On Modeling Learning Communities

Lehrstuhl Informatik 5(Information Systems)

Prof. Dr. M. JarkeI5-ZP-915-1

TeLLNet

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.

Zinayida Petrushyna, Ralf Klamma and Milos Kravcik

EC-TEL 2015,Toledo,

September 16, 2015

On Modeling Learning Communities

http://dbis.rwth-aachen.de/cms/research/MiCIS


http://creativecommons.org/licenses/by-sa/3.0/





TeLLNet Outline

Motivation and Research Question Data Collection Methods Results Evaluation Future Work and Discussions







TeLLNet

Informal learning communities need digital media to realize social context

Motivation

Motivation

Methodology

Results

Evaluation

Outlook

But online community data is huge and heterogeneous Verbert et. al., 2012

Is learning analytics a solution?Problem Learning Analytics Community ModelingDefine learner roles + +Predict learner success + +Classify a type of a community +/- +Estimate community needs +/- +Find a solution to a problem +/- +Forecast community changes +/- +







TeLLNet Modeling Informal Online Learning Communities

An efficient data management solution

A service for learning community analysis Community borders and roles of users

Kleanthous & Dimitrova, 2007, 2010 Learning community/user goals, attitudes, interests

Modeling

Refinement

Monitoring

Analysis

Petrushyna et al. 2014

Motivation

Methodology

Results

Evaluation

Outlook

A service for automatic modeling of communities A community of practice is a stereotype model Wenger, 1998 Other models from a model repository Petrushyna et al. 2010

Call to stakeholders‘ action







TeLLNet

• # posts ≈ 429K ; # users ≈ 21K; # threads ≈ 68K• Max depth(thread)=318 posts, Avg depth=6 posts• 360 characters in avg in a post• 132 communities with > 3 members

Research Example

TOEFL

GMAT

GRE

Tests Informal learning communities in URCH subforumsMotivation

Methodology

Results

Evaluation

Outlook







TeLLNet

Community detection– Define time intervals based on events of communities𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑗𝑗 = 𝑏𝑏𝑖𝑖𝑏𝑏𝑏𝑏𝑖𝑖𝑖𝑖𝑗𝑗 ,𝑖𝑖𝑏𝑏𝑖𝑖𝑖𝑖𝑖𝑖𝑗𝑗 where 𝑗𝑗 ∈ 𝐽𝐽, where J is a set of events, e.g., exams– Modularity-based community detection

Newman and Girvan, 2004

Community Detection and Evolution

Motivation

Methodology

Results

Evaluation

Outlook Community evolution Palla et al. 2007

Mapping of communities using modified Jaccard index

𝑆𝑆𝑖𝑖𝑆𝑆 𝐶𝐶𝑖𝑖𝑗𝑗 ,𝐶𝐶𝑟𝑟𝑘𝑘 = max𝐶𝐶𝑖𝑖𝑗𝑗⋂𝐶𝐶𝑟𝑟𝑘𝑘𝐶𝐶𝑖𝑖𝑗𝑗

,𝐶𝐶𝑖𝑖𝑗𝑗⋂𝐶𝐶𝑟𝑟𝑘𝑘𝐶𝐶𝑟𝑟𝑘𝑘

≥ 𝑖𝑖ℎ𝑖𝑖𝑖𝑖𝑟𝑟ℎ𝑏𝑏𝑖𝑖𝑟𝑟

Gliwa et al. 2012 Social network analysis measures Wassermann and Faust, 1994

– Detecting patterns using closeness, betweenness– Patterns: questioners, answering persons, newbies and usual users







TeLLNeti* Modeling Approach for Informal Learning

Community Modeling

Dependency resource

Goal

Softgoal

Task

Agent Role

Depender Agent

Dependee Agent

Learningresource

Learning goal

Acceptance

Support learning process

Learner A Expert

Community Learner

Motivation

Methodology

Results

Evaluation

Outlook

+ point out dependenciesbetween human and non-human agents

+ models can be createdusing XML-based format

+ models can be extendedto describe the rationale of agents

+ emphasize agents, their types and roles

+ indicate intentionsin social networks







TeLLNet i*-REST Opensource RESTful WebServices

Model creation− Strategic Dependency i*− API related to the iStarML− Models are resources (REST)− Model validation− Storage and versioning in model repository

Model visualization− From iStarML to SVG− Easy to embed into a Web page− JS extension allows user interactions

Wanted to solve

equation QuestionerThe community

with 44 users

User_id=69588

Usual userUser_id=69561Forget to

write debrief

NewbieUser_id=69575How to

solve

Goal

Role

Depender Agent

Dependee Agent

Motivation

Methodology

Results

Evaluation

Outlook







TeLLNetModeling of an URCH

Learning Community Evolution01-10.12.2004 08-17.12.2004

# posts = 471# users = 22# adjacent nodes = 43# high influence users = 13# low influence users = 2

need to learn want to writetake to solve

started to take practiceprepared to take beast

trying to learn stuff

# posts = 226# users = 20# adjacent nodes = 15# high influence users = 4# low influence users = 4

how to answerinstructed to take writing

supposed to answerplan to take GREtake to solve

Motivation

Methodology

Results

Evaluation

Outlook







TeLLNetEvaluation of Automatic Creation Process

of i* Modelsi* experts evaluated the process25 subjects, 86% agree thatMotivation

Methodology

Results

Evaluation

Outlook

– community stakeholders can understand community situations better using i* models

– emphasizing community requirements facilitate developers’ work of community information systems

SocialNetwork Analysis

Community DetectionandEvolution

IntentAnalysis

NamedEntitiesRetrieval

i* models can be abstract and not straightforward

Training is required before stakeholderscan use models







TeLLNet Conclusion and Outlook

Informal online learning community modeling workflow Integration of community analysis and modeling for

automatic creation of models

Future Work Near-real time collaborative modeling

Derntl et al. 2013, Nicolaescu et al. 2013

Further analysis of communities texts and learner roles Better usability for stakeholders Overlapping community detection Shahriari et al. 2015

Application on MOOCs

Motivation

Methodology

Results

Evaluation

Outlook







TeLLNet Call to Collaborations

Extending and applicating services for modelinglearning communities

Search on githubiStarMLModel-Servicehttp://tinyurl.com/modelingService

Visualizing service iStarMLVisualizer-Servicehttp://tinyurl.com/visualizingService





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On Modeling Learning Communities

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