After collecting the data from the outreach programs, the authors used exploratory factor analysis
to assess construct validity based on the pilot responses. In the analysis the team used principal
axis factoring and promax rotation to allow factors to be correlated, and the researchers classified
item loadings above 0.40 as significant. Items with two or more loadings above 0.30 were
considered to be cross-loading. The team used the Kaiser Criterion as well as scree plots and
interpretability to select the number of factors. The evaluators also used factor analysis on each
independent section of the survey. For instance, factor analysis was used separately on the
engineering attitudes section and on the math attitudes section. The researchers also used factor
analysis on all the attitudes questions taken as a whole (the attitudes toward science, math,
engineering, and 21st century skills) with the hope that the results would indicate that each survey section does act as a single construct. Finally, factor analysis was conducted on the 43-
item career section to determine how students tended to group careers based upon interest. In that
way each factor revealed by the analysis defined a group of careers that were similar.