Utilizing Latent Profile Analysis to Determine the Appropriate Mentorship for Community College STEM Majors

• In Event: Mentorship and Mentoring Practices SIG Paper Session

Abstract

There is a need to develop ways to increase community college science, technology, engineering, and mathematics (STEM) majors’ persistence in the field and mentorship could aid in that endeavor. A latent profile analysis (LPA) utilizing results from 343 community college students who participated in a survey study revealed that students reside in one of four classes of mentorship. It was discovered that STEM majors were 12.69 times more likely to be classified into a group where they desired a mentor would who would guide, challenge, and encourage them. STEM students could benefit from more robust mentorship at the community college and this study can inform how faculty and institutions provide the appropriate mentorship to STEM majors.

Author

• Micaela Victoria Cesario Morgan, University of California - Santa Barbara