Professionals’ Identification Within and Across Science,Technology,Engineering,and Mathematics (STEM) Fields

Abstract

Professional identity, for many, is a substantial component of their career choices and development. In this study, we utilized data from an online survey completed by 1,867 participants living across the United States to consider the extent to which an individual working in science, technology, engineering, and/or mathematics (STEM) field identifies with each discipline, and how this may be associated with recognition, competence, and sense of belonging. Results from structural equation modeling indicated that participants’ STEM field had a positive, direct impact on their discipline-specific identity but a negative, direct impact on other discipline identities. Furthermore, recognition and competence had significant direct and indirect effects on participants’ STEM identity, which was not consistent by STEM field. Alternatively, sense of belonging and self-identifying as a woman had limited effects in our model. Our findings raise questions as to the possibility (or not) of STEM as an interdisciplinary identity for professionals with a career in STEM.

Keywords

STEM identity career development competence recognition sense of belonging

For many individuals, their career is intimately associated with how they view and define themselves as a professional in their respective field(s), and who they are and are becoming while on the job and through social interactions with others in their organization and field, as well as outside their field (Caza & Creary, 2016; Hoekstra, 2011). As stated by Chope (2000), one’s career identity is the “kernel of all that you hope to be or become, the nucleus of your workplace confidence. It represents the accrual and integration of your experience, skills, interests, values, and personality characteristics” (p. 58). Further, an individual’s professional identity is multifaceted, as occupational roles and tasks are varied, skill-based, and not clearly defined (Simpson, 2018; Caza & Creary, 2016; Chope & Johnson, 2008). For example, a software engineer may view themselves as an engineer, a technologist, a mathematician, an artist, and an entrepreneur. In this study, we are interested in understanding the professional identities of adults who work in a science, technology, engineering, and/or mathematics (STEM) field. We expect their career to be a dynamic entity of shared practices and processes that transcend STEM as an interdisciplinary discipline (Moon & Singer, 2012), as opposed to isolated disciplines where content and practices are independent of one another (Briener et al., 2012).

To date, much of the research on individuals’ identity as a particular kind of person in STEM pertains to each discipline as opposed to STEM as a whole and with less attention to individuals at the professional level (Bouhafa & Simpson, 2019). We address this gap in the literature by exploring the following research question: “To what extent are recognition, competence, and sense of belonging associated with STEM professionals’ identification in each discipline?” We contend that understanding some of the factors that shape one’s professional identity in STEM is important, as one’s view of themselves in their profession impacts positive and/or negative career goal performances and progress (Creed et al., 2018); work attitudes, affect, and behaviors (e.g., Siebert & Siebert, 2005); psychological well-being (Tajfel & Turner, 1979); and life satisfaction (Garrison et al., 2017).

Literature Review and Hypotheses Development

We define one’s professional identification in STEM as a belief that an individual has about themselves in regard to each STEM discipline according to three areas: (1) recognition, (2) competence, and (3) sense of belonging. In addition, we agree with other scholars that interest in at least one of the disciplines shapes one’s professional identity in STEM (e.g., Cribbs et al., 2015; Hazari et al., 2010). However, in this study, we focused on the association of recognition, competence, and sense of belonging as constructs with which STEM professionals may identify. We further consider this association through social identity theory (SIT; Tajfel, 1982; Tajfel & Turner, 1979) and social cognitive career theory (SCCT; Lent et al., 1994, 2008). The rationale behind utilizing the SIT and the SCCT is that there is a strong link among an individual’s experiences, development and performance of their STEM identity, and the STEM social groups to which one belongs and identifies or does not belong or identify (e.g., Buse et al., 2013).

Recognition

Recognition is defined as how one sees themselves in relation to how others see them (e.g., Carlone & Johnson, 2007; Hazari et al., 2010). Recognition has been found to be one of the strongest variables directly associated with one’s identity, positively or negatively (Cribbs et al., 2015; Godwin et al., 2016; Hudson et al., 2018). For example, in considering factors associated with one’s mathematics identity, Cribbs et al. (2015) found a direct effect of recognition to be the greatest (β = .742). Research has found that identity in a STEM field is shaped by feeling recognized by established STEM professionals (Hudson et al., 2018; Malone & Barabino, 2009), colleagues (Kunhunny & Salmon, 2017), and high school teachers (Godwin & Potvin, 2017; Hazari et al., 2017). In addition, the effects of recognition for female participants may be greater than the effects of their male counterparts (e.g., Bingham, 2001; Cass et al., 2011). SIT would suggest that the process of self-categorization and positive social identity is accomplished through comparing oneself with members of their respective social group(s) (e.g., engineers) as well as with members from other social groups (e.g., linguists) to assess their distinctiveness and RC (Hudson et al., 2018; Tajfel & Turner, 1979).

Competence

Competence is defined as possessing “knowledge and understanding of science content” (Carlone & Johnson, 2007, p. 1191). In our study, competence is defined as the self-perception of possessing the skills and understanding relevant to STEM fields and measured by two subconstructs—STEM skill competence and general STEM competence. Research with undergraduate populations indicated that competence beliefs alone do not positively predict an identity in STEM, but rather competence beliefs are mediated by interest and recognition (Cass et al., 2011; Cribbs et al., 2015; Hudson et al., 2018). For example, Godwin et al. (2016) determined that the direct path of performance/competence as a combined factor negatively predicted 6,772 first-year undergraduate students’ identity in mathematics or physics. However, performance/competence beliefs were positively associated with identity in mathematics or physics when mediated by interest and recognition. In some cases, competence may be less salient as they are in a position and/or career in which relevant knowledge and understanding of their discipline is viewed as already mastered (Hudson et al., 2018), or they have a narrow view of what constitutes an appropriate knowledge base in one or more STEM disciplines (Godwin & Potvin, 2017). Women typically perceive themselves as less competent in their STEM knowledge and skills than men (e.g., Bench et al., 2015; MacPhee et al., 2013). In terms of SCCT, self-perception of one’s ability (i.e., competence) and career-related outcome expectations is a predictor of pursuing and persisting in one’s career (Lent et al., 1994).

Sense of Belonging

Sense of belonging is defined as one’s belief that they are an accepted and contributing member of a community (Cheryan et al., 2015; Good et al., 2012). In this study, sense of belonging was measured by four subconstructs, namely, community support (CS), skill perception (SP), negative affect (NA), and diversity bias (DB). As described by Leaper (2015), to develop a STEM-based professional identity, one should nurture a sense of belonging to STEM-based social groups. It is the social groups that we belong to that in turn shape our self-conceptions and identification as members of that group (e.g., Abrams & Hogg, 1990). Research has illustrated how a sense of belonging is associated with achievement, engagement, interests, perseverance, and identity in a particular STEM field (e.g., Cheryan et al., 2009; Good et al., 2012; Stevens et al., 2008). In addition, studies posited sense of belonging as a function of perceived support from peers, teachers, and family members (Rosenthal et al., 2011; Strayhorn, 2018). Further, women may report a lower sense of belonging when working in a male-dominated discipline, climate, and/or environment (e.g., Bernstein & Russo, 2008). In terms of SIT, young women are usually presented with the idea that they do not belong in STEM, and if they are successful, their skills and abilities are often challenged (Kim et al., 2018). Therefore, the negative social identity they develop within the STEM groups may lead individuals to consider different social group(s). To date, we are unaware of any studies that considered sense of belonging as a significant direct or indirect variable on one’s identity within any STEM field.

Gender

Based on gender studies in recognition, competence, and sense of belonging as discussed above, we also included self-identified gender as a measurement variable within the model. Prior research utilizing structural equation modeling and grounded in SCCT has found a small, yet direct effect of gender on outcome expectancies (Fouad & Smith, 1996). Godwin et al. (2016) found women’s identity as physicists and mathematicians was less predictive of pursing an engineering career than their male counterparts. As such, women are underrepresented in particular STEM fields (National Science Foundation [NSF], 2019), which is a long-standing and prevalent concern for those in academia and industry.

Further, we contend that race/ethnicity should also be considered in our model, as this social and cultural identity will impact people’s perceptions of themselves and others. However, as indicated in Table 1, the majority of our participants self-identified as White or Caucasian (n = 1,037; 83%), with the next most identified race/ethnicity being Asian (n = 75; <1%). Therefore, our sample is not representative of the STEM workforce (NSF, 2019), and we were not comfortable with including this as a binary measured variable in the model.

Table 1.

Self-Identified Gender and Ethnicity Characteristics of the Participants in This Study.

	Science		Technology		Engineering		Mathematics		Total
Demographics	N	%	N	%	N	%	N	%	N	%
Gender
Woman/female	560	44.8	51	32.5	97	30.4	44	32.6	752	40.4
Man/male	665	53.2	100	63.7	213	66.8	86	63.7	1,064	57.2
Did not identify as either female or male	25	2.0	6	3.8	9	2.8	5	3.7	45	2.4
Total	1,250	100.0	157	100.0	319	100.0	135	100.0	1,861	100.0
Ethnicity
American Indian or Alaskan Native	6	0.5	0	0.0	0	0.0	0	0.0	6	0.3
Asian	75	6.0	18	11.5	44	13.8	7	5.2	144	7.7
Black or African American	23	1.8	2	1.3	13	4.1	7	5.2	45	2.4
Native Hawaiian or Pacific Islander	1	0.1	0	0.0	0	0.0	0	0.0	1	0.1
White or Caucasian	1,037	83.0	120	76.4	232	72.7	103	76.3	1,492	80.2
Hispanic, Latino, or Spanish origin	40	3.2	5	3.2	12	3.8	9	6.7	66	3
Middle Eastern or North African	2	0.2	1	0.6	2	0.6	1	0.7	6	0.3
Other	27	2.2	9	5.7	6	1.9	3	2.2	45	2.4
Multicultural	39	3.1	2	1.3	10	3.1	5	3.7	56	3.0
Total	1,250	100.0	157	100.0	319	100.0	135	100.0	1,861	100.0

Note. N = 1,867.

Based on our understanding of the current literature regarding identity in a STEM field, we hypothesize the following (see Figure 1):

Hypothesis 1: Aspects of one’s career-related perceptions such as recognition, competence, and sense of belonging have a significant direct relationship to STEM identity.

Hypothesis 2: The relation between STEM field and STEM identity, as well as gender and STEM identity, was expected to be mediated by recognition, competence, and sense of belonging.

Hypothesis 3: STEM field and gender have a significant direct relationship to STEM identity.

As such, our hypotheses are exploratory in nature as we are building upon identity research grounded in postsecondary education and often situated within one STEM field. In exploring these three hypotheses, we expect to have a baseline understanding of professionals’ STEM identity to inform the field.

Method

Procedures

This proposal is part of a larger survey regarding individuals’ interest in one or more STEM fields. This is the first study to be published from this larger study. A random sample of approximately 35,000 participants from a list of close to 67,000 individuals who had received grant funding from NSF as a principal investigator between 2011 and 2016 was solicited via email to complete a 20- to 25-min online survey through Qualtrics. This list was extracted from the NSF website. As this was part of a larger survey with multiple sets or blocks of questions, we included logic in Qualtrics so that the set of questions focused on participants’ identity in STEM was randomly given to participants.

Participants

Of the 35,000 potential participants solicited, 7,126 completed the entire survey, and 1,861 of these participants were randomly selected for, and completed, the block of survey questions seeking information regarding their STEM identity. The majority of participants worked in academia (approximately 88.6%), while the remaining participants worked in industry (approximately 11.4%). Participants’ self-identified gender and ethnicity by the field in which they worked are displayed in Table 1. Additionally, participants may have been living in the United States at the time of the survey, but they represented a global population as they indicated being born in countries other than the United States.

Measures

The block of questions used in this study was designed to collect responses focusing on the constructs of identity mentioned above. These questions were obtained and adapted from established and validated surveys that specifically inquire about the variables in this study. As a first step in developing the block of identity questions, content and face validity was established through cognitive interviews and field-testing items with two researchers who examine identity, seven professionals who worked in a STEM field outside academia, and 22 undergraduate and graduate students across STEM disciplines. These individuals provided insights into the wording of some of the questions and the overall structure of the survey items. After making changes based on the information gathered from these individuals, and as a second step, we generated a simulation from 685 individuals to check for errors in flow. As a third step, we invited 3,933 members in a STEM organization at a large institution and 104 STEM professionals as part of another study to provide feedback regarding the wording of the questions, the wording of multiple-choice response options (including if important options were missing), and any other general impressions. Of these, 29 sent feedback through open-ended items following each section of the professional identity survey. Lastly, in the fourth step, we conducted an exploratory factor analysis (EFA) as a way to identify specific factors within each set of questions.

STEM field

At the beginning of the survey, participants were asked to select the STEM field with which they felt their work most closely aligned—science, technology, engineering, mathematics, or STEM education. For those who selected STEM education, we considered the major of their highest degree. STEM field was a measured predictor variable in the model.

Recognition

The questions about recognition (RC) were drawn from Hazari and colleagues’ (2010) exploration of physics identity and Cribbs et al. (2015) exploration of mathematics identity. These four questions were intended to identify how an individual felt others perceived them within their chosen STEM profession (e.g., “My supervisor(s)/colleagues/family members view me as an engineer”). For this study, these questions differed based on the STEM field they selected in the background questions, which is the only set of questions that were specific to their career field. Similar to the work of Hazari et al. (2010) and Cribbs (2015), these items were measured using Likert-type scale variables from 1 = does not describe my feelings to 5 = clearly describes my feelings. The factor analysis indicated that the 4 items were asking the same question (Cronbach’s α = .939); therefore, only 1 item was used in the model.

Competence

Questions about competence explored each individual’s perceived ability to perform specific tasks expected from the STEM fields (e.g., “I am confident in my ability to solve problems requiring mathematics” and “I am confident in my ability to troubleshoot problems”). These eight questions were developed by the research team as items encompassing professionals’ competence across the STEM spectrum were nonexistent. Specifically, the items were based on 99 interviews from professionals across STEM fields (Simpson & Maltese, 2017). Items were assessed using a 6-point Likert-type scale (1 = strongly disagree, 6 = strongly agree). Factor analysis of the competence items revealed two subconstructs—STEM skill competence (“I am confident in my ability to solve problems involving mathematics”; Cronbach’s α = .735) and general STEM competence (SC) (“I am confident in my ability to solve problems in novel ways”; Cronbach’s α = .708).

Sense of belonging

The sense of belonging questions inquired how individuals felt they were treated within their professional social group (Good et al., 2012). These 21 questions were adopted because the original measure was specific to one’s sense of belonging in mathematics. Sample items included “On an average day, individuals I work with…make me feel valued,” “…make me feel anxious,” and “…contribute to my success on a task/project.” Based on cognitive interviews (see below), we also included additional items (e.g., “…treat me differently because of my age”). Items were measured on a 6-point Likert-type scale from 1 (strongly disagree) to 6 (strongly agree). Our factor analysis revealed four factors (CS, SP, NA, and DB) with a Cronbach’s α reliability estimate ranging from .729 to .885 in this study.

Identity

Identity questions inquired about how one identified as a STEM professional and included 5 items—one from each STEM field (e.g., I view myself as a scientist) and one indicating a self-perception in the STEM community (e.g., I view myself as a member of the STEM community). These questions recognized that identity is highly personal and defined by an individual’s perceptions and experiences of a “type of person” in a particular field (Hazari et al., 2010, 2013). These items were measured using a 5-point Likert-type scale ranging from 1 = does not describe me at all to 5 = describes me extremely well. Since our interest is in understanding the subtle nuances in participants’ STEM identity, we left these as separate outcome variables as opposed to one outcome variable. For example, a median STEM identity of 1.5 would indicate that a participant had a weak STEM identity. However, we are unaware of which identities within STEM they most identify with. This can be misleading as a participant might have identified as a scientist (5), but not as an engineer (2), a technologist (1), or a mathematician (1).

Data Analysis

Descriptive statistics and crosstabs were run to obtain an initial picture of professionals’ identity in the STEM fields and how they compare across each discipline. Additionally, EFA was conducted with the measures to support or refute initial hypotheses, as research on STEM identity as an interdisciplinary identity was conceptualized and explored in this study. This was done using principal axis factoring and orthogonal varimax rotation. Kaiser-Meyer-Olkin (KMO) measure for RC, competence, and sense of belonging was .757, .869, and .924, respectively, indicating the data were suitable for EFA (Kaiser, 1974). The Bartlett’s test of sphericity for RC, χ²(6) = 629.041, p < .001, competence, χ²(36) = 4,622.621, p < .001, and sense of belonging, χ²(210) = 14,601.339, p < .001 showed that patterned relationships existed among the variable within each construct. As noted in the Measures section, RC was a single factor, explaining a cumulative variance of 84.8%. Competence was composed of two factors and explained a cumulative variance of 55.43%. Sense of belonging had four factors that explained a cumulative variance of 55.59%.

Structural equation modeling

Utilizing Mplus, further data analysis in this study was done by constructing a structural equation model (SEM) that related each variable under study with each of the STEM identities. With Mplus, we performed a maximum likelihood estimation with the missing data, which has been found to be unbiased and more efficient than other methods, namely, listwise deletion, pairwise deletion, and similar response pattern imputation (Enders & Bandalos, 2001). First, using a multiple indicators, multiple causes (MIMC) model, the six composite variables and one single measure were sorted as endogenous latent variables. These latent variables include diversity bias (DB, 4 items), community support (CS,10 items), negative affect (NA, 3 items), skill perception (SP, 3 items), general competence (GC, 4 items), and STEM compentence (SC, 5 items). In consideration of model identification, these latent variables satisfy the three-indicator rule, “A multifactor model is identified when it has three or more indicators per latent variable” (Bollen, 1989, p. 244). Although the three-indicator rule is sufficient for model identification, it is not necessary. Along with these latent variables, a single measure of RC was included as a mediating variable for the MIMC component of the SEM. This measure was treated as a single item, not as a latent variable.

Second, the four outcomes of the model were regressed on these factors. These outcomes include the four measures of professional identity for each of the four fields: science, technology, math, and engineering. This part of the modeling allowed us to test the first hypothesis of the current study: Aspects of career-related perceptions such as RC, competence, and sense of belonging significantly relate directly to STEM identity. Third, an indirect relation (mediation) between the initial background variables through the composite variables to the outcomes was measured. This part of the model allowed us to test the second hypothesis of the current study: Aspects of career-related perceptions such as RC, competence, and sense of belonging indirectly mediate STEM identity for type of work and gender.

Fourth, the initial background dichotomous variables of science field, engineering field, and math field (with technology field serving as a reference), along with a dichotomous variable for gender (woman = 1), were directly related to the same outcomes. This part of the modeling allowed us to test the third hypothesis of the current study: STEM field and gender significantly relate directly to STEM identity. As evidence of model identification, we invoke the t-rule in which the number of free elements must be fewer than the number of known elements (Bollen, 1989). The number of free elements includes 64 factor regression slopes + 29 intercepts + 29 factor loadings + 30 residual variances + 25 factor correlation = 177. The number of observed variables is 38, which leads to 38(38 + 1)/2 + 38 = 779 known elements. Since the number of free elements is less than the number of known ones, this calculation meets the t-rule, which is not a sufficient, but necessary, condition of identification.

As another satisfaction to model identification, analysis of the paths of mediation shows there is not a feedback loop; therefore, there is not a recursive element to the model (Bollen, 1989). Using the weighted least squares means and variance estimates, model fit was improved by correlating some of the errors of the items within latent variables. Model fit was improved to adequate levels (comparative fit index = .937, Tucker–Lewis index = .920, root-mean-square error of approximation = .058; e.g., Hu & Bentler, 1998). Since the standard errors produced by Mplus are inflated, the 95% confidence intervals are reported, derived using the program’s bootstrap method for 1,000 iterations.

Results

When the outcomes of professional identity were regressed on the composite variables, several significant (p < .05) relationships emerged among the standardized parameter estimates (see Table 2). Additionally, when examining the mediation effects of these parameters, a few latent variables served as significant mediators for respondents working in science, engineering, or math fields (individuals working in technology served as the reference group) and for respondents who identified as women.

Table 2.

Standardized Parameter Estimates and Direct and Indirect Effects Among Variables.

Composite variables	Professional Identity
	Science				Technology				Engineering				Math
	Estimate		95% CI		Estimate		95% CI		Estimate		95% CI		Estimate		95% CI
DB	−.045		[−.14, .02]		.010		[−0.07, 0.11]		0.057		[−0.07, 0.22]		0.043		[−0.10, 0.17]
CS	.007		[−.28, .14]		.092		[−0.17, 0.33]		−0.246		[−0.74, −0.01]		−0.272		[−0.80, −0.04]
SP	.015		[−.74, .02]		.127		[−1.35, −0.20]		0.472*		[−2.02, −0.63]		0.465*		[−1.98, −0.73]
NA	.001		[−.14, .09]		.044		[−0.14, 0.19]		−0.093		[−4.00, 0.04]		−0.107		[−0.41, 0.09]
GC	−.234		[−.19, .38]		−.528*		[−0.27, 0.43]		−0.979*		[0.14, 1.15]		−1.028*		[0.18, 1.05]
SC	.464*		[.24, .81]		.741*		[0.44, 1.20]		1.103*		[0.78, 1.80]		1.153*		[0.90, 1.93]
RC	.267*		[.15, .34]		−.085		[−0.25, 0.01]		−0.130*		[−0.33, −0.03]		−0.119		[−0.32, −0.04]
Field	Science								Technology
Field	DB	CS	SP	NA	GC	SC	RC	Direct	DB	CS	SP	NA	GC	SC	RC	Direct
Science field	—	—	—	—	—	−.309	.306	.810	—	—	—	—	—	−.494	—	−.689
Engineer field	—	—	—	—	—	—	.154	−.305	—	—	—	—	—	—	—	−.695
Math field	—	—	—	—	—	−.272	.259	—	—	—	—	—	—	−.435	—	−.786
Female	—	—	—	—	—	−.160	−.072	—	—	—	—	—	—	−.255	—	−.145
Field	Engineering								Mathematics
Field	DB	CS	SP	NA	GC	SC	RC	Direct	DB	CS	SP	NA	GC	SC	RC	Direct
Science field	—	—	—	—	.341	−.736	−.148	−.522	—	—	—	—	.358	−.768	—	—
Engineer field	—	—	—	—	—	—	−.075	.607	—	—	—	—	—	—	—	—
Math field	—	—	—	—	.323	−.647	−.125	−.597	—	—	—	—	.339	−.676	—	2.353
Female	—	—	—	—	.188	−.380	.035	—	—	—	—	—	.198	−.397	—	—
Model fit	CFI: .937		TLI: .920			RMSEA: .058

Note. Sense of belongingness: DB = diversity bias; CS = community support; SP = skill perception; NA = negative affect. Competence: GC = general competence; SC = STEM competence. Recognition: RC = recognition. CI = confidence interval; CFI = comparative fit index; TLI = Tucker–Lewis index; RMSEA = root-mean-square error of approximation.

*p < .05 for all values.

The first hypothesis regarding the significant direct effect of RC, competence, and sense of belonging on STEM identity was partially supported, as there were varying effects on participants’ identification in STEM. As the results for Hypothesis 1 suggest, competence in STEM fields was consistently, positively related to STEM identity; yet, with the exception of identification in science, STEM identity was negatively related to general work-related competence. For example, identity as a technologist had a positive direct association with SC (R² = .741) but a negative effect with general work-related competence (R² = −.528). Contrary to previous research, RC did not have a significant impact on STEM identity. In considering the association of RC with separate identities, we found this construct to be positively associated with identification as a scientist (R² = .267) and negatively associated with identification as an engineer (R² = −.130). As such, both of these effects were small in size. Additionally, the results highlighted how sense of belonging had little effect on STEM identity, as only one factor (SP) had a positive association with engineering identity (R² = .472) and mathematics identity (R² = .465).

Similarly, Hypothesis 2 was partially supported by the results of this study (see Table 2), as the constructs RC and competence indirectly mediated STEM identity by STEM field and gender. As such, sense of belonging (i.e., DB, CS, NA, and SP) was not a significant mediator for how participants identified themselves within STEM. For participants who worked in a science or mathematics field, SC was a significant, negative mediator on STEM identity. However, GC was a significant, positive mediator on identification as an engineer (R² = .341 and R² = .323, respectively) and mathematician (R² = .358 and R² = .339, respectively). For each STEM field, RC was a significant, positive mediator for a science identity (.154 < R² < .306) but was a significant, negative mediator for participants identifying as an engineer (−.148 < R² < −.075). Hence, RC is not a significant indirect indicator of STEM identity as an interdisciplinary identity. Similarly, the results highlighted that the indirect effect between STEM field and STEM identity was the same indirect effect as gender and STEM identity.

Lastly, as noted in Table 2, although participants’ career field had a direct and significant positive relationship with identifying themselves as a professional in their respective field, it at times had a negative relationship with other professional identities in STEM. For example, participants in the field of engineering identified themselves as an engineer (R² = .607) but not as a scientist (R² = −.305) or technologists (R² = −.695). One exception to this finding is participants who identified as a mathematician, as there was not a positive or negative direct relationship with identifying themselves as anything other than a mathematician. Therefore, our findings do not support our third hypothesis, as the significant positive relationship is with their self-identified STEM field and not aligned with our definition of STEM identity as an interdisciplinary belief of self. Moreover, there was neither a negative nor positive direct relationship between self-identifying as a woman in STEM and participants’ science, engineering, and mathematics identities. However, in the case of identifying as a technologist, identifying as a woman had a negative direct impact (R² = −.145). Again, the third hypothesis was not well supported, as gender had no direct or significant effect on participants’ STEM identity.

Discussion

When examining the results of the current study, we learn about the important aspects that relate to the salience of the STEM identities. Not surprisingly, the field in which the respondent worked held consistently significant, positive (and often large) effects with their corresponding professional identity outcome and in some cases, significant, negative direct effects with identities not in their specific field. This finding raises questions on the possibility of STEM as an interdisciplinary identity (Moon & Singer, 2012). Instead, participants seemed to conceptualize STEM in relation to their discipline (Briener et al., 2012). We consider our finding about STEM identity as career-specific may be due to the manner in which STEM subjects are taught as isolated fields in the K–12 U.S. educational context (e.g., Briener et al., 2012). It is also possible that individuals, in the process of self-categorization, would want to distinguish themselves from other STEM identities (Tajfel & Turner, 2004). We believe there are benefits to identifying oneself as a STEM professional as opposed to career- or discipline-specific. For example, individuals who identify within STEM may see themselves as capable of engaging in activities related to each discipline in STEM. They may also be more willing to work with members of other disciplines instead of competing or rejecting the other disciplines for a more positive social identity. Following the principles of the SIT, a STEM-identified individual may perceive members of other disciplines in STEM as members of their own group.

Moreover, the direct and indirect effects of latent variables in the model varied by STEM field and gender as well as in terms of participants’ identity in STEM. These results again highlight the notion of identity as discipline-specific as opposed to interdisciplinary. One, RC served as an inconsistent and small mediator for identification of oneself as a scientist and engineer. This is not aligned with previous research that found RC to be a strong predictor of undergraduate students’ identity as a physicist (Hazari et al., 2010), a mathematician (Cribbs et al., 2015), or an engineer (Godwin et al., 2016). In addition, this finding was also unexpected because as posited by SIT, the way in which members of another social group, or STEM field, perceive other groups shapes individual’s professional identity (Tajfel & Turner, 1979). However, it is possible that individuals do not realize, or are not willing to admit, how much of a role others play in their identity development.

Two, competence in STEM skills and competence in general career-related skills had opposing effects on STEM identity. For example, competence in STEM skills had a negative, indirect effect on mathematicians’ and scientists’ identification as a technologist and scientist, while competence in general career-related skills had a positive, indirect effect. Similar to other results in this study, this finding was unexpected because as Lent and colleagues (1994) argued through SCCT, a positive self-perception of one’s ability in a particular discipline makes a career choice more desirable and possibly plays a role in the construction of an identity in the chosen career. For example, Chemers et al. (2011) found that higher science competence is related to a higher sense of identity as a scientist.

Three, latent variables related to sense of belonging (DB, NA, and CS) were not significant (except SP that had a moderate relationship) in shaping participants’ professional STEM identity. One possible explanation for this finding is that individuals who do not feel well supported and/or do not have a strong social identity in one of the disciplines may leave the field (e.g., Bernstein, 2011; Foley & Lytle, 2015; Tajfel, 1982). However, individuals, particularly women and underrepresented minorities, may have developed resilient coping strategies within environments considered nonwelcoming and/or exhibiting a chilly climate (e.g., Wilkins-Yel et al., 2019; Solomon et al., 2016). For example, 15 women in engineering expressed finding a supportive network of peers and colleagues within their school and/or work environment, which created a sense of belonging and connectedness (Wilkins-Yel et al., 2019). These results again highlight the notion of identity as discipline-specific as opposed to interdisciplinary.

Lastly, and in general, participants self-identifying as a woman had a negative (i.e., technology identity) or no direct association with STEM identity within a discipline-specific identity or as an interdisciplinary identity. This is contrary to our third hypothesis, as well as research on women’s identity in STEM that highlight a weak STEM identification as compared to men’s identity in STEM. This may be because self-identifying as a woman and being a STEM professional are perceived as two conflicting identities within male-dominated fields (e.g., Gill et al., 2008; Hatmaker, 2013). As such, self-identifying as a woman in this study was neither a positive nor negative social identity in terms of their STEM identity, which implies identifying as a member of the in-group; in this case, a member of the STEM community (Hogg, 2016; Tajfel, 1982). This finding is of significance for several reasons: (a) STEM fields are viewed by some as more appropriate for males (e.g., Forgasz et al., 2014), (b) women are underrepresented in the STEM profession (e.g., NSF, 2019), and (c) women’s skills and abilities in STEM are often questioned by society (e.g., Kim et al., 2018).

Conclusion

Through this research, we add relevant knowledge to the limited understanding of how individuals, at the professional level, perceive their STEM identity (Bouhafa & Simpson, 2019). We provide insights about STEM professionals, which seem to be an understudied population within this topic, by exploring their self-perceptions of ability, their sense of belonging, and their perceived recognition among members of their community. One limitation of this study is the significant amount of science STEM professionals compared to other fields. This discrepancy makes it difficult for us to have a clear understanding of individuals’ identity outside of science that is more representative of their group. A second limitation is the number of participants in academic positions versus STEM professionals who work in industry-related jobs.

However, our study still provides initial thoughts and trends that may serve as a foundation for further identity research on STEM professionals. For example, future research can extend this study to consider what other professional identities are shaping STEM professionals’ work-related identity (Chope & Johnson, 2008) and account for additional self-identifying demographics such as age. Likewise, since the three constructs used in this study did not have strong direct and indirect associations with STEM identity as prior research would suggest (e.g., Hazari et al., 2010), future research should consider other constructs that professionals use in making career choices and how career success is obtained and maintained. These other constructs may inform and extend the SCCT by focusing on the interplay of factors by which individuals pursue, adapt, and maintain their interest and identity as a professional. Future research should continue to explore the direct relationship between gender and STEM identity, as the participants in this study have received an NSF grant as a principal investigator. Likewise, future researchers should continue to explore the intersectionality of a multitude of social identities (e.g., religion, sexual orientation) on STEM identity, as research has shown how identification in a STEM field is constrained and intensified by social class and race/ethnicity (e.g., Archer et al., 2013). This future research may be informed by alternative models situated in prior identity research and theories such as the model of multiple dimensions of identity (e.g., Abes et al., 2007; Jones & McEwen, 2000) as well as build upon our understanding through interviews.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Amber Simpson

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