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Title: Understanding the Effect of Group Variance on Learning
Authors: Yavuz, Sinan
Forkner, Michael
Gnesdilow, Dana
Tissenbaum, Catherine Dornfeld
Kim, Jee-Seon
Puntambekar, Sadhana
Issue Date: Jun-2019
Publisher: International Society of the Learning Sciences (ISLS)
Citation: Yavuz, S., Forkner, M., Gnesdilow, D., Tissenbaum, C. D., Kim, J., & Puntambekar, S. (2019). Understanding the Effect of Group Variance on Learning. In Lund, K., Niccolai, G. P., Lavoué, E., Hmelo-Silver, C., Gweon, G., & Baker, M. (Eds.), A Wide Lens: Combining Embodied, Enactive, Extended, and Embedded Learning in Collaborative Settings, 13th International Conference on Computer Supported Collaborative Learning (CSCL) 2019, Volume 1 (pp. 520-525). Lyon, France: International Society of the Learning Sciences.
Abstract: Given that group composition is a key factor that affects learning in CSCL environments, it is important to study how students in groups with homogeneous or heterogeneous levels of prior knowledge collaborate. This study investigated the potential differences in students' learning outcomes from participating in a 13-week design-based unit. We used the pre- and post-test data from 361 eighth grade students (102 groups) and performed a hierarchical linear model analysis to examine how the convergence or divergence in the students' level of prior knowledge affected students' learning outcomes. We found that students in homogenous groups with similar levels of initial prior knowledge scored significantly higher on their post-test when their pre-test was used as a covariate, than students in heterogeneous groups. Implications of these findings are discussed along with directions for future research.
Appears in Collections:CSCL 2019

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