Cognitive psychology, Affect, Boredom, Intelligent tutoring system and Artificial intelligence are his primary areas of study. His Cognitive psychology research is multidisciplinary, relying on both Mind-wandering, Cognitive science and Reading. The study incorporates disciplines such as Keystroke logging, Affective computing, Arousal and Body language in addition to Affect.
His Boredom research entails a greater understanding of Social psychology. His Intelligent tutoring system research is multidisciplinary, incorporating elements of Speech recognition, TUTOR, Natural language and Conversation. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Context, Natural language processing and Pattern recognition.
His primary areas of investigation include Cognitive psychology, Affect, Artificial intelligence, Mind-wandering and Boredom. Tracking is closely connected to Social psychology in his research, which is encompassed under the umbrella topic of Cognitive psychology. His research in Affect intersects with topics in Valence, Multimedia, Frustration, Developmental psychology and Affective computing.
His work deals with themes such as Context, Natural language processing, Generalizability theory, Machine learning and Pattern recognition, which intersect with Artificial intelligence. His study looks at the intersection of Mind-wandering and topics like Gaze with Eye tracking. His research investigates the connection with Boredom and areas like Intelligent tutoring system which intersect with concerns in TUTOR.
His primary areas of study are Cognitive psychology, Mind-wandering, Artificial intelligence, Context and Eye tracking. His biological study spans a wide range of topics, including Predictive validity, Eye movement, Comprehension and Reading. His research integrates issues of Mathematics education and Intelligent tutoring system in his study of Mind-wandering.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning, Affect, Set and Natural language processing. His Affect study is related to the wider topic of Social psychology. As a part of the same scientific family, Sidney K. D'Mello mostly works in the field of Eye tracking, focusing on Gaze and, on occasion, Human–computer interaction and User interface.
Sidney K. D'Mello mostly deals with Cognitive psychology, Mind-wandering, Mathematics education, Applied psychology and Context. His Cognitive psychology research incorporates elements of Nonverbal communication, Predictive validity, Social psychology and Artificial intelligence. His study in the fields of Affective science under the domain of Artificial intelligence overlaps with other disciplines such as Crowdsourcing.
Sidney K. D'Mello has included themes like Gaze, Eye tracking, Comprehension test, Instructional design and Intelligent tutoring system in his Mind-wandering study. His work in Mathematics education addresses issues such as Analytics, which are connected to fields such as Affective computing. The concepts of his Affective computing study are interwoven with issues in Deep learning, Student engagement, Learning analytics and Boredom.
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Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications
Rafael A Calvo;Sidney D'Mello.
IEEE Transactions on Affective Computing (2010)
Better to be frustrated than bored: The incidence, persistence, and impact of learners' cognitive-affective states during interactions with three different computer-based learning environments
Ryan S. J. d. Baker;Sidney K. D'Mello;Ma.Mercedes T. Rodrigo;Arthur C. Graesser.
International Journal of Human-computer Studies / International Journal of Man-machine Studies (2010)
Dynamics of affective states during complex learning
Sidney D’Mello;Art Graesser.
Learning and Instruction (2012)
Confusion can be beneficial for learning
Sidney D’Mello;Blair Lehman;Reinhard Pekrun;Art Graesser.
Learning and Instruction (2014)
Boring but important: A self-transcendent purpose for learning fosters academic self-regulation.
David Scott Yeager;Marlone Deshaun Henderson;David Paunesku;Gregory M. Walton.
Journal of Personality and Social Psychology (2014)
Toward an Affect-Sensitive AutoTutor
S. D'Mello;A. Graesser;R.W. Picard.
IEEE Intelligent Systems (2007)
Automatic detection of learner's affect from conversational cues
Sidney K. D'Mello;Scotty D. Craig;Amy Witherspoon;Bethany Mcdaniel.
User Modeling and User-adapted Interaction (2008)
A Review and Meta-Analysis of Multimodal Affect Detection Systems
Sidney K. D'mello;Jacqueline Kory.
ACM Computing Surveys (2015)
Multimodal semi-automated affect detection from conversational cues, gross body language, and facial features
Sidney K. D'Mello;Arthur Graesser.
User Modeling and User-adapted Interaction (2010)
Gaze tutor: A gaze-reactive intelligent tutoring system
Sidney D'Mello;Andrew Olney;Claire Williams;Patrick Hays.
International Journal of Human-computer Studies / International Journal of Man-machine Studies (2012)
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