Inaugural lecture

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Inaugural lecture

  1. 1. inaugurale les From findability to awareness: a short overview and future vision Katrien Verbert WISE research group Department of Computer Science katrien.verbert@vub.ac.be
  2. 2. Human-Computer Interaction HCI group prof. Erik Duval PhD. researcher Oct. 2003 – Feb. 2008 Post-doc Feb. 2008 – Dec. 2012 Web engineering group Assistant Professor Jan. 2013 – Dec 2013 WISE Assistant Professor Jan. 2014 – … 2
  3. 3. Julie Lagaisse 26-07-2013 3
  4. 4. Overview research topics 2003  |  2004  |  2005  |  2006  |  2007  |  2008  |  2009  |  2010  |  2011  |  2012  |  2013|  2014   Flexible reuse of content components Semi-automatic content assembly Interaction with RecSys • Content models • Metadata • Repositories • Recommendation • Visualisation Recommendation + Visualisation Technology Enhanced Learning (TEL) – Music – Research Information Systems - Healthcare 4
  5. 5. Overview research topics 2003  |  2004  |  2005  |  2006  |  2007  |  2008  |  2009  |  2010  |  2011  |  2012  |  2013  |  2014   Flexible reuse of content components Semi-automatic content assembly Interaction with RecSys • Content models • Metadata • Repositories • Recommendation • Visualisation Recommendation + Visualisation Technology Enhanced Learning (TEL) – Music – Research Information Systems - Healthcare 5
  6. 6. 6
  7. 7. 7
  8. 8. src: http://www.sh3.com/content-reuse-reduces-technical-translation-cost/ 8
  9. 9. That easy? Typical workflow example… 9
  10. 10. 10
  11. 11. Shared content often coarse-grained Time consuming Tedious and error-prone 11
  12. 12. Authoring-by-aggregation •  Decompose existing content into reusable components •  Integrate support for reusing components in existing authoring tools 12
  13. 13. 13
  14. 14. MS PowerPoint plug-in 14
  15. 15. User Evaluation withoutalocom withalocom Significance (2-tailed) 20 participants Total time (in minutes) 20.03 17.79 0.147 Created 2 presentations: Time normalized by number of slides 3.32 2.2 0.001 Time normalized by number of subtopics 4.5 2.9 0.016 1.  without alocom support 2.  with alocom support Measured characteristics: 1.  Time 2.  Manual versus semiautomatic reuse 3.  Granularity 4.  User satisfaction 15
  16. 16. Quality evaluation 19 reviewers 4 quality parameters: 1.  Completeness 2.  Conciseness 3.  Relevancy 4.  Accuracy 16
  17. 17. 17
  18. 18. RAMLET ¤  Resource Aggregation Model for Learning, Education and Training ¤  Defines common nomenclature and conceptual model ¤  to represent structural aspects in a uniform way ¤  covers: ¤  MPEG-21 DID ¤  Atom ¤  OAI-ORE ¤  IMS CP ¤  METS 18
  19. 19. Overview research topics 2003  |  2004  |  2005  |  2006  |  2007  |  2008  |  2009  |  2010  |  2011  |  2012  |  2013  |  2014   Flexible reuse of content components Semi-automatic content assembly Interaction with RecSys • Content models • Metadata • Repositories • Recommendation • Visualisation Recommendation + Visualisation Technology Enhanced Learning (TEL) – Music – Research Information Systems - Healthcare 19
  20. 20. Semi-automatic assembly of content Research visit Post-doctoral fellowship ¤  host: Brigham Young University (US) ¤  host university: KU Leuven, Belgium ¤  supervisor: prof. David Wiley ¤  supervisor: prof. Erik Duval ¤  period: Jan 2009 – April 2009 (3 months) ¤  period: Oct 2009 – Sept 2012 20
  21. 21. Tracking traces to support recommendation and visualisation www.role-project.eu 21
  22. 22. Recommender systems 22
  23. 23. 23
  24. 24. Recommender systems RecSysTEL workshop 2010, 2012 at RecSys and EC-TEL workshop co-chair RecSysChallenge at RecSys 2012 track co-chair Stellar Alpine Rendez-Vous 2009, 2011 workshop co-chair LAK 2013: Int. conference on Learning Analytics and Knowledge program co-chair 24
  25. 25. http://bit.ly/acBKsp 25
  26. 26. Verbert, Katrien; Manouselis, Nikos; Ochoa, Xavier; Wolpers, Martin; Drachsler, Hendrik; Bosnic, Ivana; Duval, Erik. Contextaware recommender systems for learning: a survey and future challenges, IEEE Trans. on Learning Technologies, 18 p. (2012) 26
  27. 27. Visualization to support selfawareness and reflection Co-supervision 2 PhD students: ¤  Sten Govaerts (currently at EPFL) ¤  Jose Luis Santos (KU Leuven) www.role-project.eu 27
  28. 28. Student Activity Meter (SAM) Govaerts, S., Verbert, K., Duval, E., & Pardo, A. (2012, May). The student activity meter for awareness and self-reflection. In CHI'12 EA (pp. 869-884). ACM. 28
  29. 29. Overview research topics 2003  |  2004  |  2005  |  2006  |  2007  |  2008  |  2009  |  2010  |  2011  |  2012  |  2013  |  2014   Flexible reuse of content components Semi-automatic content assembly Interaction with RecSys • Content models • Metadata • Repositories • Recommendation • Visualisation Recommendation + Visualisation Technology Enhanced Learning (TEL) – Music – Research Information Systems - Healthcare 29
  30. 30. Flexible interaction with RS Research visit ¤  Host: Carnegie Mellon University & University of Pittsburg ¤  Collaboration: John Stamper, Peter Brusilovsky Second post-doctoral fellowship FWO ¤  host university: KU Leuven, Belgium ¤  supervisor: Erik Duval ¤  period: Oct 2012 – Sept 2015 ¤  Period: April 2012 – June 2012 (3 months) 30
  31. 31. Problem statement ¤  Complexity prevents users from comprehending results ¤  Trust issues when recommendations fail ¤  Aggravated with contextual recommendation ¤  The black box nature of RS prevents users from providing feedback ¤  Algorithms typically hard-wired in the system code ¤  generate a list of top-N recommendations ¤  little research has been done to study more flexible approaches 31
  32. 32. Conference Navigator 32
  33. 33. Interrelations agents – users - tags 33
  34. 34. Interrelations agents – users 34
  35. 35. Interrelations agents - tags 35
  36. 36. TalkExplorer 36
  37. 37. effectiveness How frequently a specific combination type produced a display that was used to bookmark at least one interesting item Dimensions of relevance are not equal The more aspects of relevance are used, the more effective it is Especially effective are fusions across relevance dimensions 37
  38. 38. Summary results 38
  39. 39. information visualisation - information retrieval - information (data) mining 39
  40. 40. http://www.youtube.com/watch?v=9LwSx1V6Yxk 40
  41. 41. Vision for future research 41
  42. 42. Combining information mining and visualization Core objectives: •  make mining results comprehensible for users •  enable users to steer the information mining process
  43. 43. Research questions ¤  RQ1: How can information visualization techniques enable users to gain insight into the rationale of intelligent systems? ¤  RQ2: How can users explore these visualizations and steer the analysis process through input and feedback? ¤  RQ3: How can analysis techniques integrate input from users and automatic methods for acquiring contextual variables, while allowing for the continuous dynamic adaption depending on changing user interests and context? 43
  44. 44. Text mining Context-aware applications Flexible interactive Interfaces Learning analytics 44
  45. 45. Anthony Don, Elena Zheleva, Machon Gregory, Sureyya Tarkan, Loretta Auvil, Tanya Clement, Ben Shneiderman, and Catherine Plaisant. 2007. Discovering interesting usage patterns in text collections: integrating text mining with visualization. In CIKM '07 45
  46. 46. Context-aware applications 46
  47. 47. Learning analytics 47
  48. 48. Learning analytics
  49. 49. Source: Mathieu Plourde 49
  50. 50. http://lakconference.org/
  51. 51. http://www.nmc.org/pdf/2014-nmc-horizon-report-he-EN.pdf Slide source: Erik Duval 51
  52. 52. Collaborations Effie Law, Univ. of Leicester, UK Erik Isaksson, Matthias Palmer Uppsala University TU Eindhoven, RWTH Aachen, FIT Univ. Paul David Wiley Alexander Nussbaumer, TU Graz Sabatier BYU EPFL Nikos Manouselis, Agro-know UC3M Univ. of Pittsburgh (P. Brusilovsky) , Carnegie Mellon University Dan Suthers University of Hawaii Xavier Ochoa ESPOL, Ecuador research stays Denis Parra PUC, Chile Abelardo Pardo University of Sydney 52
  53. 53. Key publications ¤  Verbert, K., Parra, D., Brusilovsky, P. and Duval, E. (2013). Visualizing recommendations to support exploration, transparency and controllability. In Proceedings of the 17th International Conference on Intelligent User Interfaces (IUI’13), IUI’13, pages 1-12, New York, NY, USA, 2013. ACM. ¤  Verbert, K., Govaerts, S., Duval, E., Santos, J.L., Van Assche, F., Parra, G., Klerkx, J. (2013). Learning Dashboards: an Overview and Future Research Opportunities. Personal and Ubiquitous Computing (PUC) Journal, 16 pages, Springer. ¤  Verbert, K., Manouselis, N., Ochoa, X., Wolpers, W., Drachsler, H., Bosnic, I., and Duval, E. (2012) Context-aware recommender systems for learning: A survey and future challenges. IEEE Transactions on Learning Technologies, 5(4):318-335, 2012. ¤  Verbert, K., Ochoa, X., Derntl, M., Wolpers, M., Duval, E. (2012). Semi-automatic assembly of learning resources. Computers and Education, 59(4), 1257-1272. ¤  Verbert, K. and Duval, E. (2008). ALOCOM: A Generic Content Model for Learning Objects. International Journal on Digital Libraries, 9(1), pp. 41-63, 2008. 53
  54. 54. Thank you! Questions? katrien.verbert@vub.ac.be @katrien_v 54
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