The primary separate changeable in regards to our data was a scale you to catches students’ counter-stereotypical viewpoints about experts

The primary separate changeable in regards to our data was a scale you to catches students’ counter-stereotypical viewpoints about experts

Counter-stereotypical beliefs on researchers

To measure teenage students’ attitudes of experts beyond bodily traits, the analysis team adjusted four points of past associated training one interviewed elementary people (DeWitt ainsi que al., 2011) and you may youngsters (Wyer et al., 2010). A couple items find out about the kind of work one to boffins would: “Researchers always functions alone when you look at the laboratories” and you will “Experts could work within the teams or organizations”; whenever you are around three points grab viewpoints on scientists’ hobbies and personal features: “Extremely boffins is actually geeks dating a estonian man tips or nerds,” “Those who are effective in technology cannot be proficient at almost every other things, such as for instance sporting events or ways,” and you will “Experts is interested and inventive somebody.” Each one of these issues got impulse groups ranging from step one (Highly Differ) so you’re able to 4 (Firmly Consent); affairs with an awful valence (elizabeth.g., Extremely boffins are geeks otherwise nerds) was indeed opposite-coded with the intention that for everyone points, a higher score depicted a self-confident otherwise counter-stereotypical evaluate. Making use of the Skewness-Kurtosis test to own normality (thru Stata statistical software), we figured the shipping of all the five facts somewhat deviated on typical shipment out-of both thinking regarding skewness and you can kurtosis. Especially, consistent with certain prior lookup discussed above (Garriott et al., 2017; Nassar-McMillan ainsi que al., 2011), the things was basically every adversely skewed, in a manner that total people stored a bit self-confident opinions on the boffins. Thus, i dichotomized each product, in a fashion that step 1 illustrated highly agreeing with a table-stereotypical statement regarding researchers (rating regarding 4 otherwise strongly concur) and you may 0 portrayed a score of step three or lower than. Footnote 3

Independent variables

To determine the factor structure underlying the five items related to counter-stereotypical beliefs about scientists and establish its validity, we randomly divided our sample into two separate and equal-sized groups to conduct exploratory and confirmatory factor analyses (DeCoster, 1998; Fabrigar et al., 1999). The exploratory factor analysis (EFA) using a principal factors extraction method was conducted with the first sub-set of data, representing half of our dataset (N = 554). This produced a one-factor solution, as indicated by the inspection of the scree plot test and eigenvalues (Costello Osborne, 2005), that explained about 41% of the variance. The Kaiser-Meyer-Olkin measure of 0.72 indicated an acceptable sampling adequacy (Kaiser, 1974). Additionally, all items loaded onto the single factor, with factor loadings ranging from 0.58 to 0.71, and communalities ranging from 0.33 to 0.51. These moderate to strong factor loadings and our conceptualization of students’ counter-stereotypical beliefs about scientists suggest that all five items be retained (Costello Osborne, 2005). Subsequently, a confirmatory factor analysis (CFA) was conducted to validate the structure of the factor with the second half of our sample (N = 554). The fit statistics indicated an adequate model fit, including a Root Mean Square Error of Approximation (RMSEA) of 0.08 (where values less than or equal to 0.08 indicate an acceptable fit, and 90% CI is [0.05,0.11]), a comparative fit index (CFI) of 0.94 (where values greater than 0.90 indicate an acceptable model fit) and a Standardized Root Mean Squared Residual (SRMR) of 0.04 (where values less than or equal to 0.08 indicate a good fit) (Hu Bentler, 1999; Kline, 2015). While the chi-squared statistic for the CFA model was significant (? 2 = , df = 5, p < 0.001), this statistic is known to be sensitive to large sample sizes such as ours (Hair et al., 2010). The standardized factor loadings ranged from 0.41 to 0.54, with a Cronbach's alpha of 0.60, which is somewhat low but still within the acceptable range (Bagozzi Yi, 1988; Hair et al., 2010).

Fundamentally, which will make the size and style used in brand new analyses demonstrated here, students’ responses around the all the points were averaged, in order that higher scores toward measure need holding alot more restrict-stereotypic thinking from the experts, while you are straight down score depict the opposite. To phrase it differently, our size was a measure of strong restrict-stereotypical thinking regarding researchers, whilst captures values that aren’t merely basic views from researchers, but rather feedback out of researchers which might be the fresh anti-thesis out-of typically thin and you will limiting stereotypical pictures (e.g., experts is actually geeks otherwise nerds, and you may experts really works by yourself inside a laboratory). We statement intercourse and you can racial/ethnic variations in prevent-stereotypical viewpoints on the overall performance part.