Dynamic assessment of learners´ mental state for an improved learning experience

It is very challenging to provide a learning experience which is meaningful, motivated and at the same time enjoyable in nature. This often affects the students who cannot learn or do not want to learn due to lack of engagement and guidance. The same scenario is also true for working professionals in industries. Cognitive flow, defined as the mental state in which a subject is fully concentrating with a feeling of full involvement and enjoyment, is reported to play a key role in this. There are different questionnaire based indirect methods for measuring ones´ flow state. However, in our present work we attempt to measure the flow state more directly using Electroencephalogram and multi-modal physiological signals including heart rate variability and galvanic skin response. Twenty right-handed engineers from our research lab played a video game to induce conditions of boredom and flow. A modified colour based Tetris (similar to Stroop test) game is used for the said purpose. A comparative study is done between the offline questionnaire based and the physiological signal based flow measurements. From the results it is clear that flow/boredom state can be derived from brain signals, which is modeled using Markov chain, as well as from other physiological signals. Hence can be used as an important feedback in various applications for maintaining a steady flow state for a longer period. Finally, the flow-boredom model generated from brain signals has been used in Web Based Learning to automatically measure the learning experience.