Tools for Cognitive Load Evaluation in the Education Process

Abstract

Cognitive load evaluation is an approach to boost educational efficiency. According to John Sweller, cognitive load represents the effort being used by working memory. Cognitive load and overload classification can become useful for creating educational courses. In this paper, we describe an algorithm for a mental-state cognitive load classifier based on basic statistical instruments. We show the cognitive load model based on low-cost EEG frontal theta-activity (4–7 Hz) registration. We also describe an experimental algorithm to evaluate the model with Sternberg-task and show the results in terms of precision, recall, and F-score. During the approbation, the described model had shown results, that are comparable to the ones of machine-learning mental-state classifiers. This paper can be used as an instruction to quick creation and approbation of practiceoriented cognitive load models.