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Rising, Gerald R.; And Others – 1980
This student textbook is designed to incorporate programable calculators in grade 12 mathematics. The seven chapters contained in this document are: (1) Using Calculators in Mathematics; (2) Sequences, Series, and Limits; (3) Iteration, Mathematical Induction, and the Binomial Theorem; (4) Applications of the Fundamental Counting Principle; (5)…
Descriptors: Algorithms, Calculators, Educational Technology, Exponents (Mathematics)
Rushby, N. J. – 1978
This bibliography lists 86 references, most of which are annotated, to papers and journal articles on computer assisted learning (CAL) in the Soviet Union. Topics dealt with include problem solving models, decision strategies, programmed instruction, algorithms, simulation, educational games, databases, and testing. The references have been…
Descriptors: Algorithms, Annotated Bibliographies, Computer Assisted Instruction, Computer Managed Instruction
Sternberg, Robert J.; Weil, Evelyn M. – 1979
An aptitude-strategy interaction in linear syllogistic reasoning was tested on 144 undergraduate and graduate students of both sexes. It was hypothesized that the efficiency of each of four alternative strategies--control, visual, algorithmic, and mixed--would depend upon the subjects' pattern of verbal and spatial abilities. Two tests of verbal…
Descriptors: Abstract Reasoning, Algorithms, Aptitude Treatment Interaction, Cognitive Ability
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Carter, Carolyn S.; And Others – Journal of Research in Science Teaching, 1987
Reports on a study in which two spatial tests were given to science and engineering majors and to students in nursing and agriculture at Purdue University (Indiana). Scores from the tests consistently contributed a small but significant amount of success on measures of performance in chemistry. (TW)
Descriptors: Academic Achievement, Agricultural Education, Algorithms, Chemistry
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Birenbaum, Menucha; Tatsuoka, Kikumi – Journal of Educational Measurement, 1982
Empirical results from two studies--a simulation study and an experimental one--indicated that, in achievement data of the problem-solving type where a specific subject matter area is being tested, the greater the variety of the algorithms used, the higher the dimensionality of the test data. (Author/PN)
Descriptors: Achievement Tests, Algorithms, Data Analysis, Factor Structure
McIntosh, Alistair – Mathematics Teaching, 1980
More mental computation and organized and enjoyable activities to practice such skills are advocated. Suggestions for brief sessions involving challenging questions and quick recall of number facts are presented. The author presents and comments on several sample lessons designed for a wide range of student abilities. (MP)
Descriptors: Algorithms, Computation, Elementary School Mathematics, Elementary Secondary Education
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Jordan, Michael P. – Instructional Science, 1980
This discussion of information structures in written texts describes how linguistic analysis of short published reports leads to the presentation of an algorithm that depicts the problem-solving process in terms of a series of evaluative questions. (Author/CHC)
Descriptors: Algorithms, Bibliographies, Cognitive Processes, Communication Skills
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Gal-Ezer, Judith; Lichtenstein, Orna – Mathematics and Computer Education, 1997
Shows by means of a mathematical example how algorithmic thinking and mathematical thinking complement each other. An algorithmic approach can lead to questions that deepen the understanding of mathematics material. (DDR)
Descriptors: Algorithms, Case Studies, Cognitive Processes, Computer Science Education
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Nussbaum, Francis, Jr. – American Biology Teacher, 1988
Presents an algorithm for solving problems related to multiple allelic frequencies in populations at equilibrium. Considers sample problems and provides their solution using this tabular algorithm. (CW)
Descriptors: Algorithms, Biological Sciences, College Science, Genetics
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Sorkin, Sylvia J. – Mathematics and Computer Education, 1991
Presented is a way to provide students with a review and an appreciation of the versatility of pointers in data structures by improvising with binary trees. Examples are described using the Pascal programing language. (KR)
Descriptors: Algorithms, College Mathematics, Computer Science Education, Computer Software
Mason, Diana – 1995
Incident identification graphs can be used to diagnose areas of difficulty in a subject's problem-solving schema at the episodic level. In this study, 22 subjects (2 experts and 20 novices) categorized into five problem-solving groups (expert, high algorithmic/high conceptual, low algorithmic/high conceptual, high algorithmic/low conceptual, and…
Descriptors: Algorithms, Chemistry, College Students, Higher Education
Zuckerman, June T. – 1992
Various researchers have associated meaningful problem solving with methods guided directly by a conceptual knowledge base. By contast, a meaningless solving course, or sequence of operations, is essentially independent of the solver's conceptual understanding of the problem under consideration. This paper is the first to document a meaningless,…
Descriptors: Algorithms, Biology, Cognitive Processes, Conceptual Tempo
Stanford Univ., CA. School Mathematics Study Group. – 1964
This SMSG study guide is designed to aid the teacher in acquiring familiarity with digital computer concepts or to further his/her knowledge of the field. Suitable references for important topics are categorized as central, peripheral, or advanced. Topics covered include: (1) nature and organization of computers; (2) problem analysis; (3)…
Descriptors: Algorithms, Bibliographies, Computer Science, Computers
Hummel, Thomas J. – 1976
"Algorithmic counseling" is an attempt to apply recent instructional regulation techniques to graduate counselor training and research. This paper seeks to explain what algorithms are, why they could be useful, and how they can be constructed. A central motivation for studying algorithms is their utility in showing students how to accomplish a…
Descriptors: Algorithms, Computer Programs, Counseling, Counselor Training
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Hoggard, Franklin R. – Journal of Chemical Education, 1987
Suggests a method for solving verbal problems in chemistry using a linguistic algorithm that is partly adapted from two artificial intelligence languages. Provides examples of problems solved using the mental concepts of translation, rotation, mirror image symmetry, superpositioning, disjoininng, and conjoining. (TW)
Descriptors: Algorithms, Artificial Intelligence, Chemical Nomenclature, Chemical Reactions
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