Social differentiation, participation inequality and optimal collaborative learning online
Robert Jay Bruno, Purdue University, United States
Purdue University . Awarded
This dissertation examines social self-structuring processes and group collaboration online with a special focus on their learning effects. Review of empirical and theoretical literature suggests that functional differentiation and participation inequalities are a constant phenomenon in small and large groups, both online and off. This dissertation examines what effects these inequalities may have on group performance, especially with respect to learning. An optimal unevenness range is proposed in the construct model wherein a curvilinear relationship exists between participation evenness and learning outcomes. A key element of Shannon's mathematical theory of communication, the entropy function, is proposed as a measure of interaction in a wiki online collaborative environment. The author's hypothesis of a curvilinear relationship between relative group participation and learning gain is informed by a broad range of literature from small group communication, system-level analyses, recent examinations of mass collaboration and open source software development, collaborative learning theory, developmental psychology, visual feedback technology, and information theory. A quasi-experimental design was proposed as the best way to test the hypothesis and answer relevant research questions. The procedure included 170 participants on teams of 4-11 co-constructing Purdue-related topics within three broad groupings, 1) a regular wiki, 2) the entropy-enabled Visible Effort Wiki, and 3) offline. Variant entropy levels and control variables were correlated with learning gain, as measured by pretests and posttests. Perceived measures were added as well. Research results and data analysis showed the overall model to be statistically significant at the group level. All predictor variables, including entropy, technical competence, and effort level, and excepting knowledge of Purdue University, were significant. On the individual, perceived level the overall model showed a significant linear effect and all predictor variables, except knowledge of Purdue, were significant. Results support a curvilinear relationship between participation levels and learning for objective measures, and overall findings showed a clear relationship between these two variables. Discussion of findings, study limitations, implications, and avenues for future research follow.
Bruno, R.J. Social differentiation, participation inequality and optimal collaborative learning online. Ph.D. thesis, Purdue University.
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Uncovering the sequential patterns in transformative and non-transformative discourse during collaborative inquiry learning
Gaoxia Zhu, Ontario Institute for Studies in Education, Canada; Wanli Xing, Department of Educational Psychology & Leadership, United States; Vitaliy Popov, Jacobs Institute for Innovation in Education, United States
Internet and Higher Education Vol. 41, No. 1 (April 2019) pp. 51–61
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