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Alexis Lebis; Jérémie Humeau; Anthony Fleury; Flavien Lucas; Mathieu Vermeulen – International Journal of Artificial Intelligence in Education, 2024
The personalization of curriculum plays a pivotal role in supporting students in achieving their unique learning goals. In recent years, researchers have dedicated efforts to address the challenge of personalizing curriculum through diverse techniques and approaches. However, it is crucial to acknowledge the phenomenon of student forgetting, as…
Descriptors: Individualized Instruction, Curriculum Development, Curriculum Implementation, Memory
Mandel, Travis Scott – ProQuest LLC, 2017
When a new student comes to play an educational game, how can we determine what content to give them such that they learn as much as possible? When a frustrated customer calls in to a helpline, how can we determine what to say to best assist them? When an ill patient comes in to the clinic, how do we determine what tests to run and treatments to…
Descriptors: Reinforcement, Learning Processes, Student Evaluation, Data Collection
Brack, Greg; And Others – 1994
With the exception of a few key writers, counselors largely ignore the benefits that Artificial Intelligence (AI) and Cognitive Psychology (CP) can bring to counseling. It is demonstrated that AI and CP can be integrated into the counseling literature. How AI and CP can offer new perspectives on information processing, cognition, and helping is…
Descriptors: Artificial Intelligence, Cognitive Processes, Cognitive Psychology, Computer Simulation
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Waldrop, M. Mitchell – Science, 1988
Describes an artificial intelligence system known as SOAR that approximates a theory of human cognition. Discusses cognition as problem solving, working memory, long term memory, autonomy and adaptability, and learning from experience as they relate to artificial intelligence generally and to SOAR specifically. Highlights the status of the…
Descriptors: Artificial Intelligence, Cognitive Processes, Cognitive Psychology, Cognitive Structures
Psotka, Joseph – 1985
Current notions of metacognition merge with the predominant scientific model used in psychology, that of information processing. Metacognition is seen as a control process that governs the action of more elemental cognitive skills. Given the centrality of this notion, it is important that metacognition should be examined in detail. From the point…
Descriptors: Artificial Intelligence, Cognitive Processes, Cognitive Restructuring, Computer Assisted Instruction
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Langley, Pat – Cognitive Science, 1985
Examines processes by which general but weak search methods are transformed into powerful, domain-specific search strategies by classifying types of heuristics learning that can occur and components that contribute to such learning. A learning system--SAGE.2--and its structure, behavior in different domains, and future directions are explored. (36…
Descriptors: Artificial Intelligence, Computer Software, Design, Heuristics
Hankins, George. – Engineering Education, 1987
Describes the novice-to-expert model of human learning and compares it to the recent advances in the areas of artificial intelligence and expert systems. Discusses some of the characteristics of experts, proposing connections between them with expert systems and theories of left-right brain functions. (TW)
Descriptors: Artificial Intelligence, Brain Hemisphere Functions, College Science, Engineering Education
Pechenizkiy, Mykola; Calders, Toon; Conati, Cristina; Ventura, Sebastian; Romero, Cristobal; Stamper, John – International Working Group on Educational Data Mining, 2011
The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions…
Descriptors: Academic Achievement, Logical Thinking, Profiles, Tutoring
Smith, Karl A. – Engineering Education, 1987
Differentiates between learning efficiency (enhancing the rate of learning) and learning effectiveness (enhancing the mastery and retention of facts, concepts, and relationships). Discusses some of the contributions of knowledge engineering to metalearning. Provides a concept map for constructing knowledge bases, along with some possible…
Descriptors: Artificial Intelligence, College Science, Concept Formation, Concept Mapping