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Arcavi, Abraham – For the Learning of Mathematics, 1994
Attempts to describe a notion parallel to number sense, called symbol sense, incorporating the following components: making friends with symbols, reading through symbols, engineering symbolic expressions, equivalent expressions for non-equivalent meanings, choice of symbols, flexible manipulation skills, symbols in retrospect, and symbols in…
Descriptors: Algebra, Algorithms, Mathematical Concepts, Mathematics Education
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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
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Tall, David; And Others – Mathematics in School, 1984
Ideas on the long-term effects of using microcomputers in mathematics are presented. The changing perception of mathematics, the role of algorithms, the use of short computer programs, the effects on mathematical understanding, implications for teaching methods, logistic problems, examinations and assessment, and planning for the future are…
Descriptors: Algorithms, Educational Planning, Evaluation, Higher Education
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Pushkin, David B. – Journal of Chemical Education, 1998
Addresses the distinction between conceptual and algorithmic learning and the clarification of what is meant by a second-tier student. Explores why novice learners in chemistry and physics are able to apply algorithms without significant conceptual understanding. (DDR)
Descriptors: Algorithms, Chemistry, Cognitive Psychology, Concept Formation
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Thwaites, G. N. – Mathematics in School, 1982
An attempt is made to show that algebra is rarely obvious, and merely expecting children to learn rules is an oversimplification. Sections cover: (1) The Non-visual Nature of Algebra; (2) The Apparently Arbitrary Nature of Algebra; (3) The Relationship Between Symbolism, System and Question; (4) The Complex Nature of Algebra; and (5) Some…
Descriptors: Algebra, Algorithms, Equations (Mathematics), Instruction
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Frank, David V.; And Others – Journal of Chemical Education, 1987
Discusses the differences between problems and exercises in chemistry, and some of the difficulties that arise when the same methods are used to solve both. Proposes that algorithms are excellent models for solving exercises. Argues that algorithms not be used for solving problems. (TW)
Descriptors: Algorithms, Chemistry, College Science, Higher Education
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Schrader, C. L. – Journal of Chemical Education, 1987
Discusses the differences between problems and exercises, the levels of thinking required to solve them, and the roles that algorithms can play in helping chemistry students perform these tasks. Proposes that students be taught the logic of algorithms, their characteristics, and how to invent their own algorithms. (TW)
Descriptors: Algorithms, Chemistry, College Science, Higher Education
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O'Donnell, William J. – Mathematics Teacher, 1988
Discusses computer methods for finding roots of polynomials. The program provided finds rational roots and prints the roots as rational numbers. (PK)
Descriptors: Algebra, Algorithms, Computer Assisted Instruction, Computer Uses in Education
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Bodner, George M. – Journal of Chemical Education, 1987
Differentiates between problems, exercises and algorithms. Discusses the role of algorithms in solving problems and exercises in chemistry. Suggests that very real differences exist between solving problems and exercises, and that problem solving steps can be and should be taught in chemistry education. (TW)
Descriptors: Algorithms, Chemistry, College Science, Higher Education
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Burke, Paul – Journal of College Admissions, 1990
Argues that the vast majority of adults have no use for the specialized mathematics taught in high schools and required by colleges--algebra, geometry, or calculus. Suggests that colleges should accept applicants who have studied percents, formulas, logic, computer commands, and basic statistics. (TE)
Descriptors: Algebra, Algorithms, Arithmetic, Calculus
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Pickering, Miles – Journal of Chemical Education, 1987
Discusses some of the difficulties involved with chemistry laboratory experiences and some laboratory manuals. Cites studies that indicate that part of the difficulty can be attributed to constraints relating to the short-term memory of the operational information and the assumption that students have a certain level of knowledge. (TW)
Descriptors: Algorithms, Chemistry, College Science, Higher Education