Feeler: supporting reflection in learning through EEG data

The increase of smart and wearable technologies that make use of sensors to monitor physiological data has enabled people access data about their mental and physical states and therefore, gain better understanding about themselves. In education, the use of physiological data is low since teachers still have difficulties in identifying the educational affordances of the technologies currently available in the market. We argue that smart objects and wearable devices that monitor electroencephalographic activity (EEG) offer opportunities for fostering reflection, a skill which has been recognized as key in learning. We present Feeler, a prototype that seeks to foster awareness and reflection based on the visualization of students electroencephalographic data when performing academic activities. Feeler design makes use of different design strategies for supporting reflection, such as time, personal experience, the display of hidden information and incompleteness. To date, Feeler proof-of-concept prototype has been tested with 6 higher education students. In the session, we will share the results obtained after the data analysis of the tests as
well as its implication for next design iterations. Through Feeler research we aim to discuss the possibilities and challenges of EEG data in learning and education.