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EdRecSys 2016 : International Workshop on Educational Recommender Systems


When Oct 13, 2016 - Oct 13, 2016
Where Omaha, USA
Submission Deadline Jun 1, 2016
Notification Due Jun 25, 2016
Final Version Due Jul 9, 2016
Categories    data mining   recommender system   education   learning

Call For Papers

Recommender systems have been developed to alleviate information overload, aid user decision-making, and achieve different forms of personalization. Their effectiveness and usability have been demonstrated in a number of applications, including e-commerce, movies, music, travel, and social networks. The same information filtering and personalization needs are now arising in the area of educational experiences and resources. The educational learning environment is no longer limited to in-class lectures, both teaching and learning can be taken place on the Web. For example, Technology Enhanced Learning (TEL) and Massive Open Online Courses (MOOC) are two of the most popular applications that can benefit from the application of recommendation technology. Other popular applications related to recommenders in the educational domain include book recommendations for school-aged readers (i.e., K-12) as well as and the recommendation of informal learning programs.

A variety of recommendation techniques can be used to assist educational recommendations, such as semantic or content-based recommender systems, transfer learning, or collaborative intelligence. Traditional strategies, however, are not sufficient in within the academic environment, as the generated suggestions are based on needs and expectations beyond user/content similarity/historical data. The availability of more heterogeneous information (such as friendships, fellowships, social media, interactions across multiple devices, user behaviors on multiple categories of items or activities) increases the demand to (i) effectively leverage these information sources to learn how they can interact in identifying suitable items to recommend and influence users’ preferences in the educational recommender systems, and (ii) exploit these information to better suggest appropriate items (e.g., books, courses, programs, degrees, activities) to the end users.

The International Workshop on Educational Recommender Systems (EdRecSys) is a follow-up of the previous Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL):

RecsysTEL 2010: 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2010). In conjunction with the 4th ACM Conference on Recommender Systems (RecSys 2010) and the 5th European Conference on Technology Enhanced Learning (EC-TEL 2010). Barcelona, Spain, 29-30 September 2010.
RecsysTEL 2012: 2nd Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2012). In conjunction with the 7th European Conference on Technology Enhanced Learning (EC-TEL 2012). University of Saarbrücken (Germany), 18 – 19 September 2012.

The 3rd International Workshop on Educational Recommender Systems (EdRecSys) will be a half-day workshop held in conjunction with the 2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI’ 16), October, 2016, in Omaha, USA. The workshop aims to provide a dedicated forum for discussing open problems, challenges, applications and innovative research approaches in fusing different resources and information for the design and development of effective educational recommender systems. Furthermore, the workshop will feature invited speakers and/or panel discussions which will focus on interesting aspects, controversial issues, or unsolved problems related to educational recommender systems.

The scope of this workshop includes, but is not limited to:

Applications of Educational Recommender Systems
Academic (e.g., academic programs, degrees or courses ) recommendations
Recommendation of informal learning opportunities
Book recommendations
Scholar/Paper/Citation recommendations
Recommendations in Massive Open Online Courses (MOOC)
Recommendations in Technology Enhanced Learning (TEL)
Recommendations of materials for ESL users
Recommendations of K-12 educational search queries
Recommendations of materials for non-traditional student
Affective computing in educational recommender systems

Methodologies for Educational Recommender Systems
Educational Data Mining and Machine Learning
Semantic or content-based recommendations
Group/context-aware/trust-based/Cross-domain Recommendation
Affective/Emotion-aware Recommendation
Recommendation based on collaborative intelligence
Recommendation based on social networks or knowledge graphs
Recommendation based on transfer learning
Recommendations based on readability levels
Recommendations based on experts’ knowledge

Data Analytics and User Modeling for Educational Recommender Systems
Publicly available data sets for educational or TEL recommender systems
Information fusion for educational or TEL recommendation
Evaluation criteria and methods for educational or TEL recommender systems
User modeling for educational or TEL recommender systems

Paper submissions should be limited to a maximum of 4 pages (IEEE-CS format, extra payment is only available for one more extra page). The papers must be in English and should be formatted according to the IEEE 2–column format. The IEEE 2-column format and guidelines can be found at:
We accept two types of submissions:

Research Papers (4 pages): present original research work which should report on substantial contributions of lasting value.
Position Papers (2 pages): Discuss exciting new work that is not yet mature, or open challenges in promising research directions. We also accept papers presenting late-breaking research results and speculative or innovative work in progress.
All submitted papers will be reviewed by at least 2 program committee members on the basis of technical quality, relevance, significance, and clarity. The accepted papers will be included in the Workshop Proceedings published by the IEEE Computer Society Press.

The workshop only accepts online submissions. Submission system:

Important Dates (Tentative)
Submission Deadline: June 1, 2016
Acceptance Notification: June 25, 2016
Camera-Ready Deadline: July 9, 2016
Workshop Date: October 13, 2016
Conference Date: October 13-16, 2016

Workshop Co-Chairs
Olga C. Santos, UNED, Spain
Yong Zheng, DePaul University, USA
Sole Pera, Boise State University, USA
Robin Burke, DePaul University, USA
Guibing Guo, Northeastern University, China

Steering Committee
Nikos Manouselis, Agro-Know Technologies & ARIADNE Foundation, Greece
Hendrik Drachsler, Open Universiteit Nederlands, The Netherlands
Katrien Verbert, Katholieke Universiteit Leuven, Belgium

Publicity Chair
Yong Zheng, DePaul University, USA

Program Committee (to be completed)
Maria Bielikova, Slovak University of Technology, Slovak
Peter Brusilovsky, University of Pittsburgh, USA
Hana Bydzovska, Masaryk University, Czech Republic
Min Chi, North Carolina State University, USA
Michael Ekstrand, Boise State University, USA
Jonathan Gemmell, DePaul University, USA
Zhao Kang, Southern Illinois University, USA
Pythagoras Karampiperis, National Centre for Scientific Research Demokritos, Greece & Agroknow, Belgium
Estefania Martín, Universidad Rey Juan Carlos, Spain
Noboru Matsuda, Texas A&M University, USA
Cataldo Musto, University of Bari, Italy
Dennis Ng, Brigham Young University, USA
Weike Pan, Shenzhen University, China
Denis Parra, Pontifical Catholic University of Chile, Chile
Marko Tkalcic, Free University of Bozen-Bolzano, Italy

Related Resources

RecSys 2017   RecSys 2017 : 11th ACM Conference on Recommender Systems
ECML-PKDD 2017   European Conference on Machine Learning and Principles and Practice of Knowledge Discovery
AdCHIReS 2017   Special Issue on Advances in Computer-Human Interaction for Recommender Systems
DSAA 2017   The 4th IEEE International Conference on Data Science and Advanced Analytics 2017
ICONIP 2017   International Conference on Neural Information Processing
ICDM 2017   IEEE International Conference on Data Mining 2017
RecSys@FLAIRS 2017   Recommender Systems Special Track at the International FLAIRS Conference
KDD 2017   Call for Research Papers
ACM SAC-RS 2017   ACM SIGAPP Symposium On Applied Computing 2017 - Track on Recommender Systems: Theory and Applications
MLRec 2017   MLRec 2017 : 3rd International Workshop on Machine Learning Methods for Recommender Systems