– This methodology for examining the CIRP data was successful in identifying variables that consistently had statistically significant differences between the STEM and non-STEM students across the different subgroups.
– Overall, the STEM students tended to have greater academic strength and a specific reason for studying STEM while the non-STEM students tended to have a greater focus on community involvement and creative activities.
– Among the activities done more frequently by STEM studentsin the past year were “tutoring another student,” “studying with other students,” “using a personal computer,” “participating in Internet chat rooms,” and “playing a musical instrument.”
– STEM students showed consistent advantage over non-STEM students in high school grade point average (HSGPA). There were only two out of seven subgroups for which the HSGPA was not statistically significant, TAMU African-Americans and Hispanic/Latinos.
– Similarly, STEM students scored significantly higher SAT mathematics scores than non-STEM students across all seven subgroups analyzed. They scored higher average ACT Comprehensive scores than non-STEM students across three subgroups.
– There were several self-rating variables for which STEM students’ individual characteristics averaged higher than those of the non-STEM students. “Mathematical ability” was significant for all seven subgroups, “computer skills” for six subgroups, “academic ability” for five subgroups, “intellectual self-confidence” for four subgroups, and “drive to achieve” for three subgroups.
– Among the activities done more frequently by non-STEM stu-dents in the year prior to being surveyed were “discussed religion,” “was bored in class,” “drank beer/wine,” “felt overwhelmed by the workload,” “visited art galleries/museums,” “attended a public recital/concert,” “smoked,” “felt depressed,” “came to class late,” “discussed politics,” and “was a guest in a teacher’s home.”
– The future actions non-STEM students were more likely to engage in were “change major,” “change career choice,” “participate in student government,” “study abroad,” “participate in student protests,” “join student clubs/groups,” “transfer schools,” and “join a sorority/fraternity.”
2007 - A Method for Identifying Variables for Predicting STEM Enrollment
Nicholls, Gillian M., Wolfe, Harvey, Besterfield-Sacre, Mary, Shuman, Larry J., & Larpkiattaworn, Siripen
Researchers: Gillian M. NichollsHarvey WolfeLarry J. ShumanMary Besterfield-SacreSiripen Larpkiattaworn
University Affiliation:
Email: gmn3@pitt.edu
Research Question:
This research examines demographic, academic, attitudinal, andexperiential data from the Cooperative Institutional Research Program (CIRP) for over 12,000 students at two universities to test a methodology for identifying variables showing significant differences between students intending to major in science, technology, engineering, or mathematics (STEM) versus non-STEM subjects. Identifying potential candidates for STEM enrollment necessi-tates a methodology for analyzing databases containing demo-graphic, academic performance, and attitudinal information acrossa wide array of students. Finding variables that are consistently significant predictors of STEM interest and capability across a range of population subgroups requires the ability to examine a large set of variables since some variables may be significant only for specific subgroups.
Published: Yes
Journal Name or Institutional Affiliation: Journal of Engineering Education
Journal Entry: Vol. 96, No. 1, Pp. 33-44
Year: 2007
Findings:
Data Description:
CIRP survey results were obtained for incoming freshmen students from the University of Pittsburgh (Pitt) for the years 2000 through 2003. This provided a population of over 10,000 students with several large subgroups including Caucasians, African-Americans, and females. The 2002 CIRP survey results for 2,941 incoming freshmen students at Texas A&M University (TAMU) were also obtained. This provided a larger Hispanic/Latino subgroup as well as additional Caucasian and female subgroups.
Variables included high school GPA, ACT and SAT scores, estimated annual parental income, and gender. A new variable was created to classify students into those who indicated at the time they first registered that they would be pursuing a STEM degree and those who would be pursuing a non-STEM degree. Majors that concerned medicine and other highly skilled technical aspects of the health field were considered as STEM. A second new variable was constructed to represent race/ethnicity of the student.
Theoretical Framework:
Relevance:STEM Entrance and Majoring in STEM
Archives: K-16 STEM Abstracts