October 12, 2021
Artificial Intelligence, Conference, Conference, Further Education, Higher Education, Lifelong Learning, Multimodal Learning Analytics, Publication

“Soul and body, I suggest reacting sympathetically upon each other. A change in the state of the soul produces a change in the shape of the body and conversely, a change in the shape of the body produces a change in the state of the soul.”

To test this hypothesis proposed by Aristotle, our bachelor student Tetiana Buraha investigated the physiology of students performing task-switching exercises. The physiological data were collected using an Empatica E4 band. The performances of the students were compared against the physiological data using descriptive statistics and machine learning techniques.

The analysis of Tetiana enabled the identification of interesting correlations between galvanic skin response and performance, and models to predict performance based on the physiological data.

Results of her excellent thesis were published and presented at the European Conference of Technology Enhanced Learning 2021.

  1. Buraha, T., Schneider, J., Mitri, D. D., &amp Schiffner, D. (2021). Analysis of the “D’oh!” Moments. Physiological Markers of Performance in Cognitive Switching Tasks. In European Conference on Technology Enhanced Learning (pp. 137-148). Springer, Cham.