8. Day 1, Session 1
• Beham, Kump, Ley, Lindsteadt: Recommending Knowledgeable People in a
Work-Integrated Learning System
• Schoefegger, Seitlinger, Ley: Towards a User Model for Personalized
Recommendations in Work-Integrated Learning: A Report on an Experimental
Study with a Collaborative Tagging System
10. Day 1, Session 2
• Wang, Sumiya: Semantic Ranking of Lecture Slides based on Conceptual
Relationship and Presentational Structure
• Thai-Nghe, Drumond, Krohn-Grimberge, Schmidt-Thieme: Recommender
System for Predicting Student Performance
• Santos, Boticario: Modeling recommendations for the educational domain
12. Day 1, Session 3
• Marino, Paquette: A competency-driven advisor system for multi-actor learning
or work environments
• Romero, Burgos: A competency-driven advisor system for multi-actor learning or
work environments
• Sie, Bittner, Sloep: A Simulation for Content-based and Utility-based
Recommendation of Candidate Coalitions in Virtual Creativity Teams
• Drachsler, Bogers, Vuorikari, Verbert, Duval, Manouselis, Beham, Stern,
Lindsteadt, Friedrich, Wolpers: dataTEL – Issues and Considerations regarding
Sharable Data Sets for Recommender Systems in Technology Enhanced Learning
16. Day 2, Session 1
• Brusilovsky, Cassel, Delcambre, Fox, Furuta, Garcia, Shipman, Yudelson:
Social Navigation for Educational Digital Libraries
• Mödritscher: Towards a Recommender Strategy for Personal Learning
Environments
•
18. Day 2, Session 2
• Michlik, Bieliková: Exercises Recommending for Limited Time Learning
• Broisin, Brut, Butoianu, Sedes, Vidal: A Personalized Recommendation
Framework based on CAM and Document Annotations
• Sicilia, Sanchez-Alonso, Garcia-Barriocanal, Cechinel: Exploring user-based
recommender algorithms in large learning object repositories: the case of
MERLOT
• Shelton, Duffin, Wang, Ball: Linking OpenCourseWares and Open Education
Resources: Creating an Effective Search and Recommendation System
23. Schoefegger, Seitlinger, Ley
Towards a User Model for Personalized Recommendations in
Work-Integrated Learning: A Report on an Experimental
Study with a Collaborative Tagging System
55. Go interactive
Interactive versions of the bibliographic networks are available
online
•http://adenu.ia.uned.es/workshops/recsystel2010/bibliometrics/cocitations.html
•http://adenu.ia.uned.es/workshops/recsystel2010/bibliometrics/coauthors.html
56. Want to know more?
http://twitter.com/wollepb
http://isitjustme.de
http://artefact-actor-networks.net
Wolfgang Reinhardt
University of Paderborn
Department of Computer Science
Computer Science Education Group
http://ddi.upb.de