Internet of Behavior and Brain Response Identification for Cognitive Performance Analysis

Learning efficiency analysis has evolved immensely in the aftermath of the COVID-19 epidemic. Technological methods for online learning and big data in the cloud have been applied to develop various curriculums; however, an analysis of learners' performance may only be done at a similar personal background group classification level. Therefore, this study presents a machine learning model for identifying cognitive performance under the principles and characteristics of the Internet of Behavior (IoB) and human brainwaves, which is more reliable than traditional data analysis. The proposed methodology can precisely classify learners according to their current cognitive performance of the brain through simple classification and IoB analysis that can immediately enhance class manipulation.