research-article

Analyzing the flow of ideas and profiles of contributors in an open learning community

Authors:

Iassen Halatchliyski,

Tobias Hecking,

Tilman Göhnert, and

H. Ulrich HoppeAuthors Info & Claims

LAK '13: Proceedings of the Third International Conference on Learning Analytics and Knowledge

April 2013

Pages 66 - 74

https://doi.org/10.1145/2460296.2460311

Published: 08 April 2013 Publication History

Abstract

This paper provides an introduction to the scientometric method of main path analysis and its application to detecting idea flows in an online learning community using data from Wikiversity. We see this as a step forward in adapting and adopting network analysis techniques for analyzing the evolution of artifacts in knowledge building communities. The analysis steps are presented in detail including the description of a tool environment ("workbench") designed for flexible use by non-computer experts. Through the definition of directed acyclic graphs the meaningful interconnectedness of learning resources is made accessible to analysis in consideration of the temporal sequence of their creation during a collaborative process. The potential of the method is elaborated for analyzing the overall learning process of a community as well as the individual contributions of the participants.

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Cited By

Peach RGreenbury SJohnston IYaliraki SLefevre DBarahona M(2021)Understanding learner behaviour in online courses with Bayesian modelling and time series characterisationScientific Reports10.1038/s41598-021-81709-311:1Online publication date: 2-Feb-2021
https://doi.org/10.1038/s41598-021-81709-3
Saqr MNouri JRensing CDrachsler HKovanović VPinkwart NScheffel MVerbert K(2020)High resolution temporal network analysis to understand and improve collaborative learningProceedings of the Tenth International Conference on Learning Analytics & Knowledge10.1145/3375462.3375501(314-319)Online publication date: 23-Mar-2020
https://dl.acm.org/doi/10.1145/3375462.3375501
Cabrera BKönig B(2018)Extracting the Main Path of Historic Events from WikipediaNetwork Intelligence Meets User Centered Social Media Networks10.1007/978-3-319-90312-5_5(65-81)Online publication date: 1-Aug-2018
https://doi.org/10.1007/978-3-319-90312-5_5
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Published In

cover image ACM Conferences

LAK '13: Proceedings of the Third International Conference on Learning Analytics and Knowledge

April 2013

300 pages

ISBN:9781450317856

DOI:10.1145/2460296

Editors:
Dan Suthers
University of Hawaii, USA
,
Katrien Verbert
Eindhoven University of Technology, The Netherlands
,
Erik Duval
University of Leuven, Belgium
,
Xavier Ochoa
Escuela Superior Politécnica del Litoral, Ecuador

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
K.U. Leuven: K.U. Leuven
SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 April 2013

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Seventh Framework Programme

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LAK '13

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SIGWEB
K.U. Leuven
SIGCHI

LAK '13: Third Conference on Learning Analytics and Knowledge

April 8 - 13, 2013

Leuven, Belgium

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LAK '13 Paper Acceptance Rate 16 of 58 submissions, 28%;

Overall Acceptance Rate 236 of 782 submissions, 30%

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Cited By

Peach RGreenbury SJohnston IYaliraki SLefevre DBarahona M(2021)Understanding learner behaviour in online courses with Bayesian modelling and time series characterisationScientific Reports10.1038/s41598-021-81709-311:1Online publication date: 2-Feb-2021
https://doi.org/10.1038/s41598-021-81709-3
Saqr MNouri JRensing CDrachsler HKovanović VPinkwart NScheffel MVerbert K(2020)High resolution temporal network analysis to understand and improve collaborative learningProceedings of the Tenth International Conference on Learning Analytics & Knowledge10.1145/3375462.3375501(314-319)Online publication date: 23-Mar-2020
https://dl.acm.org/doi/10.1145/3375462.3375501
Cabrera BKönig B(2018)Extracting the Main Path of Historic Events from WikipediaNetwork Intelligence Meets User Centered Social Media Networks10.1007/978-3-319-90312-5_5(65-81)Online publication date: 1-Aug-2018
https://doi.org/10.1007/978-3-319-90312-5_5
Mohd Rani NYusoff MKamaruzaman M(2015)Theoretical Framework Study on Formgiving Mobile Education Game Design TechnologyInternational Colloquium of Art and Design Education Research (i-CADER 2014)10.1007/978-981-287-332-3_5(47-52)Online publication date: 2015
https://doi.org/10.1007/978-981-287-332-3_5
Chen BResendes MPistilli MWillis JKoch DArnold KTeasley SPardo A(2014)Uncovering what mattersProceedings of the Fourth International Conference on Learning Analytics And Knowledge10.1145/2567574.2567606(226-230)Online publication date: 24-Mar-2014
https://dl.acm.org/doi/10.1145/2567574.2567606
Hecking TZiebarth SHoppe HPistilli MWillis JKoch DArnold KTeasley SPardo A(2014)Analysis of dynamic resource access patterns in a blended learning courseProceedings of the Fourth International Conference on Learning Analytics And Knowledge10.1145/2567574.2567584(173-182)Online publication date: 24-Mar-2014
https://dl.acm.org/doi/10.1145/2567574.2567584
Chounta IHecking THoppe HAvouris N(2014)Two Make a Network: Using Graphs to Assess the Quality of Collaboration of DyadsCollaboration and Technology10.1007/978-3-319-10166-8_5(53-66)Online publication date: 2014
https://doi.org/10.1007/978-3-319-10166-8_5
Halatchliyski IMoskaliuk JKimmerle JCress U(2013)Explaining authors’ contribution to pivotal artifacts during mass collaboration in the Wikipedia’s knowledge baseInternational Journal of Computer-Supported Collaborative Learning10.1007/s11412-013-9182-39:1(97-115)Online publication date: 10-Oct-2013
https://doi.org/10.1007/s11412-013-9182-3

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