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Gender differences in high school students’ interest in STEM careers: a multi-group comparison based on structural equation model

Abstract

Background

Females are underrepresented in Science, Technology, Engineering, and Mathematics (STEM) fields all over the world. To encourage more girls to choose STEM majors and careers, it is critical to increase their interest in STEM careers. Many studies have investigated the factors that influence females' entry into STEM fields, but few studies have explored the gender differences in the relationships between these factors. Therefore, based on the Social Cognitive Career Theory, this study explored the gender differences in the effects of environmental factors (school education, informal education, social support, and media) on high school students' interest in STEM careers through the mediating roles of STEM self-efficacy and STEM careers perceptions.

Results

A questionnaire survey was conducted among 1240 high school students in Hunan Province, China, and the results of t-test, regression analysis, and structural equation model multi-group comparison showed that: Firstly, the scores of male students in all the dimensions except for STEM career perception were significantly higher than those of female students. Secondly, the environmental factor that had the greatest effect on male and female students' interest in STEM careers was different. Finally, there were gender differences in the mediating roles of STEM self-efficacy and STEM careers perceptions between environmental factors and interest in STEM careers.

Conclusions

This study revealed the influence mechanisms and gender differences in male and female students' interest in STEM careers in the context of Chinese Confucian culture, and the conclusions are as follows: (1) Male students' interest in STEM careers was significantly higher than that of female students; (2) The environmental factors that had the greatest effect on male and female students' interest in STEM careers were social support and media, respectively; and (3) Environmental factors could affect male students' interest in STEM careers through the mediating roles of STEM self-efficacy and STEM career perception, while environmental factors could affect female students' interest in STEM careers through the mediating role of STEM self-efficacy. Finally, the mediating mechanisms of STEM self-efficacy and STEM career perception between environmental factors and interest in STEM careers, and the importance of STEM self-efficacy for female students were discussed.

Introduction

With the advent of the fourth industrial revolution, STEM workers are more important than ever in supporting national economic development and improving the quality of human life. Many countries have enacted relevant policies to promote STEM education and re-skill workers to make them relevant for STEM related industries. Despite changes in policies to support STEM industries and workers, one issue of equity and equality persists—the problem of underrepresentation of women in STEM fields remains widespread. Female students account for only 35% of the total number of students in STEM-related fields in higher education all over the world (UNESCO, 2017). The attrition rate of females is particularly high during their studies, job search, and even in their careers, which results in a serious underrepresentation of women in STEM fields. For example, only 11% of positions in STEM fields in the UK are held by women (Kirsten, 2019). Women with a bachelor's degree or higher make up 44.2% of the STEM workforce, while women without a bachelor's degree make up 25.8% in the US (National Science Board, 2022). The China Science and Technology Statistical Yearbook 2021 shows that women account for only 26.27% of research and development personnel and 5.79% of the total number of academicians of the Chinese Academy of Sciences and Engineering in China (China Bureau of Statistics, 2022).

Education equity and gender equality are not only important components of the United Nations 2030 Agenda for Sustainable Development (United Nations, 2015), but also catalysts for achieving other sustainable development goals. Ensuring equal access for females to STEM education and increasing their representation in STEM fields are imperative. From a human rights perspective, all people are equal, and females should also have equal opportunities to study and work in STEM fields. From a scientific development perspective, the inclusion of females can unlock greater development potential from diverse perspectives and reduce bias in knowledge and solutions. From a long-term societal perspective, gender equality in STEM will ensure that males and females have equal access to skills and opportunities to contribute and benefit equally in STEM.

Interest in STEM careers could possibly predict whether a student will pursue a STEM career in the future (Bahar & Adiguzel, 2016; Miller, et al., 2018; Nugent et al., 2015). To encourage more girls to choose STEM majors and careers, it is critical to increase their interest in STEM careers. Studies have shown that the high school level is a critical period for the development of interest in STEM careers (Lindahl, 2007; Maltese & Tai, 2011; Sadler et al., 2012). Therefore, analyzing gender differences and exploring the key influencing factors in high school students' interest in STEM careers are particularly important in bridging the gender gap in STEM fields.

Literature review

Gender differences in STEM are a long-standing and pervasive problem. The proportion of females in STEM fields in higher education, especially in computing and engineering, remains low (Sax et al., 2017; Shi, 2018). Males are more likely to work in natural sciences such as physics, while females are more likely to work in humanities and social sciences such as education and health care (Kang et al., 2018; Su & Rounds, 2015). Females of all racial/ethnic backgrounds are less likely than males to find a future career in math (Howard et al., 2011). Young women may underestimate their abilities in math-related fields because of the general perception that these fields are male-dominated (Riegle-Crumb & Peng, 2021). According to the survey of Shi and Huang (2018), 20.5% of boys want to pursue science-related careers in the future compared with only 6.3% for girls. Numerous factors intersect and together influence female participation in STEM fields. Referring to the relevant report released by UNESCO (2017), this study reviewed these influencing factors at the individual, family, school, and societal levels.

Influencing factors at individual level

At the individual level, stereotypes, belonging, self-efficacy, and interest, are possible factors that influence whether girls enter STEM fields. Firstly, gender stereotypes about STEM are prevalent in the socialization of children's gender roles, and these biases negatively affect girls' STEM learning and career interest at an early age (Bian et al., 2017; Luo et al., 2021; Sadler et al., 2012). Females are less likely to have a sense of identity and belonging in STEM fields compared to males (Dasgupta & Stout, 2014; Smith et al., 2013). Secondly, self-efficacy significantly affects individuals' academic performance in STEM fields and their interest in related careers (Lv et al., 2022; Mohtar et al., 2019; Nugent et al., 2015; Wang et al., 2020). The PISA2015 results show that boys have significantly higher self-efficacy than girls in mathematics and science (OECD, 2015), and those females with strong gender stereotypes have significantly lower self-efficacy than males (Rabenberg, 2013). Finally, girls' choices of STEM majors and careers are strongly influenced by their interest in STEM careers (Su et al., 2009), and individual interest in STEM careers is directly influenced by self-efficacy and perceptions of STEM careers, and indirectly by environmental factors such as parents, peers, schools, and media (Wang & Duan, 2021).

Influencing factors at family and peer level

At the family and peer levels, family members such as parents and peers significantly influence girls' self-efficacy, interest in STEM, and whether they pursue STEM-related careers in the future. First, parents who hold traditional gender perceptions will constantly regulate their children's behavior to conform to popular gender stereotypes (Bandura & Bussey, 2004). Parents' differentiated treatment and support for boys and girls will lead to children's stereotypical perceptions of gender and STEM ability, which further lead girls to stay away from STEM fields (Wang & Degol, 2013). Second, in families with higher socioeconomic status, parents can break the shackles of traditional notions of gender roles and career choices, are able to provide more academic support for their children and they also have higher academic expectations for their children (Tenenbaum & Leaper, 2003). In comparison, families with lower socioeconomic status may not be able to provide opportunities for children to learn and experience STEM due to lack of funds, time or access. Studies have found that parents who engage in STEM careers will have an influence over their daughters’ decisions to enter the STEM field, because these parents have more access and resources to provide more support to familiarize their daughters with STEM careers and to break the traditional concept that STEM careers and family life cannot be balanced (Tan et al., 2013). In addition, peers are important social relationships for adolescent girls, and whether girls choose STEM fields is also affected by peers' perceptions of STEM subjects and careers to some extent (Robnett, 2013).

Influencing factors at school level

At the school level, teachers, teaching strategies, curriculum, and textbooks can also influence girls' interest and achievement in STEM. First, teachers are important socializing agents who promote positive beliefs towards STEM fields, and their quality is positively associated with both student math and science achievement and motivation (Ekmekci & Serrano, 2022; Lee & Lee, 2020). Female teachers not only serve as role models for girls, but also break the stereotypes that males have innate abilities in certain areas, coupled with the fact that female teachers are more nuanced than male teachers and more concerned about gender equity in classroom instruction (Rabenberg, 2013). Therefore, female teachers can have a positive impact on girls' STEM education. Teachers' beliefs and attitudes, as well as their expectations of students (i.e., pygmalion effects; LaCosse et al., 2021; Rosenthal & Jacobson, 1968; Vedder‐Weiss & Fortus, 2013), can profoundly affect girls' academic performance, interest in learning, and career aspirations in STEM subjects. Teachers' biases about gender competence may lead to gender inequality in the classroom and may also cause these gender stereotypes to be transmitted to students through instruction, reducing girls' self-efficacy in STEM fields and ultimately negatively impacting girls' participation in STEM. In addition, effective science and mathematics teaching strategies can create a favorable learning environment that motivate and attract girls into STEM fields (Hampden-Thompson & Bennett, 2013; Kang & Keinonen, 2017). Finally, the way male and female roles are represented in textbooks can also directly or indirectly convey gender differences in STEM competencies to students, further reinforcing gender stereotypes and discouraging girls from pursuing STEM careers (Benavot, 2016).

Influencing factors at informal learning level

Compared with formal learning, informal learning refers to learning activities that take place outside of the classroom and in other informal settings, such as participation in STEM competitions and camps, and visits to science and technology museums and galleries (Eshach, 2007). Some studies have shown that informal learning experiences could increase students' interest in STEM careers (Kitchen et al., 2018; Burack et al., 2019; Miller et al., 2018) and also increase students' STEM self-efficacy and STEM careers perceptions (Halim et al., 2017; Vela et al., 2020). Students who participate in STEM programs or competitions have higher interest in STEM careers than those who do not, and they are more likely to choose STEM-related courses and majors in college (Burack et al., 2019; Miller et al., 2018). Students who participate in summer STEM programs are 1.4 times more likely to pursue STEM careers in the future (Kitchen et al., 2018). There is little research on gender differences in the impact of informal learning experiences on boys' and girls' interest in STEM careers. Research has shown that informal activities where female students interact with female STEM experts not only improve girls' academic performance in STEM and mitigate gender stereotypes, but also increase their interest in STEM (McGuire et al., 2021). However, compared with girls, boys are given more opportunities for informal activities (Bonnette et al., 2019) and receive more explanations from their parents during informal scientific activities (Crowley et al., 2001). The reason for girls' lower interest in STEM is usually because they do not have equal access to STEM-related activities at home and in other settings (Sammet & Kekelis, 2016).

Influencing factors at societal level

At the societal level, sociocultural norms influence girls' perceptions of self-efficacy, social roles, and aspirations for career and life. STEM fields are often considered a "chilly climate" for female development (Seymour & Hewitt, 1997) and the reasons are as follows: Firstly, men play a dominant role in these fields, which is detrimental to women's development. Secondly, women are often perceived to be less competent than men in STEM fields. Furthermore, the society has different role expectations for men and women, and almost every country's sociocultural traditions assume that women's family responsibilities should take precedence over their social responsibilities (Wang & Degol, 2017). Some studies have suggested that the absence of females in STEM fields is caused by sociocultural factors rather than biological factors (Yang & Shen, 2020). Gender stereotypes portrayed in the media are easily internalized by both children and adults, which will affect the way they view themselves and others. Media has an important influence on adolescents' perceptions of scientists, shaping the image of scientists. Similarly, media also promotes students' understanding of STEM careers, which in turn affects students' expectations for STEM careers (Tan et al., 2015). Girls' perceptions of self-competence and interest in STEM careers are strongly influenced by gender stereotypes in the media, especially the image of STEM professionals portrayed by the media has a great impact on adolescent girls, because they are in a critical period of career identity and choice (Steinke, 2017). In addition, Wyss et al. (2012) studies have shown that watching videos of STEM professionals could improve students' interest in STEM careers and promote students' STEM careers perceptions.

Gender differences in interest in STEM careers in Chinese culture

Due to the long-standing influence of Confucianism, traditional Chinese gender norms assume that men should dominate outside matters and women are more responsible for taking care of the family and completing household chores (Jia & Ma, 2015; Liu, 2014; Yi et al., 2010). There are significant gender differences in STEM fields in China. In universities, although the number of female university students in China is slightly higher than that of male students (Ma et al., 2016), learners in STEM majors are mainly composed of male students, accounting for more than 80%, while learners in social science-related majors are mainly composed of female students, and the number of females in these majors is approximately twice that of males. In primary, middle, and high schools, there are also gender differences in interest in STEM careers between boys and girls. For example, the proportion of boys and girls who want to pursue STEM-related careers in the future is 20.5% and 6.3%, respectively (Shi & Huang, 2018). In a study conducted on 7th grade students in Zhejiang Province, the percentages of boys and girls who would like or very much like to be a scientist in the future were 43.3% and 19.6%, respectively, and boys had significantly higher science self-efficacy and participation in extracurricular science activities than girls (Zhai & Zhu, 2015). Influenced by Confucianism, most parents believe that girls should be good wives and mothers (Jia & Ma, 2015), and having stable jobs that can take care of the family are the best choice for girls, such as being teachers and doctors (He et al., 2020). Confucian culture emphasizes respecting teachers and valuing teaching, so students are mostly passive receivers of knowledge in the classroom. In addition, under the influence of pressure such as from examinations, teachers pay more attention to teaching academic knowledge and neglect the development of students' attitudes, interests, and career planning (He et al., 2020). Research has shown that current science curricula and teaching in China have not improved students' attitudes towards STEM (Zhou et al., 2019).

Overall, although many studies have explored gender differences and their influencing factors in STEM fields, most of them are limited to western cultural contexts. In addition, few studies have simultaneously explored the structural relationships between various environmental factors, individual psychological factors and interest STEM careers among different gender groups, especially in the context of Chinese Confucian culture. Therefore, this study used a structural equation model (SEM) multi-group comparison approach to explore the influence mechanisms and gender differences in Chinese culture that affect interest in STEM careers, which can provide guidance for us to design gender-responsive interventions and learning experiences in the future. This work has important implications for addressing the underrepresentation of women in STEM fields not only in China, but also internationally, as there are significant similarities in the global education issues.

Theoretical framework and research questions

This study is guided by the Social Cognitive Career Theory (SCCT) that was developed by Lent et al. (1994). The SCCT is designed under the influence of Bandura's social cognitive theory. The theory integrates external influences such as social and economic factors and individual cognitive factors (e.g., self-efficacy, outcome expectations, and career goals) to dynamically reveal the process of career choice, and has become one of the most explanatory theories for career choice and has been widely used in STEM career-related research (Bahar & Adiguzel, 2016; Kang & Keinonen, 2017; Kier et al., 2014; Maiorca et al., 2021; Mohtar et al., 2019; Nugent et al., 2015; Wang et al., 2021).

According to SCCT, external environmental factors can further influence career choices by affecting individuals' self-efficacy and outcome expectation. In addition, outcome expectation could also be affected by self-efficacy (Lent et al., 1994). For example, when an individual believes that he/she has the ability to complete an activity, he/she will have positive expectations for the outcome of the activity, which will make him/her interested in the activity. As outcome expectation refers to an individual's perceptions of what would happen if he or she engaged in a certain career, it is often replaced by career perceptions (Mohtar et al., 2019; Wang et al., 2021). As such, self-efficacy and career perceptions play key mediating roles in the formation of career interest and are the basis for the development of career interest (Wang et al., 2021). Environmental factors refer to the physical and social conditions in which individuals live and guide their lives. Due to the intricacies of environmental factors, this study classified the environmental factors (EF) that influence high school students' interest in STEM careers (ISC) into four aspects: school education, informal education, social support, and media, according to the division of environmental factors in a relevant study (Mohtar et al., 2019). Related studies have shown that school education, informal education, social support, and media can affect students' STEM self-efficacy (SSE) or students' STEM careers perceptions (SCP), which in turn affects their interest in STEM career (Kang & Keinonen, 2017; Mohtar et al., 2019; Nugent et al., 2015; Tan et al., 2015; Wang et al., 2021).

Overall, based on SCCT, this study explored the gender differences in the effects of the environmental factors (formal learning experiences, informal learning experiences, social support, and media) on high school students' interest in STEM careers through the mediating roles of STEM self-efficacy and STEM careers perceptions. The constructed theoretical framework of high school students' interest in STEM careers is shown in Fig. 1. The three research questions (RQ) that guided this study are as follows:

Fig. 1
figure 1

Theoretical framework of the effect of environmental factors on interest in STEM careers

RQ1 Are there differences in interest in STEM careers between male and female students?

RQ2 Which environmental factor has the greatest effect on male and female students' interest in STEM careers respectively?

RQ3 Are there gender differences in the mediating roles of STEM self-efficacy and STEM careers perceptions between environmental factors and interest in STEM careers?

Research methodology

Participants

In China, basic education consists of 12 grades, among which grades 1–9 are compulsory (including grades 1–6 in primary school and grades 7–9 in middle school), and grades 10–12 are high school which is non-compulsory. At the end of high school education, students take the college entrance exam, which allows them to enter different universities based on their scores. Chinese high schools are divided into provincial demonstration high schools, municipal demonstration high schools and other high schools according to their comprehensive level in descending order. At present, STEM subjects (including mathematics, physics, chemistry and biology) are compulsory courses in Chinese high schools, and integrated STEM curriculum is not yet popular. Only a few schools carry out integrated STEM education in the form of school-based curriculum.

In this study, 10th grade students in Hunan Province, mainland China, were selected for the following reasons: Firstly, high school in China includes the 10th–12th grades, and in the context of the new Chinese college entrance examination reform, 10th grade students (who are usually 15 or 16 years old as Chinese education authorities require that students should be at least 6 years old to enter the first grade) need to choose their high school courses and subjects according to the college majors they are aiming for. By the 10th grade, the students would have already thought deeply about their career interests. Secondly, compared to younger students, high school students have more independent and stable thinking ability, and can assess the influence of various factors on their career interest relatively accurately. Finally, compared with other grades in high school, 10th grade students have less academic pressure and have enough time to answer the questionnaire carefully, thus ensuring the reliability and validity of the data.

Taking the differences in educational resources and levels in different regions, 10th grade students from 5 schools in Changsha, Changde, and Xiangxi Autonomous Prefecture in Hunan Province, China, were selected for the on-site questionnaire survey in this study. Changsha is the provincial capital of Hunan Province with a good economic and educational level, Changde is a medium non-capital city of Hunan Province with a medium economic and educational level, and Xiangxi is a mountainous area in the western part of Hunan Province with a low economic and educational level. In this study, students from 3, 1 and 1 schools (we selected 1Grade 10 class from each school) in the above three cities respectively were selected as participants. To protect the privacy of the participants, the questionnaires were anonymized after consent was obtained. The participants completed the questionnaires within a specified time (about 20 min) and the results were collected on-site after completion. In addition, a teacher in each class explained the instructions and requirements to the participants. Comrey and Lee (1992) suggested that a sample size greater than 1000 is optimal in the structural equation model, so a total of 1240 paper questionnaires were collected in this study and the data was input in SPSS23.0 software. After inspection, 108 questionnaires were excluded as they were incomplete. The final number of valid questionnaires was 1132, accounting for 91.29% of the total number of questionnaires collected. Among them, 549 were male students (48.5%) and 583 were female students (51.5%), and the number of students in provincial demonstration high schools, municipal demonstration high schools and other high schools were 382 (33.7%), 369 (32.6%), and 381 (33.7%), respectively.

Instrument

The questionnaire was divided into four parts: EF, SSE, SCP and ISC (Table 1). All items are measured using the 5-point Likert scale, from "1-strongly disagree" to "5-strongly agree". Among the constructs, the EF and SCP parts were adapted from the instrument developed by Mohtar et al. (2019). The SSE part was adapted from the instruments developed by Buday et al. (2012), Kier et al. (2014) and Nugent et al. (2015). The ISC part was adapted from the instrument developed by ASPIRES Project Group, King's College London, UK (Archer et al., 2013). In order to avoid the differences in Chinese and English expressions, the original English questionnaires were translated into a Chinese questionnaire by a professor with an overseas study experience. Each item of the Chinese questionnaire was subsequently discussed and revised by the group made up of two experts engaged in scientific education, one expert engaged in education statistics, and three high school teachers. Finally, the backtranslation was conducted by a graduate student majoring in English, and the back translated questionnaire and the original English questionnaire were compared, discussed and revised, so as to align it to the original text as much as possible and conform to the Chinese cultural background and expression (Brislin, 1986). After that, there were three demographic variables and 46 items in the original questionnaire (See Appendix Tables 8 and 9). Firstly, exploratory factor analysis (EFA) was performed on each construct and item ISC5 was deleted. Then some items were parceled (Landis et al., 2000), and the EFA was performed again on all constructs. The EFA result showed that the Kaiser–Meyer–Olkin (KMO) was 0.911, and the value of Bartlett's test of sphericity is 10,888 (df = 105, p < 0.001), meeting the judgement standards (KMO > 0.70, p < 0.05) proposed by Howard (2016). The item factor loading of each construct was between 0.525 and 0.891, indicating that the structure of the questionnaire was well divided. The final constructs of the questionnaire shown in Table 1. EF, SSE and SCP include four, four and three sub-constructs respectively, and the score of each sub-construct was calculated by the average score of the items it includes. For example, the four sub-constructs of SSE are science self-efficacy, technology self-efficacy, engineering self-efficacy and mathematics self-efficacy. Each sub-construct of SSE contained four items, and the score of each sub-construct was calculated by the average score of the four items.

Table 1 Constructs of the questionnaire

The reliability and validity of the questionnaire are shown in Table 2. First, the overall Cronbach's α reliability coefficient of the questionnaire was 0.952, and the Cronbach's α of each part EF, SSE, SCP, and ISC were 0.818, 0.833, 0.834, 0.929 respectively, indicating that the questionnaire had high internal consistency and high reliability. Second, confirmatory factor analysis (CFA) was used to test the validity. The results show that the standardized factor loading of all items were between 0.546 and 0.935, which reached the standard of 0.5 to 0.95, indicating that the items and constructs were effective. The composite reliability (CR) > 0.8 and the average variance extracted (AVE) > 0.5, indicating each construct had high convergent validity. The correlation coefficient between the constructs was less than the square root of AVE in each construct, indicating that the questionnaire had good discriminant validity. From the fitting index, RMSEA = 0.060 < 0.08, SRMR = 0.075 < 0.08, and all other goodness-of-fit indexes were greater than 0.9, indicating that the data fitted well. Finally, the absolute value of the skew of each item was less than 2 and the absolute value of the kurtosis was less than 7, indicating that the data conformed to normal distribution (Kline & Little, 2011).

Table 2 Reliability and validity of the questionnaire

Data analysis

SPSS23.0 and AMOS23.0 were used for data analysis. Firstly, the Harman single factor test (Podsakoff et al., 2003) was performed to ensure that there was no serious common method deviation in this study, and the intraclass correlation analysis was conducted to determine whether cluster data analysis and multi-level SEM analysis were necessary. In order to answer the three research questions in this study, the following methods were used: (1) For RQ1, the t-test was used to judge whether there were significant differences in the scores of male and female students in each construct, and the Cohen’s d was used to judge the effect size (Cohen, 1988). (2) For RQ2, the correlation analysis was used to analyze the correlation between variables, and regression analysis was used to compare the effect size of each sub-construction of EF on ISC. (3) For RQ3, a multi-group comparison of the structural equation model was carried out and the fitting degree of the model was judged by the goodness-of- fit indexes. The p-value was used to judge whether the direct effects were significant, and the size of the effects were analyzed by the standardized path coefficient(β). To test whether the indirect effects were significant, the 95% confidence interval of Bootstrap mediation test (Preacher & Hayes, 2004) included 0 was used. The critical ratios (CR) for differences between parameters were used to judge whether the difference between male and female students on each path was significant.

Results

Common method bias test

To avoid common method bias, Harman's one-factor test was used to test the common method bias in this study (Podsakoff et al., 2003). The results showed that there were four factors with eigenvalues greater than 1, and parallel analysis results also suggested that four factors can be extracted (Franklin et al., 1995; O'Connor, 2000), which explained 74.27% of the variation in total, and the explanation rate of the largest factor variance was 46.12%, which was less than the 50% judgment standard recommended by Hair et al. (2014), indicating that there was no serious common method bias in this study.

Intraclass correlation analysis

Considering that the participants in this study came from 5 schools, participants from the same school may lead to biased results due to similar education levels (Geiser, 2013). Therefore, an intraclass correlation analysis was conducted to determine whether the data were clustered by the intraclass correlation coefficients (ICCs) of all constructs (Bowen & Guo, 2011; Silva et al., 2019). The results showed that the clustering effects for all constructs were not significant (ICC of EF = 0.022, p = 0.760; ICC of SSE = 0.003, p = 0.451; ICC of SCP = 0.010, p = 618; ICC of ISC = 0.033, p = 0.139) and their design effects were all less than 2, indicating that most observations were independent (McNeish & Stapleton, 2016). In addition, this study focuses on analyzing gender differences in structural relationships among EF, SSE, SCP, and ISC. Based on the above analysis, cluster data analysis and multi-level SEM analysis was not necessary.

Descriptive statistics and independent sample T-test

The descriptive statistical results such as the mean and standard deviation of each main variable and the t-test results are shown in Table 3. On the whole, the mean of ISC is 3.16, which shows that students' ISC are not high. The mean of EF is 2.89, which is slightly lower than the neutral level (In the questionnaire of this study, 3 means neutral). The mean of formal LE (M = 3.25) and Media (M = 3.45) are slightly higher than the neutral level, while the mean of informal LE (M = 2.04) is at a lower level, and the mean of SS (M = 2.83) is slightly lower than the neutral level. The mean of SSE was 3.49, slightly higher than the neutral level. The mean of SCP is 4.03, which is at a relatively high level. From the results of the independent sample t-test, the scores of male students in all the constructs are significantly higher than those of female students, except for SCP where there was no significant gender difference. Cohen (1988) suggested that the critical values of small, medium and large effects were 0.2, 0.5 and 0.8, respectively. Further from the d-values, there were small effect size gender differences in Environmental Factors, Media, STEM Self-efficacy, Science Self-efficacy, Engineering Self-efficacy, Mathematics Self-efficacy, and Interest in STEM Careers.

Table 3 Descriptive statistics and t-test for all variables by gender

Correlation analysis

The correlation matrix for male and female is shown in Table 4, and all variables were significantly correlated. For male, EF (r = 0.647, p < 0.001), SSE (r = 0.414, p < 0.001), and SCP (r = 0.491, p < 0.001) were all significantly correlated with the male students' ISC, and the correlations sizes between EF sub-constructs and ISC in descending order were as follows: SS (r = 0.602, p < 0.001), Media (r = 0.566, p < 0.001), informal LE (r = 0.504, p < 0.001), and formal LE (r = 0.423, p < 0.001). For female, EF (r = 0.566, p < 0.001), SSE (r = 0.399, p < 0.001), SCP (r = 0.377, p < 0.001) were also all significantly correlated with the female students' ISC, and the correlations sizes between EF sub-constructs and ISC in descending order were as follows: Media (r = 0.553, p < 0.001), SS (r = 0.507, p < 0.001), informal LE (r = 0.381, p < 0.001), and formal LE (r = 0.338, p < 0.001). Overall, there are significant correlations between all variables for both male and female, so further structural equation model testing could be carried out. In addition, in order to further explore “Which environmental factor (EF) has the greatest effect on male and female students' ISC respectively?”, regression analysis was also needed.

Table 4 Correlation matrix for male and female

Regression analysis

The results of the regression analysis of EF and ISC are presented in Table 5. For males, the regression equation model passed the F-test (F = 110.242, p < 0.000) and the model fit was good (R2 = 0.448). The effect sizes of EF sub-constructs on the male students' ISC in descending order were as follows: SS (β = 0.329, p < 0.000), Media (β = 0.295, p < 0.000), and ILE (β = 0.143, p = 0.001), while the effect of FLE (β = 0.024, p > 0.05) on the male students' ISC was not significant. For females, the regression equation model passed the F-test (F = 86.515, p < 0.000) and the model fit was good (R2 = 0.375). The effect sizes of EF sub-constructs on the female students' ISC in descending order were as follows: Media (β = 0.387, p < 0.000), SS (β = 0.279, p < 0.000), while the effect of ILE (β = 0.043, p > 0.05) and FLE (β = 0.010, p > 0.05) on the female students' ISC was not significant. In short, the environmental factors that had the greatest effect on male and female students' ISC were SS and Media, respectively.

Table 5 Regression analysis of EF and ISC

Multi-group comparison of structural equation models

To further investigate the relationships among all variables and whether there were gender differences in the mediating roles of SSE and SCP between EF and ISC, this study used a structural equation modeling multi-group comparison to construct the following three models in AMOS 23.0 with gender as the grouping variable. First, the unconstrained model M1 was constructed (the parameters of each group were estimated freely); then, the model M2 was constructed on the basis of M1 (the measurement weights of each group were equal); finally, the model M3 was constructed on the basis of M2 (the measurement weights and path coefficients of each group were equal). The fit fitness and model comparison results of the three models are shown in Table 6. In the structural equation model, when the sample size is larger than 200, it is easy to cause the cardinality value of the model to be inflated, resulting in poor model fit (Bollen & Stine, 1993), so other goodness-of-fit indicators are recommended to evaluate the model (Bentler, 1990). Although the χ2/df of this model was slightly higher than the standard value of 5 due to the large sample size, the other fit indicators were at adequate levels (CFI > 0.9, TLI > 0.9, IFI > 0.9, NFI > 0.9, RMSEA < 0.08, SRMR < 0.08) (Hu & Bentler, 1999; Keith, 2014; Wu, 2009), which indicated that the constructed model better reflected the effect mechanism of ISC of high school students. The model comparison results showed that the differences between M1 and M2 were not significant (χ2 = 12.523, df = 11, p > 0.05), indicating that the measurement weights of each question item in the questionnaire were equal across groups in the male and female samples, further indicating that the questionnaire was appropriate for both male and female students; the differences between M2 and M3 were significant (χ2 = 15.252, df = 5, p < 0.05), indicating that there were gender differences in the path coefficients. The specific paths that have gender differences needed to be analyzed in the next step.

Table 6 Model fit indices for multi-group comparison

The structural equation models for the total sample, male students, and female students are shown in Fig. 2. The numbers on each arrow in turn represent the path coefficients for the total sample, male students, and female students. From the total sample, all five path coefficients were significant, and the model explained 39% of the variance in ISC of the total sample. For male students, all paths were significant except for "SSE → SCP", and the model explained 44% of the variance in ISC of male students. For female students, all paths were significant except for "EF → SCP", and the model explained 33% of the variance in ISC of female students.

Fig. 2
figure 2

Structural equation models for full sample, male and female

All direct paths coefficients and indirect paths coefficients for the total sample, male and female, and their significance are shown in Table 7. In this study, Critical Ratios (CR value) for differences between parameters was used to test whether there was a significant gender difference in each direct path coefficient. If the absolute CR > 1.96, the difference in direct path coefficients was significant. The results showed that there were significant gender differences in the two paths EF → SCP (CR = − 2.078) and SSE → SCP (CR = 1.987). Specifically, on the path EF → SCP, the path coefficient of male students (β = 0.413, p < 0.001) is significantly higher than that of female students (β = 0.013, p > 0.05); on the path SSE → SCP, the path coefficient of female students (β = 0.474, p < 0.001) is significantly higher than that of male students (β = 0.154, p > 0.05). In order to test whether there are gender differences in the indirect effects of EF on ISC, that is, whether there are gender differences in the mediating roles of SSE and SCP between EF and ISC, this study further used the Bootstrap mediating effect test (Preacher & Hayes, 2004) with repeated sampling 5000 times and calculating 95% confidence intervals. If the 95% confidence interval did not include 0, the mediating effect of the path was significant. The mediating test results are shown in Table 7. The three mediation paths of the total sample are all significant. For male, the two mediations path were significant except for EF → SSE → SCP → ISC (β = 0.052, 95% CI [− 0.039, 0.128] including 0), indicating that EF can affect the ISC of male students through the following two mediating paths (EF → SSE → ISC, EF → SCP → ISC). For female, the two mediating paths were significant except for EF → SCP → ISC (β = 0.004, 95% CI [− 0.077, 0.127] including 0), indicating that EF could affect the ISC of female students through the following two mediating paths (EF → SSE → ISC, EF → SSE → SCP → ISC). In summary, there are gender differences in the effect mechanisms of EF on ISC, that is, there are gender differences in the mediating role of SSE and SCP between EF and ISC.

Table 7 The direct and indirect effects test for full sample, male and female

Discussion

Based on SCCT, this study investigated gender differences in high school students' ISC and answered three research questions: RQ1 Are there differences in interest in STEM careers between male and female students? RQ2 Which environmental factor has the greatest effect on male and female students' interest in STEM careers respectively? RQ3 Are there gender differences in the mediating roles of STEM self-efficacy and STEM careers perceptions between environmental factors and interest in STEM careers? In response to these three questions, the specific discussion and conclusions of this study are as follows.

RQ1: Are there differences in interest in STEM careers between male and female students?

The results of descriptive statistics and independent sample t-tests showed that there were gender differences in high school students' ISC. Specifically, male students have significantly higher ISC than female students, which is consistent with the results of similar studies (Archer et al., 2012; Lv et al., 2022) and with the current global underrepresentation of females in STEM fields. In addition, male students scored higher than female students on all environmental factors (school education, informal education, social support, media) and STEM self-efficacy, which is consistent with previous findings (Archer et al., 2012; Du, 2020; Li & Xie, 2016; Lv et al., 2022; Shi & Huang, 2018), indicating that girls are treated more or less unfairly in terms of school education, informal education, social support, and media. The results also showed that both male and female students scored relatively high and did not differ significantly in STEM careers perceptions. As the STEM careers perceptions questionnaire in this study was adapted from Mohtar et al. (2019), which includes three sub-dimensions "career prospects," "skills needed," and "self-development", the findings suggest that there is no gender difference in the perception of the value of STEM careers. That is, female students also believe that STEM careers have better prospects and are beneficial for their long-term self-development. Since there is no gender difference in the students' perceptions of the value of STEM careers, why are many female students still reluctant to enter STEM fields in the future? This study suggests that the reason may be due to the influence of environmental factors and STEM self-efficacy, which was also confirmed by Archer et al. (2012), who found that although most girls rated science highly, they were still reluctant to choose science-related careers. This is because STEM fields were generally perceived as "smart" and "masculine" fields, and this stereotype can be transmitted explicitly or implicitly through parents, teachers, peers, and the media (Fulcher, 2011).

RQ2: Which environmental factor has the greatest effect on male and female students' interest in STEM careers respectively?

The results also showed that the environmental factors that had the greatest effect on male and female students' interest in STEM careers were different. Specifically, the environmental factor that had the greatest effect on male students' interest in STEM careers was social support, while that for female students was media. The reason may be that, under the deep-rooted influence of traditional Confucianism, Chinese society generally believes that men are responsible for external affairs and women are responsible for internal affairs, and stable, low-intensity, family-centered careers are more suitable for females (Liu, 2014). Studies have found that parents tend to underestimate girls' ability in STEM subjects and overestimate boys' ability in the field (Eccles & Wigfield, 2002; Gunderson et al., 2012), and some teachers believe that mathematics is a male field and have higher expectations for boys' mathematical ability (Gunderson et al., 2012; Li, 1999). Therefore, parents and teachers are more likely to provide additional support and expectations for boys in STEM fields. As such, social support largely affects boys' interest in STEM careers. Under the influence of the slogan "women can hold up half of the sky" in China's early socialist stage and the one-child policy implemented in China since the 1980s, parents hold the same educational expectations for girls and increase investment and support for their education (Tsui & Rich, 2002). However, gender stereotypes widely existing in social and cultural norms still largely affect girls' interest in STEM careers and identity through a variety of media (e.g., most scientists in the media and textbooks are male). For example, through an assessment of curriculum frameworks in 78 countries, UNESCO found gender bias in many math and science textbooks and learning materials (Benavot, 2016). Tan et al. (2015) have divided media into entertainment media (such as movies and TV entertainment programs) and science media (popular science magazines, science documentaries, etc.). Although some media, especially entertainment media, convey sociocultural norms and gender stereotypes, positive and scientific media still could improve students' perceptions and interest in STEM careers (Wyss et al., 2012), and are useful for designing interventions to increase students' interest in STEM careers. For both boys and girls, school education had the least effect on their interest in STEM careers. A similar conclusion was obtained from a study in China that school factors had no significant effect on Chinese students' intention to pursue science-related careers (Xue et al., 2015). The reason may be that under the influence of exam-oriented education in China, teacher pay more attention to the teaching of academic knowledge, while ignoring the cultivation of literacy, self-efficacy, and career planning education (Lv et al., 2022; Zhou et al., 2019). In addition, this study and related studies have found that informal education has a greater impact on high school students' STEM career interest than school education (Halim et al., 2017; Kitchen et al., 2018; Miller et al., 2018; Wang et al., 2021); therefore, educators should actively seek interventions in informal education (museum education, summer camps, etc.) to improve students' interest in STEM careers. The study also found that the effect of informal LE on female students was not significant, possibly because female students had less access to informal LE, for example, they do not have equal access to STEM-related activities at home and in other settings (Sammet & Kekelis, 2016). Studies have shown that compared with girls, boys are given more opportunities for informal activities (Bonnette et al., 2019) and receive more explanations from their parents during informal scientific activities (Crowley et al., 2001). Informal education could offer the possibility for girls to be exposed to female STEM role models, which can eliminate gender stereotypes of girls in STEM fields, increase their STEM self-efficacy and positive perceptions of STEM careers, and in turn increase their interest in STEM careers. Parents should provide more opportunities and support for girls to participate in informal STEM education, as parents generally act as gatekeepers in the choice of their children's participation in informal education, deciding whether to support their children's participation in a particular informal STEM activity.

RQ3: Are there gender differences in the mediating roles of STEM self-efficacy and STEM careers perceptions between environmental factors and interest in STEM careers?

From the results of a multi-group comparison of structural equation model, there were gender differences in the effect mechanism of high school students' interest in STEM careers. In terms of the explanatory rate of the model, the model constructed in this study explained 44% of the variance in male students' ISC and 33% of the variance in female students' ISC, respectively, indicating that the effect mechanism of in female students' ISC is more complex. In addition, in terms of effect paths, the direct path (SSE → SCP) was not significant in the male group, and the direct path (EF → SCP) was not significant in the female group. EF could affect male students' ISC through the following two mediated paths (EF → SSE → ISC; EF → SCP → ISE), while EF could affect female students' ISC through the following two mediated paths (EF → SSE → ISC; EF → SSE → SCP → ISE). In other words, male students' ISC could be mediated by SSE or SCP, while the two mediating paths of female both include SSE, illustrating the importance of SSE in the formation of girls' ISC. A large number of studies also showed that women with low STEM self-efficacy are less likely to pursue STEM careers (Britner, 2008; Hartung et al., 2005; Litzler et al., 2014). A study by Cimpian et al. (2020) found that a large number of low-performing male students were majoring in STEM majors, the proportion of boys choosing STEM majors is much higher than that of girls among lower-performing students, and girls who enter STEM fields generally have better academic performance and higher self-efficacy. This also confirmed the importance of STEM self-efficacy for girls to pursue STEM. Based on all the above analysis, in order to improve girls' interest in STEM careers, it is crucial to develop girls' STEM self-efficacy. According to Bandura (1986), the information sources of self-efficacy include four major aspects: performance accomplishments, vicarious learning, social persuasion, and emotional arousal. First, performance accomplishments refer to the successful experience of individuals participating in activities in a certain field, and therefore girls need to be provided with more access to STEM projects to gain more successful experiences in problem solving in a real-world context. Second, vicarious learning refers to the experience of individuals seeing people similar to themselves, or role models complete a certain task. Due to the underrepresentation of women in STEM fields, girls need to be provided with more female role models and mentors to guide them. Third, social persuasion refers to the affirmation or encouragement of an individual's successful performance in a certain field by those whom the individual trusts and is close to, especially when the individual is self-doubting. Therefore, parents and teachers should give more affirmation and encouragement to girls in STEM subjects and fields, especially to encourage girls to break out of the traditional boundaries and break the gender stereotypes in STEM fields. Fourth, emotional arousal refers to the negative or positive emotional states that individuals experience when they are engaged in a task, so teachers, parents, and communities should create more positive emotional experiences for girls in STEM instruction or activities. The learning environment such as participation in STEM extracurricular activities, early experiences with STEM and family involvement in STEM have influence on students’ decision to enroll in course with STEM as the major (Gossen & Ivey, 2023).

In addition, the mechanisms and potential causes of the mediating effects of SSE and SCP deserve further analysis. For both boys and girls, EF could positively influence SSE, and SSE could further influence ISC, which is consistent with SCCT and similar studies (Lent et al., 1994; Lv et al., 2022; Mohtar et al., 2019; Wang et al., 2021). The reason may be as follows: In Chinese high schools, STEM-related subjects (mathematics, physics, chemistry, biology, etc.) are all compulsory courses and included in the college entrance examination. Therefore, Chinese society, schools, parents, and students give support and efforts to STEM-related subjects, so there is no significant difference between boys and girls in the academic performance of STEM subjects. For example, the results of PISA2015 showed that the difference in math performance among Chinese adolescents was not significant (OECD, 2015). As both boys and girls were exposed to positive environmental factors in STEM subjects learning, these environmental factors would positively affect their SSE. SSE refers to individuals' judgment or confidence in their ability to engage in STEM jobs or complete STEM tasks, which would affect his/her interest in STEM careers positively (lv et al., 2022; Mohtar et al., 2019; Wang et al., 2021). However, SCP is a little different in groups of different genders. Specifically, for male students, EF could positively affect SCP, while for female students, the effect of EF on SCP was not significant. The reason may be that boys have more access to positive environmental factors related to STEM careers and activities than girls. For example, boys have more teacher support and parental support in STEM fields (Crowley et al., 2001; Lv et al., 2022), more access to informal education opportunities (Bonnette et al., 2019; Sammet & Kekelis, 2016), and the majority of scientists portrayed in the media are male (Steinke, 2017). The above positive environmental factors would promote the SCP of male students. However, for female students, the positive environmental factors of STEM careers they acquired were less, so the direct effect of EF on SCP was not significant. Although the path EF → SCP of female students was not significant, EF could still affect SCP through the mediating effect of SSE. The reason may be that the higher a girl's SSE is, the more positive and confident she is and can resist gender stereotypes in STEM fields, and then have a more positive perception of STEM careers. SCP could positively affect ISC for both male and female students, because when individuals have more positive perceptions of STEM careers and better outcome expectations, they are more interested in STEM careers (Mohtar et al., 2019; Wang et al., 2021).

Limitation and future research

The following limitations in this study still exist. Firstly, although the sample size of this study far exceeds the basic requirements of data analysis, the sample does not cover all provinces and cities in China due to the limitation of time, resources and labor. Generally speaking, Hunan Province belongs to a province with a moderate level of economic development in China, so the generalization of the conclusion of this study needs to be further verified, and further verification, improvement and generalization should be carried out in future studies in the provinces and cities with developed economic levels as well as those with more backward economic levels. Secondly, individual career interest will not be unchanged, and students' interest in STEM careers will also fluctuate from primary school to middle school and then to high school. Therefore, future studies can conduct long-term follow-up studies to find the points where girls' interest in STEM careers fluctuate more, and then select the corresponding age or grade to carry out targeted STEM career interest cultivation. Thirdly, a curriculum and teaching framework aimed at cultivating girls' interest in STEM careers can be designed and implemented in the future. Finally, based on the core constructs of Social Cognitive Career Theory (such as self-efficacy, outcome expectation, career interest, etc.) and the instruments of outcome expectation in related studies (Kier et al., 2014; Mohtar et al., 2019), this study did not include self-identity in the questionnaire design. However, self-identity is a very important factor contributing to an individual's interest in STEM, so future research on gender differences in STEM should include the self-identity construct in the questionnaire or include it in the outcome expectation construct.

Conclusions

Based on the Social Cognitive Career Theory, this study explored the gender differences in the effects of the environmental factors (school education, informal education, social support, and media) on high school students' interest in STEM careers through the mediating roles of STEM self-efficacy and STEM careers perceptions. The results of t-test, regression analysis, and structural equation model multi-group comparison showed that: Firstly, male students' interest in STEM careers was significantly higher than that of female students. Secondly, the environmental factor that had the greatest effect on male and female students' interest in STEM careers were social support and media, respectively. Thirdly, environmental factors could affect male students' interest in STEM careers through the mediating roles of STEM self-efficacy and STEM career perception, while environmental factors could affect female students' interest in STEM careers through the mediating role of STEM self-efficacy. Finally, the mediating mechanisms of STEM self-efficacy and STEM career perception between environmental factors and interest in STEM careers and the importance of STEM self-efficacy for female students were discussed.

Although this study was conducted at the high school education level in China, there are significant similarities at the global education level, particularly the underrepresentation of females in STEM fields and the low interest in STEM careers among girls. The findings of this study could provide some reference for teachers and policy makers in the STEM field, especially for researchers who want to conduct research on STEM career interest intervention for girls.

Availability of data and materials

The datasets used during the current study are not publicly available due to the request made in the consent forms issued to participants.

Abbreviations

STEM:

Science, Technology, Engineering, and Mathematics

EF:

Environmental factors

LE:

Learning experiences

SS:

Social support

SSE:

STEM self-efficacy

SCP:

STEM careers perceptions

ISC:

Interest in STEM careers

RQ:

Research questions

SCCT:

Social Cognitive Career Theory

EFA:

Exploratory factor analysis

CFA:

Confirmatory factor analysis

KMO:

Kaiser–Meyer–Olkin

CFI:

Comparative fit index

TLI:

Tucker–Lewis index

IFI:

Incremental fit index

NFI:

Normed fit index

RMSEA:

Root mean square error of approximation

SRMR:

Standardized root mean square residual

95% bootstrap CI:

95% Bootstrap confidence interval

C.R.:

Critical ratios for differences between parameters

PISA:

Programme for International Student Assessment

OECD:

Organization for Economic Cooperation and Development

SEM:

Structural equation model

References

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Acknowledgements

The authors sincerely express gratitude to the teachers and students for their assistance in the survey process.

Funding

This research was supported by the National Natural Science Foundation of China (32171065) and National Social Science Foundation's Education Youth Project (CHA220291).

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This research was completed by a team of researchers. NW designed the research, conducted the investigation, analyzed the data and results, and wrote the manuscript. AT supervised the research design, proofread and revised the manuscript. XZ and KL contributed to the data analysis. FZ and JX contributed to the data collection. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Aik-Ling Tan.

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Appendix

Appendix

See Tables 8 and 9.

Table 8 Overview of items used in the questionnaire in English
Table 9 Overview of items used in the questionnaire in Chinese

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Wang, N., Tan, AL., Zhou, X. et al. Gender differences in high school students’ interest in STEM careers: a multi-group comparison based on structural equation model. IJ STEM Ed 10, 59 (2023). https://doi.org/10.1186/s40594-023-00443-6

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