Abstract
The use of artificial intelligence techniques has been efficiently employed not only for problem solving but also for modeling, simulation, and development of complex systems. The construction of virtual courses is a complex task since such computational systems must adapt their behavior to the student’s characteristics in a customized way. Thus, the aim of this chapter is to propose student-centered virtual course design and construction with adaptive features, through the integration of artificial intelligence techniques involving multi-agent systems and planning. It should be noted that virtual course adaptation has been performed with an emphasis on both instructional planning and student-centered intelligent selection of learning objects. The validation of the proposed model was made through the construction of an experimental computational platform called CIA (Spanish acronym for Adaptive Intelligent Virtual Courses), which carries out learning planning and individual learning object selection in an intelligent way, taking into account the students’ knowledge level, their learning styles, and their most used brain hemisphere.
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Acknowledgments
The research presented in this chapter was partially funded by the Colciencias project entitled “ROAC Creación de un modelo para la Federación de OA en Colombia que permita su integración a confederaciones internacionales” and Colciencias—PUJ Bogota—UNAL Medellin project entitled “AYLLU: Plataforma de cooperación mediada por agentes aplicada en un contexto de e-learning colaborativo (2010–2012)” with ID 1203-489-25592.
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Ovalle, D.A., Arias, F.J., Moreno, J. (2013). Student-Centered Multi-agent Model for Adaptive Virtual Course Development and Learning Object Selection. In: Sampson, D., Isaias, P., Ifenthaler, D., Spector, J. (eds) Ubiquitous and Mobile Learning in the Digital Age. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3329-3_4
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