Learning Resources LSP0339-UK 5-in-1 Outdoor Measure-Mate

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Rusbult, C. E. (1983). A longitudinal test of the investment model: The development (and deterioration) of satisfaction and commitment in heterosexual involvements. Journal of Personality and Social Psychology, 45(1), 101–117. https://doi.org/10.1037/0022-3514.45.1.101. MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1, 130–149. https://doi.org/10.1037/1082-989X.1.2.130. Some items of the MATE involve context and others do not but the role of context in measurement of acceptance was not carefully considered. Hence the I-SEA instrument puts forth a three-dimensional model where acceptance of evolution is assessed along three constructs: (1) microevolution, (2) macroevolution, and (3) human evolution. In this article, we use the word “dimension” to refer to a quantitative representation of a construct which accounts for the correlation between item responses (Kline 2014). In discussion of the methods and results, we will also use the term “factor”, which refers to an individual construct or dimension (Kline 2014). In the case of the I-SEA, Nadelson and Southerland ( 2012) use three dimensions to account for the relationships between the responses, whereas the MATE and the GAENE use a single dimension to account for the correlation between responses on their respective items. In the development of the GAENE, Smith et al. ( 2016) argue that conflation of acceptance with knowledge, belief, and religious connotation limits the content validity of the MATE, thereby limiting our ability to use the MATE as a valid measure of evolution acceptance. Smith and colleagues henceforth developed set of items which are worded in such a way that they avoid these confounding factors.

In addition to understanding how our current measures of evolution acceptance fit with conceptual work, this study also yields insight into the empirical implications for parametrizing evolution acceptance. Various parametrizations have been explored. Nadelson and Southerland ( 2012) utilized a three-dimensional model for evolution acceptance in their construction of the I-SEA, suggesting that the dimensions of evolution acceptance should be delineated by the type of evolution: microevolution, microevolution, and human evolution. What this study suggests is that, from a quantitative perspective, topic is a determinant of the difficulty of an item along the same sub-construct(Figs. 3 and 4), but it does not seem to serve as the key delimiter in terms of the unique sub-constructs. In other words, while acceptance of macroevolution, human evolution, and microevolution may be distinct in their difficulty, it may not be necessary to treat them asdistinct sub-constructs. Rather, the data show that differences between students’ responses on items across contexts are accounted for by the expected difficulty hierarchy imposed by the Rasch model (Boone 2016), making it unnecessary to define new sub-constructs to account for the different response patterns across contexts.Cherlin, A. J. (2004). The deinstitutionalization of American marriage. Journal of Marriage and Family, 66(4), 848–861. doi: 10.1111/j.0022-2445.2004.00058.x.

Rusbult, C. E. (1980). Commitment and satisfaction in romantic associations: A test of the investment model. Journal of Experimental Social Psychology, 16(2), 172–186. https://doi.org/10.1016/0022-1031(80)90007-4. Significant work has been done towards exploring the relationship between knowledge of evolution and acceptance of evolutionary theory (Nadelson and Southerland 2010; Romine et al. 2017). However, it is currently difficult to tease out how much of this relationship is due to the fact that evolution acceptance as it is currently being measured reflects knowledge of evolution. The MATE has been criticized on the grounds that it possibly conflates knowledge of evolution with acceptance of evolutionary theory (Hogan 2000; Smith 2010; Wagler and Wagler 2013), and both the MATE and the I-SEA are criticized on the grounds that they are not tied to a theoretical foundation for evolution acceptance (Smith et al. 2016). Purpose of the Research Romine WL, Todd AN, Clark TB. How do undergraduate students conceptualize acid–base chemistry? Measurement of a concept progression. Sci Educ. 2016;100(6):1150–83. The purpose of this study was to examine the measurement properties of the items contained in three quantitative evolution acceptance instruments, each of which captures evolution acceptance differently in terms of dimensionality and context. The MATE was designed as a unidimensional measure which used macroevolution and human evolution contexts in its items (Rutledge and Warden 1999). The I-SEA was developed to capture these contexts in separate constructs; it was designed to measure acceptance of microevolution, macroevolution, and human evolution as three respectivedimensions (Nadelson and Southerland 2012). The GAENEwas designed to provide a unidimensional measure of evolution acceptance which is independent of knowledge of evolution and religious orientation (Smith et al. 2016). Given the high similarity of wording between many of the items on the three instruments and the fact that they share a common Likert measurement scheme, we hypothesized that these instruments may share more similarities than differences and actually provide similar quantitative information about evolution acceptance. We found that this is the case. Putting the 57 items from the three instruments together to form an instrument-independent scaling results in useful unidimensional and two-dimensional parametrizations of evolution acceptance.Steiger JH. Understanding the limitations of global fit assessment in structural equation modeling. Person Individ Differ. 2007;42(5):893–8. Waynforth, D. (2007). Mate choice copying in humans. Human Nature, 18(3), 264–271. doi: 10.1007/s12110-007-9004-2. Johnson RL, Peeples EE. The role of scientific understanding in college: student acceptance of evolution. Am Biol Teacher. 1987;49:93–6.

Two items within the rejection of incredible ideas construct misfit with the Rasch model: MATEcred17 and MATEcred19. These items were also of relatively high difficulty, indicating that students who tended to reject the other misconception statements nonetheless tended to accept these. Students may have accepted MATEcred17, much of the scientific community doubts if evolution occurs, since the term “scientific community” is quite broad. A student who has taken a variety of science classes has likely seen that evolution is not discussed in most of these classes—especially the physical sciences, but even in biology (Padian 2010). It would therefore make sense for students to accept this statement regardless of their tendency to reject other ideas which are not credible. The misfit of MATEcred19, with few exceptions, organisms came into existence about the same time, is more difficult to explain. We argue that the rejection of incredible ideas construct is comparatively aligned with one’s understanding of evolution (cognition), so the tendency for high ability students to accept this idea may be reflective of the persistent misunderstanding of deep time and the evolutionary timeline—one of the most difficult concepts for students to comprehend (Rosengren et al. 2012). Common practice may be to simply eliminate these items from the corpus in future research. However, doing this would carry the consequence of eliminating a potentially important part of the construct. We caution against making assessment decisions based on a single number. Instead the nature of the specific construct of interest should also be considered when deciding which items to use from these three instruments. Suggestions for using current evolution acceptance instrumentation Bond T, Fox CM. Applying the Rasch model: fundamental measurement in the human sciences. New York: Routledge; 2015. Linacre JM, Tennant A. More about critical eigenvalue sizes in standardized-residual principal components analysis (PCA). Rasch Measu Trans. 2009;23(3):1228.

Popper K. Philosophy of science. In: Mace CA, editor. British Philosophy in the Mid-Century. London: George Allen and Unwin; 1957. Goldscheider, F. K., Kaufman, G., & Sassler, S. (2009). Navigating the “new” marriage market: how attitudes toward partner characteristics shape union formation. Journal of Family Issues, 30, 719–737. doi: 10.1177/0192513X09331570. Moore, F. R., & Cassidy, C. (2007). Female status predicts female mate preferences across nonindustrial societies. Cross-Cultural Research, 41(1), 66–74. doi: 10.1177/1069397106294860.

Sabini, J., & Green, M. C. (2004). Emotional responses to sexual and emotional infidelity: Constants and differences across genders, samples, and methods. Personality and Social Psychology Bulletin, 30(11), 1375–1388. https://doi.org/10.1177/0146167204264012. Kashyap, R., Esteve, A., & García-Román, J. (2015). Potential (mis)match? Marriage markets amidst sociodemographic change in India, 2005–2050. Demography, 52(1), 183–208. doi: 10.1007/s13524-014-0366-x. Romine WL, Barrow LH, Folk WR. Exploring secondary students’ knowledge and misconceptions about influenza: development, validation, and implementation of a multiple-choice influenza knowledge scale. Int J Sci Educ. 2013;35(11):1874–901.Its robust build means it will cope with vigorous use in rough terrain and all components fit into a handy mesh bag van Buuren, S., & Groothuis-Oudshoorn, K. (2011). mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3), 1–67. https://doi.org/10.18637/jss.v045.i03.