This chapter presents an analysis of recommender systems in TechnologyEnhanced
Learning along their 15 years existence (2000-2014). All recommender
systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender systems from
35 different countries have been investigated and categorised according to a given
classification framework. The reviewed systems have been classified into 7 clusters
according to their characteristics and analysed for their contribution to the evolution
of the RecSysTEL research field. Current challenges have been identified to lead the work of the forthcoming years.Hendrik Drachsler has been partly supported by the FP7 EU Project LACE (619424).
Katrien Verbert is a post-doctoral fellow of the Research Foundation Flanders
(FWO). Olga C. Santos would like to acknowledge that her contributions to this
work have been carried out within the project Multimodal approaches for Affective
Modelling in Inclusive Personalized Educational scenarios in intelligent Contexts
(MAMIPEC -TIN2011-29221-C03-01). Nikos Manouselis has been partially supported
with funding CIP-PSP Open Discovery Space (297229