ABSTRACT
Legitimate dry-contract electrode Electroencephalogram (EEG) systems finally seem to be within reach. This technical advance opens possibilities for innovation in student/trainee assessment by reducing one of the long-standing barriers to EEG use in the classroom/simulation lab environments: user acceptance. However, three major barriers remain. First, motion, muscle, and ambient electrical artifacts are still a problem. Supervised post-processing by experienced EEG technicians is still common practice. Classrooms and simulation labs do not and will not have the benefit of skilled technicians. Automated methods for reliably cleaning the data, without loss of information, are necessary. Second, the pedagogical value of EEG-based assessment must be convincingly demonstrated. Most efforts to enhance training or education through application of EEG-based assessment have been solutions in search of problems. Instead of asking what EEG can tell us and how we can use that knowledge to enhance training and education, we need to ask what the high priority training and education gaps are and whether EEG-based assessments can help fill them. Finally, signal variation, both between individuals and within individuals from day-to-day, are frequent problems in EEG signal detection. In the research environment, some of this variation is minimized through practices that will not be acceptable in the mainstream environment (e.g., limiting head movement and screening out left-handers). This variation in signal source detection needs flexible and robust solutions so that all students/trainees can receive 282any benefits that are brought about through the introduction of EEG-based assessment practices. This paper discusses these barriers and suggests solutions that are necessary for the long-heralded brain-based education and training revolution to take hold.
