Communities, Individuals, and New Technologies:

1. Communities, Individuals, and New Technologies: An E-Learning Perspective Gord McCalla ARIES Laboratory Department of Computer Science University of Saskatchewan Saskatoon, Saskatchewan CANADA

2. The Beauty of PowerPoint • We shall • fight them on • the beaches • the landing fields • the hills • never surrender • For more see • www.neversurrender.gov.uk

3. Me • professor of Computer Science, U. of S. • longstanding research contributions in AI-ish areas (since 1968!) • natural language dialogue • e-learning: artificial intelligence in education • user modelling and personalization • broad interdisciplinary interests • applications perspective: relevance trumps precision - the real world is really messy • openness to ideas from students: listen to youth (students are the big academic advantage, other than tenure!) • longstanding active member of many CoPs - scientific communities, academic communities, hobby and sporting communities, family communities, …

4. Take Away Points • key issues • fragmentation of • knowledge • culture • learning and teaching • technology • individualization, personalization • context: users, tasks, goals • change: situational (the world changes) and purposeful (education) • granularity • research projects: towards new technological support for learning communities • I-Help peer help system • ecological approach to capturing and using information about end-use of learning objects • LORNET NSERC NCE: adding agents to learning communities

5. Part 1: The Information Revolution • the information revolution is just getting underway • • coming soon: • - the billion channel universe • - radical impact of information technology on work and play • - major paradigm shifts in all areas of intellectual enquiry • - information technology pervasively part of our life • - fundamental shift in our perspectives of ourselves in relation to the world • • leading to the fragmentation of • - culture - learning - teaching - technology

6. Fragmentation of Culture • people need to put up barriers to stay sane • • localized perspective on cyberspace: • the electronic village • • each person’s village is unique: relativistic, not global • • village shares many of the characteristics of a real village: neighbours, professionals, friends, community organizations, (information) markets • • person only knows something when it comes into their village

7. Fragmentation of Culture • each village overlaps a wider world • • a person is also part of many virtual communities extending beyond their village boundaries: explicit and implicit • - each focussed on its own issues • - each with its own language and culture • - overlapping each other • - each person a member of many such communities • • learning is part of most such communities

8. the electronic village virtual communities

9. Fragmentation of Learning and Teaching • information flows at the speed of light, knowledge at the speed of human understanding • • learning between communities • - identifying the knowledge to be spread • - supporting its spread: finding collaborators to foster understanding between communities (diplomats, negotiation) • • learning within a community • - top down from community leaders and those bringing in outside knowledge (teachers, apprenticeship) • - collaboratively through internal debate • - immersing new village members in community culture

10. learning between communities

11. Fragmentation of Learning and Teaching • cultural fragmentation means learning is partitioned and fragmented • • “on-line”, learning can happen as needed in small chunks, in the context of on-going activities: just in time learning, fragmented knowledge • • human teachers are often needed, to help integrate knowledge with culture, to help translate knowledge into terms appropriate to learners in other communities • • each person can be teacher or learner, depending on the situation: fragmentation of roles

12. Fragmentation of Technology: Software Without Boundaries • the boundaries of a software system are increasingly indefinite • • software is fragmented into many quasi-independent entities (agents) • • many of these software entities come from outside a particular application “package” • • behaviour of such software systems is emergent, like an ecosystem, fundamentally unpredictable • • distinction between procedures and data, hardware and software blurs • • software exists simultaneously at manylevels of detail • • software is embedded in a complex social environment

13. Fragmentation of Technology: Software Without Boundaries • software takes on a particular coherence only relative to end use • • as defined by the purpose of the technology • • as defined by the tasks and goals of the people using it • • as defined by other people involved • • as defined by the communities in which it is used • • as defined by the resources available

14. Implications for the Design of Systems to Support E-Learning Communities • the importance of the individual • tools to support personalization • user modelling: user portfolio • motivation: the affective dimension • the importance of communities • tools to support translation of community culture and language to other communities • knowledge negotiation, knowledge brokers • community modelling • centrality of context • focus on pragmatics more so than syntax, semantics • main context elements: purposes,goals, tasks, users, resources • nothing is independent of context: active modelling

15. Implications for the Design of Systems to Support E-Learning Communities • natural “forcing functions” of information and communications technology • fundamentally localizing not globalizing: fragmentation • broadening individual perspectives • agents as a unifying metaphor • the constancy of change • tracking user behaviour: high bandwidth of interaction • possibility of mining user behaviour: the ecological approach • various purposes: recommending people or information, evaluating systems, intelligent garbage collection, … • granularity • supporting grain shifts: between individual and group, between levels of knowledge

16. Current Research Projects • I-Help • a peer help system to support learning communities • Ecological approach • mining information about user interactions with learning objects for various purposes, eg. • recommending learning objects or helpers • finding patterns of end use • LORNET • adding agents to help learning communities manage and access learning objects

17. The I-Help System • peer help system in educational and workplace environments developed in ARIES over last 7 years • aimed at providing peer help and other help while learners actually solve problems, in school or the workplace: just-in-time, contextualized • several sub-systems (and more to come) • public discussion: open peer forums • private chat: “1-to-1”, peer helper found by system to help a learner overcome impasse • HA: helping the helper • underlying agent architecture • underlying agent environment • personal agent for every learner • I-Help economy: ICU’s, to aid motivation, resource allocation • various versions tested in university courses and workplace • thousands of users over the last 5 years (especially of Pub)

18. HA WEB PDF MATCHMAKER I-Help ? ? ?

19. I-HELP Public Discussion

20. I-HELP Public Discussion

21. I-Help Private Chat

22. I-Help Private Chat

23. I-Help Private Chat

24. I-Help Private Chat

25. I-Help Private Chat

26. The Ecological Approach: Overview • an approach to capturing information about users’ interactions with technology and using it for various purposes • being explored in the context of managing learning object repositories • based on keeping fine-grained user models of each learner and attaching these to the learning object the learner is interacting with • data mining, clustering, and collaborative filtering used to make sense of the user modelling information in context: for a particular purpose and particular learner(s) • agents representing learners and learning objects carry out the purposes

27. An Example Ecological System: Research Paper Recommender • Tiffany Tang’s Ph.D. thesis • recommending papers to graduate students preparing for research in a domain (eg. data mining) • learner models of readers attached to papers • recommendations made by clustering learners according to these models and predicting usefulness of papers for the student based on the cluster they map to • repository of papers automatically kept up-to-date • new papers automatically found on CiteSeer • old papers can be intelligently garbage collected based on usage, or lack there-of • proposal with complete example due soon

28. An Example x x x x x ? x x ?

29. The Appeal of the Ecological Approach • learning objects are activated: they are not passive, but take on responsibilities for their use in support of learning • learners are “in the loop”: personal agents allow learners to be part of the educational environment • focus is on end use: essentially learning objects are tagged by models of the learners who use them, not by context-independent content tags from a pre-defined ontology of standard terms • approach is ecological: as end use experience accumulates, there can be an ever more refined understanding of what works for whom

30. The Appeal of the Ecological Approach • decision making is contextual: information is actively interpreted in context and as needed for more appropriate reactions; re-use through context capture not de-contextualization • approach is extensible and adaptable: the agent-based approach allows new learning objects and learners to be added, old ones to be deleted • approach is modular: agent approach localizes decision making and improves robustness • approach supports diversity: learners, applications, and learning objects can be integrated into one system, unified by the agent metaphor • potential downsides: privacy and tractability!!!!!!

31. LORNET Project • Five year NSERC-sponsored research network investigating learning object repositories: • theme 1: interoperability (SFU) • theme 2: aggregation (TelUQ) • theme 3: active and adaptive learning objects (U. Sask.) • theme 4: learning object mining (U. Waterloo) • theme 5: multi-media and learning objects (Ottawa U.) • theme 6: integrative theme: telelearning operations system (TelUQ, and the rest)

32. LORNET - Theme 3 • explore ecological approach to capturing and using information about learners (McCalla) • MUMS user modelling middleware (Brooks, Winter) • instructional planning and recommending through agent negotiation (Vassileva) • personal agents and agents representing learning objects • granularity of learning and learning objects (Greer) • learning object (agent) reliability and scalability (Deters) • design, construction, deployment, and evaluation of application systems • in partnership with industrial sponsors (TRLabs, Inroad Solutions) • two entirely on-line courses with 1000’s of learning objects: CS service course; CS readiness course

33. Conclusion • ICT is localizing and fragmenting • must therefore support individualization and personalization • must also work to overcome effects of such fragmentation through support for knowledge negotiation between communities • really new technologies are possible • based on understanding actual end-use • contextualized by tasks, goals, users, resources • with a focus on pragmatics • for all sorts of purposes • virtual humans are still humans and virtual communities are still communities • look to human nature • social sciences need to be deeply engaged with ICT, perhaps helping to forge new models and paradigms, new to both traditional ICT and social science

34. Acknowledgements • colleagues past and present in the ARIES Laboratory • in particular Jim Greer, Julita Vassileva, John Cooke, Ralph Deters • a host of research associates and graduate students • funding from the Natural Sciences and Engineering Research Council of Canada • funding from the LORNET NSERC Network of Centres of Excellence • earlier funding from the TeleLearning Network of Centres of Excellence (I-Help) and the IRIS Network of Centres of Excellence (SCENT granularity-based advisor system)

35. Some References • G. I. McCalla, “The Ecological Approach to the Design of E-Learning Environments: Purpose-based Capture and Use of Information about Learners”. Journal of Interactive Media in Education, Special Issue on the Educational Semantic Web (eds. T. Anderson and D. Whitelock), May 2004.http://www-jime.open.ac.uk/2004/1 • J. Vassileva, G.I. McCalla, and J.E. Greer, “Multi-Agent Multi-User Modelling in I-Help”. User Modeling and User-Adapted Interaction J., Special Issue on User Modelling and Intelligent Agents (E. André and A. Paiva, eds.), 13 (1), 2003, 1-31. • G.I. McCalla, “The Fragmentation of Culture, Learning, Teaching and Technology: Implications for the Artificial Intelligence in Education Research Agenda in 2010”. Special Millennium Issue on AIED in 2010, Int. J. of Artificial Intelligence in Education, 11, 2000, 177-196. • Contact me at • mccalla@cs.usask.ca