Can EEG-devices differentiate attention values between incorrect and correct solutions for problem-solving tasks?

The affective state of an individual can be determined using physiological parameters; important metric that then extracted is attention. Looking more closely at compact EEGs, algorithms have been implemented in such devices measure the attention and other states user. No information about these available; are feature classification accurate? An experiment was conducted with 23 subjects who utilized a pedagogical agent to learn syntax programming language Java while having their measured by NeuroSky MindWave Mobile 2. Using concurrent validity approach, values were compared band powers, as well measures task performance. results part successful supportive claim EEG device’s algorithm does fact represent user’s accurately. analysis based on raw data captured from device consistent previous literature. Inconclusive obtained relating performance