The effectiveness of an online learning system based on aptitude scores: An effort to improve students’ brain activation

The differences in learning preferences can be attributed to the differences in individuals’ cognitive capacities which may lead them to undertake a certain behavior. It is argued that characterizing the learning complexity based on the volume of information presented to learners can eliminate any avoidable load on working memory. This study examined the effectiveness of an online continuous adaptive mechanism (OCAM) based on changes in learner aptitude scores across learning sessions. The representation of the learning content in these sessions was designed for a low-, medium-, and high-aptitude individual. The brain activation of 12 students (6 male and 4 female; aged 20–25 years), obtained from using the proposed system, was examined using an electroencephalogram (EEG). The result showed that OCAM helped learners to understand the content being presented according to their aptitude scores, thus improving their brain activation. Findings from this study can be used to inform online system designers and developers about the importance of incorporating aptitude scores for customizing the representation of learning materials in an online environment.