The constantly growing offering of online learning materials to students is making it more
difficult to locate specific information from data pools. Personalization systems attempt to …

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 …

This chapter presents an analysis of recommender systems in Technology-Enhanced
Learning along their 15 years existence (2000–2014). All recommender systems considered …

To facilitate professional development of teachers in the online context, the online
community of practice (CoPs) has become an important platform in which individuals with …

The World Health Organization identifies the overall increasing of noncommunicable
diseases as a major issue, such as premature heart diseases, diabetes, and cancer …

The amount of touristic and travel information existing on the Internet is overwhelming.
Recommender systems are typically used to filter irrelevant information and to provide …

The increasing number of publications on recommender systems for Technology Enhanced
Learning (TEL) evidence a growing interest in their development and deployment. In order …

In various research areas, the availability of open datasets is considered as key for research
and application purposes. These datasets are used as benchmarks to develop new …

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

In the world of recommender systems, it is a common practice to use public available
datasets from different application environments (eg MovieLens, Book-Crossing, or Each …