Session Title: An Introduction to OER Recommender
Presenters: Seth Gurell, Doctoral Candidate, Brigham Young University
David Wiley, Associate Professor, Brigham Young University
Brett Shelton, Utah State University
Time & Date: 11:15 A.M. - 12:00 P.M., Thursday, August 13, 2009
Location: Rm. C150
Session Description: OER is a term that stands for Open Educational Resources. Gurell (2008) defines it as “educational resources (lesson plans, quizzes, syllabi, instructional modules, simulations, etc.) that are freely available for use, reuse, adaptation, and sharing”. OER can be used in a variety of contexts , from K-12 to lifelong learning. The term was first used at a UNESCO workshop in July of 2002. Since then, several prominent OER projects have emerged, such as Connexions, OER Commons, WikiEducator and many more.
What is a recommender?
Recommender systems form a specific type of information filtering (IF) technique that attempts to present information items (movies, music, books, news, images, web pages, etc.) that are likely of interest to the user. Typically, a recommender system compares the user’s profile to some reference characteristics, and seeks to predict the ‘rating’ that a user would give to an item they had not yet considered. These characteristics may be from the information item (the content-based approach) or the user’s social environment (the collaborative filtering approach).
What is OER Recommender?
Given the increasing number and decentralization of OER, finding the right one for a given context has become increasing difficult. Therefore, we felt a recommender system was warranted to help index OER and provide an alternative, usable way to find them.
OER Recommender harvests open educational resources and their metadata, and computes a large similarity index across tens of thousands of resources. Through a variety of easy to use interfaces, users can tap the index to receive suggestions of resources similar to a given resource. This service can be provided in context (?show me more OERs like this one?) or can be used like a traditional search engine.
In this presentation we will discuss and demonstrate the OER Recommender, show OER sites how to integrate the service into their sites, and show OER collections how to insure your resources are part of the master index.
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