The extent to which gender roles are still present in the education system is evident in the low numbers of female students in STEM subjects. Our research synthesis explores which measures could be effective in schools to reduce gender differences in stereotypical subjects (such as mathematics, science or reading). Our focus is primarily on interventions that target so-called motivational-affective factors such as students' interest, motivation, enjoyment, and self-concept. The aim is to identify ways in which all students - regardless of gender - can reach their full potential in all subjects.
Research Questions
- Do interventions in school that strengthen and promote motivational-affective student factors have different effects for the stereotypically disadvantaged and stereotypically non-disadvantaged gender in a given subject?
- Which measures are most effective in reducing stereotypical gender attributions regarding school subjects?
Results
Our research synthesis provides an overview of the origins of gender gaps in educational contexts and provides insight into what interventions in school contexts hold promise for addressing them.
- School interventions are successful in terms of factors such as motivation and interest.
- Girls can be inspired to pursue STEM subjects.
- The extra effort required for innovative measures in the classroom pays off in the long term.
- Measures in the school context are worthwhile because they have the potential to contribute to greater gender equality.
- Girls benefit more than boys from school-based measures in STEM subjects.
- Gender-related differences in school may be reduced in this way.
- Taking girls into account is both meaningful and necessary.
- It is worthwhile to focus on the disadvantaged gender in STEM subjects, i.e. girls.
- Girls may benefit more, but interventions also have a positive impact on boys.
- Early interventions designed to break down gender stereotypes are particularly successful.
- Traditional stereotypes can be disrupted, especially in elementary school.
- It makes sense to consider gender issues in schools right from the beginning.
- Promoting girls as early as elementary school could be helpful for a greater proportion of women in STEM professions.
- Although interventions are most successful in elementary school, characteristics such as interest and motivation remain shapeable throughout life.
Scientific Publications
Lesperance, K., Hofer, S., Retelsdorf, J., & Holzberger, D. (2022). Reducing gender differences in student motivational-affective factors: A meta-analysis of school-based interventions. British Journal of Educational Psycholog y, 00, 1–35. doi: 10.1111/bjep.12512
In the first step, which was the literature search, we found a large amount of studies related to the topic. In order to sort the relevant studies, we first defined keywords. We used a combination of keywords related to the target group (e.g., "students" or "school"), gender differences, school-based interventions, and motivational-affective factors. We conducted the literature search primarily in online databases.
In the course of screening, we screened individual studies based on their titles and abstracts. We used pre-specified criteria to determine which studies would be included in our research synthesis:
- Evaluation of a school-based interventions at the primary and secondary education levels.
- Examination of at least one motivational-affective factor within the study
- Comparison of one group that received the intervention to another that did not receive the intervention (control group)
- Focus on subjects from STEM (math, computer science, science) or reading/language
The next step was the Coding, which means we coded the overall content of each research study. To answer our research questions, we filtered out relevant information from the studies and again sorted out studies that turned out not to be relevant after all, or whose information turned out to be insufficient. Quality and effect size, meaning the size of the effect of interventions, played an important role in this fine coding.
After coding all relevant criteria, we summarized the results of the individual studies into an average effect size using statistical calculations as part of the data analysis. Our research synthesis therefore is a meta-analysis.