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Arthur C. Graesser [20]Art Graesser [4]
  1. Sidney D'Mello, Rick Dale & Art Graesser (2012). Disequilibrium in the Mind, Disharmony in the Body. Cognition and Emotion 26 (2):362-374.
  2. Sidney D'Mello & Art Graesser (2011). The Half-Life of Cognitive-Affective States During Complex Learning. Cognition and Emotion 25 (7):1299-1308.
  3. Arthur C. Graesser & Danielle S. McNamara (2011). Computational Analyses of Multilevel Discourse Comprehension. Topics in Cognitive Science 3 (2):371-398.
    The proposed multilevel framework of discourse comprehension includes the surface code, the textbase, the situation model, the genre and rhetorical structure, and the pragmatic communication level. We describe these five levels when comprehension succeeds and also when there are communication misalignments and comprehension breakdowns. A computer tool has been developed, called Coh-Metrix, that scales discourse (oral or print) on dozens of measures associated with the first four discourse levels. The measurement of these levels with an automated tool helps researchers track (...)
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  4. Shulan Lu, Derek Harter & Arthur C. Graesser (2009). An Empirical and Computational Investigation of Perceiving and Remembering Event Temporal Relations. Cognitive Science 33 (3):345-373.
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  5. Scotty D. Craig, Sidney D'Mello, Amy Witherspoon & Art Graesser (2008). Emote Aloud During Learning with AutoTutor: Applying the Facial Action Coding System to Cognitive–Affective States During Learning. Cognition and Emotion 22 (5):777-788.
  6. Manuel de Vega, Arthur M. Glenberg & Arthur C. Graesser (eds.) (2008). Symbols and Embodiment: Debates on Meaning and Cognition. Oxford University Press.
    Cognitive scientists have a variety of approaches to studying cognition: experimental psychology, computer science, robotics, neuroscience, educational psychology, philosophy of mind, and psycholinguistics, to name but a few. In addition, they also differ in their approaches to cognition - some of them consider that the mind works basically like a computer, involving programs composed of abstract, amodal, and arbitrary symbols. Others claim that cognition is embodied - that is, symbols must be grounded on perceptual, motoric, and emotional experience. The existence (...)
     
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  7. Arthur C. Graesser & G. Tanner Jackson (2008). Body and Symbol in AutoTutor: Conversations That Are Responsive to the Learners' Cognitive and Emotional States. In Manuel de Vega, Arthur M. Glenberg & Arthur C. Graesser (eds.), Symbols and Embodiment: Debates on Meaning and Cognition. Oxford University Press. 33.
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  8. Arthur C. Graesser, Moongee Jeon, Zhiqiang Cai, Danielle S. McNamara, J. Auracher & W. van Peer (2008). Automatic Analyses of Language, Discourse, and Situation Models. In Jan Auracher & Willie van Peer (eds.), New Beginnings in Literary Studies. Cambridge Scholars Pub..
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  9. Kurt VanLehn, Arthur C. Graesser, G. Tanner Jackson, Pamela Jordan, Andrew Olney & Carolyn P. Rosé (2007). When Are Tutorial Dialogues More Effective Than Reading? Cognitive Science 31 (1):3-62.
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  10. Derek Harter, Arthur C. Graesser & Stan Franklin (2001). Bridging the Gap: Dynamics as a Unified View of Cognition. Behavioral and Brain Sciences 24 (1):45-46.
    Top-down dynamical models of cognitive processes, such as the one presented by Thelen et al., are important pieces in understanding the development of cognitive abilities in humans and biological organisms. Unlike standard symbolic computational approaches to cognition, such dynamical models offer the hope that they can be connected with more bottom-up, neurologically inspired dynamical models to provide a complete view of cognition at all levels. We raise some questions about the details of their simulation and about potential limitations of (...)
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  11. Stan Franklin & Art Graesser (1999). A Software Agent Model of Consciousness. Consciousness and Cognition 8 (3):285-301.
    Baars (1988, 1997) has proposed a psychological theory of consciousness, called global workspace theory. The present study describes a software agent implementation of that theory, called ''Conscious'' Mattie (CMattie). CMattie operates in a clerical domain from within a UNIX operating system, sending messages and interpreting messages in natural language that organize seminars at a university. CMattie fleshes out global workspace theory with a detailed computational model that integrates contemporary architectures in cognitive science and artificial intelligence. Baars (1997) lists the psychological (...)
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  12. Katja Wiemer-Hastings & Arthur C. Graesser (1999). Perceiving Abstract Concepts. Behavioral and Brain Sciences 22 (4):635-636.
    The meanings of abstract concepts depend on context. Perceptual symbol systems (PSS) provide a powerful framework for representing such context. Whereas a few expected difficulties for simulations are consistent with empirical findings, the theory does not clearly predict simulations of specific abstract concepts in a testable way and does not appear to distinguish abstract noun concepts (like truth) from their stem concepts (such as true).
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  13. Katja Wiemer-Hastings & Arthur C. Graesser (1998). Who Needs Created Features? Behavioral and Brain Sciences 21 (1):39-39.
    Schyns, Goldstone & Thibaut present reasonable arguments for feature creation in category learning. We argue, however, that they do not provide unequivocal evidence either for the necessity or for the occurrence of feature creation. In an effort to sharpen the debate, we take the stand that a fixed feature approach is to be preferred in the absence of compelling evidence.
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  14. Arthur C. Graesser (1997). Where is the Body in the Mental Model for a Story? Behavioral and Brain Sciences 20 (1):25-25.
    Researchers in the field of discourse processing have investigated how mental models are constructed when adults comprehend stories. They have explored the process of encoding various classes of inferences “on-line” when these mental microworlds are constructed during comprehension. This commentary addresses the extent to which these inferences and mental microworlds are “embodied.”.
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  15. Arthur C. Graesser, Cheryl A. Bowers, Tom Trabasso, Brian Harvey, Sunil Cherian, Wade O. Troxell, Timothy Joseph day, Robert M. French, Roger Sansom, Kenneth Aizawa, David Shier, Yakir Levin & Nicholas Power (1996). Book Reviews. [REVIEW] Minds and Machines 6 (3).
  16. Arthur C. Graesser (1989). Creativity and the Psychology of Science. In Barry Gholson (ed.), Psychology of Science: Contributions to Metascience. Cambridge University Press. 165.
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  17. Karl F. Haberlandt & Arthur C. Graesser (1985). Component Processes in Text Comprehension and Some of Their Interactions. Journal of Experimental Psychology 114 (3).
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  18. Glenn V. Nakamura & Arthur C. Graesser (1985). Memory for Script-Typical and Script-Atypical Actions: A Reaction Time Study. Bulletin of the Psychonomic Society 23 (4):384-386.
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  19. Arthur C. Graesser & Glenn V. Nakamura (1984). The Impact of a Schema on Comprehension and Memory. In Gordon H. Bower (ed.), The Psychology of Learning and Motivation. Academic Press. 16--59.
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  20. Arthur C. Graesser (1983). How to Develop a Theory of Story Points. Behavioral and Brain Sciences 6 (4):600.
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  21. Andrew D. Cohen & Arthur C. Graesser (1980). The Influence of Advanced Outlines on the Free Recall of Prose. Bulletin of the Psychonomic Society 15 (5):348-350.
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  22. Jan C. Rabinowitz & Arthur C. Graesser (1976). Word Recognition as a Function of Retrieval Processes. Bulletin of the Psychonomic Society 7 (1):75-77.
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  23. Gordon Stanley & Arthur C. Graesser (1973). Constancy Scaling and the Brackets Illusion. Bulletin of the Psychonomic Society 2 (4):198-200.
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