
Artificial Intelligence For Automatic Generation Of Customized Courses
PROCEEDINGS
Néstor Darío Duque Méndez, Demetrio Arturo Ovalle Carranza, Jovani Alberto Jiménez Builes, Universidad Nacional de Colombia, Colombia
EdMedia + Innovate Learning, in Orlando, FL USA ISBN 978-1-880094-60-0 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
Abstract
This work presents a Virtual Course Model that is adapted to the own characteristics of each student. This model is oriented by goals or educational objectives, that are trying to be covered by offering multiple educational materials or activities according to the academic trajectory (goals reached) and are associated to the psycho-pedagogic profile of the learner (learning style). The specification of the properties of the educational units respects, as much as possible, internationally recognised standards. Due to the complexity of the courses generation, and to the detail level and the hierarchy in the pedagogic objectives, the use of Artificial Intelligence Planning techniques was decided. This implies the definition of automatic mechanisms for carrying course elements over to the planning environment and the determination of the action model of the planner: to define the operators, the methods, and the problem in terms of the selected planner.
Citation
Duque Méndez, N.D., Ovalle Carranza, D.A. & Jiménez Builes, J.A. (2006). Artificial Intelligence For Automatic Generation Of Customized Courses. In E. Pearson & P. Bohman (Eds.), Proceedings of ED-MEDIA 2006--World Conference on Educational Multimedia, Hypermedia & Telecommunications (pp. 2693-2698). Orlando, FL USA: Association for the Advancement of Computing in Education (AACE). Retrieved September 28, 2023 from https://www.learntechlib.org/primary/p/23388/.
© 2006 Association for the Advancement of Computing in Education (AACE)
Keywords
References
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Silvia Baldiris Navarro, University of Girona; Sabine Graf, Athabasca University; Ramon Fabregat & Nestor Duque Méndez
The International Review of Research in Open and Distributed Learning Vol. 13, No. 5 (Nov 08, 2012) pp. 76–101
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