Cognitive engagement is essential for effective learning,particularly within collaborative learning contexts.However,imbalances in cognitive engagement among collaborative learners can result in negative behaviors,such as"free-riding".Additionally,precisely measuring cognitive engagement remains a challenge due to its implicit nature.Advances in physiological data collection technologies offer a promising approach to reveal the"black box"of cognitive engagement measurement in collaborative settings.This study conceptualizes cognitive engagement in collaborative scenarios through two dimensions:arousal and adaptability.A total of 184 university students participated in a collaborative task called"Sponge Campus Design",during which portable physiological devices were used to collect skin conductance and heart rate data.The goal was to develop a measurement model of cognitive engagement in collaborative learning contexts.Results indicate that sympathetic nervous system activity effectively reflects arousal levels,while parasympathetic nervous system activity serves as a more accurate measures of adaptation.Using signal processing and feature engi-neering techniques,the study identified 15 features across time-domain,frequency-domain,and morphological levels of the physio-logical data.Principal component regression analysis revealed that this feature set accounted for 39.7％of the variance in cognitive engagement,demonstrating strong reliability and validity of the measurement model.Adaptation,representing the directionality of cog-nitive engagement in collaborative tasks,was found to have greater educational value than arousal.During the collaborative process,learners'arousal levels followed a decreasing-then-increasing trend,while adaptation consistently improved.This study contributes to the theory of cognitive engagement,provides teachers with a deeper understand of student learning,and offers insights for enhancing collaborative learning outcomes.
维普
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