AI in Education: Detecting emotions to improve learning

Can AI detect emotion? Can this ability be used in online education to improve student attention and performance? Affective computing is a branch of AI concerned with development of systems that can recognize, interpret, process, and simulate human affects.

Our affective computing research uses a facial recognition technique for detection of microexpressions. We are studying the identification of states such as Cognitive Dissonance, using these microexpression patterns. In this talk, we discuss how emotion detection techniques can be used in online education to improve student’s attention and performance using the example of cognitive dissonance detection. We will discuss some of our data and findings from our research. More broadly, we will discuss deep learning and machine learning for computational modelling of cognition and behaviour. We are looking for collaborators in the education domain for our work.

 

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