Study site
Study participants were recruited from the full list of employees that were considered faculty at a major public Midwestern university during the 2010 – 2011 academic year. This definition was at the discretion of the Office of Institutional Research at the research site, and included 1595 potential participants. Faculty members were contacted via email where they were directed to voluntarily proceed to an online survey.
Data were kept anonymous; however participants were given the opportunity to submit another email contact for use in a random drawing for one of ten $50.00 gift cards to a local bookstore. Data were collected over several months, with two reminder emails being sent to the potential participants. Relevant demographic data for the population as a whole was obtained from the Office of Institutional Research at the study site.
Survey instrument
The variables of interest in this study are participant knowledge of biological evolution, acceptance of biological evolution. In order to accurately measure both of those variables, distinct sets of questions are required.
We used an unmodified Knowledge of Evolution Exam (KEE) to measure participant knowledge of evolutionary concepts. The KEE has been used in previous studies and has been shown to be both a reliable and valid measure of a participant’s knowledge of biological evolution for several different groups (Moore et al., 2009). The ten questions on the KEE cover content on biological evolution that would be familiar to students in an introductory college biology course.
To assess acceptance of biological evolution, we used an unmodified version of the Measure of Acceptance Toward Evolution (MATE). The MATE has also been used in previous studies measuring acceptance of biological evolution and has been shown to be a valid and reliable measure (Rutledge and Sadler, 2007; Moore and Cotner, 2009a; Moore and Cotner, 2009b). The twenty questions on the MATE examine the participants’ views of whether humans and other animals have evolved, whether biological evolution is science, the age of the Earth, whether biological evolution is testable, and other related views.
A section of the survey was devoted to measuring participant understanding of the nature of science (NOS). Understanding of NOS has been previously shown to be related to an individual’s knowledge and acceptance of biological evolution, and thus was of interest. This portion of the survey was based on the Student Understanding of Science and Science Inquiry (SUSSI) and had several alterations (Liang et al., 2008). This section was placed at the beginning of the survey so as to avoid any potential negative bias associated with a discussion of biological evolution. This portion of the survey was intended to address research questions beyond the scope of this manuscript, and will be reported elsewhere.
In total, the survey used here consisted of 54 multiple-choice questions and 7 text response questions. Besides the KEE, MATE, and SUSSI sections, three other questions examined participant views of educational policies, public acceptance/rejection of biological evolution, and their personal theistic view. Five questions at the end of the survey were of a demographic nature (sex, age, area of expertise, employment level, and amount of science education received). Of the seven text response questions, three were relevant to the MATE and KEE portions while the remaining four were relevant to the SUSSI portion and thus are not discussed here.
309 complete surveys were received from the 1595 faculty members contacted. An additional 139 incomplete surveys were also collected; however, none of these responses reached a level of completeness to be useable in the analyses.
The resulting sample was examined both as a whole and in specific subgroups. The demographic and theistic view questions allowed the sample to broken down into specific categories of interest: area of expertise, theistic view, and amount of science education. Participants were grouped for area of expertise according to their response to the question: “What is your area/field of work? (e.g. Chemistry, History, etc.)”. Based on the responses, participants were grouped together into the following categories: Social Science (e.g., Economics, Psychology, Education, and History), Physical Science (e.g., Physics, Chemistry and Geology), Business (e.g., Finance, Marketing, and Accounting), Applied Science/Engineering (e.g., Civil Engineering, Aerospace Engineering, and Industrial Engineering), Life Science (e.g., Agronomy, Cell Biology, Genetics, and Horticulture), Humanities (e.g., Music, Theatre, English, and Philosophy), Veterinary Medicine, and those that did not answer. Twenty eight responses were collected that did not fit in this categorization scheme and were too few in number to warrant inclusion as their own group (e.g., Information Systems, Statistics). Of these 28, all were placed in the “Not Answered” category.
For theistic view, the survey provided several possible categories: Young Earth Creationist, Old Earth Creationist, Theistic Evolutionist, Agnostic Evolutionist, Atheistic Evolutionist, and a not answered/other group. This categorization scheme is based on a similar set of categories described by Scott (2005). During the analysis, these six categories were reduced to four, for two main reasons. First, in our opinion the distinction between some of the full six categories were not relevant to the primary research questions being considered. Second, using the full six categories would have left some categories too small to be statistically useful. Therefore, Young Earth Creationist and Old Earth Creationist were placed into one group, Theistic Evolutionist was a second group, Agnostic Evolutionist and Atheistic Evolutionist was a third group, and the Not Answered/Other responses were a fourth group.
The amount of science education included the following four choices: 9 or more science courses, 5–8 science courses, 1–4 science courses, or no science courses. The results from the KEE and MATE portions of the survey were summed into percentage scores for the analyses reported below, unless otherwise noted.
Statistical analyses
In this study, we were interested in measuring the relationship between knowledge of biological evolution and acceptance of biological evolution across several variables, including theistic position, amount of science education, and area of expertise. In order to assess the overall relationship between knowledge of biological evolution and acceptance of biological evolution, we used a simple linear regression comparing the percentage scores of all the participants on the knowledge of biological evolution measure to their percentage scores on the acceptance of evolution measure. In addition, we performed an ordination analysis to obtain a graphical visualization of the patterns present in the data. For this, we first created a distance matrix among individuals by calculating pairwise Jaccard’s distance between individuals, based on participant responses to each question. We then used principal coordinate analysis (PCoA) to generate an ordination of the response data space. Individual participants were then color-coded by grouping variables to provide a visual examination of whether or not a particular group displayed similar responses to the questionnaire. One-way ANOVAs were then used to examine several relationships. First, we tested for the presence of a significant relationship between the percentage scores for participant knowledge of biological evolution by their theistic view; their area of expertise; and the amount science education they reported. Second, we tested for the presence of a significant relationship between the percentage scores for participant acceptance of biological evolution by their theistic view; their acceptance of biological evolution; their area of expertise; and the amount of science education they reported.
In order to identify potential interaction between the grouping factors of area expertise and theistic viewpoint, two-way ANOVAs were performed. These tests were used to examine whether the relationships described in the one-way ANOVAs were the same or different when another variable was considered. As with prior analyses, two-way ANOVAs were performed separately on survey questions relating to: 1) knowledge of biological evolution, and 2) acceptance of biological evolution. Mantel tests were also performed on separate distance matrices of the participant responses to the knowledge and acceptance portions of the survey to assess the degree of association between participant scores on the knowledge of evolution, acceptance of evolution, and the grouping variables of area of expertise and theistic view. Specifically, Mantel correlations were calculated between knowledge of biological evolution and acceptance of biological evolution across all participants; between knowledge of biological evolution and acceptance of biological evolution for those participants with differing theistic views (e.g., creationist); and between knowledge of biological evolution and acceptance of biological evolution for each area of expertise (life science, humanities, etc.).
In order to identify potential interaction between the grouping factors of theistic viewpoint and amount of science education, two-way ANOVAs were performed. Again, these tests were used to examine whether the relationships described in the one-way ANOVAs were the same or different when another variable was considered. As with prior analyses, two-way ANOVAs were performed separately on survey questions relating to: 1) knowledge of biological evolution, and 2) acceptance of biological evolution. Mantel tests were also performed on separate distance matrices of the participant responses to the knowledge and acceptance portions of the survey to assess the degree of association between participant scores on the knowledge of evolution, acceptance of evolution, and the grouping variables of theistic view and amount of science education. In this case Mantel correlations were calculated between knowledge of biological evolution and acceptance of biological evolution across all participants; between knowledge of biological evolution and acceptance of biological evolution for those participants with differing theistic views (e.g., young earth creationist); and between knowledge of biological evolution and acceptance of biological evolution by how much science education participants reported.
One-way ANOVA tests were used to examine whether participant knowledge of biological evolution and acceptance of biological evolution were different between each category of interest (theistic view, area of expertise, amount of science education). Linear regression was also used to identify the relationship between variables such as between knowledge of biological evolution and acceptance of biological evolution for physical scientists. Since we are interested in seeing which factors explain the variation we see in the data (e.g., does amount of science or theistic view have more impact on an individual’s knowledge of biological evolution and acceptance of biological evolution), we used Akaike Information Criterion (AIC) to compare the fit of the resulting models. Specifically, we used AIC to compare models based on participant theistic view, area of expertise, or amount of science education regarding their fit to participant knowledge of biological evolution and acceptance of biological evolution. We also used permutation tests to examine whether the observed results from some specific tests were significantly different from a random result.
Finally, pairwise t-tests were used to compare the knowledge of biological evolution and acceptance of biological evolution of the participants between each area of expertise as well as within each area of expertise but between their theistic views (e.g. creationist business faculty compared to non-creationist business faculty).
All statistical computations and procedures were performed in R 2.12.1 (R Core Team 2014).