Abstract

Brain-computer interfaces, or BCIs, are hardware and software communication systems that can read and process brain signals. They can be classified into invasive, semi-invasive, and non-invasive categories based on their requirements for neurosurgery. Non-invasive BCIs that do not require brain surgery and use external sensing methods, like electroencephalography (EEG), can be used in research settings to understand brain function in cognitive psychology, access a person’s engagement level in activities, and control aspects of computers from neural signals. In an educational environment, they can monitor students’ drop in engagement and evaluate what teaching methods cause students to lose focus. We reviewed various studies that utilize BCIs to improve the quality of K-12 and post-secondary education and tutoring. Then, we conducted a case study using a public dataset to understand the correlation between attention, measured through EEG, and test scores based on the method of instruction.

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