| Learning is the process of acquiring knowledge, skills and values, through lifelong education. Learning abilities are affected by the subject's cognitive skills showing how they think, process information, pay attention and remember things. The dynamic nature of a human's mental state usually impacts the aforementioned structural characteristics of human cognition, hindering learning performance as well. Nowadays, technological advances in Brain-Computer Interface (BCI) systems, in combination with advanced processing methods, have paved the way for the highly accurate capturing of human brain activity, helping to decode cognitive and mental status to adapt the learning process. This paper aims to present the first research outcomes of a study in progress. More specifically, the main proposition lies in extending the basic functionalities of our electroencephalography (EEG)-based e-learning prototype system to deliver personalized solutions by taking into account the individual cognitive differences of the learners. Some primary findings are showcased that investigate the potential association of cognitive style with the power spectral features of brain activity in a specific context where the subjects execute a visual task. It is anticipated that the real-time recognition of the learner's cognitive style will help educators adapt and advance the learning process. |
*** Title, author list and abstract as seen in the Camera-Ready version of the paper that was provided to Conference Committee. Small changes that may have occurred during processing by Springer may not appear in this window.