No Guru, No Method, No Teacher: Self-Classification and Self-Modelling of E-Learning Communities

Lehrstuhl Informatik V(Informationssysteme)

Prof. Dr. M. JarkeI5-RK-0808-1

CUELC

Zinayida Petrushyna, Ralf Klamma

RWTH Aachen University

EC-TEL 2008, Maastricht, The Netherlands

September 18, 2008

No Guru, No Method, No Teacher: Self-Classification and Self-

Modelling of E-Learning Communities



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Agenda

Motivation Self-regulated life-long learning Communities of Practice(CoP) model and dimensions Self-monitoring of E-Learning repositories Results of Self-modelling of E-Learning communities Conclusions and outlook



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Motivation

Firstly to learn, secondly to learn and thirdly to learn (Lenin, 1923)

V1V1

V2V2

V3V3V4V4

V5V5

V6V6

TEPL

IST challenge

(3G, IpV6, nanotechnologies, convergence, web services,ambient intelligence scenario)

Industry challenges: •Performance support•Continuous improvement•Incremental development•Processed based integratedlearning)

Industry challenges: •Innovation•Entrepreneurship•ability to change•Competency and performance

management

Learner’s perspective:Continuous personal DevelopmentRecognition and portabilityOf learning achievements

Socio-economic Systems :Market take-up

Social inclusion

The Six Prolearn Vision Statements

“Everyone should be able to learn anything at anytime at anyplace”

(personalization – adaptation)

“Learning as a means to support and enhance work performance”

“Promote innovation and creativity and entrepreneurship”

“Learning as a means to increase employability”

(flexibility and survivability of employees)

“Socio-economic systems – market take up”

“Access to professional learning for all – extending the knowledge based society”

ROADMAP(Prolearn)



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Self-regulated Life-long Learning

Dynamic perspective on communities Defining disturbances (Troll) Analyzing communities Application of patterns(Troll) Reflecting models according

to the reality Adapting reflected

models



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CoP Model

I* Modelling (Yu et. al, 1994)



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CoP Dimensions

Mutual engagement(ME) If you are aware of "what matters" in the scope of a community your engagement is enabled

Joint enterprises(JE) CoPs and theirs members can follow the situations happeningaround them and because of them

Shared repertoire(SR)Members represent community knowledge



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Prolearn MediaBase – the Repository of Web-based E-Learning Resources

Data management: Database and crawlersMailWatcher refinement for Pattern Analysis thread identification script

– reply_to field– subject field22% of thread reduction

Data cleaning script for thread content– No HTML tags and technical data– No duplicates (Levenshtein, 1969)

Project

Project

Project

Mailing lists

Thread

Thread

Thread

Thread

Thread

Thread

Thread

Thread

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail

Mail



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Fundamentals and Methodologies of Monitoring

Network analysis and graph theories – G=(V, E), weight w(v), w(e), degree d(v)– Centrality indices: betweenness, closeness (Wasserman & Faust,

1994) Social network analysis

– Dynamic social network analysis (Newmann et al., 2006)– Patterns: spammer, trolls, structural hole, innovative star, weak tie

(Klamma et al., 2006)– Web 2.0 and social software

Linguistic and emotional analysis– Part-of-Speech tags (Manning et al., 1999)– Sentiment extraction (Mishne et al., 2006; Pennebaker et al., 2007)



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Mutual Engagement Conectiveness, biconectiveness

– How dense the connections?– How diverse the community?

Hubs, authorities and scale free networkIs it possible to differentiate between the nodes?

Degree centrality, closeness centrality, betweenness centrality– Who is central?– Who is the most connected? – Who influences mostly on the community?

Emotional impactWhat categories of words is used mostly within the community?



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Joint Enterprises & Shared Repertoire

Affordance– What are the types of processes one can execute? – What functions/features does the medium possess?

AwarenessDo the community members know about changes?

Media centric theory of learningWhat kind of changes happens when a process is performed?

Sentence model + Part-of-Speech taggingWhat is the content of the context?



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Self-monitoring of the E-Learning Repository

Structural monitoring– Monologues threads– Reply-senders, reply-receivers– Communicators– Cross-users

Word category Number of words in the dictionary

Included words

FRIENDS 36 companion, friend, mate, etc.

ANGER 364 defense, rude, victim, etc.

INSIGHT(understanding)

193 become,feel, inform, seem, think, etc.

FILLER 8 yakno, ohwell, etc.

POSEMO 405 agree, improve, support, etc.

NEGEMO 495 fury, panic, temper, etc.

Semantical monitoring32 word categories(4500 words)– psychological constructs– 7 personal concern– 3 paralinguistic dimensions



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Hierarchical ClusteringResults

Question-answer community– dyadic and sequent communications– “insight” and “discrep” words – the query-

explanation nature

Disputative community– reply-sender– “explanation”, “disagreement” and “quarells” –

the discussion nature



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Factor AnalysisResults

Question-answer community– reply sender– “motion”, “social”, “filler”, “persuade” and “insight” words



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Conclusions & Outlook

E-Learning communities as CoP Monitoring means (structure + semantics) Modelling hypotheses with Hierarchical Clustering and Factor

Analysis

Influence of the analysis on the learning process Application of linguistic techniques on the semantic analysis Methods of self-modelling of CoP Recommendations in Life-long Learning based on game-

theoretic models

No Guru, No Method, No Teacher: Self-Classification and Self-Modelling of E-Learning Communities

Technology

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