The Issue Of Few Women In Science, Technology And Engineering

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This study will examine reasons why few girl and women take Science, Technology, Engineering and Mathematics (STEM) subjects in Universities. STEM is hypothesized to have fewer female representations than male. Participants will be 200 female first year students from Australian National University. They will self-report reasons why they took or did not take STEM subjects in University. Half of the participants will attend STEM classes and the other half will attend the non-STEM classes for a whole semester. They will complete the Positive and Negative Affect Schedule (PANAS) every day of their attendance. It is predicted that gender bias, the climate of STEM departments in university, and stereotypes have direct effects on women choice of subjects in universities. Those who attend the non-STEM classes will report high moods, happiness and having enjoyed their classes more than those who attend the STEM classes. The study will also include statistics on girls and boys participation and performance in these classes. It is predicted that girl in non-STEM classes will have a high participation and performance than those in STEM classes. This report will help provide new ideas on what can be done to enhance girls experience in STEM classes and reduce the stereotype.

Women are underrepresented in STEM subjects in learning institutions such as universities, and in STEM occupations globally, (White & Massiha, 2016). In UK for example, women make up 14.4 percent of the entire working population despite their number in the workforce being half the population (Eddy & Brownell, 2016). There are many reasons for the existence of gender gap in STEM. Hall, Schmader, Aday and Croft (2019) found out that fewer girls select STEM subjects in secondary schools and in the university. They claim that interventions globally show that the increase of girls and women in STEM subjects and careers has a very slow increase.

Biological explanations rely on the fact that girls are best at verbal recall tasks and that boys are good at spatial tasks (Levine et al., 2015). Such information does not have reliable data and what is available shows a small difference that is not enough to connect to STEM variation. Meta-analysis consistently reveals that on average, boys’ and girls’ performance are similar but that similarity is not portrayed across various skills. For example, in a meta-analysis comprising 100 studies testing over 3 million people on gender differences in Science and Mathematics revealed that girls outperformed boys in primary schools. While in secondary schools there was no difference; both genders performed the same (Eddy & Brownell, 2016). However, when it comes to end term tests, the same girls who outperformed boys in class work scored low marks. The report factors on the levels of anxiety and self-confidence towards science and mathematics. Eddy & Brownell, (2016), argues that girls have all the intelligence needed to perform excellently in STEM examinations but will always let stereotype and gender bias barriers cause anxiety and low self-confidence. Broadley (2015) points out that “girls are more anxious about tests than boys and this is what affects their score.”

ChRistensen, KnezeK & Tyler-Wood (2015) claim that a during an examination, female student experiences an extra emotional and cognitive burden of anxiety and worry brought about by the stereotype that girls are not good in sciences and math, and that they cannot be excellent engineers. They continue to argue that anxiety increases and performance level drops as they sit for the exams in a room consisting of mostly men. Such a stereotype threat can explain why there are few women in STEM classes and employment.

Studies show that most girls and women have fixed mindset and that is why they lose confidence when they encounter challenges in science and mathematics during an examination (White & Massiha, 2016). “People with a fixed mindset believe that intelligence is static, while those with a growth mindset believe that intelligence can be developed” Lerback & Hanson, (2017). Those with a growth mindset want to learn more and take challenges positively. They view efforts as a path to mastery and are inspired by other people’s success. Those with a fixed mindset fear obstacles and lose confidence when they encounter a challenge (Lerback & Hanson, 2017). Such a study is important (for women) because in scientific work, it is normal to encounter challenging problems and obstacles. Women should prepare their mind to learn more things and to tackle more problems. In the meta-analysis performed by Levine et al. (2015), those people with a fixed mindset believed that if they are smart, things should come their way without struggle. Girls should eliminate such a mindset and replace it with a growth mindset to enable them deal with both environmental and social growth particularly those aspiring to take STEM subjects.

Previous studies have provided essential insight on the reasons why there are few women and girls in STEM careers and subjects. However, few researches have exhaustively investigated reasons why some girls perform best in STEM subjects than others. Additionally, criticism has been pointed to methodologies used in these studies, for example, ChRistensen, KnezeK and Tyler-Wood, (2015), took a limited sample size which could not represent the whole population.

This study aims to be conduct in a real world setting where a larger sampling will be taken from first year university students who are fresh from different high schools. They will represent the different secondary schools from all over the world because some will be international students. It is hypothesized that environmental and social barriers such as gender bias, stereotype and culture play a significant role in deterring women and girls from taking STEM subjects and careers.

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The participants will be 200 Female students from Australian National University. Participants will be recruited from non-STEM and STEM classes. Only those willing to participate will be allowed to participate in the recruitment. Those who have a natural hate for STEM subjects and who performed them poorly in high school will be excluded. Participants will be selected from first year students of Australian National University and must be 18 years of age or older. the participants will also be of a right mental health to participate in the research. The Human Research Ethics Committee of Australian National University will approve all the procedures of the study.


The independent variables, participation and performance, will comprise two level: the students who will attend the non-STEM classes and the female students who will attend the STEM classes. Mood will be the dependent variable. The research will be a quasi-experimental, independent measure design. Participants who will report not ever liking STEM subjects since they were kids or those who report hating non-STEM subjects will be excluded from participating in the study.


Mood will be evaluated comparing average affect score for 200 participants who will be classified as non-STEM female students and 200 participants who will be classified as STEM female students. The mood will be measured in the Positive and Negative Affect Schedule (PANAS) which is an interval scale proven to effectively and independently measure positive and negative affects. Two subtests will be performed to measure Twenty positive affect and Twenty negative affect schedules. The participants will rate them as 1 = not at all, 2 = very slightly, 3 = average, 4 = good and 5 = extremely. The score for each subtest will range from 50 to 200 and will have a lower positive score on subtest 1 reflecting less positive affect and a higher negative score on subtest 2 which reflects a lower negative affect.


Each participant will be asked to report her performance on STEM subjects since she was in primary school and how she liked them. She will be asked to provide her data on the score of each subject since primary (if available) and secondary school. Each participant’s data will be calculated on average per every STEM subject to reflect her average performance in a statistical manner. The average previous performance score will be calculated from the self-reported data in percentage. An score of between 30 - 50 percent will be rated as an average score and score above 50 will be rated as above average. The participants with less than 30 percent average on more than two subjects will not be allowed to participate on the study. All participants will be asked to complete the PANAS after attending or failing to attend a class daily. Participation will be voluntary and those participating will have the freedom to leave at will though the importance of completion will be communicated in the beginning.

Expected Outcome and Implication

If the hypothesis is supported, then the relationship between low performance and negative mood may be explained by environmental and social barriers such as stereotypes, climate of engineering and science departments, and gender bias in universities and other lower learning institutions. Broadley (2015) argue that “women in science, technology, engineering and math (STEM) fields dace significant implicit bias on the basis of their gender.” Stereotype can reduce girls’ aspirations for STEM subjects in colleges and universities (Eddy & Brownell, 2016). Lerback & Hanson (2017) points out that an environment of study determines the positive or negative outcome in learning institutions including universities.

Women/girls are reportedly saying that they feel unwelcome in STEM classes by both the lecturers and the male students (Lerback & Hanson, 2017). A stereotype threat arises where a negative stereotype becomes relevant in assessment of performance and causes the female student experience emotional and cognitive burden of anxiety and worry (White & Massiha, 2016). Studies reveal that many people claim that they do not hold on to the belief that female are not as good as male in STEM subjects in their conscious mind, however, they do it in their unconscious mind (ChRistensen, KnezeK & Tyler-Wood, 2015). Encouraging girls and women by telling them that they have the ability to succeed in these subjects if they would refrain from focusing on the negative barriers will raise their morale and increase their motivation and desire to take STEM subjects in school and in career choice.

If the hypothesis is not supported then, having a low mood in STEM classes in this study can be attributed by a natural dislike for the subjects by many girls and women as compared to men. In many communities girls grow knowing that certain roles are men’s and others are women. Most may take the same belief to school and let it determine the subjects they will perform optimally and those they won’t (Broadley, 2015).

There are some design limitations in the proposed study. Previous performance data in this study will not be manipulated and it will not use random selection. It is possible that those who will voluntarily apply to participate in the study may not represent a fair population of the girls who like the STEM subjects or those that performed well yet did not take STEM subjects in universities. There are many reasons why girls may not want to participate including being shy. Additionally, the result of the study may not be reliable because it will be restricted to undergraduate university students from Australian National University and not all learning institutions such as primary and secondary schools. Moreover, there are many universities in Australia and a study from only one university cannot adequately represent findings of all universities word wide and the general public. Future research should involve the participation of women from other learning institutions and should manipulate data and engage a wider and varied participant sample. However, the results of this study may suggest that there is more work for the parents and the learning institutions to find strategies of eliminating stereotypes, gender bias and workplace culture to help more girls take STEM subjects and engage in STEM careers.


  1. Broadley, K. (2015). Entrenched gendered pathways in science, technology, engineering and mathematics: Engaging girls through collaborative career development. Australian Journal of Career Development, 24(1), 27-38.
  2. ChRistensen, R., KnezeK, G., & Tyler-Wood, T. (2015). Gender differences in high school student dispositions toward science, technology, engineering, and mathematics careers. Journal of Computers in Mathematics and Science Teaching, 34(4), 395-408.
  3. Eddy, S. L., & Brownell, S. E. (2016). Beneath the numbers: A review of gender disparities in undergraduate education across science, technology, engineering, and math disciplines. Physical Review Physics Education Research, 12(2), 020106.
  4. Hall, W., Schmader, T., Aday, A., & Croft, E. (2019). Decoding the dynamics of social identity threat in the workplace: a within-person analysis of women’s and men’s interactions in STEM. Social Psychological and Personality Science, 72, 1-14.
  5. Lerback, J., & Hanson, B. (2017). Journals invite too few women to referee. Nature News, 541(7638), 455.
  6. Levine, M., Serio, N., Radaram, B., Chaudhuri, S., & Talbert, W. (2015). Addressing the STEM gender gap by designing and implementing an educational outreach chemistry camp for middle school girls. Journal of Chemical Education, 92(10), 1639-1644.
  7. White, J. L., & Massiha, G. H. (2016). The Retention of Women in Science, Technology, Engineering, and Mathematics: A Framework for Persistence. International Journal of Evaluation and Research in Education, 5(1), 1-8.
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