SIRTEL 2007
 Social Information Retrieval in
Technology-Enhanced Learning

       September 18, Sissi, Crete, Greece
Who?

• Riina Vuorikari, Katholieke Universiteit
  Leuven & European Schoolnet, Belgium

• Nikos Manouselis, Informatics L...
Where? When?

• Sissi, Crete, Greece
  – September 18, 2007

• In conjunction with 2nd European
  Conference on Technology...
Why?


quot;We use people to find content. We
   use content to find people.“

          P.Morville, 2004
Background

• Social information retrieval (SIR) around
  since the popularisation of WWW

• Refers to family of technique...
In TEL

• SIR systems discussed and prototyped
  in TEL since late ‘90s

• Manouselis et al., 2008 about 10 TEL
  recommen...
A 2nd wave?



• Web 2.0 technologies & applications
  seem to be bringing a new generation
  of SIR systems into this dis...
SIR in TEL today 1/6

Collaborative tagging

• not anymore one metadata record produced
  by one content expert…

• …but l...
SIR in TEL today 2/6

Social bookmarking
• Reference to photos, books, links, music,..
• allows other users to navigate in...
SIR in TEL today 3/6

Expressing social ties
• not only seeing networks of friends
• professional, personal, recreational,...
SIR in TEL today 4/6

“Clicksteam” & user behaviour on the
 Web not property of commercial
 applications

• Attentional me...
SIR in TEL today 5/6

Recommender systems introduced to
 propose learning resources, events,
 tutors, study-buddies to use...
SIR in TEL today 6/6

Content for educational use seeing a
 change
• more & more user-generated content
  on the Web
• Col...
To sum up…

• Social context is how we express
  the who, where and with whom

• Social content are the objects or
  digit...
Agenda

• 09h30 - 10h00: Keynote MyStrands
• 10h00 - 10h30: Coffee
• 10h30 - 12h30: Annotation & Visualisation
  Session
•...
Lets start!
KEYNOTE

MyStands
• Music recommender
  – And more... buy music, find likeminded, be
    recommended, MyStrands.tv
• Franc...
Next



Annotation & Visualisation
         Session
Next

• 10h30 - 11h00:
  – Analysis of User Behavior on Multilingual Tagging of Learning
    Objects (Riina Vuorikari, Xav...
Next



Recommender Systems
      Session
Next
• 14h00 - 14h30:
   – Recommendations for learners are different: Applying memory-based
     recommender system techn...
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What's new in SIR for TEL? Sirtel07 Intro

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These are slides to introduce the SIRTEL07 workshop, its goals and sessions with speakers.

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What's new in SIR for TEL? Sirtel07 Intro

  1. 1. SIRTEL 2007 Social Information Retrieval in Technology-Enhanced Learning September 18, Sissi, Crete, Greece
  2. 2. Who? • Riina Vuorikari, Katholieke Universiteit Leuven & European Schoolnet, Belgium • Nikos Manouselis, Informatics Laboratory of Agricultural University of Athens & Greek Research and Technology Network, Greece • Erik Duval, Katholieke Universiteit Leuven, Belgium & ARIADNE Foundation
  3. 3. Where? When? • Sissi, Crete, Greece – September 18, 2007 • In conjunction with 2nd European Conference on Technology Enhanced Learning (EC-TEL'07) – September 19-20, 2007
  4. 4. Why? quot;We use people to find content. We use content to find people.“ P.Morville, 2004
  5. 5. Background • Social information retrieval (SIR) around since the popularisation of WWW • Refers to family of techniques that assist users in obtaining information by harnessing knowledge or experience of other users – collaborative filtering, social network analysis, social navigation, social bookmarking, … – sharing queries, tags, annotations, ratings, evaluations, …
  6. 6. In TEL • SIR systems discussed and prototyped in TEL since late ‘90s • Manouselis et al., 2008 about 10 TEL recommender systems – lots more conceptual designs – very few implemented & tested with real users
  7. 7. A 2nd wave? • Web 2.0 technologies & applications seem to be bringing a new generation of SIR systems into this discussion
  8. 8. SIR in TEL today 1/6 Collaborative tagging • not anymore one metadata record produced by one content expert… • …but lots of annotational and attentional metadata by lots of users
  9. 9. SIR in TEL today 2/6 Social bookmarking • Reference to photos, books, links, music,.. • allows other users to navigate in personal collections • Similar resource-user-tag links – recommendation purposes – emerging social networks
  10. 10. SIR in TEL today 3/6 Expressing social ties • not only seeing networks of friends • professional, personal, recreational, etc • Portability of these networks an issue for better designs of tmr – social-network-portability group – PeopleWeb
  11. 11. SIR in TEL today 4/6 “Clicksteam” & user behaviour on the Web not property of commercial applications • Attentional metadata a huge source of information that is focused on now – Contextual Attention Matadata, Attention Profiling Mark-up Language, Attention Trust, …
  12. 12. SIR in TEL today 5/6 Recommender systems introduced to propose learning resources, events, tutors, study-buddies to users • Potential to play an important educational role as well
  13. 13. SIR in TEL today 6/6 Content for educational use seeing a change • more & more user-generated content on the Web • Collaboration aspect is facilitated by Web
  14. 14. To sum up… • Social context is how we express the who, where and with whom • Social content are the objects or digital artefacts that are in the center of the communication, exchange and networks
  15. 15. Agenda • 09h30 - 10h00: Keynote MyStrands • 10h00 - 10h30: Coffee • 10h30 - 12h30: Annotation & Visualisation Session • 12h30 - 14h00: Lunch • 14h00 - 16h00: Recommender Systems Session • 16h00 - 16h30: Coffee • 16h30 - 17h30: Discussion Session: Enablers & Challenges for SIR in TEL
  16. 16. Lets start!
  17. 17. KEYNOTE MyStands • Music recommender – And more... buy music, find likeminded, be recommended, MyStrands.tv • Francisco J.Martin (CEO) • Jim Shur (Chief Architect) • Rick Hangartner (Chief Scientist)
  18. 18. Next Annotation & Visualisation Session
  19. 19. Next • 10h30 - 11h00: – Analysis of User Behavior on Multilingual Tagging of Learning Objects (Riina Vuorikari, Xavier Ochoa, Erik Duval) • 11h00 - 11h30: – Tag, Annotate, Rate and Share: Activites of Daily Living on the Web (Shelley Henson, Justin Ball, David Wiley, Brandon Muramatsu) • 11h30 - 12h00: – Reward structures for participation and contribution in K-12 OER communities (Griff Richards) • 12h00 - 12h30: – Visualizing Social Bookmarks (Joris Klerkx, Erik Duval)
  20. 20. Next Recommender Systems Session
  21. 21. Next • 14h00 - 14h30: – Recommendations for learners are different: Applying memory-based recommender system techniques to lifelong learning (Hendrik Drachsler, Hans G. K. Hummel, Rob Koper) • 14h30 - 15h00: – Exploring affiliation network models as a collaborative filtering mechanism in e-learning (Miguel-Angel Sicilia, Salvador Sanchez-Alonso, Leonardo Lezcano) • 15h00 - 15h30: – Simulated Analysis of MAUT Collaborative Filtering for Learning Object Recommendation (Nikos Manouselis, Riina Vuorikari, Frans Van Assche) • 15h30 - 16h00: – System Demo: Knowledge Sharing in Information Seeking and Retrieval Situations (Preben Hansen, Claus-Peter Klas)

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