Physiological Computing-Based Cognitive Load Assessment:Motivations,Key Issues and Features—A Physiological Computing Framework for Cognitive Status Assessment
Cognitive load assessment in the learning field suffers from the problems of lack of process data,single dimension of assessment,and insufficient accuracy of assessment.Multimodal data fusion and analysis technology reveals the representation mechanism of cognitive load from multidimensional spatial and temporal scales,and re-examines the cognitive load measurement problem in a data-driven paradigm,which can help to form a more effective method to understand the learning cognition and related laws.Based on this,the article analyzes the motivations for integrating physiological data to drive cognitive load measurement from the overview of the current state of cognitive load measurement research.It also analyzes the key issues involved in the development of related research,such as the computability of cognitive load,the interpretability of cognitive load representation model,and the computation of cognitive load element weights,and clarifies the multidimensional,process,and accuracy characteristics of the fusion of physiological data-driven cognitive load assessment.Finally,the article analyses and explains the educational physiological computational framework based on the idea of"theoretical model—data collection—model construction—computational analysis and pattern recognition".
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