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

This is the authors' abstract. We don't add key points for this paper.

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.