Communication Technologies, pp. 612–617 (2011)
Millán, E., Pérez-De-La-Cruz, J.L.: A Bayesian diagnostic algorithm for student modeling and its evaluation. User Model. User-Adap. Inter. 12, 281–330 (2002)
Millán, E., Descalço, L., Castillo, G., Oliveira, P., Diogo, S.: Using Bayesian networks to improve knowledge assessment. Comput. Educ. 60(1), 436–447 (2013)
Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publishers Inc., San Mateo (1988)
Ramírez-Noriega, A., Juárez-Ramírez, R., Huertas, C., Martínez-Ramírez, Y.: A methodology for building bayesian networks for knowledge representation in intelligent tutoring systems. In: Congreso Internacional de Investigación e Innovación en Ingeniería de Software 2015, San Luís Potosí, pp. 124–133 (2015)
Roche Beltrán, F.: Metodo para obtener conocimiento utilizando redes Bayesianas y procesos de aprendizaje con algoritmos evolutivos. Ph.D. thesis, Universidad de Sevilla (2002)
Santhi, R., Priya, B., Nandhini, J.: Review of intelligent tutoring systems using bayesian approach. arXiv preprint arXiv:1302.7081 (2013)
Shishehchi, S., Banihashem, S.Y.: Learning content recommendation for visual basic.net programming language based on ontology. J. Comput. Sci. 7(2), 188–196 (2011)
Xiao-xuan, H., Hui, W., Shuo, W.: Using expert’s knowledge to build bayesian networks. In: 2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007), pp. 220–223 (2007)
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Ramirez-Noriega, A., Juárez-Ramírez, R., Jiménez, S., Martínez-Ramírez, Y., Armenta, J. (2017). Building a Bayesian Network for Object Oriented Programming with Experts’ Knowledge. In: Rocha, Á., Correia, A., Adeli, H., Reis, L., Costanzo, S. (eds) Recent Advances in Information Systems and Technologies. WorldCIST 2017. Advances in Intelligent Systems and Computing, vol 569. Springer, Cham. https://doi.org/10.1007/978-3-319-56535-4_27
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DOI: https://doi.org/10.1007/978-3-319-56535-4_27
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