ISITC Hammam Sousse April 2011

1. Future Learning Landscapes
Towards the Convergence of Pervasive and
Contextual Computing, Global Social Media and
Semantic Web in Technology Enhanced Learning
Serge Garlatti

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
¢ Conclusion
page 1 Hammam Sousse ISITC 2011 Futures Learning Landscapes

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/
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4. WEB 2.0

5. Web 2.0
Source: Dion Hincliffe
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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…)
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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, Etherpad
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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 user
page 7 Hammam Sousse ISITC 2011 Futures Learning Landscapes

9. Web 2.0 - Applications
¢ Social bookmarking
• Keep reference of interesting material
• Organising information with tags
• Taking benefit from resources found by others
page 8 Hammam Sousse ISITC 2011 Futures Learning Landscapes

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
explanations
page 9 Hammam Sousse ISITC 2011 Futures Learning Landscapes

11. Web 2.0 - Applications
¢ Social networking
• Keeping in touch with relations, forming and
supporting social communities
• For education
- Course animation outside the class
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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 automatically
page 11 Hammam Sousse ISITC 2011 Futures Learning Landscapes

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 control
page 12 Hammam Sousse ISITC 2011 Futures Learning Landscapes

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 peer
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15. WEB 2.0: Emerging Paradigm
How to access Data?
PLE
page 14 Hammam Sousse ISITC 2011 Futures Learning Landscapes

16. Mobile, Pervasive, Ubiquitous
Learning

17. Mobile, Pervasive, Ubiquitous Learning
Is-it a technological problem?
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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. 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
adaptations
page 18 Hammam Sousse ISITC 2011 Futures Learning Landscapes

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 learning
page 19 Hammam Sousse ISITC 2011 Futures Learning Landscapes

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. 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. 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. 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
technology
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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 contexts
page 24 Hammam Sousse ISITC 2011 Futures Learning Landscapes

26. Mobile, Pervasive, Ubiquitous Learning
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27. Mobile, Pervasive, Ubiquitous Learning
Metadata Features
Relevant content
Input
content: Clustering Ranking/
Filtering Display
Annotation
Resources
{«Good» «Average» «Bad»}
Situation
Context Features
Adaptation process
According to resource category!
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28. Mobile, Pervasive, Ubiquitous Learning
¢ Is-it possible to manage
• Context Awareness,
• Adaptation
• Seamless Learning
By Search engine like
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29. Mobile, Pervasive, Ubiquitous Learning
We need a kind of
page 28 Hammam Sousse ISITC 2011 Futures Learning Landscapes

30. Semantic Web & Linked
Data

31. Semantic Web &
Linked Data
Who is teaching at Telecom Bretagne
and riding a motorcycle
across Europe?
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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 Actor
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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 metadata
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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...
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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. 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 Database
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37. Convergence

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.
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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 sensors
page 38 Hammam Sousse ISITC 2011 Futures Learning Landscapes

40. Inquiry-Based Science
Teaching V. 1

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. 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?rubrique17
page 41 Hammam Sousse ISITC 2011 Futures Learning Landscapes

43. Inquiry Based Science Teaching: IBST V. 1
page 42 Hammam Sousse ISITC 2011 Futures Learning Landscapes
Vestige

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 / discussion
page 43 Hammam Sousse ISITC 2011 Futures Learning Landscapes

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. Inquiry-Based Science
Teaching V. 2

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 / discussion
page 46 Hammam Sousse ISITC 2011 Futures Learning Landscapes

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 records
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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.
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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.
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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 localization
page 50 Hammam Sousse ISITC 2011 Futures Learning Landscapes

52. Inquiry Based Science Teaching: IBST V. 2
Activities Tool families Content produced
Searching 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.
CMS
Group Chat, Microblogging, Real-time information
communication Voice, Video, etc. sharing for work group
coordination.
page 51 Hammam Sousse ISITC 2011 Futures Learning Landscapes

53. Inquiry Based Science Teaching: IBST V. 2
Activities Tool families Content produced
Collaborative Maps Knowledge restructuration
Collected Data Mind map tools.
analysis
Collaborative Shared bibliography Final report : knowledge
Report writing Annotations, Notes, construction
Images, Videos, etc.
and Collaborative
Writing Tools
Peer assessment Collected Group work Quality analysis, Hints,
Rating based on an
assessment scheme
page 52 Hammam Sousse ISITC 2011 Futures Learning Landscapes

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. 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 schemas
page 54 Hammam Sousse ISITC 2011 Futures Learning Landscapes

56. A Cloud Learning Environment
World
Of Widget
Widgets Model
Course Cloud
Notifications Component
RSS/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. 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. 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