Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. There are plenty of resources available on the Web, both in terms of digital learning content and people resources (e.g. other learners, experts, tutors) that can be used to facilitate teaching and learning tasks. Recommendation methods have been used by the Educational Technology community to help identify suitable learning resources from a potentially overwhelming variety of choices. In addition, recommendation techniques are being used in Learning Analytics dashboards to provide actionable feedback to learners based on observed behavior and to recommend peer learners.
The aim of the Workshop is to bring together researchers and practitioners that are working on topics related to the design, development and evaluation of recommender systems in educational settings as well as present the current status of research in this area and create cross-disciplinary liaisons between the RecSys and LAK communities. Overall, it aims to outline the rich potential of Learning Analytics as an application area for recommender systems, as well as expose participants to the challenges of developing such systems in a learning analytics context.
We invite authors to submit their original unpublished work. The submissions need to be formatted using the LAK companion proceedings template. They should be submitted using EasyChair system using the link below and they should not exceed 12 pages.
Each of the submitted paper will be reviewed by at least two members if the Program Committee. The accepted papers will be published in the Companion Proceedings of the LAK 2020 conference.
*All submissions should be made through Easychair
EDRECSYS2020 will be organised as a half-day event as part of LAK 2020 conference. The Workshop aims to be an interactive, engaging experience that will motivate participants to get involved and start fruitful discussions on its topics. For that, it will combine several activities. On the one hand, a highly recognised keynote speaker will be invited to open the workshop. On the other hand, the Workshop would like to give to participants the opportunity to be engaged into creative and motivating discussions about the key issues related to LAK recommender systems. To this end, a panel of selected experts will be asked to pose a number of key questions that are related to enablers and challenges for recommender systems for learning, and then facilitate the discussion of these questions in a number of dedicated Working Groups.
Papers submitted to the workshop and accepted by the Program Committee will be presented during the workshop. However, the presentations are not given by the authors themselves. Instead, accepted papers will be presented this time by other authors in 5-10 minutes each. Thus, each author has to deal with a different topic in advance and so the workshop becomes more interactive. Subsequently, the actual author has time to comment briefly and to supplement explanations. After each presentation there will be a short discussion with all workshop participants about the paper. The Workshop is expected to end with a small ceremony for giving the best paper awards.