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Ryan Daniel Budnick – ProQuest LLC, 2023
The past thirty years have shown a rise in models of language acquisition in which the state of the learner is characterized as a probability distribution over a set of non-stochastic grammars. In recent years, increasingly powerful models have been constructed as earlier models have failed to generalize well to increasingly complex and realistic…
Descriptors: Grammar, Feedback (Response), Algorithms, Computational Linguistics
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Claybrook, Billy G. – 1974
A new heuristic factorization scheme uses learning to improve the efficiency of determining the symbolic factorization of multivariable polynomials with interger coefficients and an arbitrary number of variables and terms. The factorization scheme makes extensive use of artificial intelligence techniques (e.g., model-building, learning, and…
Descriptors: Algorithms, Artificial Intelligence, Computer Programs, Computers
Peer reviewed Peer reviewed
Gravina, Robert M. – Computers and Education, 1979
Demonstrates that an elementary understanding of computer programing and the development and illustration of the structure of computer program analysis will be valuable assets in the understanding and teaching of mathematics and may be used as modeling devices to simulate the stages of learning. (Author)
Descriptors: Algorithms, Flow Charts, Learning Theories, Mathematics Instruction
Scandura, Joseph M. – Journal of Structural Learning, 1971
Descriptors: Algorithms, Behavior Patterns, Behavior Theories, Educational Theories
Falkenhainer, Brian; And Others – 1987
This description of the Structure-Mapping Engine (SME), a flexible, cognitive simulation program for studying analogical processing which is based on Gentner's Structure-Mapping theory of analogy, points out that the SME provides a "tool kit" for constructing matching algorithms consistent with this theory. This report provides: (1) a…
Descriptors: Algorithms, Analogy, Artificial Intelligence, Cognitive Structures
Falkenhainer, Brian; And Others – 1986
This paper describes the Structure-Mapping Engine (SME), a cognitive simulation program for studying human analogical processing. SME is based on Gentner's Structure-Mapping theory of analogy, and provides a "tool kit" for constructing matching algorithms consistent with this theory. This flexibility enhances cognitive simulation studies by…
Descriptors: Algorithms, Artificial Intelligence, Cognitive Processes, Cognitive Structures
Brecke, Fritz H.; And Others – 1975
The concept of an algorithm derives from the physical sciences, but it has often been misunderstood and misapplied in the social sciences and in education. The theoretical and practical significance of algorithms stems from their applicability to problems of learning, instruction, and instructional design, and they may potentially provide the…
Descriptors: Algorithms, Cognitive Processes, Learning Processes, Learning Theories
Peer reviewed Peer reviewed
Self, John – Instructional Science, 1986
Considers possibility of developing a computer tutor around an explicit concept-learning theory derived from machine learning techniques. Some problems with using the focusing (and similar) algorithms in this role are discussed and possible solutions are developed. Design for a guided discovery learning system for tutoring concepts is proposed.…
Descriptors: Algorithms, Computer Software, Concept Teaching, Databases
Stinaff, Russell D. – 1973
The problem of structuring sequences of instructional stimuli such that learning is optimized is modelled as a sequential decision problem with an imbedded mathematical model of learning providing a criterion function. Three types of optimization methods for such a representation are investigated for the specific case of paired-associate learning…
Descriptors: Algorithms, Computer Oriented Programs, Computer Science, Educational Research
Blevins, Belinda; And Others – 1981
The results of an investigation of the development of children's knowledge of addition and subtraction concepts before they start school are detailed. The purpose of the study was to test the predictions of the three-stage model about the distinctions between the last two stages. Twenty-four children participated in the investigation. None of…
Descriptors: Addition, Algorithms, Basic Skills, Cognitive Development