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      University Students’ Conceptual Knowledge of Randomness and Probability in the Contexts of Evolution and Mathematics

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          Abstract

          Two instruments—Randomness and Probability Test in the Context of Evolution (RaProEvo) and Randomness and Probability Test in the Context of Mathematics (RaProMath)—that include both multiple-choice and free-response items were developed. The results indicate that they generate reliable and valid inferences.

          Abstract

          Students of all ages face severe conceptual difficulties regarding key aspects of evolution—the central, unifying, and overarching theme in biology. Aspects strongly related to abstract “threshold” concepts like randomness and probability appear to pose particular difficulties. A further problem is the lack of an appropriate instrument for assessing students’ conceptual knowledge of randomness and probability in the context of evolution. To address this problem, we have developed two instruments, Randomness and Probability Test in the Context of Evolution (RaProEvo) and Randomness and Probability Test in the Context of Mathematics (RaProMath), that include both multiple-choice and free-response items. The instruments were administered to 140 university students in Germany, then the Rasch partial-credit model was applied to assess them. The results indicate that the instruments generate reliable and valid inferences about students’ conceptual knowledge of randomness and probability in the two contexts (which are separable competencies). Furthermore, RaProEvo detected significant differences in knowledge of randomness and probability, as well as evolutionary theory, between biology majors and preservice biology teachers.

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          Most cited references 86

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          A Coefficient of Agreement for Nominal Scales

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            Comparative fit indexes in structural models.

             P. Bentler (1990)
            Normed and nonnormed fit indexes are frequently used as adjuncts to chi-square statistics for evaluating the fit of a structural model. A drawback of existing indexes is that they estimate no known population parameters. A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models. Two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes. CFI avoids the underestimation of fit often noted in small samples for Bentler and Bonett's (1980) normed fit index (NFI). FI is a linear function of Bentler and Bonett's non-normed fit index (NNFI) that avoids the extreme underestimation and overestimation often found in NNFI. Asymptotically, CFI, FI, NFI, and a new index developed by Bollen are equivalent measures of comparative fit, whereas NNFI measures relative fit by comparing noncentrality per degree of freedom. All of the indexes are generalized to permit use of Wald and Lagrange multiplier statistics. An example illustrates the behavior of these indexes under conditions of correct specification and misspecification. The new fit indexes perform very well at all sample sizes.
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              Categorization and Representation of Physics Problems by Experts and Novices*

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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
                Summer 2017
                : 16
                : 2
                Affiliations
                Department of Biology Education, Leibniz Institute for Science and Mathematics Education at Kiel University, 24118 Kiel, Germany
                Institute of Educational Sciences at Kiel University, 24118 Kiel, Germany
                Author notes
                *Address correspondence to: Daniela Fiedler ( fiedler@ 123456ipn.uni-kiel.de ).
                Article
                CBE.16-07-0230
                10.1187/cbe.16-07-0230
                5459256
                28572180
                © 2017 D. Fiedler et al. CBE—Life Sciences Education © 2017 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 for Cell Biology.

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                June 1, 2017

                Education

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