Advanced Learning Assistant System (ALAS) for Engineering Education

This study aims to develop a biofeedback tool to assess the efficiency of different learning and teaching techniques. Here, neuroengineering tools are used to detect and compare the level of learning obtained through two different modalities: a traditional text and an interactive video. Electroencephalographic signals were recorded in two groups during learning tasks, and performance was evaluated with an exam. Results showed better performance on the video group, as well as power changes in theta and beta bands, mainly in frontal and occipital cortices. A real time monitoring protocol of these features could be implemented to develop a learning evaluation tool based on biometric signals.