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WP 2: Infrastructure WP 2: Infrastructure Fridolin Wild, Thomas Ullmann, Bernhard Hoisl OU | The Open University 2 , WU | Vienna University of Economics and Business Katja Buelow (OU), Robert Koblischke (WUW), Markus Essl (BIT MEDIA), Traian Rebedea (PUB-NCIT), Vlad Posea (PUB-NCIT), Thomas Markus (UU), Eline Westerhout (UU), Sonia Mandin (UPMF), Hendrik Drachsler (OUNL), Gaston Burek (UTU), Hristo Kostov (IPP-BAS), Alex Simov (IPP-BAS)

PLEs and textmining for lifelong learning

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Personal learning environments (PLE) combined with natural language processing is an explosive combination: it can be used to provide guidance and instant feedback. This presentation describes the framework developed within the European Commission funded language technology for lifelong learning (LTfLL) project.

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Page 1: PLEs and textmining for lifelong learning

WP 2: InfrastructureWP 2: InfrastructureFridolin Wild, Thomas Ullmann, Bernhard HoislOU | The Open University2, WU | Vienna University of Economics and BusinessKatja Buelow (OU), Robert Koblischke (WUW), Markus Essl (BIT MEDIA), Traian Rebedea (PUB-NCIT), Vlad Posea (PUB-NCIT), Thomas Markus (UU), Eline Westerhout (UU), Sonia Mandin (UPMF), Hendrik Drachsler (OUNL), Gaston Burek (UTU), Hristo Kostov (IPP-BAS), Alex Simov (IPP-BAS)

Page 2: PLEs and textmining for lifelong learning

ObjectivesObjectivesObjectivesObjectives

O1 | Integration guidelines

O2 | Access to language technology resources

O3 | Adaptation of existing language technology

O4 | Service integration (from WP4-6)

O5 | Technical validation of the services

#2

Task 1: PLE

Task 2: LT

Page 3: PLEs and textmining for lifelong learning

PLEsPLEsPLEsPLEsA landscape of tools (institutionally

offered or personally chosen) that

brings a learner together

with others and content artefacts

in activities that support in

constructing and processing

information and knowledge.

A landscape of tools (institutionally

offered or personally chosen) that

brings a learner together

with others and content artefacts

in activities that support in

constructing and processing

information and knowledge.

#3

Page 4: PLEs and textmining for lifelong learning

Competences Competences motivated by PLEsmotivated by PLEs

Planning competence refers to those skills, abilities, habits, attitudes, and knowledge that fix how goals, schedules, and paths are set.

Reflection is creative sense making of the past and enables planning.

Monitoring refers to how progress control is performed.

Last but not least, the pair acting and interacting group social & collaboration and information & tool competences.

Planning competence refers to those skills, abilities, habits, attitudes, and knowledge that fix how goals, schedules, and paths are set.

Reflection is creative sense making of the past and enables planning.

Monitoring refers to how progress control is performed.

Last but not least, the pair acting and interacting group social & collaboration and information & tool competences.

plan

reflect

monitor

act interact

(Wild et al., 2009)

Qualitative Interviews with stakeholders (learners, facilitators, learning designers, researchers): 15 persons in 5 sessions (each 40 min to 1 hour) #4

Page 5: PLEs and textmining for lifelong learning

Users involve in use-cases.

Each case deploys widgets in support of the given task.

Widgets use infrastructure services & data (from within the PLE container or from the Web 2.0).

A directory serves the management and deployment of the portfolio.

Interoperability standards secure the flexible recombination of widgets, services, and data.

PL

E A

rchitectu

reP

LE

Arch

itecture

#5

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#6

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LTfLL PLE

#13

+

(Wild et al., 2009b; Wild et al., 2010)

Page 14: PLEs and textmining for lifelong learning

directoryservice

PLE runtime containerPLE runtime container

DPpedia

WP 6

fossa

RSS

transf

CONSPECT

http://augur.wu.ac.at/elgg

#14

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Interwidget CommunicationInterwidget Communication

#15

+

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Example of Example of Interwidget Interwidget CommunicationCommunication

#16

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AuthenticationAuthentication

• openID to avoid lock-in

• Challenges forprotected exchange of data

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Corporate Design & Corporate Design & LocalisationLocalisation

Example:

Pensum

#18

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Next steps: Widget ArrangementsNext steps: Widget Arrangements

• Model dependencies (by type, by token)

• Patterns and Pattern Exchange

• Set-Up and wiring with IWC

#19

PenSum Conspect PolyCAFe

PenSumPenSum

PenSum

PolyCAFe

PolyCAFe

thread1

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AchievementsAchievements• Service integration of WP4/5/6

into one PLE (side by side)• Documentation of

services of WP4/5/6

• Complete rewrite of Elgg plug-in • Apache Wookie extensions

• Interwidget communication• OpenID authentication mechanisms• Corporate Design • Localisation facilities

• Started: widget arrangements Explored: deep integration

#20

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ImpactImpact• Elgg plug-in

– three public releases: 2.0, 2.1, 2.2

– 2.3 is being prepared

– 440 downloads as of April 22, 2010

• Wookie server– fork released

– Apache incubator workshop planned, negotiating with the Apache Software Foundation

• Workshop MUPPLE’09 at EC-TEL• Special Issue on Mash-Up Personal Learning

Environments in the International Journal of Technology Enhanced Learning (May 21st)

#21http://wiki.apache.org/concom-planning/WookieLondonJuly2010

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ConclusionConclusion

• The upcoming threads will supervise us in deepening interoperability of the PLE/LT services

Task 1: PLE

Task 2: LT

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Questions? Comments?Questions? Comments?

Add-onsAdd-ons

#23

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PLE Implementation PLE Implementation StrategiesStrategies• Coordinated Use

– e.g. with the help of browser bookmarks to involved web apps

• Simple Connectors for Data Exchange and service interoperability

• Abstracted Connectors that form Conduits– e.g. those supported by the social browser Flock – e.g. by the service-oriented PLE Plex

(Wilson et al., 2007)