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Article

Impacts of Gender, Engineering, and Role Models on High School Students’ Overall STEM Interest and Perceptions of Engineering

by
Nigar Altindis
*,
Christopher Adah Ocheni
,
Yan Tong
and
Kayode Obafemi
College of Education, The University of Alabama, Tuscaloosa, AL 35487, USA
*
Author to whom correspondence should be addressed.
Educ. Sci. 2025, 15(9), 1217; https://doi.org/10.3390/educsci15091217
Submission received: 28 June 2025 / Revised: 8 September 2025 / Accepted: 11 September 2025 / Published: 14 September 2025
(This article belongs to the Special Issue Mathematics in Engineering Education)
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Abstract

This study explores the impact of gender, engineering experiences, and role models on high school students’ overall STEM interests and perceptions of engineering. A survey with Likert-scale and open-ended questions was given to 96 high school students (51 female, 45 male; 83% African American, 8% white, and 8% other races) in grades 9–12. We developed a scale measuring STEM interest, mathematical problem-solving confidence, misconceptions about engineering, perceptions of STEM, and self-efficacy. The STEM Dimension Survey (SDS) has a strong Cronbach alpha (= 0.96) and inter-coder agreement (Cohen’s Kappa = 0.77). ANOVA analysis on open response categories and the survey indicates that gender had a relatively small but statistically significant effect on STEM interest, with female students reporting slightly lower interest levels than male students. Students with prior engineering-related experiences demonstrated significantly higher STEM interest and more positive perceptions of engineering, but did not differ in self-efficacy or misconceptions. Notably, 63% of students reported no role model in STEM, and these students consistently reported lower interest, confidence, and self-efficacy. In contrast, those who identified role models reported significantly more positive STEM outcomes across all dimensions. The findings highlight the importance of recognizing students’ lived experiences and their definitions of engineering rather than relying solely on adult-defined narratives. Engineering-related experiences and role model presence are strongly linked to students’ interest and confidence in STEM.

1. Introduction

Despite a growing emphasis on increasing STEM engagement among youth, many high school students still have limited exposure to engineering (National Science Board, 2024; Lane & Id-Deen, 2020). Research highlights the importance of cultivating positive STEM perceptions to foster long-term participation, especially among underrepresented groups (Wang & Degol, 2017). Yet, STEM opportunities for students often fall short. In many schools, engineering-focused clubs are designed to expand students’ experiences with engineering. However, these clubs often have limited capacity, serving only 10 to 15 students in the entire school, and they frequently focus on narrow activities such as building cars or pre-designed robots (Nugent et al., 2016). As a result, most high school students conceptualize engineering as mechanics, labor, and technician (Wu & Dalal, 2024).
These limited conceptualizations and experiences may unintentionally exclude students who do not see themselves reflected in these traditional engineering projects. Girls, in particular, may be less likely to participate when engineering is framed solely around mechanical or competitive tasks (Brickhouse et al., 2000; Ong et al., 2011). Such approaches rarely offer space for exploration, creativity, or problem-solving (Tan et al., 2013). Consequently, students who might otherwise develop an interest in engineering are left out, not due to lack of ability, but due to lack of opportunities.
Expanding the definition and scope of engineering experiences can help address these participation gaps (Carlone et al., 2014; Barton et al., 2013). When engineering is presented through culturally relevant, identity-affirming, and meaningful activities, it not only boosts students’ confidence and interest but also cultivates a sense of belonging, especially among students marginalized by gender, race, or limited prior exposure to engineering (Aikenhead & Michell, 2011; Archer et al., 2010). This study will expand the body of work by examining how gender, engineering experiences, and role models affect high school students’ engagement in STEM.
Given the persistent gender disparities in STEM (Charlesworth & Banaji, 2019; Wang & Degol, 2017), limited exposure to engineering in K–12 education (Sneider & Ravel, 2021), and the lack of accessible, relatable role models (Gladstone & Cimpian, 2021), this study examines how students’ gender, prior engineering experiences, and the presence or absence of role models influence their engagement with STEM. It also validates the STEM Dimensions Survey (SDS), which measures five constructs: STEM interest, mathematical problem-solving confidence, misconceptions about engineering, perceptions of STEM, and self-efficacy. By linking survey findings to students’ gender, experiences, and role model exposure, this study provides new insights into broadening participation in engineering.

2. Background Literature

2.1. Gender and STEM Engagement

Gender stereotypes—preconceived beliefs about the traits and roles suitable for each gender—play a role in shaping students’ engagement with STEM fields. These stereotypes often portray engineering as a male-dominated domain, reinforcing ideas about who “belongs” (Boucher et al., 2017). Such portrayals reduce girls’ interest and self-efficacy, discouraging them from seeing themselves as future engineers (Cundiff et al., 2013; Schuster & Martiny, 2017). At the secondary level, mathematics and physics are frequently associated with masculine traits, further cementing the notion that these subjects are more appropriate for boys (Makarova et al., 2019). Classroom dynamics also reflect gendered expectations: masculine traits are often associated with increased in-class participation, while feminine traits are more strongly linked to out-of-class student–professor interactions (Leraas et al., 2018).
Although girls perform as well as, or better than, boys in school-based math and science assessments, gender disparities in STEM engagement and career trajectories remain persistent (Boucher et al., 2017; Wang & Degol, 2017). Girls continue to be underrepresented in postsecondary STEM programs, with challenges in retention and persistence particularly evident in engineering education in the United States (Lichtenstein et al., 2014). These differences are not rooted in ability but in confidence, interest, and identity formation shaped by cultural norms that frame STEM as a male domain (Cheryan et al., 2017; Cvencek et al., 2011).
These patterns are further reflected in students’ academic and career decision-making. For Example, Naukkarinen and Bairoh (2020) found that Finnish girls applying to STEM programs rarely viewed engineering and science/math as interchangeable, underscoring the rigidity of gendered preferences. Similarly, Merayo and Ayuso (2023) reported that only 6.5% of Spanish girls expressed interest in engineering compared to 25.7% of boys. Together, these findings illustrate the persistent gender divide in STEM aspirations and highlight the importance of examining how high school students’ perceptions of STEM—shaped by stereotypes, experiences, and opportunities—affect their engagement, a focus of the present study.

2.2. Students’ Engineering Experiences in K-12 Schools

K–12 engineering education remains less developed than other STEM fields (Katehi et al., 2009). Opportunities often take the form of short-term, out-of-school interventions with small sample sizes and unclear objectives (Prieto-Rodriguez et al., 2020; Moore et al., 2014). Longer-term interventions, such as robotics clubs or maker spaces, tend to emphasize mechanical construction or competitive robotics activities that may appeal to only a limited group of students (Capobianco et al., 2011). These narrow experiences can reinforce stereotypes about engineering and alienate students who do not identify with building cars or coding robots (Cheryan et al., 2015).
Participation in these programs is especially limited among Black, Indigenous, and Latinx students, as well as girls, particularly when the curriculum lacks cultural relevance or connections to community-based problem-solving (Barton et al., 2013; Tan et al., 2013; Lane & Id-Deen, 2020). Broadening engineering activities to emphasize creative, collaborative, and socially relevant projects, with a focus on real-world connections and teamwork, has been shown to foster more positive associations with the field among a wider range of students (Cunningham & Kelly, 2022). To be effective, such programs must be designed around “the problems” relevant to students’ lives and be accessible to all students (Singh & Kittur, 2024). This highlights a need for research that centers students’ own definitions and experiences of engineering, rather than relying on adult intuition or assumptions.

2.3. Role Models and Their Impacts in STEM

Role models—whether they are teachers, peers, external figures, or imagined future selves—play a critical role in shaping students’ interest, motivation, and identity development in STEM (Lockwood, 2006; Zirkel, 2002; Herrmann et al., 2016). Students are more likely to envision themselves in STEM careers when they encounter individuals who reflect their identities and lived experiences (Herrmann et al., 2016), offering emotional pathways to imagine themselves as STEM learners and professionals (Herrmann et al., 2016). For underrepresented students, such as girls and students of color, role models foster belonging and make STEM trajectories more tangible (Makarova et al., 2019; Merayo & Ayuso, 2023; Msambwa et al., 2024).
Structured exposure to women in engineering has been shown to boost student motivation and broaden career aspirations (González-Pérez et al., 2020). These effects are especially strong when role models reflect students’ gender or cultural backgrounds, shaping STEM identity and encouraging persistence (Steinke, 2017). Female representation also disrupts stereotypes, challenges the view of STEM as a male-dominated field (Cheryan et al., 2009; Faulkner, 2015). Such shifts in social norms enhance students’ belief in their own STEM potential (Dasgupta & Stout, 2014) and provide tangible evidence that success is attainable (Vogt et al., 2007). In a large-scale experiment, Breda et al. (2023) found that even brief exposure to female scientists significantly increased high-achieving girls’ enrollment in selective, male-dominated STEM fields, particularly when role models emphasized opportunity rather than underrepresentation. This finding aligns with a growing body of research demonstrating that exposure to female STEM professionals enhances girls’ self-efficacy and interest in STEM while countering misconceptions about engineering and gender roles (Cheryan et al., 2009; Dasgupta & Stout, 2014; Faulkner, 2015; González-Pérez et al., 2020; Msambwa et al., 2024; Naukkarinen & Bairoh, 2020; Plant et al., 2009; Stout et al., 2011).
Conversely, the absence of relatable role models exacerbates feelings of isolation and diminishes self-efficacy, particularly for girls of color (Hernández-Matías et al., 2023). In male-dominated STEM environments, many struggle to reconcile gender identity with societal expectations, leading to lower career aspirations (Prieto-Rodriguez et al., 2020; Dasgupta & Stout, 2014). Without visible role models, girls may internalize gender stereotypes, develop reduced self-confidence (Zeldin & Pajares, 2000), and enter a cycle in which low self-efficacy discourages STEM participation, reinforcing underrepresentation (Seymour & Hewitt, 1997). As Msambwa et al. (2024) note, challenges in the personal domain include poor self-concept, negative attitudes, low motivation, and limited career planning.

3. Purpose of the Study

Persistent gender disparities in STEM (Charlesworth & Banaji, 2019; Wang & Degol, 2017), limited early exposure to engineering (Aguirre-Muñoz & Pantoya, 2016), and the lack of accessible, relatable role models (Gladstone & Cimpian, 2021) continue to shape students’ engagement in STEM. To address these challenges, this study have two aims: (1) validates and assesses the reliability of the STEM Dimensions Survey (SDS), which measures five constructs: STEM interest, mathematical problem-solving confidence, misconceptions about engineering, perceptions of STEM, and self-efficacy; and (2) examine how gender, self-reported engineering experiences, and exposure to role models influence students’ responses across these constructs.
This work is guided by the following research questions:
  • RQ1: What is the construct validity, item fit, and reliability of the SDS?
  • RQ2: To what extent does gender influence students’ interest in STEM, mathematical problem-solving confidence, misconceptions of engineering, perceptions of STEM, and self-efficacy in STEM?
  • RQ3: To what extent do high school students’ self-reported engineering experiences relate to their interest in STEM, mathematical problem-solving confidence, misconceptions of engineering, perceptions of STEM, and self-efficacy in STEM?
  • RQ4: To what extent do different types of role models influence students’ attitudes and beliefs related to STEM, including interest, confidence, perception, and self-efficacy?

4. Methods

4.1. Context of the Study and Participants

The study employed a mixed-methods approach (Creswell & Creswell, 2005), developing SDS items and administering them to a high school with 96 participants (51 female, 45 male) who answered six open-ended questions. The participants were in grades nine to twelve in mathematics classrooms, including 80 African American students, eight White students, and eight students from other racial backgrounds (Table 1). The survey was conducted during the fall 2024 semester via Qualtrics by mathematics teachers. Participants were selected from high school students in the Southern U.S.

4.2. Measures

We developed 55 Likert-scale survey items using a five-point scale ranging from “strongly disagree” to “strongly agree.” In addition to these items, the survey included demographic questions (e.g., grade level, school, gender) and short, open-response items.
We shared the items with three experts to establish content validity (Haynes et al., 1995; Rubio et al., 2003). These experts included an Electrical Engineer, a Computer Science Engineer, and an expert in Educational Measurement. Each expert provided feedback on the 55 items, and based on this feedback, the items were revised to better align with the intended constructs and content domains. However, after piloting and reviewing the performance of these items, we eliminated 4 items because they were factorially impure and had low item-total correlation values (Aday & Cornelius, 2006). An indication that the 4 items do not contribute adequately to the overall indices of the scale.
After finalizing the five factors (articulated in the Results for Reliability and Validity), we focused on analyzing open-response questions, which broadly invited students to share their perceptions of engineering, experiences with robotics, sources of inspiration, perceived challenges, and potential community impact. From this full set, we focused on Questions 3 and 6 because they were the most relevant to our research questions (RQ2-4). We used constant comparison coding (Glaser & Strauss, 2017; Saldaña, 2021) to inductively identify themes across student responses. In this paper, we focus specifically on two open-response questions: “What is the most exciting thing you have done related to robotics or engineering?” and “Who has inspired you to explore robotics or engineering? How have they influenced you?”

4.3. Data Analysis

4.3.1. Quantitative Data Analysis: Likert-Type Items

We used several methods to evaluate the quality of the survey scale. First, we employed exploratory factor analysis (EFA) to assess the construct validity of the items, to check whether the items grouped together in ways that provided evidence for the construct validity of the scale. EFA is particularly useful when the goal is to identify the underlying factors that explain relationships among items without assuming a predefined structure (Watkins, 2018). This analysis identified five distinct factors: Interest in STEM (e.g., “I find robotics exciting”), Mathematical Problem-solving Confidence (e.g., “I can analyze and break down a mathematical problem into smaller steps to understand it better”), Misconceptions about engineering (e.g., “Engineering is a man’s thing because it’s too demanding”), Perception of STEM (e.g., “Engineering can make a positive difference in the community”), and Self-Efficacy (e.g., “I am confident in my ability to build a robot”). Next, we calculated Cronbach’s alpha to assess the reliability of the scale. Finally, we applied the Partial Credit Model (PCM) under the Rasch model framework to evaluate item fit (Lopez-Pina et al., 2016). All analyses are performed using R (R Core Team, 2023), utilizing the extended Rasch model (eRM) package (Mair & Hatzinger, 2007).

4.3.2. Qualitative Analysis: Open-Response Items

To analyze the open-ended questions, we employed Glaser and Strauss’s (2017) constant comparative method. Three researchers (Authors 1, 3, and 4) independently coded all responses and then compared their coding to refine categories. For the first question, summary tables were created to illustrate categories with sample responses, which the team collaboratively reviewed. For the remaining questions, two researchers (Authors 3 and 4) applied the shared codebook, while Author 1 joined to resolve disagreements and ensure shared interpretations.
After finalizing the codebook, Authors 3 and 4 recoded all responses, and we calculated inter-coder reliability using Cohen’s Kappa. Values across the six questions ranged from 0.66 to 0.94, with an average of 0.77—indicating moderate agreement (McHugh, 2012; Warrens, 2015). To improve clarity and reliability, the team also held several follow-up meetings to refine the codes further.

4.3.3. Integrating Quantitative and Qualitative Analyses

Once validity, reliability, and coding consistency were confirmed, we calculated average scores for each factor and examined how they related to selected open-response questions. Factor scores were also checked for consistency, and the results supported the use of average scores in subsequent analyses.
We used one-way ANOVA as the appropriate statistical method for addressing our research questions (Blanca Mena et al., 2017). Shapiro–Wilk tests indicated violations of normality for Interest in STEM (p = 0.0107), Mathematical Problem-Solving Confidence (p = 0.0019), Perception of STEM (p = 6.57e-06), and Self-Efficacy in STEM (p = 0.0173), while Misconceptions of Engineering met the normality assumption (p = 0.4213). Levene’s test indicated that homogeneity of variance was satisfied for Interest in STEM (p = 0.173), Mathematical Problem-Solving Confidence (p = 0.386), Misconceptions of Engineering (p = 0.560), and Self-Efficacy in STEM (p = 0.420), but was violated for Perception of STEM (p = 0.0004). While ANOVA is generally robust to moderate violations of normality when sample sizes are large our group sizes were not perfectly equal, which could increase the impact of assumption violations. To address this, we used Welch’s ANOVA for variables that violated both normality and homogeneity assumptions, such as Perception of STEM, while standard ANOVA was used for the remaining variables. Additionally, non-parametric Kruskal–Wallis tests were conducted as a sensitivity check, and these produced results consistent with the ANOVA (Siegel & Castellan, 1988).

5. Results

5.1. Reliability and Validity

The construct validity of the SDS Scale was established through EFA, which identified a five-factor structure: Interest in STEM, Mathematical Reasoning, Misconceptions of STEM, Perception of STEM, and Self-Efficacy in STEM. These factors collectively accounted for 49% of the total variance, with individual contributions ranging from 4.3% to 19.5%. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was 0.77, and Bartlett’s test of sphericity was significant (χ2 = 4589.52, p < 0.00), confirming the suitability of the data for factor analysis. Items with factor loadings of 0.40 or higher were retained, demonstrating factorial purity and supporting the scale’s construct validity. These five factors were defined based on both theoretical considerations and prior research in engineering and STEM Education. Specifically, constructs such as interest in STEM and self-efficacy (Cundiff et al., 2013; Schuster & Martiny, 2017), mathematical problem solving and confidence (Tan et al., 2013), misconception of STEM and perceptions of STEM (Wang & Degol, 2017) were all identified both from prior work and from the way our items clustered during factor analysis. Item content was carefully examined to ensure alignment between theory and the emerging statistical structure, which informed the final factor labels.
The item fit indices of the SDS were evaluated using the PCM within Item Response Theory. The results indicated strong model-data fit, with Infit and Outfit Mean Square Error (MSE) values close to the ideal benchmark of 1.00 for both items and persons. Specifically, the mean Infit MSE for items was 0.98 (SD = 0.2), and the mean Outfit MSE was 1.01 (SD = 0.29). The standardized residuals for all items fell within the acceptable range of ±2, confirming that responses aligned with model expectations. Additionally, the item difficulty parameters ranged from −1.01 (most difficult, Item 41) to 0.87 (easiest, Item 33), with well-distinguished threshold parameters for response categories, further validating the scale’s precision.
The reliability of the SDS was assessed using Cronbach’s alpha, which yielded an overall coefficient of 0.96, indicating excellent internal consistency. The subscales also demonstrated strong reliability, with coefficients of 0.96 for Interest in STEM, 0.93 for Mathematical Reasoning, 0.90 for Misconceptions in STEM, 0.81 for Perception of STEM, and 0.74 for Self-Efficacy in STEM. The item-total correlations ranged from 0.24 to 0.77, confirming that all items contributed meaningfully to their respective factors.

5.2. Response to RQ2: Gender’s Impact on Students’ STEM Interests, Confidence, Misconceptions, Perceptions, and Self-Efficacy

In response to RQ2, we examined the extent to which gender influences students’ interest in STEM, mathematical problem-solving confidence, misconceptions of engineering, perceptions of STEM, and self-efficacy in STEM. Linear regression assumptions (linearity, independence, homoscedasticity, and normality of residuals) were tested and met, ensuring the validity of the analysis (Osborne & Waters, 2002).
A statistically significant effect of gender was found on interest in STEM (β = −0.3699, p = 0.0459), with female participants reporting lower levels of interest compared to male participants. However, the small effect size (R2 = 0.0417) indicates that gender accounts for only a limited portion of the variance in STEM interest, suggesting that other factors likely contribute to these differences.
In contrast, no significant differences were observed in mathematical problem-solving confidence, with the p-value for gender at 0.366 (p > 0.05), indicating no statistical significance. Similarly, misconceptions about engineering showed no significant gender differences (p = 0.169), with a minimal coefficient for females (−0.2322) and a very small effect size (R2 = 0.01998). Regarding perceptions of STEM, the analysis revealed no significant gender differences (β = −0.1197, p = 0.458), with a very low R2 value (0.0059), indicating that gender has minimal influence on STEM perceptions. Lastly, the analysis showed no significant gender differences in self-efficacy in STEM (p = 0.914), and the coefficient for females (0.01856) was minimal. The R2 value for self-efficacy (0.0001248) further suggests that gender has an almost negligible effect on self-efficacy in STEM.

5.3. Response to RQ3: Students Reported Engineering Experiences and STEM Engagement

To examine how high school students’ self-reported engineering experiences relate to the STEM dimension survey factors, we analyzed responses to the open-ended prompt, “What is the most exciting thing you have done related to robotics or engineering?” This analysis revealed several categories, and we examined how they are distributed by gender (Figure 1).
When collapsed into three categories, the majority of students reported experiences related to Building and Creating (n = 52, 54.2%), which included building, coding, technology-driven projects, and robotics team participation. A smaller subset reported ‘I Don’t Know’ (n = 9, 9.4%), while the remaining responses were grouped under ‘Others’ (n = 35, 36.5%).
Gender patterns show that Building and Creating was reported by 24.0% of females (n = 23) and 30.2% of males (n = 29). I Don’t Know responses were given by 4.2% of females (n = 4) and 5.2% of males (n = 5). Others accounted for 24.0% of females (n = 23) and 12.5% of males (n = 12). The Other category consisted of vague or non-substantive responses such as “nothing,” “math,” “a class in middle school,” or “look at it.” Because these responses did not provide interpretable insight into students’ perspectives on engineering, they were grouped under the Other category for analysis.
We then performed ANOVA and post-hoc tests to see if students’ engagement with STEM constructs varied across these experience-based categories. Gender was not included in these analyses because the research question centered on engineering experiences, and preliminary checks indicated minimal gender variation that would not affect group comparisons.

5.3.1. Engineering Experiences and STEM Interests

We found a significant effect, F(2, 84) = 8.33, p < 0.001. Post-hoc Tukey tests indicated that students in the Others group scored significantly lower in interest in STEM compared to the Building and Creating group (mean difference = −0.81, p < 0.001). However, no significant difference was found between the IDK group and the Building and Creating group (mean difference = −0.38, p = 0.42), or between the IDK group and the Others group (mean difference = −0.44, p = 0.37).

5.3.2. Engineering Experiences and Mathematical Problem-Solving Confidence

Results indicated a marginal effect, F(2, 84) = 2.58, p = 0.082. Tukey’s post-hoc analysis did not show significant differences among any of the groups. No post-hoc comparisons reached significance, though the largest difference—between Others and Building and Creating (mean difference = −0.50, p = 0.066)—approached the threshold.

5.3.3. Engineering Experiences and Misconceptions of Engineering

There was no significant effect, F(2, 84) = 2.09, p = 0.13. Tukey’s post-hoc analysis confirmed that there were no significant pairwise differences among the groups. Although group means varied, these differences were not statistically significant. The IDK group had the highest misconceptions score (M = 3.24, SD = 0.57), followed by the Building and Creating (M = 2.69, SD = 0.78) and Others groups (M = 2.68, SD = 0.82).

5.3.4. Engineering Experiences and Perception of Engineering

A significant effect was found, F(2, 84) = 8.12, p < 0.001. The Others group reported significantly lower perceptions of STEM than Building and Creating (mean difference = −0.68, p = 0.0006). Differences involving the IDK group were not significant.

5.3.5. Engineering Experiences and Self-Efficacy in STEM

No significant differences were found, F(2, 84) = 1.18, p = 0.31, and post-hoc tests confirmed no reliable group effects. This suggests that students’ self-efficacy in STEM was similar across the three groups, indicating that engineering experiences may not have a strong influence on their perceived self-efficacy in STEM fields.

5.3.6. Summary

Table 2 highlights key findings. First, significant differences in interest in STEM were observed, with the Others group scoring notably lower than the Building and Creating group. In contrast, no significant differences were found in mathematical problem-solving confidence across the groups; however, the Others group tended to report slightly lower confidence compared to the Building and Creating group. Regarding misconceptions about engineering, no significant differences were observed, although the IDK group exhibited the highest level of misconceptions. In terms of perceptions of STEM, significant differences were again evident, with the Others group demonstrating a significantly lower perception of engineering compared to the Building and Creating group. Lastly, no significant differences in self-efficacy in STEM were noted across the groups, indicating that engineering experiences may not strongly influence students’ perceived self-efficacy in STEM fields. These findings highlight the importance of cultivating positive STEM experiences and perceptions to support more equitable engagement in engineering and STEM learning.

5.4. Response to RQ4: High School Students’ Self-Reported Role Models and Absence of Role Models

To examine how role models, or the absence thereof, influence students’ engagement with STEM, we analyzed responses to the open-ended prompt: “Who has inspired you to explore robotics or engineering? How have they influenced you?” Role models were categorized as External Role Models (e.g., teachers, peers, or family members), “Myself,” or “Nobody” (Figure 2). We then conducted a series of ANOVA tests and post-hoc comparisons to determine whether students’ engagement with key constructs differed based on the presence or absence of a role model. Levene’s tests were non-significant for all analyses, supporting the assumption of homogeneity of variances.
The majority of students (63%) reported that no one had inspired them to explore robotics or engineering. This indicates a lack of role models or influential figures among this group of students.
30% of the students identified external role models, including teachers, friends, parents, and other influential figures. For instance, one student shared, “My teacher inspired me to explore robotics by showing how fun and creative it can be”. Some students were influenced by family members working in engineering or related fields. One student noted, “My dad, by talking about it,” while another mentioned, “My cousin, she became an engineer and helped NASA.” However, in this population, the absence of role models is reported by 63% of the students, which is twice as many as the 30% of students who reported having a role model. A small group of students (7%) cited themselves as their own inspiration, reflecting a self-driven interest in robotics and engineering. One such student remarked, “I inspired myself to explore engineering.”

5.4.1. Role Models and Interest in STEM

There was a significant effect of role model category on interest in STEM (F = 9.99, p < 0.001). Post-hoc analysis using Tukey’s HSD test showed a significant difference between students who identified an external role model (External Role Models) and those who reported having no role model (Nobody) (p < 0.001). However, no significant differences were found among the other groups. These suggest that having an external role model significantly enhances students’ interest in STEM compared to those who report having no role model.

5.4.2. Role Models and Math Problem-Solving Confidence

Role model category significantly affected students’ mathematical problem-solving confidence, F(2, 70) = 4.65, p = 0.012. Students who reported having a role model displayed significantly higher confidence in mathematical problem-solving compared to those who reported having no role model (Nobody group) (p = 0.016) and those who identified themselves as their own role model (Myself group) (p = 0.048).

5.4.3. Role Models and Misconceptions of Engineering

No significant effect of role model category on engineering misconceptions was observed, F(2, 70) = 2.68, p = 0.07. However, there was a marginal trend indicating that students without any role model (“Nobody” group) may have more misconceptions compared to those with an external role model, though this difference did not reach statistical significance.

5.4.4. Role Model and Perceptions of STEM

There is a significant effect of role model category on STEM perception, F(2, 70) = 4.12, p = 0.020. Students with external role models reported more positive perceptions than those without role models (p = 0.047). The difference between the external role model and self-role model groups approached significance (p = 0.062).

5.4.5. Role Model and Self-Efficacy in STEM

Finally, the role model category had a significant effect on self-efficacy in STEM, F(2, 70) = 4.04, p = 0.022. Students with external role models reported significantly greater self-efficacy than those without role models (p = 0.017). No significant difference was found between the external role model and self-role model groups. Table 3 summarizes the effects of role model presence on students’ STEM attitudes across survey factors.

6. Discussion and Implications

Understanding the factors that shape students’ engagement in STEM is essential for broadening participation and supporting equitable engineering opportunities. This study examines how gender, prior engineering experiences, and the presence of role models influence students’ STEM engagement. Importantly, the focus on a predominantly African American student population provides critical insights into groups that remain underrepresented in engineering fields. By centering the voices and experiences of these students, the findings highlight not only the structural barriers but also the pathways that can foster confidence, interest, and persistence in STEM.
We developed and validated a scale measuring five dimensions: STEM interest, mathematical problem-solving confidence, misconceptions about engineering, perceptions of STEM, and self-efficacy. Results revealed that gender had minimal influence on these constructs, with only a small but statistically significant effect on STEM interest—female students reported lower interest than male students. Students who reported prior engineering-related experiences (e.g., building or creating) expressed significantly higher STEM interest and more favorable perceptions of engineering; however, these experiences did not significantly impact self-efficacy, math confidence, or misconceptions. Finally, students with identified role models exhibited higher STEM interest, confidence, perceptions, and self-efficacy compared to those without role models.

6.1. Reliability and Validity of the Scale

This study provides empirical support for the reliability of this instrument, particularly among students of color, a group often underrepresented in STEM assessment validation studies. The EFA supported a clear five-factor structure—Interest in STEM, Mathematical Reasoning, Misconceptions in STEM, Perception of STEM, and Self-Efficacy, explaining 49% of the variance, with strong loadings and a KMO of 0.77. The Rasch model analysis using PCM demonstrated ideal item fit (Infit MSE = 0.98; Outfit MSE = 1.01), acceptable residuals, and a relatively moderate range of item difficulties (−1.01 to 0.87), confirming measurement precision. Cronbach’s alpha indicated excellent internal consistency (α = 0.96 overall; subscales α = 0.74–0.96), with item-total correlations ranging from 0.24 to 0.77. Together, these findings provide solid evidence that the scale is both valid and reliable for assessing students’ STEM-related attitudes.

6.2. No Gender-Related Differences on STEM Interests, Confidence, Misconceptions, Perceptions, and Self-Efficacy

The analysis revealed a statistically significant but small effect of gender on students’ interest in STEM, with female students reporting lower interest levels than their male counterparts. However, gender did not significantly predict students’ mathematical problem-solving confidence, misconceptions about engineering, perceptions of STEM, or self-efficacy in STEM. This diverges from earlier research suggesting that girls tend to report lower levels of confidence and self-efficacy in STEM settings (Eccles & Wang, 2016; Wang & Degol, 2017). One possible explanation might be that in this study’s context—primarily an African American high school in the Southern U.S.—gender is less salient than other social or contextual factors in shaping STEM engagement. This may be due in part to students’ conceptions of engineering as contextually framed and shaped by social influences (Capobianco et al., 2011). Additionally, in the context of this study, which focuses on 83% African American high school students, gender may not be a salient factor influencing STEM-related dimensions. It is also possible that both boys and girls in these school settings have comparable access to, or perhaps a shared lack of, opportunities related to engineering and broader STEM engagement. Future research could investigate how contextual factors, such as school resources, engineering clubs, and community engagement, shape STEM attitudes among African American youth.

6.3. Hands-On Engineering Promotes Students’ STEM Interest and Perception

Students’ interest in STEM varied significantly depending on the type of engineering experiences they reported. Specifically, students in the “Building and Creating” group, those who engaged in hands-on, design-oriented experiences, expressed notably higher interest in STEM compared to those in the “Other” group. This suggests that tangible, construction-based activities play a role in sparking students’ enthusiasm for STEM fields. These findings align with research showing that active, creative engagement in engineering tasks fosters interest and relevance (Capobianco et al., 2011; Carlone et al., 2014). Furthermore, students in the “Building and Creating” group also demonstrated significantly more positive perceptions of STEM and engineering. These findings conform to previous research that not all engineering exposure is equally impactful; experiences that are collaborative, constructive, and engaging appear to foster more favorable attitudes (Prieto-Rodriguez et al., 2020). This supports earlier findings that hands-on experiences are key to shaping how students view STEM (Tan et al., 2013; Lane & Id-Deen, 2020).
Consistent with prior work (Capobianco et al., 2011; Oware et al., 2007), we found that students who reported engaging in hands-on engineering experiences, such as building or creating things, tended to demonstrate more positive attitudes and conceptions of STEM. Although no statistically significant differences emerged across most STEM-related dimensions (e.g., mathematical problem-solving confidence, misconceptions of engineering, and self-efficacy in STEM), students in the Building and Creating group consistently had higher mean scores compared to those who responded with “I don’t know” when asked about prior engineering experiences. This suggests that recalled experiences of building and creating, even when not formally part of a curriculum, may serve as early indicators or contributors to students’ developing interest and orientation toward STEM (Capobianco et al., 2011; Nugent et al., 2016).
Notably, students who reported no memorable engineering experience (“I don’t know”) not only showed lower interest in STEM but also exhibited higher levels of misconceptions about engineering. These findings may point to the importance of early and accessible exposure to engineering-related opportunities, particularly those that allow for creativity, construction, and collaboration (Tan et al., 2013). Importantly, engineering activities need not be limited to stereotypical contexts such as robotics or car-building (Capobianco et al., 2011); students may benefit equally from engineering design experiences tied to health, fashion, sustainability, or other culturally and personally relevant domains. Future research should explore how the nature and context of these hands-on experiences influence different dimensions of STEM, particularly among underrepresented student groups.

6.4. Role Models Strengthen STEM Interest, Confidence, and Self-Efficacy

This study found that students who identified external role models, such as teachers, friends, and family members, demonstrated significantly higher interest in STEM, greater confidence in mathematical problem-solving, more positive perceptions of STEM, and stronger STEM self-efficacy compared to students who reported having no role model. These findings corroborate research emphasizing the impact of representation and visibility in STEM (González-Pérez et al., 2020; Msambwa et al., 2024; Herrmann et al., 2016). Role models appear to act as powerful anchors, helping students, especially those from underrepresented backgrounds, envision themselves in STEM roles by making success feel attainable and real (Dasgupta & Stout, 2014; Faulkner, 2015).
Interestingly, students who selected themselves as their role model (referred to as the “Myself” group) did not demonstrate the same positive outcomes as those who identified external influences. This suggests that although internalized motivation and future-self imagery can be meaningful (Herrmann et al., 2016), they may lack the motivational weight and emotional resonance provided by real-world exemplars. External role models offer not only inspiration but also validation, modeling how to navigate barriers and pursue STEM goals, an especially crucial form of social support for students.
About 63% of the students in our study reported that no one had inspired them in their STEM learning or aspirations. For example, one student plainly stated, “No one has really inspired me to explore robotics or engineering.” This reveals a troubling gap: a lack of visible, accessible role models in many students’ lives. It also suggests an absence of structured opportunities within schools and communities to foster mentorship. These findings indicate a need for educators, community members, and STEM outreach professionals to play a more intentional and visible role in students’ lives, not only by delivering content but by serving as inspirational figures who broaden students’ visions of what is possible.
In summary, this study provides insights into how engineering experiences, gender, and role models influence high school students’ perceptions, interest, and self-efficacy in STEM. The findings suggest that while gender has a minimal effect on students’ attitudes toward STEM, prior engineering experiences and the presence of external role models significantly impact their overall STEM interests and perception of engineering.

7. Limitations

This study provides important insights into the factors shaping students’ STEM interests and perceptions of engineering; however, several limitations warrant discussion. First, the sample size was relatively small and drawn primarily from a context, with the majority of participants identifying as African American. While this focus provides a valuable contribution by centering the perspectives of a population often underrepresented in STEM education research, it also limits the generalizability of the findings to broader or more demographically diverse student populations. Second, although the survey measured multiple dimensions of STEM engagement, the constructs may not fully capture the complexity of students’ lived experiences. To mitigate this concern, we included both Likert-scale and open-ended questions, allowing students to elaborate on their perspectives in their own words. Finally, while we implemented validity and reliability procedures to strengthen the instrument, some degree of subjective interpretation was necessary, particularly in coding open-ended responses and mapping them to quantitative constructs.

Author Contributions

N.A. led the study design, data collection, quantitative analysis, and manuscript writing. C.A.O. conducted the reliability analysis and contributed to interpreting the results. N.A., Y.T. and K.O. conducted the qualitative analysis of open-response items. Y.T. and K.O. supported data organization and manuscript revisions. All authors have read and agreed to the published version of the manuscript.

Funding

The authors did not receive support from any organization for the submitted work.

Institutional Review Board Statement

Informed consent was obtained from all individual participants included in the study. Participants were informed that their anonymized responses may be used in research publications, and all agreed to these terms.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets generated and/or analyzed during the current study are not publicly available due to [e.g., institutional restrictions, privacy concerns], but are available from the corresponding author on reasonable request. No custom code was developed for this study.

Acknowledgments

We would like to extend our appreciation to the students who participated in the study and to the instructors and administrators who supported data collection efforts.

Conflicts of Interest

All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.

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Education 15 01217 g001
Figure 1. Categories of Self-reported Engineering Experiences: “What is the most exciting thing you have done related to robotics or engineering?”.
Figure 1. Categories of Self-reported Engineering Experiences: “What is the most exciting thing you have done related to robotics or engineering?”.
Education 15 01217 g001
Education 15 01217 g002
Figure 2. Distribution of High School Students’ Self-Identified Role Models or Absence of Them Nobody (n = 46, 63%).
Figure 2. Distribution of High School Students’ Self-Identified Role Models or Absence of Them Nobody (n = 46, 63%).
Education 15 01217 g002
Table 1. Participants’ Demographics.
Table 1. Participants’ Demographics.
Number of Students (n) and Percentage (%)
Gender
Female51 (53%)
Male45 (47%)
Grade Level
9th grade27 (28.12%)
10th grade23 (23.96%)
11th grade27 (28.12%)
12th grade19 (19.79%)
Race
African American80 (83.33%)
White8 (8.33%)
Other Races8 (8.33%)
Table 2. Summary Table.
Table 2. Summary Table.
FactorsF-Valuep-ValueEffect Size (η2)Post-hoc Results
Interest in STEM8.33<0.001 **0.09Others-Building and Creating < IDK-Building and Creating (p < 0.001 **)
Mathematical Problem-Solving Confidence2.580.0820.06No significant differences.
Misconceptions of Engineering2.090.1310.05No significant differences.
Perception of STEM8.12<0.001 **0.18Others-Building and Creating < IDK-Building and Creating (p < 0.001 **), Others-Building and Creating < IDK (p < 0.001 *)
Self-Efficacy in STEM1.180.3120.03No significant differences.
Note: Significance is indicated by asterisks (* p < 0.05, ** p < 0.001).
Table 3. A Summary of the Presence or Absence of Role Models and Their Impact on Interest in STEM, Mathematical Problem-Solving Confidence, Misconceptions of Engineering, Perceptions of STEM, and Self-Efficacy in STEM.
Table 3. A Summary of the Presence or Absence of Role Models and Their Impact on Interest in STEM, Mathematical Problem-Solving Confidence, Misconceptions of Engineering, Perceptions of STEM, and Self-Efficacy in STEM.
FactorF-Valuep-Value Effect Size (η2)Post-hoc Result
Interest in STEM9.99<0.001 **0.22External Role Models > Nobody
Math Problem-Solving Confidence4.650.0123 *0.12External Role Models > Nobody, Myself
Misconceptions-of Engineering2.680.07550.07No significant differences
Perception of STEM4.120.0204 *0.11External Role Models > Nobody
Self-Efficacy in STEM4.040.0218 *0.10External Role Models > Nobody
Note: Significance is indicated by asterisks (* p < 0.05, ** p < 0.01).
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Altindis, N.; Ocheni, C.A.; Tong, Y.; Obafemi, K. Impacts of Gender, Engineering, and Role Models on High School Students’ Overall STEM Interest and Perceptions of Engineering. Educ. Sci. 2025, 15, 1217. https://doi.org/10.3390/educsci15091217

AMA Style

Altindis N, Ocheni CA, Tong Y, Obafemi K. Impacts of Gender, Engineering, and Role Models on High School Students’ Overall STEM Interest and Perceptions of Engineering. Education Sciences. 2025; 15(9):1217. https://doi.org/10.3390/educsci15091217

Chicago/Turabian Style

Altindis, Nigar, Christopher Adah Ocheni, Yan Tong, and Kayode Obafemi. 2025. "Impacts of Gender, Engineering, and Role Models on High School Students’ Overall STEM Interest and Perceptions of Engineering" Education Sciences 15, no. 9: 1217. https://doi.org/10.3390/educsci15091217

APA Style

Altindis, N., Ocheni, C. A., Tong, Y., & Obafemi, K. (2025). Impacts of Gender, Engineering, and Role Models on High School Students’ Overall STEM Interest and Perceptions of Engineering. Education Sciences, 15(9), 1217. https://doi.org/10.3390/educsci15091217

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