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Future Learning Landscapes  Towards the Convergence of Pervasive and  Contextual Computing, Global Social Media and  Seman...
Outline         ¢    Introduction         ¢    Web 2.0         ¢    Mobile, Pervasive, Ubiquitous Learning         ¢  ...
Introduction         ¢  Contributors           •  JM Gilliot, Telecom Bretagne, l’un de ses Blogs           •  C. Pham Ng...
WEB 2.0
Web 2.0Source: Dion Hincliffe     page 4   Hammam Sousse ISITC 2011   Futures Learning Landscapes
Web 2.0 - Applications         ¢  Blogs           •  Personal publication + comments by others           •  Linking facil...
Web 2.0 - Applications         ¢  Wikis           •  Collaborative writing & content organisation           •  For educat...
Web 2.0 - Applications         ¢  Conversational           Arenas           •  One-to-one or one-to-many conversations be...
Web 2.0 - Applications         ¢ Social     bookmarking          •  Keep reference of interesting material          •  Or...
Web 2.0 - Applications         ¢  Media    sharing and manipulation           •  Tools to upload, download, design and ed...
Web 2.0 - Applications      ¢  Social    networking          •  Keeping in touch with relations, forming and             ...
Web 2.0 - Applications      ¢  Syndication          & Notifications          •  Users can ‘subscribe’ to RSS feed enabled...
WEB 2.0: Emerging Paradigm      ¢  Personal       Learning Environment          •  Definition (M. A. Chatti)            -...
WEB 2.0: Emerging Paradigm      ¢  Personal       Learning Environment          •  Fit well with socio-constructivist lea...
WEB 2.0: Emerging ParadigmHow to access Data?                                 PLE   page 14   Hammam Sousse ISITC 2011   F...
Mobile, Pervasive, UbiquitousLearning
Mobile, Pervasive, Ubiquitous LearningIs-it a technological problem?   page 16   Hammam Sousse ISITC 2011   Futures Learni...
Mobile, Pervasive, Ubiquitous Learning     ¢  A   first definition          •  Learning with portable technology: PDA,   ...
Mobile, Pervasive, Ubiquitous Learning          ¢  Mobile      Computing             •  Mobile computing: increasing our ...
Mobile, Pervasive, Ubiquitous Learning           ¢  Ubiquitous        Computing              •  Integrating large-scale m...
Mobile, Pervasive, Ubiquitous Learning           ¢    Bomsdorf 2005                  -  « Ubiquitous learning is the next...
Mobile, Pervasive, Ubiquitous Learning          ¢    (Hundebol and Helms 2006)                 -  « Pervasive learning en...
Mobile, Pervasive, Ubiquitous Learning           ¢  Mobility              •  Portable Technologies              •  Spatia...
Mobile, Pervasive, Ubiquitous Learning          ¢  Social    Community            •  Learning is a social process which l...
Mobile, Pervasive, Ubiquitous Learning          ¢  Enable                  learning activities difficult before,         ...
Mobile, Pervasive, Ubiquitous Learningpage 25   Hammam Sousse ISITC 2011   Futures Learning Landscapes
Mobile, Pervasive, Ubiquitous Learning                      Metadata Features                                             ...
Mobile, Pervasive, Ubiquitous Learning      ¢  Is-it   possible to manage          •  Context Awareness,          •  Adap...
Mobile, Pervasive, Ubiquitous LearningWe need a kind of page 28   Hammam Sousse ISITC 2011   Futures Learning Landscapes
Semantic Web & LinkedData
Semantic Web &           Linked DataWho is teaching at Telecom Bretagneand riding a motorcycleacross Europe? page 30   Ham...
Semantic Web & Linked Data      ¢  Find   the movies of type « thriller »      ¢  And    classified      ¢  And    appr...
Semantic Web & Linked Data      ¢  Goals          •  Reuse and sharing of data          •  Interoperability at semantic l...
Semantic Web & Linked Data      ¢  Description        of Telecom Bretagne website          •  Subject                 Ver...
Semantic Web & Linked Data      ¢  In   DBpedia            •  Telecom Bretagne dbpprop:president Paul Friedel(en)        ...
Semantic Web & Linked Data      ¢  Linked      Data          •  Published data according to standards            -  RDF /...
Convergence
Convergence      ¢  A global, distributed and open architecture          perspective          •  Composed of social web e...
Convergence      ¢  Reuse,  analyze and manage content across web          application sources      ¢  Monitor and analy...
Inquiry-Based ScienceTeaching V. 1
Inquiry Based Science Teaching: IBST V. 1      ¢    IBST features            •  Authentic and problem-based learning acti...
Inquiry Based Science Teaching: IBST V. 1      ¢  The   complete problem          •  Problem 1: understand the industrial...
Inquiry Based Science Teaching: IBST V. 1page 42    Hammam Sousse ISITC 2011   Futures Learning Landscapes Vestige
Inquiry Based Science Teaching: IBST V. 1      Prototypical Scenario          1.  Problem analysis in small groups        ...
Inquiry Based Science Teaching: IBST V. 1      ¢     Historical reading and understanding of an             industrial la...
Inquiry-Based ScienceTeaching V. 2
Inquiry Based Science Teaching: IBST V. 2      Prototypical Scenario          1.  Problem analysis in small groups        ...
Inquiry Based Science Teaching: IBST V. 2      ¢  Smartphones          •  Camera,          •  GPS          •  Network acc...
Inquiry Based Science Teaching: IBST V. 2      ¢  Recommend    suitable entities                Resources, activities, to...
Inquiry Based Science Teaching: IBST V. 2      ¢  Three    Push modes          •  Recommend information from Navy museum ...
Inquiry Based Science Teaching: IBST V. 2      ¢  Pull   Mode          •  A query filters concepts, resources, activities...
Inquiry Based Science Teaching: IBST V. 2    Activities                  Tool families                Content producedSear...
Inquiry Based Science Teaching: IBST V. 2    Activities                Tool families                Content producedCollab...
Inquiry Based Science Teaching: IBST V. 2      ¢  Models enable us to have common vocabularies to          ensure exchang...
Inquiry Based Science Teaching: IBST V. 2      ¢  Some metadata can be generated automatically          (sometimes on the...
A Cloud Learning Environment                                                                         World                ...
Conclusions      ¢  Convergence           of          1.  Personal Leaning environment,          2.  Ubiquitous learning ...
Conclusions      ¢  Technical       issues          •  Context management          •  Distributed user model          •  ...
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Future Learning Landscapes

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ISITC Hammam Sousse

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Transcript of "Future Learning Landscapes"

  1. 1. Future Learning Landscapes Towards the Convergence of Pervasive and Contextual Computing, Global Social Media and Semantic Web in Technology Enhanced LearningSerge Garlatti
  2. 2. Outline ¢  Introduction ¢  Web 2.0 ¢  Mobile, Pervasive, Ubiquitous Learning ¢  Semantic Web, Linked Data ¢  Convergence ¢  Inquiry Based Science Teaching: IBST V. 1 ¢  Inquiry Based Science Teaching: IBST V. 2 ¢  An Ubiquitous Cloud Learning Environment •  Models, architecture and tools ¢  Conclusionpage 1 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  3. 3. Introduction ¢  Contributors •  JM Gilliot, Telecom Bretagne, l’un de ses Blogs •  C. Pham Nguyen, Telecom Bretagne •  S. Laubé, UBO, PAHST •  Yan Peter, LIFL •  A. Bouzeghoub, Telecom SudParis ¢  Some references •  http://conferences.telecom-bretagne.eu/futurelearning2010/ •  http://molene.enstb.org/futurelearning/ •  http://molene.enstb.org/mlearning09/page 2 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  4. 4. WEB 2.0
  5. 5. Web 2.0Source: Dion Hincliffe page 4 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  6. 6. Web 2.0 - Applications ¢  Blogs •  Personal publication + comments by others •  Linking facilities at the level of information & people •  For education -  Reflection, diary, assignment publishing -  Course information & follow up (answering questions…)page 5 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  7. 7. Web 2.0 - Applications ¢  Wikis •  Collaborative writing & content organisation •  For education -  Supporting group and project work, Annotated reading list, Practicing writing skills ¢  Collaborative editing •  Web tools are used collaboratively to design, construct and distribute some digital product -  Google Docs, Etherpadpage 6 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  8. 8. Web 2.0 - Applications ¢  Conversational Arenas •  One-to-one or one-to-many conversations between internet users •  ¢  Online Games and virtual world •  Rule-governed games or themed environments that invite live interaction with other internet userpage 7 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  9. 9. Web 2.0 - Applications ¢ Social bookmarking •  Keep reference of interesting material •  Organising information with tags •  Taking benefit from resources found by otherspage 8 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  10. 10. Web 2.0 - Applications ¢  Media sharing and manipulation •  Tools to upload, download, design and edit digital media files •  For education -  Images & videos can be provided -  Annotation on the images or video can support specific explanationspage 9 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  11. 11. Web 2.0 - Applications ¢  Social networking •  Keeping in touch with relations, forming and supporting social communities •  For education -  Course animation outside the classpage 10 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  12. 12. Web 2.0 - Applications ¢  Syndication & Notifications •  Users can ‘subscribe’ to RSS feed enabled websites so that they are automatically notified of any changes or updates in content via an aggregator. -  Easy notification of updates, automatic media distribution (podcast episodes) •  For education -  A way to keep an eye on learners’ progress -  A way to distribute course content automaticallypage 11 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  13. 13. WEB 2.0: Emerging Paradigm ¢  Personal Learning Environment •  Definition (M. A. Chatti) -  A PLE is characterized by the freeform use of a set of lightweight services and tools (Web 2.0) that belong to and are controlled by individual learners. •  Built by the learner for a specific & personal learning goal -  Mashing up the services that will support best the goal -  No institutional drive or controlpage 12 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  14. 14. WEB 2.0: Emerging Paradigm ¢  Personal Learning Environment •  Fit well with socio-constructivist learning approaches -  Foster collaborative knowledge sharing and building and reflective practices in a social context -  Foster self-regulated learning sequences by student and discursive argumentation and communication with peerpage 13 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  15. 15. WEB 2.0: Emerging ParadigmHow to access Data? PLE page 14 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  16. 16. Mobile, Pervasive, UbiquitousLearning
  17. 17. Mobile, Pervasive, Ubiquitous LearningIs-it a technological problem? page 16 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  18. 18. Mobile, Pervasive, Ubiquitous Learning ¢  A first definition •  Learning with portable technology: PDA, smartphones, PSP, PDA phones, mobile phones, Ipods, Iphones, MP3 players, labtop, UMPC, etc. everytime, everywhere.page 17 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  19. 19. Mobile, Pervasive, Ubiquitous Learning ¢  Mobile Computing •  Mobile computing: increasing our capability to physically move computing services with us. •  The computing device cannot seamlessly and flexibly obtain information about the context in which the computing takes place and adjust it accordingly. ¢  Pervasive Computing •  Capability to obtain information from the environment in which it is embedded and use it to dynamically build models of computing. •  Acquisition /management of context models and adaptationspage 18 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  20. 20. Mobile, Pervasive, Ubiquitous Learning ¢  Ubiquitous Computing •  Integrating large-scale mobility with pervasive computing features ¢  Featuresof mobile, pervasive, ubiquitous computing belong to those of mobile, pervasive, ubiquitous learningpage 19 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  21. 21. Mobile, Pervasive, Ubiquitous Learning ¢  Bomsdorf 2005 -  « Ubiquitous learning is the next step in performing e-learning and by some groups it is expected to lead to an educational paradigm shift, or at least, to new ways of learning. The potential of ubiquitous learning results from the enhanced possibilities of accessing learning content and computer- supported collaborative learning environments at the right time, at the right place, and in the right form. Furthermore, it enables seamless combination of virtual environments and physical spaces ».page 20 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  22. 22. Mobile, Pervasive, Ubiquitous Learning ¢  (Hundebol and Helms 2006) -  « Pervasive learning environment is a context (or state) for mediating learning in a physical environment enriched with additional site-specific and situation dependent elements – be it plain data, graphics, information -, knowledge -, and learning objects, or, ultimately, audio-visually enhanced virtual layers“.page 21 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  23. 23. Mobile, Pervasive, Ubiquitous Learning ¢  Mobility •  Portable Technologies •  Spatial Mobility -  Learners moving between different learning settings •  Tool and Thematic Mobility -  Learners alternating between different tools and topics •  Temporal Mobility -  Learning is cumulative, current learning builds on previous learning and are the basis for future learning.page 22 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  24. 24. Mobile, Pervasive, Ubiquitous Learning ¢  Social Community •  Learning is a social process which links learners to communities, people and situations •  Learners are not taught by one teacher, but rather by a community •  Collaborative learning -  Learning happens in collaboration between people and technologypage 23 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  25. 25. Mobile, Pervasive, Ubiquitous Learning ¢  Enable learning activities difficult before, sometimes impossible •  Learning may occur in location and time which are significant and relevant for learners •  Learning occurs in the context of activities involving an authentic task or problem, a location, a time, an environment, a social community, etc. •  Learning in context and across contextspage 24 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  26. 26. Mobile, Pervasive, Ubiquitous Learningpage 25 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  27. 27. Mobile, Pervasive, Ubiquitous Learning Metadata Features Relevant content Input content: Clustering Ranking/ Filtering Display AnnotationResources {«Good» «Average» «Bad»} Situation Context Features Adaptation process According to resource category! page 26 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  28. 28. Mobile, Pervasive, Ubiquitous Learning ¢  Is-it possible to manage •  Context Awareness, •  Adaptation •  Seamless Learning By Search engine likepage 27 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  29. 29. Mobile, Pervasive, Ubiquitous LearningWe need a kind of page 28 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  30. 30. Semantic Web & LinkedData
  31. 31. Semantic Web & Linked DataWho is teaching at Telecom Bretagneand riding a motorcycleacross Europe? page 30 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  32. 32. Semantic Web & Linked Data ¢  Find the movies of type « thriller » ¢  And classified ¢  And appreciated by at least four friends on •  Or those following me on ¢  And without Leonardi Di Caprio as Actorpage 31 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  33. 33. Semantic Web & Linked Data ¢  Goals •  Reuse and sharing of data •  Interoperability at semantic level ¢  How? •  Associate semantic metadata to resources •  Linked data silos by these semantic metadatapage 32 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  34. 34. Semantic Web & Linked Data ¢  Description of Telecom Bretagne website •  Subject Verb Object •  Telecom Bretagne has a president Paul Friedel •  Telecom Bretagne is a French Grande Ecole •  Telecom Bretagne has a website http://www.tele...page 33 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  35. 35. Semantic Web & Linked Data ¢  In DBpedia •  Telecom Bretagne dbpprop:president Paul Friedel(en) •  Telecom Bretagne dbpprop:type French Grande Ecole(en) •  Telecom Bretagne dbpprop:website http://www.tele... ¢  Question •  French Grande Ecole whose Paul Friedel is a President? -  ?Grande_Ecole dbpprop:president Paul Friedel (en) -  ?Grande_Ecole dbpprop:type French Grande Ecole (en)page 34 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  36. 36. Semantic Web & Linked Data ¢  Linked Data •  Published data according to standards -  RDF / RDFS / OWL -  SPARQL Access Point –  Query language + Access protocol The Web will be a Tremendous Global Databasepage 35 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  37. 37. Convergence
  38. 38. Convergence ¢  A global, distributed and open architecture perspective •  Composed of social web environments, institutional learning environments and personal learning environments exposing, sharing, and connecting data on the Web.page 37 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  39. 39. Convergence ¢  Reuse, analyze and manage content across web application sources ¢  Monitor and analyze user activities and content production, to get user traces and to provide guidance and advices according to user activities and needs ¢  Combination of all these resources and techniques allow getting contextual data from web environments and sensorspage 38 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  40. 40. Inquiry-Based ScienceTeaching V. 1
  41. 41. Inquiry Based Science Teaching: IBST V. 1 ¢  IBST features •  Authentic and problem-based learning activities which are ill- defined and have several answers •  A certain amount of experimental procedures, experiments and activities involving practical experience of equipment and including searching for information; •  Self regulated learning sequences where student autonomy is emphasized; •  Discursive argumentation and communication with peers ("talking science").page 40 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  42. 42. Inquiry Based Science Teaching: IBST V. 1 ¢  The complete problem •  Problem 1: understand the industrial landscape in the area of the bridge (Brest is a shipbuilding arsenal for the Navy). •  Problem 2: understand what is the historical and technological method of problem solving that led to the construction of the swinging bridge. •  Problem 3: understand the rotating mechanism of the swinging http://plates-formes.iufm.fr/ressources-ehst/spip.php?rubrique17page 41 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  43. 43. Inquiry Based Science Teaching: IBST V. 1page 42 Hammam Sousse ISITC 2011 Futures Learning Landscapes Vestige
  44. 44. Inquiry Based Science Teaching: IBST V. 1 Prototypical Scenario 1.  Problem analysis in small groups 2.  Activation of prior knowledge 3.  Elaboration of a strategy to find needed information (define collaborative and cooperative activities) 4.  Collaborative work and exploitation 5.  Peer-assessment 1 6.  Collaborative report writing 7.  Peer-assessment 2 8.  Institutionalization / discussionpage 43 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  45. 45. Inquiry Based Science Teaching: IBST V. 1 ¢  Historical reading and understanding of an industrial landscape (scenario stage 4) •  Photograph all elements of the current landscape with historical aspects about cranes and bridges of the arsenal, •  Locate the different elements on a current map of Brest, •  Identify and photograph the actual bridges and cranes linked existing bridges and cranes from previous: what continuities ? What ruptures? •  Store and publish information on the corresponding tools.page 44 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  46. 46. Inquiry-Based ScienceTeaching V. 2
  47. 47. Inquiry Based Science Teaching: IBST V. 2 Prototypical Scenario 1.  Problem analysis in small groups 2.  Activation of prior knowledge 3.  Elaboration of a strategy to find needed information (define collaborative and cooperative activities) 4.  Collaborative work and exploitation 5.  Peer Assessment 1 6.  Collaborative report writing 7.  Peer Assessment 2 8.  Institutionalization / discussionpage 46 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  48. 48. Inquiry Based Science Teaching: IBST V. 2 ¢  Smartphones •  Camera, •  GPS •  Network access ¢  Three groups •  Site visit •  Information seeking in navy museum •  Information seeking in local public recordspage 47 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  49. 49. Inquiry Based Science Teaching: IBST V. 2 ¢  Recommend suitable entities Resources, activities, tools, persons, … –  Depending on the current situation without any human interventions ¢  Push mode •  Groups or individuals can be notified according to the situation changes. •  The group/individual can select or not one of the given recommendations.page 48 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  50. 50. Inquiry Based Science Teaching: IBST V. 2 ¢  Three Push modes •  Recommend information from Navy museum and local public records retrieved by other group members or subgroup according to the needed domain concepts identified on the port and/or the current activities •  Recommend and provide information from subgroup visiting the port to other subgroups or group members •  Recommend checking some domain concepts missed by students or subgroups on the port.page 49 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  51. 51. Inquiry Based Science Teaching: IBST V. 2 ¢  Pull Mode •  A query filters concepts, resources, activities and persons •  Write queries -  On relevant domain concepts like “crane”, “bridge”, etc. according to the current context (activities and localization), -  On retrieved information from other group members or subgroups according to activities and/or localizationpage 50 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  52. 52. Inquiry Based Science Teaching: IBST V. 2 Activities Tool families Content producedSearching Search engines, Shared bibliography information Social book-marking, Annotations, Notes, Blogs, Wikis, etc. images, videos, etc., potentially geo-localised.Site visit Smart terminal with Geo-localised text, pictures, Camera, GPS and videos. CMSGroup Chat, Microblogging, Real-time information communication Voice, Video, etc. sharing for work group coordination. page 51 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  53. 53. Inquiry Based Science Teaching: IBST V. 2 Activities Tool families Content producedCollaborative Maps Knowledge restructuration Collected Data Mind map tools. analysisCollaborative Shared bibliography Final report : knowledge Report writing Annotations, Notes, construction Images, Videos, etc. and Collaborative Writing ToolsPeer assessment Collected Group work Quality analysis, Hints, Rating based on an assessment scheme page 52 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  54. 54. Inquiry Based Science Teaching: IBST V. 2 ¢  Models enable us to have common vocabularies to ensure exchange, reuse and sharing of resources at semantic level (Ontologies) •  A context model -  including a user model, a scenario model •  A domain model •  A resource model (a metadata schema) •  A peer assessment model •  A recommendation model (adaptation model),page 53 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  55. 55. Inquiry Based Science Teaching: IBST V. 2 ¢  Some metadata can be generated automatically (sometimes on the fly) •  from the tool databases according to common vocabularies like -  Dublin Core, SKOS, SIOC, FOAF, OPO, etc. ¢  Most of these vocabularies are lightweight ontologies that can fit well database schemaspage 54 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  56. 56. A Cloud Learning Environment World Of Widget Widgets Model Course CloudNotifications ComponentRSS/SParQL& Queries Queries Push/Pull flow Notification Widget Information Widget My CLE WebApps Self-defined Widget page 55 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  57. 57. Conclusions ¢  Convergence of 1.  Personal Leaning environment, 2.  Ubiquitous learning environment 3.  Semantic Web Main Issue How could we change our practices and/or learning scenarios to enhance the learning processes?page 56 Hammam Sousse ISITC 2011 Futures Learning Landscapes
  58. 58. Conclusions ¢  Technical issues •  Context management •  Distributed user model •  Ontology management •  Peer Assessment model •  Tags versus Ontologies •  etc.page 57 Hammam Sousse ISITC 2011 Futures Learning Landscapes
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