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How Do Different Levels of AU4 Impact Metacognitive Monitoring During Learning with Intelligent Tutoring Systems?
Abstract: We investigated how college students’ (n = 40) different levels of action unit 4 (AU4: brow lowerer), metacognitive monitoring process use and pre-test score were associated with metacognitive monitoring accuracy during learning with a hypermedia-based ITS. Results revealed that participants with high pre-test scores had the highest accuracy scores with low levels of AU4 and use […]
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How Are Students’ Emotions Associated with the Accuracy of Their Note Taking and Summarizing During Learning with ITSs?
Abstract: The goal of this study was to examine 38 undergraduate and graduate students’ note taking and summarizing, and the relationship between emotions, the accuracy of those notes and summaries, and proportional learning gain, during learning with MetaTutor, an ITS that fosters self-regulated learning while learning complex science topics. Results revealed that students expressed both […]
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Leverage Score Ordering
Abstract:Â In this paper we present Leverage Score Ordering, a novel technique for determining the ordering of data in the training of deep neural networks. Our technique is based on the distributed computation of leverage scores using random projections. These computed leverage scores provide a flexible and efficient method to determine the optimal ordering of training […]
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Impact of Learner-Centered Affective Dynamics on Metacognitive Judgements and Performance in Advanced Learning Technologies
Abstract: Affect and metacognition play a central role in learning. We examine the relationships between students’ affective state dynamics, metacognitive judgments, and performance during learning with MetaTutorIVH, an advanced learning technology for human biology education. Student emotions were tracked using facial expression recognition embedded within MetaTutorIVH and transitions between emotions theorized to be important to […]
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Discrimination between smiling faces: Human observers vs. automated face analysis
Abstract:Â This study investigated (a) how prototypical happy faces (with happy eyes and a smile) can be discriminated from blended expressions with a smile but non-happy eyes, depending on type and intensity of the eye expression; and (b) how smile discrimination differs for human perceivers versus automated face analysis, depending on affective valence and morphological facial […]
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How Does Food Taste in Anorexia and Bulimia Nervosa? A Protocol for a Quasi-Experimental, Cross-Sectional Design to Investigate Taste Aversion or Increased Hedonic Valence of Food in Eating Disorders
Background: Despite on-going efforts to better understand dysregulated eating, the olfactory-gustatory deficits and food preferences in eating disorders (ED), and the mechanisms underlying the perception of and responses to food properties in anorexia nervosa (AN) and bulimia nervosa (BN) remain largely unknown; both during the course of the illness and compared to healthy populations. It is, […]
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Toward A Companion Robot Fostering Perseverance in Math: A Pilot Study
Abstract: Challenging math problems without immediate solutions often invite students to ride an “emotional roller-coaster” through episodes of confusion, frustration, surprise and joy. Those problem solving experiences provide rich opportunities to cultivate mathematical perseverance, the mentality to forge ahead in face of ambiguity or difficulty. An ideal teacher closely monitors the problem solving process and […]
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A Test of the Rapid Formation of Design Cues for Product Body Shapes and Features
Abstract: Consumers often use a product’s visual design as a mental shortcut to judge its unobservable attributes. Mental associations between visual design and unobservable attributes aid consumers in their judgments, and hypothetically reduce consumers’ mental load. This paper describes a study that shows the possibility of quickly creating an association in subjects’ minds between a […]
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Emotion recognition for semi-autonomous vehicles framework
Abstract: The human being in his blessed curiosity has always wondered how to make machines feel, and, at the same time how a machine can detect emotions. Perhaps some of the tasks that cannot be replaced by machines are the ability of human beings to feel emotions. In the last year, this hypothesis is increasingly […]
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A Classification Model for Sensing Human Trust in Machines Using EEG and GSR
Abstract: Today, intelligent machines interact and collaborate with humans in a way that demands a greater level of trust between human and machine. A first step towards building intelligent machines that are capable of building and maintaining trust with humans is the design of a sensor that will enable machines to estimate human trust level […]
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