Vasiliki Georgoulas

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Computational models that automatically detect learners’ affective states are powerful tools for investigating the interplay of affect and learning. Over the past decade, affect detectors—which recognize learners’ affective states at run-time using behavior logs and sensor data—have advanced substantially across a range of K-12 and postsecondary education(More)
We report the case of a 57-year old man who was admitted to our department because of worsening dyspnea - orthopnea and whose aortic valve had been replaced 31 years previously, with a Starr-Edwards caged-ball prosthesis. His symptoms' deterioration was due to a recent myocardial infarction which in combination with the chronic mitral regurgitation of(More)
Tutoring systems researchers have recognized the need to identify and address affective states that lead to disengagement in learning activities (Baker, D’Mello, Rodrigo, & Graesser, 2010; D’Mello, Lehman, & Graesser, 2011; D’Mello Strain, Olney, & Graesser, 2013; Forbes-Riley, Litman, Friedberg, 2011; Gee, 2004, 2007; Picard et al., 2004). Some affective(More)
The role of affect in learning has received increasing attention from AIED researchers seeking to understand how emotion and cognition interact in learning contexts. The dynamics of affect over time have been explored in a variety of research environments, allowing researchers to determine the extent to which common patterns are captured by hypothesized(More)
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