Research on the Dynamic Evolution of Cognitive Engagement in Complex Problem Solving—From the Perspective of Synchronous Physiological Response Events
In today's society,the dynamic nature puts unprecedented demands on learners'complex problem solving ability,and learners'cognitive engagement in solving complex problems directly affects the efficiency and quality of task completion.The study collects learners'galvanic skin response data in the context of design-based problem-solving,and proposes a method for measuring cognitive engagement based on synchronous physiological response events.The study focuses on the dynamic evolution features of cognitive engagement in complex problem-solving,analyzes its association with individual and group performance,and ultimately uses the random forest algorithm to construct a predictive model for individual and group performance.It is found that the frequency of synchronous physiological response events gradually increases when the group solving complex problems.At the individual level,learners'engagement agility and persistence demonstrate significant dynamic evolution.At the group level,high-performance groups exhibit significant changes in engagement intensity and synchronicity,while low-performance groups show significant changes only in engagement persistence.Among all features,the engagement agility in the plan generation phase is a key factor to predict individual performance,and the engagement persistence in the perspective exchange phase has the best predictive effect on group performance.The study expands the method of identifying cognitive patterns in complex situations,and provides empirical evidence for improving students'abilities to solve complex problems.
Complex Problem SolvingCognitive EngagementSynchronous Physiological Response EventsDynamic EvolutionLearning Prediction
NETL
NSTL
万方数据
