What Do You Mean by Collaboration Analytics? A Conceptual Model

Using data to generate a deeper understanding of collaborative learning is not new, but automatically analyzing log data has enabled new means of identifying key indicators of effective collaboration and teamwork that can be used to predict outcomes and personalize feedback. Collaboration analytics...

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Bibliographic Details
Published in:Journal of Learning Analytics Vol. 8; no. 1; pp. 126 - 153
Main Authors: Martinez-Maldonado, Roberto, Gašević, Dragan, Echeverria, Vanessa, Fernandez Nieto, Gloria, Swiecki, Zachari, Buckingham Shum, Simon
Format: Journal Article
Language:English
Published: Society for Learning Analytics Research 01.01.2021
Subjects:
Case Studies
Communities of Practice
Computer Mediated Communication
Concept Mapping
Cooperative Learning
Design
Instructional Design
Learning Analytics
Simulation
Teamwork
Validity
ISSN:1929-7750, 1929-7750
Online Access:Get full text
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Summary:Using data to generate a deeper understanding of collaborative learning is not new, but automatically analyzing log data has enabled new means of identifying key indicators of effective collaboration and teamwork that can be used to predict outcomes and personalize feedback. Collaboration analytics is emerging as a new term to refer to computational methods for identifying salient aspects of collaboration from multiple group data sources for learners, educators, or other stakeholders to gain and act upon insights. Yet, it remains unclear how collaboration analytics go beyond previous work focused on modelling group interactions for the purpose of adapting instruction. This paper provides a conceptual model of collaboration analytics to help researchers and designers identify the opportunities enabled by such innovations to advance knowledge in, and provide enhanced support for, collaborative learning and teamwork. We argue that mapping from low-level data to higher-order constructs that are educationally meaningful, and that can be understood by educators and learners, is essential to assessing the validity of collaboration analytics. Through four cases, the paper illustrates the critical role of theory, task design, and human factors in the design of interfaces that inform actionable insights for improving collaboration and group learning.
ISSN:1929-7750
1929-7750
DOI:10.18608/jla.2021.7227