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Forbes-Lorman, Robin; Korb, Michele; Moser, Amy; Franzen, Margaret A.; Harris, Michelle A. – Journal of College Science Teaching, 2022
Physical and life science disciplines emphasize how basic structural units influence function, yet it is challenging for students to understand structure-function relationships, particularly at molecular scales. Undergraduates in our biology capstone course struggled to connect mutations in a gene encoding a key protein in a cell development…
Descriptors: Formative Evaluation, Science Education, Undergraduate Students, Summative Evaluation
Trejo, Sam; Domingue, Benjamin W. – Grantee Submission, 2019
Results from a genome-wide association study (GWAS) can be used to generate a polygenic score (PGS), an individual-level measure summarizing identified genetic influence on a trait dispersed across the genome. For complex, behavioral traits, the association between an individual's PGS and their phenotype may contain bias (from geographic,…
Descriptors: Genetics, Individual Characteristics, Nature Nurture Controversy, Heredity
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Cisterna, Dante; Ingram, Erin; Bhattacharya, Devarati; Roy, Ranu; Forbes, Cory – Science and Children, 2020
A set of core ideas in the life sciences revolve around genetics, variation, and inheritance. While the "Next Generation Science Standards" (NGSS; NGSS Lead States 2013) emphasize teaching and learning about these concepts across K-12 grades, it is critical for early learners to begin to develop understanding of them. By the end of fifth…
Descriptors: Science Instruction, Plants (Botany), Genetics, Elementary School Science
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Dar-Nimrod, Ilan; Heine, Steven J. – Psychological Bulletin, 2011
In the target article (Dar-Nimrod & Heine, 2011), we provided a social-cognitive framework which identified genetic essentialist biases and their implications. In their commentaries, Haslam (2011) and Turkheimer (2011) indicated their general agreement with this framework but highlighted some important points for consideration. Haslam…
Descriptors: Student Attitudes, Genetics, Models, Heredity
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Singh, Gurmukh; Siddiqui, Khalid; Singh, Mankiran; Singh, Satpal – Journal of Educational Technology Systems, 2011
The current research article is based on a simple and practical way of employing the computational power of widely available, versatile software MS Excel 2007 to perform interactive computer simulations for undergraduate/graduate students in biology, biochemistry, biophysics, microbiology, medicine in college and university classroom setting. To…
Descriptors: Heredity, Genetics, Biological Sciences, Medical Education
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Hoyt, William T. – Psychological Methods, 2007
Rater biases are of interest to behavior genetic researchers, who often use ratings data as a basis for studying heritability. Inclusion of multiple raters for each sibling pair (M. Bartels, D. I. Boomsma, J. J. Hudziak, T. C. E. M. van Beijsterveldt, & E. J. C. G. van den Oord, 2007) is a promising strategy for controlling bias variance and may…
Descriptors: Research Design, Research Methodology, Genetics, Validity
Unger, Lawrence; Blystone, Robert V. – Bioscene, 1996
Discusses whether the discovery in 1956 that humans have a chromosome number of 46, as opposed to 47 or 48 as previously thought, fits into a paradigm shift of the Kuhnian type. Concludes that Kuhn probably would not have considered the chromosome number shift to be large enough to be a focus for one of his paradigms. (AIM)
Descriptors: Biological Parents, Genetic Engineering, Genetics, Heredity
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Santos, Silvia J.; Hurtado-Ortiz, Maria T.; Sneed, Carl D. – Hispanic Journal of Behavioral Sciences, 2009
This study examined the validity of the Klonoff and Landrine Illness-Belief Scale when applied to Latino college students (n = 156; 34% male, 66% female) at high risk for future diabetes onset. Principal factor analysis yielded four significant factors--emotional, folk beliefs, punitive, gene/hereditary--which accounted for 64.5% of variance and…
Descriptors: College Students, Diabetes, Factor Analysis, Correlation
Simonton, Dean Keith – Journal for the Education of the Gifted, 2005
The genetic endowment underlying giftedness may operate in a far more complex manner than often expressed in most theoretical accounts of the phenomenon. First, an endowment may be emergenic. That is, a gift may consist of multiple traits (multidimensional) that are inherited in a multiplicative (configurational), rather than an additive (simple)…
Descriptors: Gifted, Genetics, Models, Talent
Crow, James F. – Harvard Educ Rev, 1969
Descriptors: Environmental Influences, Genetics, Heredity, Intelligence
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Wilson, Edward O. – BioScience, 1973
Discusses interdemic (interpopulation) selection, the Levins and Boorman-Levitt models, and the significance of group selection for ecology. (JR)
Descriptors: Biological Sciences, College Science, Ecology, Evaluation
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Capron, Christiane; Vetta, Adrian R.; Vetta, Atam – Race, Gender & Class, 1998
The biometrical school of scientists who fit models to IQ data traces their intellectual ancestry to R. Fisher (1918), but their genetic models have no predictive value. Fisher himself was critical of the concept of heritability, because assortative mating, such as for IQ, introduces complexities into the study of a genetic trait. (SLD)
Descriptors: Biological Influences, Genetics, Heredity, Intelligence Quotient
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Hull, Peter – Journal of Biological Education, 1977
Descriptors: Biology, Computer Programs, Genetics, Heredity
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Small, James W., Jr.; Edwards, Kathryn L. – American Biology Teacher, 1979
Presents some techniques developed to help improve student understanding of Mendelian principles through the use of a computer simulation model by the genetic system of the fruit fly. Includes discussion and evaluation of this computer assisted program. (MA)
Descriptors: Biology, Computer Assisted Instruction, Genetics, Heredity
Goldberger, Arthur S. – 1975
The estimation of genetic models reported by J. L. Jinks and L. J. Eaves in a recent review are critically examined. A number of errors in procedure and interpretation are found. It is concluded that the evidence, provided by kinship correlations, for the proposition that intelligence is highly heritable, is not persuasive. (Author/BJG)
Descriptors: Comparative Analysis, Correlation, Environmental Influences, Genetics
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