Recommender systems in e-learning domain play an important role in assisting the learners
to find useful and relevant learning materials that meet their learning needs. Personalized …

Educational data mining (EDM) is an emerging interdisciplinary research area that deals
with the development of methods to explore data originating in an educational context. EDM …

A recommender system aims to provide users with personalized online product or service
recommendations to handle the increasing online information overload problem and …

We propose that the design and implementation of effective Social Learning Analytics (SLA)
present significant challenges and opportunities for both research and enterprise, in three …

Recommender systems have been researched extensively by the Technology Enhanced
Learning (TEL) community during the last decade. By identifying suitable resources from a …

Technology enhanced learning (TEL) aims to design, develop and test socio-technical
innovations that will support and enhance learning practices of both individuals and …

Recommender systems attempt to guide users in decisions related to choosing items based
on inferences about their personal opinions. Most existing systems implicitly assume the …

In this era when every aspect of society is accelerating, people are always seeking
improvement to stay competitive in their careers. E-learning systems fit into the ever …

With the development of sophisticated e-learning environments, personalization is
becoming an important feature in e-learning systems due to the differences in background …

Recommender systems for technology-enhanced learning are examined in relation to
learners' agency, that is, their ability to define and pursue learning goals. These systems …