Mining physiological data for automated educational feedback - new attitude to learning in virtual environments

Abstract

The authors present, on the base of recent studies, the great potential of data, obtained from 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 data acquisition approaches and methods (including technical and physiological), as well as constraints, done by the hardware and software limits, by the necessity of individual setup (often continuous), by the problems with real time data processing, including wrong data recognition and elimination, etc.

Analyzing data of GSR, EEG and eye tracking studies.