The dynamics of student engagement in cooperative science learning: a multimodal approach

Student engagement is critical for effective cooperative learning, but engagement is hard to measure due to its multidimensional and implicit nature. Here, we applied video coding, microanalysis, and neural measures to examine how students engage in group work. Nine groups of high school students (four students per group) participated in a cooperative learning task, in which they collaboratively created a model of a cell while their Electroencephalogram (EEG) brain activity was being recorded.

The whole session was also videotaped, transcribed, and coded offline. Analysis of video recordings revealed that students alternated between on-task, off-task, and idle states every 10–30 s on average. The duration of time students were on-task significantly predicted test performance.

EEG analysis revealed that both theta (4–7 Hz) and alpha activity (8–12 Hz) during idle states were indistinguishable from off-task states but significantly different from on-task states. Our findings point to the complexity of assessing student engagement in group work and to the need for interdisciplinary work that considers both brain and behavior as complementary information sources. We would like to thank the students who participated in the study and their school for supporting our research.

We would also like to thank D. Salas for their contribution to the microanalysis, and Z. Li for her contribution to statistical analyses.

This material is based upon work supported by the National Science Foundation under Awards #1661016 and #2526250, and European Research Council Award #ERC-CONS 101124369—Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them. Lynch School of Education and Human Development, Boston College, Chestnut Hill, MA, USA Psychology Department, Harvard University, Cambridge, MA, USA Department of Psychology, New York University, New York, NY, USA Gabriella A.

Ali, Laura Noejovich, Henry Valk, Dana Bevilacqua, David Poeppel & Suzanne Dikker Teachers College, Columbia University, New York, NY, USA Department of Experimental Psychology, Ghent University, Ghent, Belgium The authors declare no competing interests. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material.