Learning object recommender systems: issues for their improvement / Objetos de aprendizaje: cuestiones involucradas para su mejora
Abstract
Learning Object Recommender Systems are important to help training professionals because they can find the educational resources that best fit the learning style and the profile of the user. In this article, several issues related to improving the usability of repositories of educational resources are presented to assist in the management of these repositories. First, to support the document collection tasks carried out by the repository administrator in order to detect plausible documents to be loaded in these repositories together with their metadata of interest. In addition, proposals to facilitate the loading of educational resources to the repository using the automatic extraction of metadata are presented. In this way, there should be an increase of the population of documents in these repositories, accompanying the development of Open Access Institutional Repositories, which is a priority within the
framework of the policies of the Ministry of Science, Technology and Innovation and the Inter-University Council of Argentina. Another aspect is to improve the information search by working on the automatic recommendation of learning
objects considering the user profile and also the collaborative assessment of similar groups of users.
Keywords: Learning objects, recommender systems, metadata.
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