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Simone Dunphy; Zachary Weisse – Journal of Chemical Education, 2025
Dimensional analysis is an algorithm currently in use in almost every chemistry classroom in the United States. Chemistry educators use this procedural tool in the classroom with the intention of providing students with a reliable method to solve many of the relatively simple math problems they encounter. The unintended consequence of using this…
Descriptors: Science Education, Chemistry, Introductory Courses, Scientific Concepts
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Christoph G. Salzmann; Sophia M. Vecchi Marsh; Jinjie Li; Luca Slater – Journal of Chemical Education, 2025
Proportional-Integral-Derivative (PID) controllers are essential in ensuring the stability and efficiency of numerous scientific, industrial, and medical processes. However, teaching the principles of PID control can be challenging, especially when the introduction focuses on the underlying mathematical framework. To address this, we developed the…
Descriptors: Science Education, Science Instruction, Teaching Methods, Demonstrations (Educational)
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Reid, Norman; Yang, Mei-Jung – Research in Science and Technological Education, 2002
Offers a simple classification of problems and seeks to explore the many factors that may be important in the successful solving of problems. Considers the place of procedures and algorithms. Solving open-ended problems is extremely important in education and offering learners experience with this in a group work context is a helpful way forward.…
Descriptors: Algorithms, Chemistry, Problem Solving, Science Education
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Niaz, Mansoor – Science Education, 1995
Describes a study with the main objective of constructing models based on strategies students use to solve chemistry problems and to show that these models form sequences of progressive transitions termed "problemshifts" that increase the explanatory/heuristic power of the model. Results implies that the relationship between algorithmic…
Descriptors: Algorithms, Chemistry, Concept Formation, Models
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Stencel, John E. – American Biology Teacher, 1991
A real world sample of actual data that students can use to see the application of the Hardy-Weinberg law to a real population is provided. The directions for using a six-step algorithmic procedure to determine Hardy-Weinberg percentages on the data given are described. (KR)
Descriptors: Algorithms, Biology, Genetics, Problem Solving
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Still, Ebbe; Sara, Rolf – Journal of Chemical Education, 1977
Presents compact algorithms, suitable for use with hand held calculators, for the calculation of potentiometric titration curves. (SL)
Descriptors: Algorithms, Calculators, Chemical Reactions, Chemistry
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Knudson, George E.; Nimrod, Dale – Journal of Chemical Education, 1977
Presents an exact equation for calculating the volume of titrant as a function of the hydrogen ion concentration suitable for calculation on a hand held calculator. (SL)
Descriptors: Algorithms, Calculators, Chemical Reactions, Chemistry
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Thomson, Norman; Stewart, James – Journal of Biological Education, 1985
Explains an algorithm which details procedures for solving a broad class of genetics problems common to pre-college biology. Several flow charts (developed from the algorithm) are given with sample questions and suggestions for student use. Conclusions are based on the authors' research (which includes student interviews and textbook analyses).…
Descriptors: Algorithms, Biology, Genetics, Learning Strategies
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Gfeller, Mary K.; Niess, Margaret L.; Lederman, Norman G. – School Science and Mathematics, 1999
Examines solutions presented by preservice teachers for solving graphical and numerical problems involving the arithmetic mean. Participants presented two methods: algorithmic computation and balancing deviations about the mean. A significant difference was found between science and mathematics preservice teachers in the use of balancing…
Descriptors: Algorithms, Higher Education, Mathematics Education, Preservice Teacher Education
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Coulter, David – School Science and Mathematics, 1981
A study to investigate one of the mechanisms teachers may use to convince themselves incorrectly that students have learned science concepts requiring formal operational ability is presented. The investigation indicates instructors may actually teach and test for memorization of algorithms rather than understanding. (MP)
Descriptors: Algorithms, Chemistry, Educational Research, Learning Theories
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Stencel, John E. – Journal of College Science Teaching, 1992
Explains how a simple three-step algorithm can aid college students in solving synapse transmission problems. Reports that all of the students did not completely understand the algorithm. However, many learn a simple working model of synaptic transmission and understand why an impulse will pass across a synapse quantitatively. Students also see…
Descriptors: Algorithms, Anatomy, Biology, College Science
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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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Baker, Claire A.; Frank, David V. – Hoosier Science Teacher, 1988
Defines one approach to problem solving in terms of student use of algorithms to find their solutions and gives examples. Discusses how problems and algorithms relate to each other. Describes strategies for teaching problem solving using algorithms. (CW)
Descriptors: Algorithms, Chemistry, Cognitive Development, Computation
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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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Middlecamp, Catherine; Kean, Elizabeth – Journal of Chemical Education, 1987
Discusses the difference between a generic chemistry problem (one which can be solved using an algorithm) and a harder chemistry problem (one for which there is no algorithm). Encourages teachers to help students recognize these categories of problems so they will be better able to find solutions. (TW)
Descriptors: Algorithms, Chemistry, College Science, Higher Education
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