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Sung, Rou-Jia; Swarat, Su L.; Lo, Stanley M. – Journal of Biological Education, 2022
Exams constitute the predominant form of summative assessment in undergraduate biology education, with the assumption that exam performance should reflect student conceptual understanding. Previous work highlights multiple examples in which students can answer exam problems correctly without the corresponding conceptual understanding. This…
Descriptors: Biology, Problem Solving, Undergraduate Students, Scientific Concepts

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

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

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

Stewart, Jim; Dale, Michael – Science Education, 1989
Investigates high school students' understanding of the physical relationship of chromosomes and genes as expressed in their conceptual models and in their ability to manipulate the models to explain solutions to dihybrid cross problems. Describes three typical models and three students' reasoning processes. Discusses four implications. (YP)
Descriptors: Algorithms, Biology, Concept Formation, Fundamental Concepts
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