Title
Open Educational Resources Platform Based on Collective Intelligence
Abstract
Open Educational Resources (OER) are educational resources openly available to be used by educators and students and are an important tool to support education. A considerable effort has been made to build repositories that allow the sharing and reuse of these OERs. However, many of these repositories offer unsatisfactory search engines, resulting in a frustrating experience for users. The problem of content search is partly explained by the lack of appropriate metadata on resources and the lack of ranking mechanisms, for instance based on user interaction over the educational objects. In this paper, we present the Plataforma Integrada do MEC (MEC's Integrated Platform), a novel Digital Educational Resources platform, which employs concepts of social networks to create a collective intelligence system to improve and refine search results. Platform users are able to evaluate the available resources and also publish new ones. A ranking is associated with these users and it is used to determine the relevance of their actions on the platform. High ranking users can publish new content that will be considered relevant in the platform, eliminating the need for resources to be evaluated by an expert. Unlike other repositories, where authorization must be given for content publication, on this platform the user has the opportunity to actively contribute with new content. A prototype of this platform was developed, and made available as free software. Preliminary results indicate viability of the proposal and that the system opens a path to effective knowledge diffusion.
Year
DOI
Venue
2018
10.1109/CIC.2018.00053
2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC)
Keywords
Field
DocType
open educational resources,educational platform,collective intelligence,social networks
Publication,Metadata,Computer vision,World Wide Web,Ranking,Task analysis,Reuse,Computer science,Collective intelligence,Open educational resources,Artificial intelligence,Web service
Conference
ISBN
Citations 
PageRank 
978-1-5386-9503-6
0
0.34
References 
Authors
1
7