Department of Curriculum, Teaching and Learning University of Toronto
Andante, Allegro o Silenzio: An Examination of Background Music Tempo on Facial Emotions, Electrodermal Responses, and Reading Task Performance
Current literature has established that learner’s emotions are an integral part of the learning experience (Pekrun & Perry, 2014) and have significant effects on learning processes that optimize performance (Cunningham, Dunfield, & Stillman, 2013), and attentional responses (Kärner & Kögler, 2016). This present study examines the psychoemotional and psychophysiological effects that variations in the tempo of background music have on learners who are completing reading comprehension tasks. To accomplish this, the present study examines how learning performance is modulated through the expressed emotions and bodily responses of participants and how our understanding of the relationship between the emotional experience and cognitive functions in learning tasks.
This study utilized modern facial-recognition technology to collect real-time data about participant emotions and provide a quantitative rating of emotions based on facial muscular movements using iMotions Emotient (FACET) 7.1 software. The software recorded an 8-second baseline that was used to set participant responses for the entire study. This data was collected using a Logitech 1080p HD web camera for processing and analysis. GSR was measured using a Biopac™ MP160 system with 2 wet sensors that were
attached to the palm of the participant’s non-dominant hand. Once the sensors were placed and attached to the central unit, the researchers ensured that the participant had 46 adequate range of motion so that their hand was not impeded. These sensors measure changes to arousal to provide a view into the psychophysiological impulses and changes that may occur as a result of internal response mechanisms
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of Curriculum, Teaching and Learning University of Toronto
© Copyright by Matthew Moreno, 2020