Mining physiological data for automated feedback in virtual learning environments

Authors present the great potential of data, obtained from real time physiological measurement, for immediate and individualized reaction on the learning process of the learning subject in virtual learning environments. The simple, non invasive, easily available and cheap methods like eyes tracking, blink rate and blink speed measurements, electrodermal activities measurements, and heart and/or respiration rate, are emphasized for their potential to reflect decreasing attention, increasing visual or cognitive information load, task difficulty, tension, stress and fatigue. Presented paper highlights the advantages and constraints of different data acquisition approaches, as well as constraints, done by hardware and software limits, and discusses their future potential for the out of laboratory uses.