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
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-2
CUELC
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
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-3
CUELC
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)
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-4
CUELC
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
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-5
CUELC
CoP Model
I* Modelling (Yu et. al, 1994)
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-6
CUELC
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
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-7
CUELC
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
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-8
CUELC
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)
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-9
CUELC
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?
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-10
CUELC
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?
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-11
CUELC
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
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-12
CUELC
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
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-13
CUELC
Factor AnalysisResults
Question-answer community– reply sender– “motion”, “social”, “filler”, “persuade” and “insight” words
Lehrstuhl Informatik V(Informationssysteme)
Prof. Dr. M. JarkeI5-RK-0808-14
CUELC
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