Collaboratively Filtering Learning Resources
Originally published by the Association for Educational Communications and Technology (AECT). Submitted version of the chapter is available through remote link.
Abstract
This chapter describes and discusses the application of collaborative filtering techniques to the design of metadata structures for learning objects, and its implications for instruction. This approach enables context-sensitive discovery and recommendation of learning objects. The discussion is based upon research in developing and evaluating a collaborative filtering system, which enables users to share ratings, opinions, and recommendations about resources on the Web. An additional benefit of this approach is that it also allows a user to locate other users that share similar interests for further communication and collaboration.
