His scientific interests lie mostly in Developmental psychology, Cognitive psychology, Intelligent tutoring system, Artificial intelligence and Restructuring. His Developmental psychology study integrates concerns from other disciplines, such as Mental representation and Control. He combines subjects such as Representation and Eye movement with his study of Mental representation.
His Intelligent tutoring system study combines topics from a wide range of disciplines, such as Subject matter knowledge, Novelty and Computation. His Pattern matching study in the realm of Artificial intelligence interacts with subjects such as Generalization error. The Information processing theory study combines topics in areas such as Social psychology and Cognitive science.
His scientific interests lie mostly in Artificial intelligence, Cognitive psychology, Cognitive science, Human–computer interaction and Conceptual change. Stellan Ohlsson usually deals with Artificial intelligence and limits it to topics linked to TUTOR and Multimedia. The study incorporates disciplines such as Developmental psychology, Social psychology, Categorization and Intelligence quotient in addition to Cognitive psychology.
In his research, Procedural knowledge is intimately related to Learning theory, which falls under the overarching field of Cognitive science. His study in Human–computer interaction is interdisciplinary in nature, drawing from both Creativity and Linked list. The concepts of his Conceptual change study are interwoven with issues in Concept learning, Belief revision and Science education.
The scientist’s investigation covers issues in Cognitive psychology, Artificial intelligence, Conceptual change, Human–computer interaction and Cognitive science. The Cognitive psychology study combines topics in areas such as Memory training, Common sense and Verbal iq, Intelligence quotient. His Artificial intelligence research includes themes of Domain, Cognitive architecture, Descriptive knowledge and Natural language processing.
His Conceptual change research is multidisciplinary, relying on both Cognitive development, Belief revision, Cognitive dissonance, Categorization and Concept learning. He works mostly in the field of Belief revision, limiting it down to concerns involving Creativity and, occasionally, Novelty and Intelligent tutoring system. Stellan Ohlsson combines subjects such as Data-driven and Knowledge management with his study of Human–computer interaction.
Stellan Ohlsson mainly focuses on Artificial intelligence, Intelligent tutoring system, Educational technology, Human–computer interaction and Program evaluation. The study incorporates disciplines such as Verbal reasoning, Cognitive psychology and Verbal iq, Intelligence quotient in addition to Artificial intelligence. His Intelligent tutoring system research includes elements of Belief revision and Creativity.
His biological study spans a wide range of topics, including Software engineering, TUTOR and World Wide Web. His Human–computer interaction study frequently draws parallels with other fields, such as Data-driven.
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Thoughts beyond words : When language overshadows insight
Jonathan W. Schooler;Stellan Ohlsson;Kevin Brooks.
Journal of Experimental Psychology: General (1993)
Constraint relaxation and chunk decomposition in insight problem solving
Giinther Knoblich;Stellan Ohlsson;Hilde Haider;Detlef Rhenius.
Journal of Experimental Psychology: Learning, Memory and Cognition (1999)
Information-processing explanations of insight and related phenomena
Advances in the psychology of Thinking (1992)
Learning from Performance Errors.
Psychological Review (1996)
An eye movement study of insight problem solving
Günther Knoblich;Stellan Ohlsson;Gary E. Raney.
Memory & Cognition (2001)
Deep Learning: How the Mind Overrides Experience
Evaluation of a Constraint-Based Tutor for a Database Language
Antonija Mitrovic;Stellan Ohlsson.
Some principles of intelligent tutoring
artificial intelligence in education (1987)
Constraint-Based Student Modeling
Learning to do and learning to understand : a lesson and a challenge for cognitive modeling
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