An Enhanced Learner Evaluation Method Based on Psychophysiological Signals

Learning evaluation techniques have been a topic of interest in the research world during the past decades. Evaluation procedures of most of these techniques are based on the answers/evidence provided by the learners. The current evaluation techniques are not capable enough to analyze the psychophysiological parameters to evaluate the actual biological status of the learners. This study suggests an approach to analyze the psychophysiological parameters of the learners to evaluate their performance. The study is focused on utilizing the most suitable quantitative analysis technique to predict whether the learner had previous knowledge about a particular learning content. The first two objective levels of the Bloom's Taxonomy were assessed in this study; pictures of human faces were used to evaluate the first level, and mathematical equations were used to evaluate the second level. The main findings of this research are, 1) the psychophysiological signals captured from the human brain during the engagement in the first two objective levels of the Bloom's Taxonomy showed a clear difference, 2) the amplitude level for the positive activation in the brain cortex was higher when experimented with pictures of mathematical equations than using pictures of human faces. These findings merit further research in this area.