A fast increasing in the volume of digital educational resources available on the open Web or even private digital libraries has occurred in recent years.Due to the large volume of resources available, it is a hard task for a user to find the content which his/her is interested. Personalized Recommendation Systems have recently emerged to address this problem. However, such systems need to be better disseminated among users of educational resources, such as students and teachers, as these systems will help significantly in the performance of their activities. In this chapter, the concepts, the principal techniques and information filtering algorithms will be viewed with applications for recommendation of digital educational resources, demonstrating the potential of this type of system.
Over the last decade, research in the area of e-learning has employed efforts to propose solutions for sharing and reuse of educational resources. Such initiative has increased with the rise of the so-called Open Educational Resources (OER). OER are freely accessible documents and media that are useful for learning purposes. Hence, the Web today offers a comprehensive amount of OER repositories. However, these efforts led to a fragmented landscape of concurrent metadata schemas or interface mechanisms that were not designed to offer mechanisms to enable the exchange of resources between these repositories. Recent studies show that this scenario makes it harder the reuse of resources located in OER Repositories. This paper conduct a study using a questionnaire to analyze how students and professors search for educational resources on the Web, in order to better characterize the problem. Questionnaire results confirm the low reuse of educational resources. To alleviate this problem, our conclusions indicate the need for an integrated approach to search for Educational Resources.
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