skip to main content
10.1145/2723576.2723626acmotherconferencesArticle/Chapter ViewAbstractPublication PageslakConference Proceedingsconference-collections
research-article

From contingencies to network-level phenomena: multilevel analysis of activity and actors in heterogeneous networked learning environments

Published: 16 March 2015 Publication History

Abstract

Learning in social settings is a complex phenomenon that involves multiple processes at individual and collective levels of agency. Thus, a richer understanding of learning in socio-technical networks will be furthered by analytic methods that can move between and coordinate analyses of individual, small group and network level phenomena. This paper outlines Traces, an analytic framework designed to address these and other needs, and gives examples of the framework's practical utility using data from the Tapped In educator professional network. The Traces framework identifies observable contingencies between events and uses these to build more abstract models of interaction and ties represented as graphs. Applications are illustrated to identification of sessions and key participants in the sessions, relations between sessions as mediated by participants, and longer-term participant roles.

References

[1]
I. E. Allen and J. Seaman, Changing Course: Ten Years of Tracking Online Education in the United States, 2013.
[2]
J. Andriessen, M. Baker and D. D. Suthers, eds., Arguing to Learn: Confronting Cognitions in Computer-Supported Collaborative Learning Environments., Kluwer, Dordrecht, 2003.
[3]
S. A. Barab, R. Kling and J. H. Gray, Designing for Virtual Communities in the Service of Learning, Cambridge University Press, New York, 2004.
[4]
V. D. Blondel, J.-L. Guillaume, R. Lambiotte and E. Lefebvre, Fast unfolding of communities in large networks, Journal of Statistical Mechanics: Theory and Experiment, http://dx.doi.org/10.1088/1742-5468/2008/10/P10008 (2008).
[5]
D. Boyd and K. Crawford, Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon, nformation, Communication, & Society, 15 (2012), pp. 662--679.
[6]
R. Bromme, F. W. Hesse and H. Spada, eds., Barriers and Biases in Computer-Mediated Knowledge Communication And How They May Be Overcome, Springer, New York, 2005.
[7]
C. Charles, Analysis of Communication Flow in Online Chats, Department of Computer Science and Applied Cognitive Science, Unpublished Master's Thesis, University of Duisburg-Essen, Duisburg, Germany, 2013, pp. 90.
[8]
M. De Laat, Networked Learning, Politie Academie, Apeldoorn, 2006.
[9]
M. De Laat, V. Lally, L. Lipponen and R.-J. Simons, Investigating patterns of interaction in networked learning and computer-supported collaborative learning: A role for Social Network Analysis, International Journal of Computer Supported Collaborative Learning, 2 (2007), pp. 87--103.
[10]
U. Farooq, P. Schank, A. Harris, J. Fusco and M. Schlager, Sustaining a community computing infrastructure for online teacher professional development: A Case Study of Designing Tapped In, Computer Supported Cooperative Work, 16 (2007), pp. 397--429.
[11]
S. Fortunato, Community detection in graphs, Physics Reports, 486 (2010), pp. 75--174.
[12]
I. Halatchliyski, T. Hecking, T. Göhnert and H. U. Hoppe, Analyzing the path of ideas and activity of contributors in an open learning community, Journal of Learning Analytics, 1 (2014), pp. 72--93.
[13]
C. Haythornthwaite and A. Gruzd, Analyzing networked learning texts, in V. Hodgson, C. Jones, T. Kargidis, D. McConnell, S. Retalis, D. Stamatis and M. Zenios, eds., Proc. 6th International Conference on Networked Learning, Lancaster University, Halkidiki, Greece, 2008.
[14]
T. Hecking, S. Manske, L. Bollen, S. Govaerts, A. Vozniuk and H. U. Hoppe, A Flexible and Extendable Learning Analytics Infrastructure, in E. Popescu, R. H. Lau, K. Pata, H. Leung and M. Laanpere, eds., Advances in Web-Based Learning -- ICWL 2014, Springer International Publishing, 2014, pp. 123--132.
[15]
S. Joseph, V. Lid and D. D. Suthers, Transcendent Communities, in C. Chinn, G. Erkens and S. Puntambekar, eds., The Computer Supported Collaborative Learning (CSCL) Conference 2007, International Society of the Learning Sciences, New Brunswick, 2007, pp. 317--319.
[16]
B. Latour, Reassembing the Social: An Introduction to Actor-Network-Theory, Oxford University Press, New York, 2005.
[17]
J. Lave and E. Wenger, Situated Learning: Legitimate Peripheral Participation, Cambridge University Press, Cambridge, 1991.
[18]
J. L. Lemke, Across the scales of time: Artifacts, activities, and meanings in ecosocial systems, Mind, Culture & Activity, 7 (2000), pp. 273--290.
[19]
A. Martínez, Y. Dimitriadis, E. Gómez-Sánchez, B. Rubia-Avi, I. Jorrín-Abellán and J. A. Marcos, Studying participation networks in collaboration using mixed methods, International Journal of Computer-Supported Collaborative Learning, 1 (2006), pp. 383--408.
[20]
R. Milo, S. S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii and U. Alon, Network Motifs: Simple building blocks of complex networks, Science, 298 (2002), pp. 824--827.
[21]
P. R. Monge and N. S. Contractor, Theories of Communication Networks, Oxford University Press, Oxford, 2003.
[22]
M. Newman, Networks: An Introduction, Oxford University Press, 2010.
[23]
T. O'reilly, What is Web 2.0 - Design patterns and business models for the next generation of software, http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html, 2005.
[24]
J. Perkins, Python Text Processing with NLTK 2.0 Cookbook, Packt Publishing, Birmingham, UK, 2010.
[25]
J. Raskin, The Humane Interface: New Directions for Designing Interactive Systems, Addison Wesley, Reading, Mass., 2000.
[26]
K. A. Renninger and W. Shumar, Building Virtual Communities: Learning and Change in Cyberspace, Cambridge University Press, Cambridge, 2002.
[27]
B. Rogoff, Observing sociocultural activity on three planes: Participatory appropriation, guided participation, and apprenticeship., in J. V. Wertsch, P. D. Rio and A. Alvarez, eds., Sociocultural Studies of Mind, Cambridge University Press, New York, 1995, pp. 139--164.
[28]
C. P. Rosé, Y.-C. Wang, Y. Cui, J. Arguello, K. Stegmann, A. Weinberger and F. Fischer, Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning, International Journal of Computer-Supported Collaborative Learning, 3 (2008), pp. 237--271.
[29]
D. Rosen and M. Corbit, Social network analysis in virtual environments, Proc. 20th ACM conference on Hypertext and hypermedia (HT '09), ACM, New York, NY, 2009, pp. 317--322.
[30]
M. Scardamalia and C. Bereiter, Higher Levels of Agency for Children in Knowledge Building: A Challenge for the Design of New Knowledge Media, The Journal of the Learning Sciences, 1 (1991), pp. 37--68.
[31]
M. Schlager, J. Fusco and P. Schank, Evolution of an Online Education Community of Practice, in K. Renninger and W. Shumar, eds., Building Virtual Communities, Cambridge University Press, Cambridge, 2002, pp. 129--158.
[32]
G. Siemens, Massive Open Online Courses: Innovation in Education?, in R. McGreal, W. Kinuthia, S. Marshall and T. McNamara, eds., Open Educational Resources: Innovation, Research and Practice, Commonwealth of Learning and Athabasca University, Vancouver, 2013, pp. 5--15.
[33]
G. Stahl, Group Cognition: Computer Support for Collaborative Knowledge Building, MIT Press, Cambridge, MA, 2006.
[34]
D. D. Suthers, Technology affordances for intersubjective meaning-making: A research agenda for CSCL, International Journal of Computer Supported Collaborative Learning, 1 (2006), pp. 315--337.
[35]
D. D. Suthers and C. Desiato, Exposing chat features through analysis of uptake between contributions, Proc. Hawaii International Conference on the System Sciences (HICSS-45), January 4--7, 2012, Grand Wailea, Maui, Hawai'i (CD-ROM), Institute of Electrical and Electronics Engineers, Inc. (IEEE), New Brunswick, 2012.
[36]
D. D. Suthers and N. Dwyer, Identifying uptake, sessions, and key actors in a socio-technical network, Proc. Hawaii International Conference on the System Sciences (HICSS-44), January 5--8, 2011, Kauai, Hawai'i (CD-ROM), Institute of Electrical and Electronics Engineers, Inc. (IEEE), New Brunswick, 2015, pp. CD-Rom.
[37]
D. D. Suthers, N. Dwyer, R. Medina and R. Vatrapu, A framework for conceptualizing, representing, and analyzing distributed interaction, International Journal of Computer Supported Collaborative Learning, 5 (2010), pp. 5--42.
[38]
D. D. Suthers, J. Fusco, P. Schank, K.-H. Chu and M. Schlager, Discovery of community structures in a heterogeneous professional online network, Proc. Hawaii International Conference on the System Sciences (HICSS-46), January 7--10, 2013, Grand Wailea, Maui, Hawai'i (CD-ROM), Institute of Electrical and Electronics Engineers, Inc. (IEEE), New Brunswick, 2013.
[39]
D. D. Suthers, K. Lund, C. P. Rosé, C. Teplovs and N. Law, Productive Multivocality in the Analysis of Group Interactions, Springer, New York, 2013.
[40]
D. D. Suthers and D. Rosen, A unified framework for multilevel analysis of distributed learning in G. Conole, D. Gašević, P. Long and G. Siemens, eds., Proc. First International Conference on Learning Analytics & Knowledge, Banff, Alberta, February 27--March 1, 2011, ACM, New York, NY, 2011, pp. 64--74.
[41]
S. Trausan-Matu and T. Rebedea, A polyphonic model and system for inter-animation analysis in chat conversations with multiple participants, in A. Gelbukh, ed., Computational Linguistics and Intelligent Text Processing, Springer, Berlin, 2010, pp. 354--363.
[42]
S. Wasserman and K. Faust, Social Network Analysis: Methods and Applications, Cambridge University Press, New York, 1994.

Cited By

View all
  • (2024)Architectural learning networks: a study on eliciting the learning agendas of architectural schoolsArchnet-IJAR: International Journal of Architectural Research10.1108/ARCH-12-2023-0358Online publication date: 13-May-2024
  • (2024)How group structure, members' interactions and teacher facilitation explain the emergence of roles in collaborative learningLearning and Individual Differences10.1016/j.lindif.2024.102463112(102463)Online publication date: May-2024
  • (2024)Integrating Theories of Learning and Social Networks in Learning AnalyticsTheory Informing and Arising from Learning Analytics10.1007/978-3-031-60571-0_9(139-151)Online publication date: 29-Dec-2024
  • Show More Cited By

Index Terms

  1. From contingencies to network-level phenomena: multilevel analysis of activity and actors in heterogeneous networked learning environments

          Recommendations

          Comments

          Information & Contributors

          Information

          Published In

          cover image ACM Other conferences
          LAK '15: Proceedings of the Fifth International Conference on Learning Analytics And Knowledge
          March 2015
          448 pages
          ISBN:9781450334174
          DOI:10.1145/2723576
          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 the author(s) 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].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          Published: 16 March 2015

          Permissions

          Request permissions for this article.

          Check for updates

          Author Tags

          1. interaction analysis
          2. learning analytics
          3. networked learning environments
          4. social network analysis

          Qualifiers

          • Research-article

          Funding Sources

          Conference

          LAK '15

          Acceptance Rates

          LAK '15 Paper Acceptance Rate 20 of 74 submissions, 27%;
          Overall Acceptance Rate 236 of 782 submissions, 30%

          Contributors

          Other Metrics

          Bibliometrics & Citations

          Bibliometrics

          Article Metrics

          • Downloads (Last 12 months)4
          • Downloads (Last 6 weeks)1
          Reflects downloads up to 20 Jan 2025

          Other Metrics

          Citations

          Cited By

          View all
          • (2024)Architectural learning networks: a study on eliciting the learning agendas of architectural schoolsArchnet-IJAR: International Journal of Architectural Research10.1108/ARCH-12-2023-0358Online publication date: 13-May-2024
          • (2024)How group structure, members' interactions and teacher facilitation explain the emergence of roles in collaborative learningLearning and Individual Differences10.1016/j.lindif.2024.102463112(102463)Online publication date: May-2024
          • (2024)Integrating Theories of Learning and Social Networks in Learning AnalyticsTheory Informing and Arising from Learning Analytics10.1007/978-3-031-60571-0_9(139-151)Online publication date: 29-Dec-2024
          • (2023)Forum posts, communication patterns, and relational structures: A multi-level view of discussions in online coursesEducational technology research and development10.1007/s11423-023-10262-972:5(2655-2678)Online publication date: 28-Jun-2023
          • (2022)A Systems Approach to Studying Online CommunitiesMedia and Communication10.17645/mac.v10i2.504210:2(29-40)Online publication date: 29-Apr-2022
          • (2022)Temporal networks in collaborative learning: A case studyBritish Journal of Educational Technology10.1111/bjet.1318753:5(1283-1303)Online publication date: 10-Feb-2022
          • (2021)Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching SituationsSensors10.3390/s2123799821:23(7998)Online publication date: 30-Nov-2021
          • (2021)Educational dialogues and computer supported collaborative learning: critical analysis and research perspectivesInternational Journal of Computer-Supported Collaborative Learning10.1007/s11412-021-09359-116:4(583-604)Online publication date: 3-Dec-2021
          • (2021)Modelling diffusion in computer-supported collaborative learning: a large scale learning analytics studyInternational Journal of Computer-Supported Collaborative Learning10.1007/s11412-021-09356-4Online publication date: 2-Dec-2021
          • (2020)Are forum networks social networks?Proceedings of the Tenth International Conference on Learning Analytics & Knowledge10.1145/3375462.3375531(366-375)Online publication date: 23-Mar-2020
          • Show More Cited By

          View Options

          Login options

          View options

          PDF

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader

          Media

          Figures

          Other

          Tables

          Share

          Share

          Share this Publication link

          Share on social media