IEEE Transactions on Affective Computing · 2023 · 15 citations · 28 references
EducationEducational PsychologyEducational TechnologyInstructional DesignNonverbal CommunicationStudent EngagementAffective ComputingAffective Computing In EducationAffective State DetectionEmotion RecognitionEmotional ExpressionFacial ExpressionAffectAffective Facial ExpressionsEmotion Recognition From Nonverbal BehaviorFacial Affect AnalysisFacial Affect RecognitionFacial Emotion PerceptionFacial Expression RecognitionSelf-reports Of Affect
Recent technological and educational shifts have made it possible to capture students' facial expressions during learning with the goal of detecting learners' emotional states. Those interested in affect detection argue these tools will support automated emotions-based learning interventions, providing educational professionals with the opportunity to develop individualized, emotionally responsive instructional offerings at scale. Despite these proposed use-cases, few have considered the inherent ethical concerns related to detecting and reporting on learners' emotions specifically within applied educational contexts. As such, this paper utilizes a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Reflexive Principlism</i> approach to establish a typology of proactive reflexive ethical implications in tracking students' emotions through changes in their facial expressions. Through this approach the authors differentiate between use in research and applied education contexts, arguing that the latter should be curtailed until the ethics of affective computing in educational settings is better established.
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Comprehensive database for facial expression analysis
Takeo Kanade, Jeffrey F. Cohn, Yingli Tian · 2002 · 2.6K citations