English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Educational Recommender Systems aim to provide students with search relevant results adapted to their needs or preferences and delivering those educational contents such as Learning Objects (LOs) that could be closer than expected. LOs can be defined as a digital entity involving educational design characteristics. Each LO can be used, reused, or referenced during computer-supported learning processes, aiming at generating knowledge, skills, attitudes, and competences based on the student profile. The aim of this paper is to present a student-centered LO recommender system based on a hybrid recommendation technique that combines three following approaches: content-based, collaborative and knowledge-based. In addition, those LOs adapted to the student profile are retrieved from LO repositories using the stored descriptive metadata of these objects. A testing phase with a case study is performed in order to validate the proposed hybrid recommender system that demonstrates the effectiveness of using this kind of approaches in virtual learning environments.

A Student-Centered Hybrid Recommender System to Provide Relevant Learning Objects from Repositories