Predicting Study Outcomes in STEM Areas

• In Event: Underresearched Student Populations and Access, Transitions, and Success

Abstract

Interests as well as prior study experiences are well-known predictors for successful study outcomes and theories like the socio-cognitive career theory or Holland’s theory about vocational interests model such effects. STEM areas, however, are often seen as “hard” study areas and there are several gender phenomena reported for STEM. Therefore, the paper focuses on how far there are specific indicators that allow to predict study outcomes in STEM. The study analyzed data from a large-scale panel study in Germany and focuses male and female students in STEM areas with a low and medium proportion of female students. The results show, besides high-school grade point average, subject and gender specific prediction pattern that should be considered for career counselling.

Authors

• Bernhard M. Ertl, Universität der Bundeswehr München
  Presenting Author

• Florian G. Hartmann, Paris Lodron University Salzburg
  Non-Presenting Author