INSTRUCTIONAL DESIGN BASED ON THE ASSESSMENT OF COGNITIVE LOAD AND WORKING MEMORY LOAD

Abstract

Instruction is usually designed based on the cognitive load theory. Human cognition can be portrayed as a native information processing system while handling biologically secondary information, which works similarly to the information processing during evolution by natural selection. There is a critical aspect to be taken into account assuming that human cognition does not explicitly evolve to learn topics that require domain-specific knowledge. This characteristic of human cognition strongly related to the capacity of working memory is essential for the development of a germane architecture to instructional design. Considering that the working memory applies to a biologically secondary domain-specific knowledge that requires instruction, cognitive load provides techniques for calibrating working memory load during this process. The evaluation of a learning process performance for either standard systems or virtual e-learning environments is mainly associated with working memory activities. The goal of our work is to study different approaches to assess and classify cognitive load and working memory activity along teaching activity during stressful conditions. For this purpose, Electroencephalography (EEG) signals were acquired using both high-end and wireless EEG acquisition devices. The EEG signals were acquired from users involved in memory tests and typical reasoning scenarios. Electroencephalogram (EEG) recordings offer insightful information concerning diagnosis and prognosis of human thinking and memory-related processes, aiding researchers and physicians in Brain-Computer Interface (BCI) systems development. Oscillatory activity in all frequency bands characterizes with high accuracy different memory tasks. Alpha rhythms are spontaneous waves that appear in healthy awake adults under relaxation and mental inactivity. Beta waves are specific for central and frontal locations on the scalp enhancing during mental computations. Theta and delta rhythms are typically observed during deep sleep. Under task conditions, Theta reflects the degree of difficulty and portraits the transfer of information between long-term memory and memory functions. Considered the optimal frequency of brain functioning, Gamma brainwaves are patterns related to perception and consciousness. A statistical analysis of the EEG data is performed, while a comparison between several classifiers is meant to emphasize their fitting for working memory activities identification.