Educational recommendation in an informal intentional learning system

Recommender systems have become part of the standard toolkit of web personalization. These same tools and techniques are now making their way into educational and adaptive e-learning systems. In this chapter, we will discuss aspects of a prototype system, the Customized Learning Service for Concept Knowledge (CLICK), an application designed to provide digital library resources recommendations based on user's concept knowledge demonstrated through automated evaluation and approximation of their knowledge state from essay writing. We present the underlying concepts behind recommender systems, review learner models as they are designed within the CLICK environment, and review the lessons learned. We will discuss aspects of how CLICK supports intentional learning as well as extensions to the existing technology to improve such support. Future challenges and directions for CLICK and related technologies are also discussed.