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Mining physiological data for automated educational feedback

Publication at Faculty of Mathematics and Physics |
2009

Abstract

The authors present, on the base of their own research activities and recent studies, dealing with neurology, educational psychology, cognitive brain science, etc., the great potential of data, obtained from noninvasive physiological measurement, for immediate and individualized reaction on the learning process of the learning subject. They emphasized electrodermal activities (e.g. galvanic skin response) measurements, eyes tracking, blink rate and blink speed measurements, and heart rate (esp.

EEG), for their potential to reflect decreasing attention, increasing visual or cognitive information load, task difficulty, tension, arousal, stress and fatigue of the learning subject. The present paper highlights the advantages and constraints of different physiological monitoring approaches, their advantages as well as constraints, done by (1) the hardware and software limits, (2) by the necessity of individual setup (often continuous), (3) by the problems with real time data processing.