1. Theme 3: Active and Adaptive Learning Objects “Influenced by and Influencing Social Computing” Jim Greer, Gordon McCalla, Ralph Deters, Julita Vassileva Department of Computer Science University of Saskatchewan

2. University of Saskatchewan Introduction  Why social computing?  Our deployed learning environments have convinced us that there is an increasing social dynamic to be captured  This dynamic has two sides relevant to educational technology research:  It’s important. Learners collaborate just-in- time all of the time, and expect nothing less. Access to email, chat, and instant messaging within a learning environment has changed the ways learners do this online.  We can capture it. Learners are turning increasingly to technology to engage in their learning activities, and we have the option to be in the thick of it all. Introduction 3 Specific projects: ▪ Jim Greer 4 ▪ Julita Vassileva 4 ▪ Ralph Deters 7 ▪ Gord McCalla 8 Conclusions 2

3. University of Saskatchewan Social Computing in E-Learning  We teach/learn in a [usage] data saturated environment  The tools in iHelp capture this attention metadata  iHelp Courses, a standards-based research LCMS  iHelp Discussions, an asynchronous forum system  iHelp Chat, a synchronous forum system  iHelp Share, online collaborative code annotation groupware (demo at poster session)  We aim to capture fine grained attention metadata  Who reads what? [post/object/chat]  How long do they read it? Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

4. University of Saskatchewan Making Sense of Data  Of course, usage data isn’t the only data of interest  Content data  We are working with theme 1 (SFU) theme 4 (Waterloo) to dig into this data a bit more  Can ontologies help to organize and provide deductive reasoning over our collected data?  Can ontologies provide a bridge between real usage data and learning standards (e.g. IMS LD)?  How do user inputs (e.g. collaborative tagging) compare to automatic metadata generation?  Can content metadata be leveraged alongside content interaction metadata? Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

5. University of Saskatchewan Awareness and Assistance in iHelp  Are my friends around?  Who is doing what?  Where do I stand?  Who is willing and able to help?  Is an instructor available?  What resources might fit my needs right now?  Who is at risk?  How healthy is the learning environment?  What kinds of interactions are occurring? Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

6. University of Saskatchewan Specific Projects - Jim Greer  Christopher Brooks  Basic Approach  Real systems, real learners  Large scale deployments  Collaboration in a safe environment  Building respect for privacy  Enabling and utilizing publicity Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

7. University of Saskatchewan iHelp Share  The iHelp project is still ongoing  Collaborative document annotation  Programmer help  Writing help  Augmented by chat and discussion or voice  Why not collaborative editing?  Research opportunities  Willingness to collaborate  Tutor training  Demo by Stephen Damm, student Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

8. University of Saskatchewan Privacy in e-Learning  Virtual learning communities may not be a circle of close friends  How to protect privacy  Add pseudonymity  Building trust through reputation  But without full identity  Reliable sharing of reputation data  How?  What about fusing partial reputations?  What about transfer of reputation?  Poster by Mohd Anwar, PhD student Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

9. University of Saskatchewan E-Portfolios to Learner Models  Learner model is a detailed cognitive representation of a learner  Can an e-portfolio initialize a learner model?  What information can be automatically extracted?  How can evidence be used to support claims about cognitive abilities?  The process of “evidencing”  Reflection has its benefits  User study  Poster by Zinan Guo, MSc student Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

10. University of Saskatchewan Specific Projects – Julita Vassileva  Comtella – a community for sharing  Participation is the key problem!  Previous (now deployed) approaches:  Incentive mechanisms: rewarding participation through social visibility, status and privileges  Successful, but do not necessarily help learning (students “optimize” their participation to yield the rewards)  New approaches:  Making the system immediately useful – embedding sharing into Personal Information Management (PIM) – in blogs  Exploiting/Fostering interpersonal relationships to generate recommendations of RSS  Bridging communities – in this way even small communities can reach a “critical mass” since the community doesn’t need to provide all the services and users don’t need to start from scratch Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

11. University of Saskatchewan Collaborating through blogs  Sharing? Why?  Need to be useful for self first, then to others  Sharing by default? Personal info management  Need to be convenient, manage access seamlessly  Blogs – personal info space  Currently – open for everyone to see (like a homepage), e.g. MySpace, LifeJournal  Managing access rights – very much needed  Who sees what? Delegating access rights to groups.  Collaborating – allowing others to modify blog  Prototype – a blog system allowing users to manage access rights to their blogs  Special language: user groups, access rights packages (roles), item groups (rooms)  Usability evaluation  See Indratmo’s poster (PhD student) Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

12. University of Saskatchewan Social networks for recommending content  Current recommender systems:  Content based, Collaborative and Hybrid  Collaborative recommender systems use data about past user actions (rating, buying), correlates it and finds users who have liked similar things in the past  recommendations  However, recommendations are faceless “people who in the past have bought similar things like you bought this item”.  Information spreads using social networks  Diseases spread also using social networks  Open model of the relationships of influence between users,  show it to users,  allow users to add /remove people of influence they wish  use these relationships to recommend content  applied to recommend RSS  Evaluation: outperforms classic collaborative filtering even in a static database  Applicable also for recommending new items  See Andrew Webster’s Poster (MSc student) Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

13. University of Saskatchewan Bridging online communities  Currently, online communities are “islands”.  Can we enable users to seamlessly jump across communities, without abandoning their old communities?  Three problems:  Identity management across communities  Translation of user data across communities  Negotiation of policies across communities  Exploring solutions in the Comtella system  Mutli-community, multi-node framework  Different user roles, rights and priviledges  Communities and nodes are autonomous, with own policies.  Decentralized user modelling  See Tariq Muhammad’s poster (MSc student) Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

14. University of Saskatchewan Scalability & Mobility – Ralph Deters  How to enable scalable solutions?  Open, agile, manageable, etc… with great performance  How to support users of mobile devices?  Support the mobile learner, anytime, anywhere Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

15. University of Saskatchewan Scalability & Manageability  Delivering/Accessing Learning Objects via Web Services  SOAP is Expensive  How to handle large volumes of requests?  Scheduling of Requests  Dmytro Dyachuk’s Poster Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

16. University of Saskatchewan Scalability & Manageability  Defining Learning Workflows  Use variety of accessible Learning Objects  How to manage instances of workflows?  How to ensure SLA?  ……  Management of Workflows  Dong Liu’s Poster Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

17. University of Saskatchewan Scalability & Manageability  Accessing Learning Objects  What happens if some LO are not accessible?  How to use redundancy?  How to ensure more reliable access?  P2P?  Integration of P2P into Web Services  Self-organizing  Dynamic discovery  Weidong Han - Work completed Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

18. University of Saskatchewan Supporting Mobile Learners  Enabling access without stable networks! Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

19. University of Saskatchewan Challenges Wireless Network XML Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

20. University of Saskatchewan Supporting Mobile Learners  Using a cache to overcome signal loss!  How to cache  What to cache?  How to cache?  When to cache?  Location of cache?  …..  Model-Driven Caching  Xin Liu’s Poster Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

21. University of Saskatchewan Specific Projects: Gord McCalla  Basic philosophy  fragmented learning environments: just in time learning, mediated by each individual learner’s various virtual communities  active learner modelling: model only what is needed for a particular pedagogical purpose  ecological approach: each learning object in a learning object repository has attached to it all the information known about each learner who interacted with it and what the interactions were at a fine-grained level; these learner model instances can be mined for interesting pedagogical insight Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

22. University of Saskatchewan Research Paper Recommender  Tiffany Tang, Ph.D., expected 2007  capturing pedagogical features of research papers in order to recommend them to students who are learning about a research area  matching these pedagogical features to models of learners to determine which papers are appropriate for which learners  ties in to ecological approach: can we capture information about learners’ actual interactions with the learning material in order to make better recommendations? Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

23. University of Saskatchewan Data Mining of Learner Interactions  Wengang Liu, M.Sc., expected 2007  huge amount of interaction data in iHelp and iHelp courses  are there patterns in these data?  one approach: bottom-up from data trying to find pedagogically useful patterns, using data mining and clustering algorithms  current approach: define pedagogically interesting aspects of the learner and try to build metrics to measure these aspects  ties in to ecological approach  see poster at this conference Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

24. University of Saskatchewan Building Usable Metadata  Scott Bateman, M.Sc., expected 2007  goal is to make the tagging by humans of learning objects more flexible and more useful  one approach: social tagging by the learners, implemented in OATS system  another approach: use WordNet as a closed ontology from which learners (and teachers) select metadata vocabulary, implemented in CommonFolks system  look for OATS demo, talk on CommonFolks, and poster Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

25. University of Saskatchewan OATS Screen Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

26. University of Saskatchewan Purpose-Based Open Learner Modelling  Collene Hansen, M.Sc., expected 2007  goal is to open the learner model to the learner, the teacher, or to other learners when appropriate  for various pedagogical purposes active models of learner(s) can be computed and displayed appropriately  can be very informative to learners and teachers  system built and now being tested in courses at U. of S.  see example, next slide Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

27. University of Saskatchewan An Example Purpose and Visualization Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

28. University of Saskatchewan Enhancing Social Capital  Ben Daniel, Ph.D., expected 2007  goal is to understand what affects social capital in virtual learning communities and in distributed communities of practice  many empirical studies carried out, seeking variables and studying their affect  modelling of variable interactions with Bayes-Nets  see paper at this conference Introduction Specific projects: ▪ Jim Greer ▪ Julita Vassileva ▪ Ralph Deters ▪ Gord McCalla Conclusions

29. University of Saskatchewan The Broader Picture  In addition to in-lab projects, we are working with industrial and other partners  Parchoma Consulting: Dissemination of the state of the art in learning object practice. Developed and deployed content for the Canadian Association of Prior Learning Assessment (CAPLA), using iHelp as a basis  Desire2Learn: Initial meetings on technology integration, focusing on issues in and around data mining  Technology Enhanced Learning: Cooperating with university endeavours to realise iHelp systems in a larger scenario, and bringing the concepts of sociability into the online classroom  TR Labs: Working with theme 3 on many of the systems issues that crucially affect performance of e-learning systems Introduction Specific projects: ▪ Jim Greer ▪ Ralph Deters ▪ Julita Vassileva ▪ Gord McCalla Conclusions

30. University of Saskatchewan Conclusions  The educational technology domain could be a role model for new methods in psychological and social sciences research  Learning is necessarily situated in the real world – small experiments and “controlled studies” have limited impact  E-learning provides environments that are both saturated in data about learner interactions and also about which we can know much about learner purposes and goals: implies we can carry out fine grained studies in the real world  This kind of education research may be a prototype for fine-grained studies of people in various kinds of social situations, not just in learning contexts  Happy to answer any questions! Introduction Specific projects: ▪ Julita Vassileva ▪ Ralph Deters ▪ Jim Greer ▪ Gord McCalla Conclusions