Utilization of Bio-Signals to Understand the Physiological States of e-Learners and Improve the Learning Contents
This paper presents a new dimension in e-learning by collecting and analyzing physiological data during real-world e-learning sessions. Two different content materials, namely Interactive (IM) and Non-interactive (N-IM), were utilized to determine the physiological state of e-learners. Electrocardiogram (ECG) and Skin Conductance Level (SCL) were recorded continuously while learners experienced IM and N-IM for about 25 minutes each. Data from 18 students were collected for analysis. As a result significant difference between IM and N-IM was observed in SCL (p < .01) meanwhile there were no significance in other indices such as heart rate and its variability, and skin conductance response (SCR). This study suggests a new path in understanding e-learners' physiological state with regard to different e-learning materials; the results of this study suggest a clear distinction in physiological states in the context of different learning materials.
e-learning ecg skin conductance level skin conductance response heart rate variability