The current study examined EEG coherence across Coach-Learner dyads on a spatial reasoning video game, Tetris®, using an event-locked psychophysiological synching platform. We hypothesized that (1) an intra-individual increase in Theta and a decrease in high Alpha (10-12 Hz) fronto-temporal coherence would occur across increasing difficulty levels, and (2) inter-individual fronto-temporal coherence in high Alpha would increase among lower skilled players. A sample of n = 5 healthy dyads completed the protocol with each learner playing 3 rounds of Tetris®. Across all participants (low-skilled and high-skilled), the intra-individual preliminary results presented herein indicate significant elevation in fronto-parietal coherence. Moreover, the low-skilled players experienced an increase in Theta coherence and high Alpha coherence–the latter not as expected from literature. The high-skilled players had significant reductions in fronto-parietal high Alpha coherence and small increases in Theta. The inter-individual (coach-learner) dyadic coherence results for the low-skilled player showed increased Theta coherence for Coach-Frontal: Learner-Parietal (CF:LP), with no significant change in high Alpha. Meanwhile, an increase in high Alpha coherence was observed in the Coach-Parietal: Learner-Frontal (CP:LF). The high-skilled player experienced decreased Theta coherence for CF:LP, with no significant change in high Alpha, yet a substantial increase in Theta coherence and decrease in high Alpha coherence was observed for CP:LF. These data support the application of coherence analyses for the improvement of pedagogical approaches and provide optimism that further granulated explorations of the data herein could lead to a more thorough understanding of the dynamics of dyadic learning.
CITATION STYLE
Stone, B., Correa, K., Thor, N., & Johnson, R. (2015). EEG coherence within tutoring dyads: A novel approach for pedagogical efficiency. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9183, pp. 697–706). Springer Verlag. https://doi.org/10.1007/978-3-319-20816-9_67
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