Further thoughts on context-aware paper recommendations for education

Document Type

Article

Publication Date

1-1-2014

Abstract

Simply matching learner interest with paper topic is far from enough in making personalized paper recommendations to learners in the educational domain. As such, we proposed the multidimensional recommendation techniques that consider (educational) context-aware information to inform and guide the system during the recommendation process. The contextual information includes both learner and paper features that can be extracted and learned during the pre- and post-recommendation process. User studies have been performed on both undergraduate (inexperienced learners) and graduate (experienced learners) students who have different information-seeking goals and educational backgrounds. Results from our extensive studies have been able to show that (1) it is both effective and desirable to implement the multidimensional recommendation techniques that are more complex than the traditional single-dimensional recommendation; (2) recommendation from across different learning groups (with different pedagogical features and learning goals) is less effective than that from within the same learning groups, especially when collaborative filtering technique is applied.

Publication Title

Recommender Systems for Technology Enhanced Learning: Research Trends and Applications

First Page Number

159

Last Page Number

173

DOI

10.1007/978-1-4939-0530-0_8

This document is currently not available here.

Share

COinS