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      The Dominance Concept Inventory: A Tool for Assessing Undergraduate Student Alternative Conceptions about Dominance in Mendelian and Population Genetics

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          Abstract

          Biology undergraduates often have difficulty understanding dominance in genetics. The authors developed and evaluated the Dominance Concept Inventory, a tool to measure the prevalence of four alternative conceptions about dominance. It was found that the test is an effective tool and that introductory and advanced students harbor confusions about dominance.

          Abstract

          Despite the impact of genetics on daily life, biology undergraduates understand some key genetics concepts poorly. One concept requiring attention is dominance, which many students understand as a fixed property of an allele or trait and regularly conflate with frequency in a population or selective advantage. We present the Dominance Concept Inventory (DCI), an instrument to gather data on selected alternative conceptions about dominance. During development of the 16-item test, we used expert surveys ( n = 12), student interviews ( n = 42), and field tests ( n = 1763) from introductory and advanced biology undergraduates at public and private, majority- and minority-serving, 2- and 4-yr institutions in the United States. In the final field test across all subject populations ( n = 709), item difficulty ranged from 0.08 to 0.84 (0.51 ± 0.049 SEM), while item discrimination ranged from 0.11 to 0.82 (0.50 ± 0.048 SEM). Internal reliability (Cronbach's alpha) was 0.77, while test–retest reliability values were 0.74 (product moment correlation) and 0.77 (intraclass correlation). The prevalence of alternative conceptions in the field tests shows that introductory and advanced students retain confusion about dominance after instruction. All measures support the DCI as a useful instrument for measuring undergraduate biology student understanding and alternative conceptions about dominance.

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          Coefficient alpha and the internal structure of tests

          Psychometrika, 16(3), 297-334
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            R: A language and environment for statistical computing

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              Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM.

              Reliability, the consistency of a test or measurement, is frequently quantified in the movement sciences literature. A common metric is the intraclass correlation coefficient (ICC). In addition, the SEM, which can be calculated from the ICC, is also frequently reported in reliability studies. However, there are several versions of the ICC, and confusion exists in the movement sciences regarding which ICC to use. Further, the utility of the SEM is not fully appreciated. In this review, the basics of classic reliability theory are addressed in the context of choosing and interpreting an ICC. The primary distinction between ICC equations is argued to be one concerning the inclusion (equations 2,1 and 2,k) or exclusion (equations 3,1 and 3,k) of systematic error in the denominator of the ICC equation. Inferential tests of mean differences, which are performed in the process of deriving the necessary variance components for the calculation of ICC values, are useful to determine if systematic error is present. If so, the measurement schedule should be modified (removing trials where learning and/or fatigue effects are present) to remove systematic error, and ICC equations that only consider random error may be safely used. The use of ICC values is discussed in the context of estimating the effects of measurement error on sample size, statistical power, and correlation attenuation. Finally, calculation and application of the SEM are discussed. It is shown how the SEM and its variants can be used to construct confidence intervals for individual scores and to determine the minimal difference needed to be exhibited for one to be confident that a true change in performance of an individual has occurred.
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                Author and article information

                Contributors
                Role: Monitoring Editor
                Journal
                CBE Life Sci Educ
                CBE-LSE
                CBE-LSE
                CBE-LSE
                CBE Life Sciences Education
                American Society for Cell Biology
                1931-7913
                1931-7913
                Summer 2014
                : 13
                : 2
                : 349-358
                Affiliations
                [1]*Department of Biological Science, California State University–Fullerton, Fullerton, CA 92831
                [2] Department of Biology, University of Wisconsin–La Crosse, La Crosse, WI 54601
                [3] School of Interdisciplinary Arts and Sciences, University of Washington–Bothell, Bothell, WA 98011
                Author notes
                Address correspondence to: Joel K. Abraham ( jkabraham@ 123456fullerton.edu ).
                Article
                CBE-13-08-0160
                10.1187/cbe.13-08-0160
                4041511
                26086665
                b03322b7-8455-42de-a2ad-4c3a3dc3e162
                © 2014 J. K. Abraham et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License ( http://creativecommons.org/licenses/by-nc-sa/3.0).

                “ASCB®” and “The American Society for Cell Biology®” are registered trademarks of The American Society of Cell Biology.

                History
                : 16 August 2013
                : 3 January 2014
                : 3 January 2014
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                June 2, 2014

                Education
                Education

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