Factors influencing female decisions to opt out of math-intensive STEM fields:
- cognitive 
- motivational 

Potential factors :
- developmental period
- Biological & sociocultural 

Factors Causing Underrepresentation of Women in Math-Intensive STEM Fields.  

- Continue to focus on building STEM abilities
- focus more on enhancing female interest in STEM subjects
- Intervene at earlier grades to light interest
- Break down stereotypes
- Highlight the importance of hard work vs. talent
- use innovate techniques to teach STEM (i.e. storytelling)
- Communicate how STEM expertise will translate to a career
- Spotlight female role models in STEM
- Make necessary familial accommodations


Recommendations to Decrease the Gender Gap in Math-Intensive STEM Fields 

The performance differences between genders in math-intensive science fields. 

Gender Gap in Math-Intensive Science Fields

Women in the United States are underrepresented in math-intensive STEM fields: 
- mathematics and statistics
- computer and information sciences
- engineering
- physical and technological sciences
- Other scientific fields

San Jose State University

The achievement gap that exists in mathematics courses/math-intensive fields between male and female students.

Gender Gap In Mathematics

Wang, M. T., & Degol, J. L. (2017). Gender Gap in Science, Technology, Engineering, and Mathematics (STEM): Current Knowledge, Implications for Practice, Policy, and Future Directions. Educational psychology review, 29(1), 119–140. https://doi.org/10.1007/s10648-015-9355-x

Gender Gap in Science, Technology, Engineering, and Mathematics (STEM): Current Knowledge, Implications for Practice, Policy, and Future Directions

Gender Gap in Math-Intensive STEM Fields 

According to The Programme for International Student Assessment (PISA), the average gender differential within OECD countries in mathematics at age 15 is 0.11 standard deviations in favor of males (OECD 2015). 
Italy is one of the countries with the largest gap, equal to 0.24 standard deviations. 


Possible explanations:
-	Gender-stereotypes in parent’s evaluation of children abilities
-	Females’ lower self-esteem in math
-	Socioeconomic status
-	Parental education and occupation
-	School educational methods


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