Title:
E-Learning and Intelligent Planning: Improving Content Personalization [Descargar]Autores/as:
Garrido, Antonio and Morales, Lluvia
Términos Índice:
Recommender systems;Electronic learning;Education courses;Metadata;Least squares approximations;Data mining;Maintenance engineering;Educational technology;electronic learning;computer aided instruction;courseware;content personalization
Resumen:
Combining learning objects are a challenging topic because of its direct application to curriculum generation, tailored to the students' profiles and preferences. Intelligent planning allows us to adapt learning routes (i.e., sequences of learning objects), thus highly improving the personalization of contents, the pedagogical requirements, and specific necessities of each student. This paper presents a general and effective approach to extract metadata information from the e-learning contents, a form of reusable learning objects, to generate a planning domain in a simple, automated way. Such a domain is used by an intelligent planner that provides an integrated recommendation system, which adapts, stores, and reuses the best learning routes according to the students' profiles and course objectives. If any inconsistency happens during the route execution, e.g., the student fails to pass an assessment test, which prevents him/her from continuing the natural course of the route, the system adapts and/or repairs the course to meet the new objectives.
DOI:
Cómo citar:
Garrido, Antonio and Morales, Lluvia, "E-Learning and Intelligent Planning: Improving Content Personalization" in IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, pp. 1-7, Feb. 2014. doi: 10.1109/RITA.2014.2301886