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Novick, Laura R.; Stull, Andrew T.; Catley, Kefyn M. – BioScience, 2012
Although differently formatted cladograms (hierarchical diagrams depicting evolutionary relationships among taxa) depict the same information, they may not be equally easy to comprehend. Undergraduate biology students attempted to translate cladograms from the diagonal to the rectangular format. The "backbone" line of each diagonal…
Descriptors: Biology, Eye Movements, Science Education, Science Instruction
Musante, Susan – BioScience, 2012
The story of biology is far more complex and fascinating than straightforward facts or neatly labeled diagrams of structures and systems. Although exams can motivate students, the key to using these extrinsic motivators to increase student understanding lies in the way the assessments are designed and what they measure. Those involved in…
Descriptors: Advanced Placement, Scientific Principles, Interests, Lifelong Learning
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Moore, Randy; Cotner, Sehoya – BioScience, 2009
The responses of biology majors in their first year of college differed significantly from those of first-year non-biology majors on only 3 of the 20 items on the Measure of Acceptance of the Theory of Evolution survey instrument. Despite these differences, and regardless of whether students were or were not biology majors, several findings from…
Descriptors: Biology, Majors (Students), Student Attitudes, Theories
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Maloney, Peter C.; Wilson, T. Hastings – BioScience, 1985
Constructs an evolutionary sequence to account for the diversity of ion pumps found today. Explanations include primary ion pumps in bacteria, features and distribution of ATP-driven pumps, preference for cation transport, and proton pump reversal. The integrated evolutionary hypothesis should encourage new experimental approaches. (DH)
Descriptors: Biology, College Science, Cytology, Evolution
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Birx, H. James – BioScience, 1971
Descriptors: Biology, College Science, Evolution, Instruction
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Pimentel, David – BioScience, 1971
Descriptors: Biology, Entomology, Evolution, Genetics
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Crow, James F. – BioScience, 1971
Descriptors: Biology, Environment, Environmental Influences, Evolution
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Baker, Herbert G. – BioScience, 1971
Descriptors: Biology, Botany, Ecology, Environmental Influences
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Scheer, Bradley T. – BioScience, 1979
Written in response to an earlier article questioning certain aspects of evolution theory. Discusses ontogeny and phylogeny, the basis of evolution, chance or purpose in evolution, micro and macro-evolution, reversibility, and the evolution processes today. (MA)
Descriptors: Biological Influences, Biology, Evolution, Genetics
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Azar, Larry – BioScience, 1978
In this article a philosophy teacher looks at some of the questions raised by the concept of evolution and what biologists have said about them throughout the ages. (BB)
Descriptors: Biological Sciences, Biology, Classification, Evolution
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Carson, Hampton L. – BioScience, 1972
Cites examples of the contribution of basic research in evolutionary biology to the solution of problems facing society (1) by dispelling myths about human origins, the nature of the individual, and the nature of race (2) by providing basic data concerning the effects of overpopulation, the production of improved sources of food, resistance of…
Descriptors: Anthropology, Biology, Evolution, Overpopulation
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Bajema, Carl Jay – BioScience, 1971
Descriptors: Biology, Contraception, Demography, Evolution
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Margulis, Lynn – BioScience, 1990
The meaning and history of the term symbiosis is discussed. The role of symbiosis in evolution is suggested. Research in the field of endocytobiology on symbiotic relationships is proposed. (CW)
Descriptors: Biology, College Science, Ecology, Evolution
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Gould, Stephen Jay – BioScience, 1978
Describes a computer simulation of the evolution of species. This is a model for sorting out random and correlated paleontological events. (BB)
Descriptors: Archaeology, Biology, Computer Oriented Programs, Computers
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Hyatt, Gary W.; And Others – BioScience, 1972
Illustrates an account of the University of Illinois Programmed Logic for Automatic Teaching Operations (PLATO) system of individualized instruction by describing four undergraduate topics. (AL)
Descriptors: Biochemistry, Biology, College Science, Computer Assisted Instruction
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