Electroencephalogram (EEG) Signals for Modern Educational Research

Present classroom observation techniques include live or video surveillance, metrics for self-reports interviews, and questionnaires. Nevertheless, such conventional techniques are subject to biases by investigators in evaluating behavioral aspects and are challenging to analyze for quick and effective reviews. Moreover, the inclusion of additional persons as investigators in the lecture hall can modify the dynamics between teachers and students. The recent extensive developments in portable electroencephalogram (EEG) devices have paved the way for a comparatively new source of quantitative data, independent from observational prejudice and commonly equipped with built-in analytical tools for convenience. In this chapter of this book, we begin the discussion of the fundamentals of electroencephalogram (EEG) signals in the field of education. Afterward, we summarize the current use of EEG signals and explore how these signals could be used as monitoring resources for educational scientists. We found that EEG signals were primarily used in the following areas: learning performance promotion, motor skills acquisition, e-learning, edutainment, interactive behavior, learning materials presentation behaviors, and reading context. We also found that EEG signals were mostly used to test students' concentration and meditation, and most of the EEG studies lasted less than an hour, the sample sizes of EEG signals-based studies were limited, and the largest study group were university students. We also discuss in the book chapter that, although current EEG signals based portable devices are yet to be adapted for usage in a classroom, these devices have tremendous promise as a source of producing quantitative findings when used efficiently, with flexible, accurate, objective, and speedy results to complement current techniques for conducting classroom teaching research. We address the challenges of EEG signal devices in the final section of the book chapter, and they face two main challenges: substantial calculation mistakes and discomfort to wear in large-scale and long-term studies. There are also some testing constraints: not just the absence of experiments of naturalistic classroom conditions but also the absence of studies to explore all cognitive facets. In the near future, EEG signals-based devices can be used widely in the field of education if it can overcome the above-mentioned challenges.