Factors Influencing Undergraduate Student Retention in STEM Majors: Career Development, Math Ability, and Demographics

Christopher T. Belser, M. Ann Shillingford, Andrew P. Daire, Diandra J. Prescod, Melissa A. Dagley

The United States is facing a crisis with respect to filling job vacancies within science, technology, engineering, and math (STEM) industries and with students completing STEM undergraduate degrees. In addition, disparities exist for females and ethnic minorities within STEM fields. Whereas prior research has centered on disparities in STEM fields, retention rates, and some intervention programs, researchers have not given much attention to the role of career development initiatives within STEM recruitment and retention programming. The purpose of the present study was to incorporate demographic variables, math performance, and career development–related factors into predictive models of STEM retention with a sample of undergraduate students within a STEM recruitment and retention program. The resulting two models accurately predicted first-year to second-year retention with 73.4% of the cases and accurately predicted first-year to third-year retention with 70.0% of the cases. Based on the results, the researchers provide a rationale for STEM career programming in K–12 and higher education settings and for the inclusion of career development and career counseling in STEM education programming.

Keywords: STEM, retention, career development, career counseling, undergraduate student


The United States lacks an adequate number of workers to keep up with the demand for trained workers in science, technology, engineering, and mathematics (STEM) fields (National Center for Science and Engineering Statistics [NCSES], 2017; National Science Board, 2018; Sithole et al., 2017). Researchers have pointed to the overall stagnancy of undergraduate students declaring and completing STEM degrees (Carnevale, Smith, & Melton, 2011; Doerschuk et al., 2016; Sithole et al., 2017). Additionally, underrepresentation is a problem for racial and ethnic minorities and females in STEM fields (NCSES, 2017). Because of these disparities, universities have developed programs centered on recruitment and retention of STEM undergraduates (Bouwma-Gearhart, Perry, & Presley, 2014; Dagley et al., 2016; Schneider, Bickel, & Morrison-Shetlar, 2015) and both government and private entities invest billions of dollars annually toward STEM initiatives at the K–12 and higher education levels (Carnevale et al., 2011). However, many of these endeavors have failed to incorporate components centered on career development or career planning.

The National Career Development Association (2015) defined career development as “the sequence of career-related choices and transitions made over the life span” (p. 4) and career planning as a structured process through which a person makes decisions and plans for a future career. Career development activities, such as structured career planning courses, have shown efficacy with general undergraduate populations (Osborn, Howard, & Leierer, 2007; Reardon, Melvin, McClain, Peterson, & Bowman, 2015) but have been studied less commonly with STEM-specific undergraduate populations (Belser, Prescod, Daire, Dagley, & Young, 2017, 2018; Prescod, Daire, Young, Dagley, & Georgiopoulos, in press). In the present study, researchers examined a STEM recruitment and retention program that did include a career planning course. More specifically, the research team sought to investigate relationships between demographics (e.g., gender, ethnicity), math scores, and various aspects of the undergraduate STEM program and student retention in the first 2 years of college.

Gender, Ethnicity, and STEM

Gender disparities are a common sight within STEM degree programs and the larger STEM workforce (NCSES, 2017). Females who are interested in math and science are more likely to be tracked into non-diagnosing health practitioner fields, such as nursing (ACT, 2018; NCSES, 2017). Some researchers have pointed to the K–12 arena as the root of these gender disparities that permeate undergraduate programs and STEM professions (Mansfield, Welton, & Grogan, 2014), whereas others have identified specific problems, such as differences in math and science course completion over time (Chen & Soldner, 2013; Riegle-Crumb, King, Grodsky, & Muller, 2012), stereotype threat (Beasley & Fischer, 2012), and STEM confidence (Litzler, Samuelson, & Lorah, 2014). As a result, existing predictive models typically indicate a lower likelihood of females completing a STEM degree compared to male students (Cundiff, Vescio, Loken, & Lo, 2013; Gayles & Ampaw, 2014).

Similarly, disparities in STEM degree completion and STEM job attainment exist between ethnic groups (NCSES, 2017; Palmer, Maramba, & Dancy, 2011). Although progress has been made in degree attainment in certain STEM areas, other areas have stagnated or are declining in participation by ethnic minority students (Chen & Soldner, 2013; NCSES, 2017). Foltz, Gannon, and Kirschmann (2014) identified protective factors for minority students in STEM, such as receiving college-going expectations from home, establishing connections with STEM faculty members (particularly those of color), and developing connections with other minority students in STEM majors; however, the disparities in STEM programs help perpetuate a cycle of many students not being exposed to these protective factors. The intersectionality of ethnicity and gender in STEM fields has become a topic producing interesting findings (Riegle-Crumb & King, 2010). In addition to observing disparities across ethnic groups, researchers have observed disparities within ethnic groups based on gender (Beasley & Fischer, 2012; Cundiff et al., 2013; Riegle-Crumb & King, 2010). Specifically with males of color, predictive models have been inconclusive, with some showing a higher likelihood of completing a STEM degree (Riegle-Crumb & King, 2010) and others showing a lower likelihood (Cundiff et al., 2013; Gayles & Ampaw, 2014).

Mathematics and STEM

The SAT is one of the most widely used college admissions tests (CollegeBoard, 2018). Researchers have correlated the math sub-score with undergraduate math and science classes within the first year, indicating that higher SAT math scores indicate a higher probability of higher course grades in math and science courses (Wyatt, Remigio, & Camara, 2012). Additionally, researchers have identified SAT scores as predictors of academic success and university retention (Crisp, Nora, & Taggart, 2009; Le, Robbins, & Westrick, 2014; Mattern & Patterson, 2013; Rohr, 2012). Despite its wide use in higher education admissions, the SAT may not be free from bias. Numerous scholars have highlighted potential test bias, particularly against ethnic minorities (Dixon-Román, Everson, & McArdle, 2013; Lawlor, Richman, & Richman, 1997; Toldson & McGee, 2014). Nevertheless, its wide use makes it a prime instrument for research.

In addition to the SAT scores, researchers also have demonstrated that taking higher-level math courses and having higher math self-efficacy translate to better outcomes within STEM majors (Carnevale et al., 2011; Chen & Soldner, 2013; Nosek & Smyth, 2011). Specifically, taking calculus-based courses in high school correlated with retention in STEM majors (Chen & Soldner, 2013). Nosek and Smyth (2011) found connections between gender and internalized math variables, such as warmth for math, identification with math, and self-efficacy; females across the life span showed lower levels of each of these variables, but the authors did not test these against retention outcomes in STEM majors. However, one could hypothesize that having lower levels of warmth toward math and not being able to identify with math would likely impact one’s career decisions, particularly related to math and science fields.

Career Interventions and STEM

Career theory can provide for understanding one’s interest in STEM fields (Holland, 1973), one’s exposure to STEM fields (Gottfredson, 1981), and one’s beliefs or expectations about the process of choosing a STEM field (Lent, Brown, & Hackett, 2002; Peterson, Sampson, Lenz, & Reardon, 2002). However, career interventions, such as a career planning class, are more likely to make a direct impact on career outcomes with undergraduates. In one review of research on undergraduate career planning courses, more than 90% of the courses produced some measurable positive result for students, such as increased likelihood of completing a major, decreased negative career thinking, and increased career self-efficacy (Reardon & Fiore, 2014). Other researchers have reported similar results with generic undergraduate career planning courses (Osborn et al., 2007; Saunders, Peterson, Sampson, & Reardon, 2000).

Researchers have studied structured career planning courses specific to STEM majors with much less frequency. In one such study, Prescod and colleagues (in press) found that students who took a STEM-focused career planning course scored lower on a measure of negative career thinking at the end of the semester. In a similar study, STEM-interested students in a STEM-focused career planning course had lower posttest scores on a measure of negative career thinking than declared STEM majors at the end of the same semester (Belser et al., 2018). Additionally, in a pilot study, Belser and colleagues (2017) found that greater reductions in negative career thinking predicted higher odds of being retained in a STEM major from the first to second year of college; in this same study, the authors found that students who participated in a STEM-focused career planning course were more likely to be retained in a STEM major than students in an alternative STEM course. Researchers have not given ample attention to determining how career planning and other career variables fit into predictive models of retention in STEM majors.

Statement of the Problem and Hypotheses

As previously noted, prior researchers have paid limited attention to developing predictive models that incorporate career development variables along with demographics and math performance. Developing effective predictive models has implications for researchers, career practitioners, higher education professionals, and the STEM workforce. To this end, the researchers intend to test two such models related to retention in STEM majors using the following hypotheses:

Hypothesis 1: First-year to second-year undergraduate retention in STEM majors can be predicted by ethnicity, gender, initial major, math placement–algebra scores, SAT math scores, STEM course participation, and Career Thoughts Inventory (CTI) change scores.

Hypothesis 2: First-year to third-year undergraduate retention in STEM majors can be predicted by ethnicity, gender, initial major, math placement–algebra scores, SAT math scores, STEM course participation, and CTI change scores.


In this study, researchers examined multi-year retention data for students in a STEM recruitment and retention program at a large research university in the Southeastern United States and utilized a quasi-experimental design with non-equivalent comparison groups (Campbell & Stanley, 1963; Gall, Gall, & Borg, 2007). Because this study was part of a larger research project, Institutional Review Board approval was already in place.

The COMPASS Program

The COMPASS Program (Convincing Outstanding Math-Potential Admits to Succeed in STEM; Dagley et al., 2016) is a National Science Foundation–funded project that seeks to recruit and retain undergraduate students in STEM majors. To enter the program, students must have a minimum SAT math score of 550, an undeclared major at the time of applying to the university and program, and an expressed interest in potentially pursuing a STEM degree. However, some students accepted to the COMPASS Program declare a STEM major between the time that they are accepted into the COMPASS Program and the first day of class, creating a second track of students who were initially uncommitted to a major at the time of application. Students in both tracks have access to math and science tutoring in a program-specific center on campus, are matched with undergraduate mentors from STEM majors, have access to cohort math classes for students within the program, and can choose to live in a residence hall area designated for COMPASS participants. Depending on which COMPASS track students are in, they either take a STEM-focused career planning course or a STEM seminar course during their first semester.

COMPASS participants who started college without a declared major take a STEM-focused career planning class in their first semester. The activities of this course include a battery of career assessments and opportunities to hear career presentations from STEM professionals, visit STEM research labs, and attend structured career planning activities (e.g., developing a career action plan, résumé and cover letter writing, small group discussions). The first author and fourth author served as instructors for this course, and both were counselor education doctoral students at the time.

Participants who had declared a STEM major between the time they were accepted into the COMPASS Program and the first day of class took a STEM seminar course instead of the career planning class. The structure of this course included activities designed to help students engage with and be successful in their selected STEM majors, including presentations on learning styles and strategies, time management, study skills, professional experiences appropriate for STEM majors, and strategies for engaging in undergraduate research. Guest speakers for the class focused more on providing students with information about how to be successful as a STEM student. The course did not include career planning or career decision-making activities specifically geared toward helping students decide on a major or career field. A science education doctoral student served as the instructor of record for the course, with graduate students from various STEM fields serving as teaching assistants.


The university’s Institutional Knowledge Management Office provided demographic data on program participants. Table 1 displays descriptive data for participants, organized by second-year retention data (i.e., retention from the first year of college to the second year of college, for Hypothesis 1) and third-year retention data (i.e., retention from the first year of college to the third year of college, for Hypothesis 2). The frequencies for the subcategories were smaller for the third-year retention data (Hypothesis 2) because fewer participants had matriculated this far during the life of the project. Table 1 also breaks down each subset of the data based on which students were retained in a STEM major and which were not retained.


Table 1

Descriptive Statistics for Categorical Variables

Second-Year Retention Descriptives Third-Year Retention Descriptives
Variables Retained Not Retained Total Retained Not Retained Total
n %a n %b n %c n %a n %b n %c
   Male 159   58.9   74   46.5 233   54.3   72   55.8   65   44.8 137   50.0
   Female 111   41.1   85   53.5 196   45.7   57   44.2   80   55.2 137   50.0
   Total 270 100.0 159 100.0 429 100.0 129 100.0 145 100.0 274 100.0
   Caucasian/White 147   54.4 100   62.9 247   57.6   66   51.2   85   58.6 151   55.1
   African Am./Black   31   11.5   16   10.1   47   11.0   16   12.4   18   12.4   34   12.4
   Hispanic   57   21.1   34   21.4   91   21.2   29   22.5   32   22.1   61   22.3
   Asian/Pacific Islander   24     8.9     4     2.5   28     6.5   10     7.8     5     3.4   15     5.5
   Other   11     4.1     5     3.1   16     3.7     8     6.2     5     3.4   13     4.7
   Total 270 100.0 159 100.0 429 100.0 129 100.0 145 100.0 274 100.0
   Career Planning 137   50.7 120   75.5 257   59.9   76   58.9 112   77.2 188   68.6
   STEM Seminar 133   49.3   39   24.5 172   40.1   53   41.1   33   22.8   86   31.4
   Total 270 100.0 159 100.0 429 100.0 129 100.0 145 100.0 274 100.0
Initial Major
   Undeclared 130   48.1   72   45.3 202   47.1   65   50.4   63   43.4 128   46.7
   STEM 124   45.9   40   25.2 164   38.2   55   42.6   39   26.9   94   34.3
   Non-STEM   16     5.9   47   29.6   63   14.7     9     7.0   43   29.7   52   19.0
   Total 270 100.0 159 100.0 429 100.0 129 100.0 145 100.0 274 100.0

Note. a = percentage of the Retained group. b = percentage of the Not Retained group. c = percentage of the Total group.


Gender representation within the two samples was split relatively evenly, with female participants represented at a higher rate in the sample than in the larger population of STEM undergraduates and at a higher rate than STEM professionals in the workforce. Both samples were predominantly Caucasian/White, with no other ethnic group making up more than one-fourth of either sample individually; these ethnicity breakdowns were reflective of the university’s undergraduate population and somewhat reflective of STEM disciplines. The students who took the STEM-focused career planning course accounted for a larger percentage of both total samples and also of the not-retained groups. Regarding initial major, the largest percentage of students fell within the initially undeclared category, with the next largest group being the initially STEM-declared group (these students officially declared a STEM major but were uncommitted with their decision).

The researchers conducted an a priori power analysis using G*Power 3 (Cohen, 1992; Faul, Erdfelder, Lang, & Buchner, 2007), and the overall samples of 429 and 271 were sufficient for the binary logistic regression. With logistic regression, the ratio of cases in each of the dependent outcomes (retained or not retained) to the number of independent variable predictors must be sufficient (Agresti, 2013; Hosmer, Lemeshow, & Sturdivant, 2013; Tabachnick & Fidell, 2013). Following Peduzzi, Concato, Kemper, Holford, and Feinstein’s (1996) rule of 10 cases per outcome per predictor, the samples were sufficient for all independent variables except ethnicity, which had multiple categories with fewer than 10 cases. However, Field (2009) and Vittinghoff and McCulloch (2006) recommended having a minimum of five cases per outcome per predictor, which the sample achieved for all independent variables.

Variables and Instruments

The analysis included 10 independent variables within the logistic regression models. The university’s Institutional Knowledge Management Office (IKMO) provided data for the four categorical variables displayed in Table 1 (gender, ethnicity, course, and initial major). Four of the independent variables represented the participants’ total and subscale scores on the CTI, which students completed in either the career planning course or the STEM seminar course. The other two independent variables were participants’ scores on the SAT math subtest and the university’s Math Placement Test–Algebra subscale; the IKMO provided these data as well.

Career Thoughts Inventory (CTI). The CTI includes 48 Likert-type items and seeks to measure respondents’ levels of negative career thinking (Sampson, Peterson, Lenz, Reardon, & Saunders, 1996a, 1996b). To complete the CTI, respondents read the 48 statements about careers and indicate how much they agree using a 4-point scale (strongly disagree to strongly agree). The CTI provides a total score and scores for three subscales: (a) Decision Making Confusion (DMC); (b) Commitment Anxiety (CA); and (c) External Conflict (EC). Completing the instrument yields raw scores for the assessment total and each of the three subscales, and a conversion table printed on the test booklet allows respondents to convert raw scores to T scores. Higher raw scores and T scores indicate a higher level of problematic thinking in each respective area, with T scores at or above 50 indicating clinical significance. For the college student norm group, internal consistency alpha coefficients were .96 for the total score and ranged from .77 to .94 for the three subscales (Sampson et al., 1996a, 1996b). With the sample in the present study, the researchers found acceptable alpha coefficients that were comparable to the norm group. The researchers used CTI change scores as predictors, calculated as the change in CTI total and subscale scores from the beginning to the end of either the career planning class or the STEM seminar class.

SAT Math. High school students take the SAT as a college admissions test typically in their junior and/or senior years (CollegeBoard, 2018). Although the SAT has four subtests, the researchers only used the math subtest in the present study. The math subtest is comprised of 54 questions or tasks in the areas of basic mathematics knowledge, advanced mathematics knowledge, managing complexity, and modeling and insight (CollegeBoard, 2018; Ewing, Huff, Andrews, & King, 2005). In a validation study of the SAT, Ewing et al. (2005) found an internal consistency alpha coefficient of .92 for the math subtest and alpha coefficients ranging from .68 to .81 for the four math skill areas. The researchers were unable to analyze psychometric properties of the SAT math test with the study sample because the university’s IKMO only provided composite and subtest total scores, rather than individual item responses.

Math Placement Test–Algebra Subtest. The Math Placement Test is a university-made assessment designed to measure mathematic competence in algebra, trigonometry, and pre-calculus that helps the university place students in their first math course at the university. All first-time undergraduate students at the university are required to take the test; when data collection began, the mandatory completion policy was not yet in place, so some earlier participants had missing data in this area. The test is structured so that all respondents first take the algebra subtest and if they achieve 70% accuracy, they move to the trigonometry and pre-calculus subtests. Similar to the SAT, the researchers were unable to analyze psychometric properties of the test because the IKMO provided only composite and subtest total scores.


Because the dependent variables (second-year retention and third-year retention) were dichotomous (i.e., retained or not retained), the researchers used the binary logistic regression procedure within SPSS Version 24 to analyze the data (Agresti, 2013; Hosmer et al., 2013; Tabachnick & Fidell, 2013). The purpose of binary logistic regression is to test predictors of the binary outcome by comparing the observed outcomes and the predicted outcomes first without any predictors and then with the chosen predictors (Hosmer et al., 2013). The researchers used a backward stepwise Wald approach, which enters all predictors into the model and removes the least significant predictors one by one until all of the remaining predictors fall within a specific p value range (Tabachnick & Fidell, 2013). The researchers chose to set the range as p ≤ .20 based on the recommendation of Hosmer et al. (2013).

Preliminary data analysis included identifying both univariate and multivariate outliers, which were removed from the data file; conducting a missing data analysis; and testing the statistical assumptions for logistic regression. There were no missing values for categorical variables, but the assessment variables (CTI, SAT, and Math Placement Test) did have missing values. Results from Little’s (1988) MCAR test in SPSS showed that these data were not missing completely at random (Chi-square = 839.606, df = 161, p < .001). The researchers chose to impute missing values using the Expectation Maximization procedure in SPSS (Dempster, Laird, & Rubin, 1977; Little & Rubin, 2002). The data met the statistical assumptions of binary logistic regression related to multicollinearity and linearity in the logit (Tabachnick & Fidell, 2013). As previously discussed, the data also sufficiently met the assumption regarding the ratio of cases to predictor variables, with the exception of the ethnicity variable; after removing outliers, the Asian/Pacific Islander subcategory in the non-retained outcome had only four cases, violating the Peduzzi et al. (1996) and Field (2009) recommendation of having at least five cases. However, because the goal was to test the ethnicity categories separately rather than collapsing them to fit the recommendation, and because Hosmer et al. (2013) noted this was a recommendation and not a rule, the researchers chose to keep the existing categories, noting the potential limitation when interpreting this variable.

The sections that follow provide the results from each of the hypotheses and interpretation of the findings.

Hypothesis 1

Hypothesis 1 stated that the independent variables could predict undergraduate STEM retention from Year 1 to Year 2. As stated previously, the backward stepwise Wald approach involved including all predictors initially and then removing predictors one by one based on p value until all remaining predictors fell within the p ≤ .20 range. This process took five steps, resulting in the removal of four variables with p values greater than .20: (a) CTI Commitment Anxiety Change, (b) CTI External Conflict Change, (c) Gender, and (d) CTI Decision Making Confusion Change, respectively. The model yielded a Chi-square value of 91.011 (df = 10, p < .001), a -2 Log likelihood of 453.488, a Cox and Snell R-square value of .198, and a Nagelkerke R-square value of .270. These R-square values indicate that the model can explain between approximately 20% and 27% of the variance in the outcome. The model had a good fit with the data, as evidenced by the Hosmer and Lemeshow Goodness of Fit Test (Chi-square = 6.273, df = 8, p = .617). The final model accurately predicted 73.4% of cases across groups; however, the model predicted the retained students more accurately (89.6% of cases) than the non-retained cases (45.8% of cases).

Table 2 explains how each of the six variables retained in the model contributed to the final model. The odds ratio represents an association between a particular independent variable and a particular outcome, or for this study, the extent that the independent variables predict membership in the retained outcome group. With categorical variables, this odds ratio represents the likelihood that being in a category increases the odds of being in the retained group over the reference category (i.e., African American/Black participants were 1.779 times more likely to be in the retained group than White/Caucasian students, who served as the reference category). With continuous variables, odds ratios represent the likelihood that quantifiable changes in the independent variables predict membership in the retained group (i.e., for every unit increase in SAT math score, the odds of being in the retained group increase 1.004 times). The interpretation of odds ratios allows them to be viewed as a measure of effect size, with odds ratios closer to 1.0 having a smaller effect (Tabachnick & Fidell, 2013).


Table 2

Variables in the Equation for Hypothesis 1

95% C.I. for O.R.
Variable B S.E. Wald O.R. Lower Upper
Ethnicity 10.319*
Ethnicity (African American/Black) .576 .393    2.148 1.779 .823 3.842
Ethnicity (Hispanic) .068 .290     .054 1.070 .606 1.889
Ethnicity (Asian/Pacific Islander) 1.889 .637 8.803** 6.615 1.899 23.041
Ethnicity (Other) .258 .714 .131 1.295 .320 5.246
Initial Major  35.824***
Initial Major (Declared STEM) .412 .265 2.422 1.511 .899 2.539
Initial Major (Declared Non-STEM) -1.944 .375 26.905*** .143 .069 .298
STEM Seminar (Non-CP) .850 .258 10.885** 2.340 1.412 3.879
SAT Math .004 .002 2.411 1.004 .999 1.008
Math Placement–Algebra .002 .002 2.080 1.002 .999 1.005
CTI Total Change .017 .007 5.546* 1.017 1.003 1.032
Constant -2.994 1.378 4.717 .050

 Note: B = Coefficient for the Constant; S.E. = Standard Error; O.R. = Odds Ratio; * p < .05; ** p < .01; *** p < .001.


With logistic regression, the Wald Chi-square test allows the researcher to determine a coefficient’s significance to the model (Tabachnick & Fidell, 2013). Based on this test, Initial Major was the most significant predictor to the model (p < .001). Students in the initially Declared STEM category were 1.511 times more likely to be in the retained group than those in the initially Undeclared category (the reference category); the odds of being in the retained group decreased by a factor of .143 for students in the initially Declared Non-STEM group. The STEM course was the predictor with the second most statistical significance (p < .01), with students in the STEM seminar class being 2.340 times more likely to be in the retained outcome than those in the career planning class. The CTI Total Change score was statistically significant (p < .05), indicating that for every unit increase in CTI Total Change score (i.e., the larger the decrease in score from pretest to posttest), the odds of being in the retained group increase by a factor of 1.017. Ethnicity was a statistically significant predictor (p < .05), with each subcategory having higher odds of being in the retained group than the White/Caucasian group; however, the researchers caution the reader to read these odds ratios for ethnicity with caution because of the number of cases in some categories. SAT Math and Math Placement–Algebra were not statistically significant, but still fell within the recommended inclusion range (p < .20).

Hypothesis 2

Hypothesis 2 stated that the independent variables could predict undergraduate STEM retention from Year 1 to Year 3. As stated previously, the backward stepwise Wald approach involved including all predictors initially and then removing predictors one by one based on p value until all remaining predictors fell within the p ≤ .20 range. This process took six steps, resulting in the removal of five variables with p values greater than .20: (a) CTI Commitment Anxiety Change, (b) CTI Decision Making Confusion Change, (c) Gender, (d) CTI External Conflict Change, and (e) CTI Total Change, respectively. The model yielded a Chi-square value of 55.835 (df = 9, p < .001), a -2 Log likelihood of 307.904, a Cox and Snell R-square value of .191, and a Nagelkerke R-square value of .255. These R-square values indicate that the model can explain between approximately 19% and 26% of the variance in the outcome. The model had a good fit with the data, as evidenced by the Hosmer and Lemeshow Goodness of Fit Test (Chi-square = 9.187, df = 8, p = .327). The model accurately predicted 70.0% of cases across groups. In this analysis, the model predicted the non-retained students more accurately (72.7% of cases) than the retained cases (66.9% of cases).

Table 3 explains how the variables within the model contributed to the final model. Based on the Wald test, Initial Major was the most significant predictor to the model (p < .001). Students in the initially Declared STEM category were 1.25 times more likely to be in the retained group than those in the initially Undeclared category (the reference category); the odds of being in the retained group decreased by a factor of .167 for students in the initially Declared Non-STEM group. The Math Placement–Algebra variable was statistically significant (p < .05), and the odds ratios indicated that for every unit increase in Math Placement–Algebra test score, the odds of being in the retained group are 1.005 higher. The STEM course variable was slightly outside the statistically significant range but fell within the inclusion range, with students in the STEM seminar class being 2.340 times more likely to be in the retained outcome than students in the career planning class. SAT Math was not statistically significant but still fell within the recommended inclusion range (p < .20). Ethnicity also was not a statistically significant predictor but fell within the inclusion range, with each subcategory having higher odds of being in the retained group than the White/Caucasian group; however, the researchers caution the reader to read these odds ratios for ethnicity with caution because of the number of cases in some categories.


Table 3

Variables in the Equation for Hypothesis 2

95% C.I. for O.R.
Variable B S.E. Wald O.R. Lower Upper
Ethnicity 6.445
Ethnicity (African American/Black) .542 .448 1.467 1.719 .715 4.134
Ethnicity (Hispanic) .243 .349 .484 1.275 .643 2.528
Ethnicity (Asian/Pacific Islander) 1.636 .698 5.494* 5.137 1.307 20.185
Ethnicity (Other) .403 .684 .347 1.497 .391 5.725
Initial Major 17.362**
Initial Major (Declared STEM) .223 .328 .460 1.250 .656 2.379
Initial Major (Declared non-STEM) -1.792 .468 14.664** .167 .067 .417
STEM Seminar (Non-CP) .588 .323 3.327 1.801 .957 3.389
SAT Math .004 .003 2.536 1.004 .999 1.010
Math Placement–Algebra .005 .002 5.449* 1.005 1.001 1.009
Constant -2.994 1.378 4.717 .050

Note: B = Coefficient for the Constant; S.E. = Standard Error; O.R. = Odds Ratio; * p < .05; *** p < .001.



The researchers sought to determine the degree to which a set of demographic variables, math scores, and career-related factors could predict undergraduate retention in STEM majors. Based on descriptive statistics, the participants are remaining in STEM majors at a higher rate than other nationwide samples (Chen & Soldner, 2013; Koenig, Schen, Edwards, & Bao, 2012). The sample

in this study was quite different based on gender than what is commonly cited in the literature; approximately 46% of the study’s sample was female, whereas the NCSES (2017) reported that white females made up approximately 31% of those in STEM fields, with minority females lagging significantly behind. The present study’s sample was more in line with national statistics with regard to ethnicity (NCSES, 2017; Palmer et al., 2011).

With Hypothesis 1, the researchers sought to improve on a pilot study (Belser et al., 2017) that did not include demographics or math-related variables. Adding these additional variables did improve the overall model fit and the accuracy of predicting non-retained students, but slightly decreased the accuracy of predicting retained students, as compared to the Belser et al. (2017) model. In addition to improving the model fit, adding in additional variables reversed the claim by Belser et al. (2017) that students in the STEM-focused career planning class were more likely to be retained than the STEM seminar students. In the present study, the STEM seminar students, who declared STEM majors prior to the first day of college, were more likely to be retained in STEM majors, which is in line with prior research connecting intended persistence in a STEM major to observed retention (Le et al., 2014; Lent et al., 2016).

With Hypothesis 2, the researchers sought to expand on the Belser et al. (2017) study by also predicting retention one year farther, into the third year of college. In this endeavor, the analysis yielded a model that still fit the data well. However, this model was much more accurate in predicting the non-retained students and was slightly less accurate in predicting the retained students, with the overall percentage of correct predictions similar to Hypothesis 1. This finding indicates that the included predictors may provide a more balanced ability to predict long-term retention in STEM majors than in just the first year. The initial major and STEM course variables performed similarly as in Hypothesis 1, and as such, similarly to prior research (Le et al., 2014; Lent et al., 2016).

Although sampling issues warrant the reader to read ethnicity results with caution, ethnicity did show to be a good predictor of retention in STEM majors with both Hypotheses 1 and 2. More noteworthy, the African American/Black and Hispanic students had higher odds of being retained. This is inconsistent with most research that shows underrepresented minorities as less likely to be retained in STEM majors (Chen & Soldner, 2013; Cundiff et al., 2013; Gayles & Ampaw, 2014); however, at least one study has previously found results in which ethnic minority students were more likely to be retained in STEM majors (Riegle-Crumb & King, 2010).

Gender was removed as a predictor from both models because of its statistical non-significance. Prior research has shown that females are less likely to be retained in STEM majors (Cundiff et al., 2013; Gayles & Ampaw, 2014; Riegle-Crumb et al., 2012), which separates this sample from prior studies. However, the COMPASS sample did have a larger representation of females than typically observed. Moreover, the COMPASS Program has been mindful of prior research related to gender and took steps to address gender concerns in program development (Dagley et al., 2016).

The continuous variables retained in the models showed only a mild effect on predicting STEM retention. The SAT Math and Math Placement–Algebra scores did perform consistently with prior research, in which higher math scores related to higher odds of retention (CollegeBoard, 2012; Crisp et al., 2009; Le et al., 2014; Mattern & Patterson, 2013; Rohr, 2012). The CTI variables that were retained in the models performed in line with the Belser et al. (2017) pilot study specific to STEM majors and with prior research examining negative career thoughts in undergraduate retention in other majors (Folsom, Peterson, Reardon, & Mann, 2005; Reardon et al., 2015).


Limitations and Implications

The present study has limitations, particularly with regard to research design, sampling, and instrumentation. First, the researchers used a comparison group design rather than a control group, and as such, there were certain observable differences between the two groups. Not having a control group limits the researchers’ ability to make causal claims regarding the predictor variables or the STEM career intervention. The researchers also only included a limited number of predictors; the inclusion of additional variables may have strengthened the models. Although the sample size was sufficient based on the a priori power analysis, the low number of participants in some of the categories may have resulted in overfitting or underfitting within the models. Finally, the researchers were not able to test psychometric properties of the SAT Math subtest or the Math Placement–Algebra subtest with this sample because of not having access to the participants’ item responses for each. The researchers attempted to mitigate limitations as much as possible and acknowledge that they can and should be improved upon in future research.

Future research in this area would benefit from the inclusion of a wider variety of predictor variables, such as math and science self-efficacy, outcome expectations, and internal processes observed with gender and ethnic minority groups (e.g., stereotype threat; Cundiff et al., 2013; Litzler et al., 2014). The researchers also recommend obtaining a larger representation of ethnic minority groups to ensure an adequate number of cases to effectively run the statistical procedure. Future researchers should consider more complex statistical procedures (e.g., structural equation modeling) and research designs (e.g., randomized control trials) to determine more causal relationships between predictors and the outcome variables.

Because the results of this study indicate that a more solidified major selection is associated with higher odds of retention in STEM majors, university career professionals and higher education professionals should strive to develop programming that helps students decide on a major earlier in their undergraduate careers. Structured career development work, often overlooked in undergraduate STEM programming, may be one such appropriate strategy. Additionally, any undergraduate STEM programming must be sensitive to demographic underrepresentation in STEM majors and the STEM workforce and should take steps to provide support for students in these underrepresented groups.

Similar to work with undergraduates, this study’s results provide a rationale for school counselors to engage students in STEM career work so that they can move toward a solidified STEM major prior to enrolling in college. The industry-specific career development work discussed within this study is just as important, if not more important, for students in K–12 settings. Moreover, school counselors, through their continued access to students, can serve as an access point for researchers to learn more about the STEM career development process at an earlier stage of the STEM pipeline. All of these endeavors point to the need for counselor educators to better prepare school counselors, college counselors, and career counselors to do work specifically with STEM and to become more involved in STEM career research.

In the present study, the researchers built upon prior research in the area of STEM retention to determine which variables can act as predictors of undergraduate STEM retention. The binary logistic regression procedure yielded two models that provide insight on how these variables operate individually and within the larger model. Finally, the researchers identified some key implications for counselors practicing in various settings and for researchers who are interested in answering some of the key questions that still exist with regard to STEM career development and retention.


Conflict of Interest and Funding Disclosure

Data collected in this study was part of a dissertation study by the first author. The dissertation was awarded the 2018 Dissertation Excellence Award by the National Board for Certified Counselors.



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Christopher T. Belser, NCC, is an assistant professor at the University of New Orleans. M. Ann Shillingford is an associate professor at the University of Central Florida. Andrew P. Daire is a dean at Virginia Commonwealth University. Diandra J. Prescod is an assistant professor at Pennsylvania State University. Melissa A. Dagley is an executive director at the University of Central Florida. Correspondence can be addressed to Christopher Belser, 2000 Lakeshore Drive, Bicentennial Education Center Room 174, New Orleans, LA 70148, ctbelser@uno.edu.

Career Counseling in Middle Schools: A Study of School Counselor Self-Efficacy

Carrie Sanders, Laura E. Welfare, Steve Culver

Students in K–12 schools benefit from career counseling as a means to improve their readiness for academic and career success. This quantitative study explored the career counseling self-efficacy of 143 practicing middle school counselors using the Career Counseling Self-Efficacy Scale-Modified and a subscale of the School Counselor Self-Efficacy Scale. Although school counselors were confident overall, evidence of specific areas of concern and limited time for career counseling was found. Results related to the importance of prior teaching experience in relation to career counseling self-efficacy also were highlighted. Implications for school counselors and policymakers include examining the amount of time school counselors spend on providing career counseling in comparison to time spent on non-counseling–related duties.

Keywords: career counseling, middle schools, school counselors, self-efficacy, time

All students in K–12 do not have the same exposure to career opportunities. Providing avenues for students to learn about and identify ways to access a variety of careers is the responsibility of counselors in the school setting. School counselors contribute to students’ development in the domains of academic, career, and social and emotional development through comprehensive school counseling programs (American School Counselor Association [ASCA], 2014). ASCA published ASCA Mindsets and Behaviors for Student Success: K–12 College and Career Readiness Standards for Every Student (2014), which offers a framework of desired mindsets and behaviors for college and career readiness. This resource and others highlight the importance of a school counselor’s work in the career domain. However, school counselors’ knowledge and self-efficacy in the career counseling field may impact their ability to be effective in this aspect of their work (O’Brien, Heppner, Flores, & Bikos, 1997; Perrone, Perrone, Chan, & Thomas, 2000). This quantitative study explored the career counseling self-efficacy of practicing middle school counselors. As students move through elementary and secondary school, they continuously learn valuable knowledge and skills to explore postsecondary options and prepare to enter into the world of work. Middle school is an important time in this continuum for students as they consider their future academic and career plans and identify pathways to achieve their goals. The results of this study, as well as results related to the amount of time middle school counselors spend providing career counseling, yielded valuable implications for school counselors, K–12 stakeholders, and counselor educators.

The Importance of Career Counseling

Students begin to develop career awareness in elementary school, explore careers during middle school, and move into career preparation and planning in high school. Career counseling connects the experiences students have in school to their future, which enhances academic motivation and provides meaning to and purpose for the work they are doing in school (Curry, Belser, & Binns, 2013; Scheel & Gonzalez, 2007). As children and adolescents learn about themselves and the world of work, they are more likely to make informed career decisions, value school, succeed academically, and engage in school offerings (Kenny, Blustein, Haase, Jackson, & Perry, 2006; Orthner, Jones-Sanpei, Akos, & Rose, 2013; Perry, Liu, & Pabian, 2010).

Career counseling is needed in middle school in order to inspire young adolescents to make preliminary career decisions, to prepare them to take desired high school classes, and to equip them for future career pathways (Akos, 2004; Osborn & Reardon, 2006). Curriculum that integrates postsecondary college and career options in middle school has the potential to provide support and motivation for students (Curry et al., 2013). This type of curriculum connects directly to the comprehensive school counseling program. In schools with fully implemented comprehensive counseling programs that include career counseling, students self-reported higher grades, perceived they are better prepared for the future, recognized the relevance of school, and experienced a sense of belonging and safety, more so than in schools with less comprehensive school counseling programs (Lapan, Gysbers, & Petroski, 2001; Lapan, Gysbers, & Sun, 1997). In summary, establishing connections between a student’s academic preparation and possible career options benefits students in various ways, and school counselors are essential guides in the career exploration process.

Career Counseling in Schools

Despite this empirical evidence of its importance (Anctil, Smith, Schenck, & Dahir, 2012; Barker & Satcher, 2000; Osborn & Baggerly, 2004), school counselors can face barriers to implementing career counseling, including limited time because of competing demands, negative perceptions about career counseling, and low school counselor self-efficacy. For example, school counselors are often called upon to perform non-counseling tasks that take time away from providing a comprehensive school counseling program. School counselors desire to be engaged in promoting positive student outcomes and would prefer to spend less time on non-counseling–related activities (Orthner et al., 2013; Scarborough & Culbreth, 2008). There is some evidence that the desire to spend more time on counseling applies directly to career counseling, as found in a study of school counselors at all levels (Osborn & Baggerly, 2004). But, other studies have found that some school counselors are uncertain about the importance of career counseling (Perrone et al., 2000). These findings may indicate that although there is a desire to spend more time providing career counseling, there is uncertainty about its value.

Another potential barrier that is a focus of this study is individual school counselor self-efficacy. Self-efficacy, a core construct in this study, centers on the belief one has in his or her ability to perform a task (Bandura, 1986, 1997; Eccles & Wigfield, 2002). Self-efficacy of school counselors would be defined as beliefs about their abilities to provide effective counseling services (Larson & Daniels, 1998). High self-efficacy among school counselors would promote adaptive delivery of school counseling services to meet the needs of diverse student populations (Bodenhorn & Skaggs, 2005; Larson & Daniels, 1998). Social cognitive career theory (Lent & Brown, 2006; Lent, Brown, & Hackett, 2000) offers a framework for understanding self-efficacy in action—that is, how it impacts the interactions between individuals, their behaviors, and their environments. O’Brien and Heppner (1996) explored social cognitive career theory as it applies to interest, engagement, and performance of career counseling.

The interaction between people, their behavior, and their environment provides a highly dynamic relationship. Performance in educational activities is the result of ability, self-efficacy beliefs, outcome expectations, and established goals. School counselors have varied training experiences and personal self-efficacy beliefs that impact the delivery of a career counseling program. A school counselor’s self-efficacy in career counseling can increase through four primary sources: personal performance, vicarious learning, social persuasion, and physiological and affective states (Bandura, 1997). School counselor self-efficacy may be influenced by many things such as graduate training, service learning, internships, professional development, and years of experience (Barbee, Scherer, & Combs, 2003; Lent, Hill, & Hoffman, 2003; O’Brien et al., 1997). Teaching is a related experience that may impact career counseling self-efficacy. Some authors have highlighted prior teaching experience as helpful in the preparation of school counselors; others have not found such evidence (Baker, 1994; Peterson & Deuschle, 2006; Smith, Crutchfield, & Culbreth, 2001). Skills school counselors use to provide classroom guidance, which is one delivery method for career counseling services, are similar skills to those used by effective teachers (Akos, Cockman, & Strickland, 2007; Bringman & Lee, 2008; Peterson & Deuschle, 2006), so it is reasonable to expect that school counselors without teaching experience may be less comfortable managing a classroom of students than those with teaching experience (Geltner & Clark, 2005; Peterson & Deuschle, 2006).

There are two studies that have explored self-efficacy of school counselors with and without prior teaching experience. Scoles (2011) compared self-efficacy of 129 school counselors serving across all grade levels and did not find a statistically significant difference between those with and without teaching experience. In contrast, Bodenhorn and Skaggs (2005) found that respondents with teaching experience (n = 183) reported significantly stronger self-efficacy than those without teaching experience (n = 42). These conflicting findings about the importance of prior teaching experience suggest that further study is warranted.

Purpose for the Study

Given the importance of beginning career exploration early and the essential role school counselors play in that process, this study focused on career counseling in the middle school setting. Understanding practicing school counselors’ self-efficacy and their time spent providing career counseling will help administrators and policymakers better understand ways to increase career counseling in middle schools. As such, the following research questions were posed: (1) What are middle school counselors’ levels of self-efficacy in career counseling? (2) How does middle school counselor self-efficacy in career counseling vary with previous K–12 teaching experience? and (3) What is the relationship between middle school counselor self-efficacy in career counseling and the amount of time spent providing career counseling?


A quantitative research design was used for this study. The researcher examined school counselor self-efficacy in the career counseling domain. A school counselor was invited to participate if he or she was a current middle school (sixth, seventh, or eighth grade) counselor in Virginia at the time of the study and his or her email information was provided on a district or school website. The electronic survey included three instruments: an information questionnaire that was used to collect data about personal experiences and training, the Career Counseling Self-Efficacy Scale-Modified (CCSES-Modified; O’Brien et al., 1997), and a subscale of the School Counselor Self-Efficacy Scale (SCSE-Subscale; Bodenhorn & Skaggs, 2005).

Descriptive statistics were compiled by computing means, standard deviations, and minimum and maximum scores for total career counseling self-efficacy, as identified by both the CCSES-Modified and the SCSE-Subscale independently. Means and standard deviations of the 25 items of the CCSES-Modified and the seven items of the SCSE-Subscale also were calculated.

Two analyses of variance (ANOVA) and a t-test were used to determine if there were statistically significant differences among means. Participants were given the opportunity to report their years of counseling experience both full- and part-time, and the researcher combined these to get a total number. This number was obtained by taking the total reported number of years as a full-time school counselor and adding that to .5 multiplied by the reported number of years as a part-time school counselor. Then, the researcher created discrete levels to represent groups of experience once the data had been collected in order to conduct the analysis. Identifying the range of experience of the sample and using a scale appropriate for the sample determined the discrete levels. These three levels represented those who had the least experience, those in the middle, and those with the most experience as a school counselor. The researcher conducted an ANOVA with these groups and the SCSE-Subscale mean and a separate ANOVA with the identified groups and the CCSES-Modified mean.

The researcher obtained an answer of “yes” or “no” to indicate previous teaching experience. A separate value was given to answers of “yes” and “no” and the values were used to run a t-test with the mean for the SCSE-Subscale and the CCSES-Modified mean.

Participants indicated the total number of hours of conference presentations, workshops, or trainings that focused primarily on career counseling within the last 3 years. First, the researcher identified the range of the number of hours of training participants reported receiving in career counseling within the last 3 years. Then, the researcher created discrete levels to represent groups of recent training once the data was collected in order to conduct the analysis.

The third research question required a correlation to analyze the relationship between school counselor self-efficacy in career counseling and the amount of time (measured in percent) spent providing career counseling.


The participants for this study were practicing middle school counselors, defined as counselors working in a school housing students in grades 6 through 8 at the time the survey was completed. The data cleaning procedures described below resulted in 143 participants out of 567 invitations, which is a 25% response rate. Of the 143 participants, 23 (16.1%) were male and 117 (81.8%) were female (three participants omitted this item). Regarding race, 110 participants (76.9%) identified as White/Caucasian, 20 (14.0%) as African American, four (2.8%) as Hispanic/Latino, and one (0.7%) as Multiracial, while five (3.5%) preferred not to answer and three participants omitted this item. Participants’ ages ranged from 25 to over 65 years with an average age of 45 years (SD = 11; respondents who reported being 65 and over were coded as 65).

Regarding training, the participants reported their highest level of education: 125 participants (87.4%) reported having a master’s degree as their highest level of education, 11 (7.7%) had an education specialist degree, six (4.2%) reported having a doctoral degree, and one participant omitted this item. Participants reported a mean of 13.3 years (SD = 7.4) of experience providing school counseling. Regarding full-time teaching experience in a K–12 school, 47 (32.9%) participants had experience, while 94 (65.7%) did not have this experience, and two people omitted this item.


The 49-item online survey included 17 items to gather demographic and professional information, the 25-item CCSES-Modified (O’Brien et al., 1997), and seven items from the Career and Academic Development subscale of the SCSE (Bodenhorn & Skaggs, 2005).

Career Counseling Self-Efficacy Scale-Modified. The CCSES-Modified (O’Brien et al., 1997) was used to assess overall career counseling self-efficacy. Participants were asked to indicate their level of confidence in their ability to provide career counseling. For this study, the terms “client” and “career client” were replaced with the term “student” to be more congruent with school counselor terminology. Permission was granted from the first author of the scale to the researcher to make these changes (K. O’Brien, personal communication, January 7, 2013). The CCSES-Modified contains 25 items that are rated on a 5-point Likert-type scale (0 = Not Confident, 4 = Highly Confident). Within the CCSES-Modified, there are four subscales: Therapeutic Process and Alliance Skills, Vocational Assessment and Interpretation Skills, Multicultural Competency Skills, and Current Trends in the

World of Work, Ethics, and Career Research. The full scale has a reported internal consistency reliability coefficient of .96 (O’Brien et al., 1997).

 School Counselor Self-Efficacy Scale-Subscale. One subscale from the SCSE (Bodenhorn & Skaggs, 2005) was included in this study. The SCSE Career and Academic Development subscale was designed for school counselors to examine self-efficacy in the career domain. Using a 5-point Likert-type scale (1 = Not Confident, 5 = Highly Confident), participants indicated their level of confidence on each of the seven items. Bodenhorn and Skaggs (2005) reported a subscale internal consistency reliability coefficient of .85.

Indices of Reliability in the Present Study

The internal consistency reliability in this sample for the CCSES-Modified was α = 0.941 and the SCSE-Subscale was α = 0.871. The CCSES-Modified had four subscales: Therapeutic Process and Alliance Skills (10 items, α = 0.820), Vocational Assessment and Interpretation skills (6 items, α = 0.855), Multicultural Competency Skills (6 items, α = 0.913), and Current Trends in the World of Work, Ethics, and Career Research (3 items, α = 0.747). All of these exceed the common threshold for reliability for similar measures. The CCSES-Modified total score and the SCSE-Subscale score had a strong positive 2-tailed Pearson correlation (0.792), which was statistically significant at the 0.01 level. This strong positive relationship suggests these two measures captured related information from the participants.


The original sampling frame consisted of 576 middle school counselors with publicly available email addresses, which were collected from public school websites in all counties in Virginia. After Institutional Review Board approval was secured, participants were sent an email invitation with the informed consent and link to the web survey. One week later, participants were sent a reminder email. Upon completion of the survey, participants were given the opportunity to vote for one of five organizations to receive a $100 donation as a token of appreciation for their time completing the survey. After the recruitment email was sent, there were nine people who indicated they were not eligible to participate. These included three individuals who sent a return email indicating that they were out of the office during the survey administration, three who were not currently middle school counselors, two who reported needing school division approval, and one person who had difficulty accessing the survey. This reduced the actual sampling frame to 567.

Data Cleaning

One hundred and sixty-one respondents answered the survey items. There were 18 respondents who omitted 15% or more of the items from the CCSES-Modified or the SCSE-Subscale and were therefore removed from the study. This changed the total number of remaining respondents to 143. Of the 143 remaining, there were eight respondents who each omitted one item that was used to measure career counseling self-efficacy on the CCSES-Modified or the SCSE-Subscale. Each omitted item was replaced with the individual’s scale mean (e.g., mean imputation; Montiel-Overall, 2006), and those respondents were included in the analyses. When the omitted item was part of an analysis for Research Question 2 or 3, the respondent was removed from the affected analysis. Omissions on the demographic questionnaire are noted above in the description of the participants.


RQ1: What are school counselors’ levels of self-efficacy in career counseling?

Overall, middle school counselors who participated in this study were moderately confident, confident, or highly confident in their ability to provide career counseling services. According to the CCSES-Modified, counselors felt least confident in the subscales of Multicultural Competency Skills and Current Trends in the World of Work, Ethics, and Career Research, while they reported the most confidence in their Therapeutic Process and Alliance Skills. Specific areas of school counselor self-efficacy deficits were related to special issues present for lesbian, gay, and bisexual students in the workplace and in career decision-making, as well as special issues related to gender and ethnicity in the workplace and in career decision-making. Table 1 provides descriptive statistics and reliability for each subscale and the total scale.

Table 1 Career Counseling Self-Efficacy Scale-Modified Subscale Scores (N = 143)






Item M

Item SD

Therapeutic Process andAlliance Skills(10 items)








Vocational Assessment andInterpretation Skills(6 items)








Multicultural Competency Skills(6 items)








Current Trends in the World of Work,Ethics, and Career Research(3 items)








Total ScaleTotal Instrument Score (25 items)








Note. 1 = Not Confident and 4 = Highly Confident.

The means and standard deviations for the SCSE-Subscale are listed in Table 2. On average, participants were confident or highly confident in their abilities to attend to student career and academic development.

Table 2
School Counselor Self-Efficacy Scale-Subscale Individual Item Responses  (N = 143)

% Response








1. Implement a program which enables all students to make
informed career decisions.








2. Deliver age-appropriate programs through which students
acquire the skills needed to investigate the world of work.







3. Foster understanding of the relationship between learning
and work.







4. Teach students to apply problem-solving skills toward
their academic, personal, and career success.







5. Teach students how to apply time and task management







6. Offer appropriate explanations to students, parents, and
teachers of how learning styles affect school performance.







7. Use technology designed to support student successes and
progress through the educational system.







Total Subscale Score



Note. 1 = Not Confident, 3 = Moderately Confident, 5 = Highly Confident.

RQ2: How does school counselor self-efficacy in career counseling vary with previous K–12 teaching experience?

Two t-tests were conducted to identify if there was a difference between career counseling self-efficacy among participants with and without previous experience as a teacher. Separate means and standard deviations were calculated for the two groups—those who had teaching experience (n = 47) scored higher on the CCSES-Modified (M = 82.2, SD = 9.7) and the SCSE-Subscale (M = 30.9, SD = 3.4) than those without teaching experience (n = 94), CCSES-Modified (M = 75.8, SD = 14.7) and SCSE-Subscale (M = 29.4, SD = 4.3).

Independent t-tests were performed to determine if the differences between the groups were statistically significant. For the CCSES-Modified, the assumption of homogeneous variances was not satisfied (Levene’s test, F = 7.13, p < .05); therefore, the more conservative t-test was used to assess for a statistically significant difference (t = -3.06, p = .003). The mean score for the teaching experience group (M = 82.2, SD = 9.7) was statistically higher than the mean score for those without teaching experience (M = 75.8, SD = 14.7). For the SCSE-Subscale, the assumption of homogeneous variances was satisfied (Levene’s test, F = 3.71, p = .055, d = .51). The mean score of the group with teaching experience (M = 30.9, SD = 3.4, d = .39) was statistically different from the mean score of the group without teaching experience (M = 29.4, SD = 4.3), t = -2.03, p = .045. Cohen’s d is a valuable index of effect size for statistically significant mean differences (Cohen, 1988). The Cohen’s d of .51 for the CCSES-Modified and .39 for SCSE-Subscale both represent medium effect sizes.

RQ3: What is the relationship between middle school counselor self-efficacy in career counseling and the amount of time spent providing career counseling?

The third research question required a correlation to analyze the relationship between school counselor self-efficacy in career counseling and the percent of work time spent providing career counseling. Participants reported the percentage of time they spend providing responsive services to students in the three school counseling domains, as well as testing coordination and other non-counseling–related activities, which is represented in Table 3. The averages and standard deviations of the percentage of time spent in each subscale were: personal/social counseling (M = 36.25, SD = 15.39), academic counseling (M = 23.32, SD = 10.47), career counseling (M = 12.15, SD = 6.98), Virginia State Standards of Learning (SOL) testing coordination (M = 11.83, SD = 12.88), and other non-counseling–related activities (M = 16.44, SD = 12.55). One participant omitted this item; therefore, N = 142 in Table 3. There was no statistically significant relationship between the CCSES-Modified and time providing career counseling (r = .160, p = .057) and a statistically significant weak positive relationship (r = .286, p = .001) between the SCSE-Subscale and time providing career counseling.

Table 3 Self-Efficacy and Time Providing Career Counseling

  % Career Counseling

Career Counseling Self-Efficacy Scale-Modified Pearson Correlation


Sig. (2-tailed)




School Counselor Self-Efficacy Scale-Subscale Pearson Correlation


Sig. (2-tailed)




Note. *Correlation is significant at the 0.01 level (2-tailed)


There were several key findings from this study of middle school counselors’ self-efficacy with career counseling. First, it is important to note that there was a wide range in the total self-efficacy scores for middle school counselors. As a group, these counselors were the most confident in their Therapeutic Process and Alliance Skills, and least confident in Multicultural Competency Skills and Current Trends in the World of Work, Ethics, and Career Research. Specifically, special issues related to gender, ethnicity, and sexual orientation in career decision-making and in the workplace were areas of concern. School counselors who had previous K–12 teaching experience were significantly more confident providing career counseling than those without, as assessed by both measures. Finally, a Pearson correlation indicated there was a weak positive correlation between the SCSE-Subscale and the percentage of time school counselors indicated they spend providing career counseling. There was not a statistically significant relationship between the CCSES-Modified and time spent providing career counseling.

In this study, results indicate that middle school counselors spend more time doing non-counseling–related activities than providing career counseling, which is alarming. Career development is one of the three primary domains of a comprehensive school counseling program, and it is important for school counselors to create career development opportunities for students. The majority of school counselors report the importance of career counseling; however, middle school counselors acknowledge they spend less time on career counseling than they prefer (Osborn & Baggerly, 2004). There is a need to reprioritize career counseling, which includes recognizing and acknowledging how career counseling intersects with academic and personal and social counseling in K–12 schools (Anctil et al., 2012).

Career counseling is valuable and evidence needs to be provided to indicate how non-counseling–related tasks take time away from school counselors’ ability to offer adequate career counseling for students. Test coordination is time-consuming and an example of a non-counseling duty that some school counselors perform. Considering the amount of time this role requires, school counselors would find more time to provide career counseling services for students without this obligation. School counselors should gather evidence and provide accountability reports about how career counseling efforts contribute to student engagement and success.

Implications for School Counselors, K–12 Stakeholders, and Counselor Educators

In general, the practicing school counselors in this study had ample self-efficacy with regard to providing career counseling. However, there were certain items on the CCSES-Modified and the SCSE-Subscale that reveal discrepancies in middle school counselors’ levels of confidence. Counselors felt least confident in the subscales of Multicultural Competency Skills and Current Trends in the World of Work, Ethics, and Career Research. Specifically, they reported lower self-efficacy addressing special issues related to gender, ethnicity, and sexual orientation in relation to the world of work. In light of these findings, counselor preparation programs need to further investigate what is being taught in career counseling courses, how the content is being delivered, possible gaps in curriculum, and opportunities for outreach to current school counselors through continuing education. Given the powerful movement for advocacy related to these important social issues, it is in some ways confirming that the practicing counselors in this study felt less confident in these areas. Perhaps the national attention on issues of privilege and oppression related to gender, ethnicity, and sexual orientation has shed light on individual or systemic challenges these school counselors face as they try to serve diverse young adolescents in a dynamic phase of their development.

There are opportunities to increase career counseling self-efficacy related to gender, ethnicity, and sexual orientation in relation to the world of work. Bandura (1997) highlighted personal performance, vicarious learning, and social persuasion as particularly effective strategies for increasing self-efficacy. Continuing education, supervision, and professional organization engagement may be the best opportunities for continued development in these areas (Tang et al., 2004). In-service training and continuing education could be offered to provide school counselors relevant information to support their professional development and promote an increase in career counseling self-efficacy. Gaining up-to-date knowledge about the experiences of students with varied gender identities, ethnicities, and sexual orientations will best prepare school counselors to serve the entire student body. Observing advocacy approaches modeled by other leaders may inspire school counselors to use their voices in their own systems. Relatedly, this finding makes it apparent that K–12 school systems need clear and powerful policies and leadership around gender-, ethnicity-, and sexual orientation-related issues. School counselors are well positioned to partner with principals and superintendents in this important change process.

The second research question provided additional information about a somewhat contentious issue in previous research. School counselors who had teaching experience had higher career counseling self-efficacy than those who did not have teaching experience. This finding contradicts the findings of a study conducted with school counselors in Ohio (Scoles, 2011) and supports the findings of the national study conducted by Bodenhorn and Skaggs (2005), as described above. Contradictory findings like these beg for more research. Perhaps the higher self-efficacy of those with previous teaching experience is related to the preparation in specific academic disciplines that teachers receive. It could be that because these school counselors were previously trained in a specific academic area, they are more confident in talking with students about careers in that particular career cluster (e.g., science teachers who become school counselors may be more prepared to discuss careers in science, technology, engineering, and mathematics with students). Conversely, this potentially narrow view of career opportunities may limit the career exploration of students if school counselors do not include a wide array of career options. An excellent area for further research would be to identify how previous teaching experience may specifically impact school counselor self-efficacy.

School counselors without teaching experience, although lower in self-efficacy than those school counselors with teaching experience, still had high career counseling self-efficacy. This suggests that school counselors without teaching experience have confidence in their ability to provide career counseling. If, as Peterson and Deuschle (2006) suspected, the advantage of those with prior teaching experience is because of the increased training and practice in classroom management and lesson preparation, one would expect that effect to diminish as years of school counseling experience are accumulated. A larger sample than the one in this study would be necessary to test that empirically. If, however, the impetus for the significant impact of teaching experience is more general, those newer school counselors without teaching experience may be adjusting to the setting and to new ways of managing their time, balancing multiple roles and responsibilities, incorporating community involvement, working with parents, fostering collaborative relationships, and becoming familiar with local resources. All of these tasks take time and effort and could impact a school counselor’s self-efficacy to provide adequate services to students. It may be helpful for school counselors without teaching experience to ask for support and suggestions from seasoned school counselors in the district to learn from their experiences. In addition, professional development programming could be established for school counselors to become more familiar with the specific roles and responsibilities related to the career information, education, and counseling needs within a particular community.

Finally, the third focus of the study was on how school counselors use their time and if self-efficacy is related to that allocation. Most alarming about these findings was that school counselors are spending less time providing career counseling than they are doing non-counseling–related duties. A large percentage of middle school counselors’ time was reported to be spent coordinating testing or doing other non-counseling–related tasks, which is not the most efficient use of school counselors’ strengths. School counselors are uniquely trained to provide supplemental support for students in the academic, personal and social, and career domains in order to promote student success; therefore, it would be advantageous if they were able to utilize their time in a way that is consistent with the needs of students. One option to address the time constraint, particularly in this day of tighter budgets, is to utilize someone with an administrative background for the non-counseling duties in order for the school counselor to have time to incorporate adequate career counseling into their school counseling program. This is particularly important for middle school counselors providing career counseling because middle school students are preparing academic and career plans that will serve as a guide through high school and postsecondary educational endeavors (Trusty, Niles, & Carney, 2005; Wimberly & Noeth, 2005).

The world of work is continually changing, which makes it important to be aware of the current trends in this area. As these changes happen, marginalized populations face unique issues in the area of career exploration and planning. Counselors need to be trained adequately to provide career counseling to clients. In addition to providing relevant information, promoting thoughtful reflection, and facilitating discussions for counselors-in-training, counselor educators could provide outreach and continuing education opportunities focused on career counseling.

Just as career counseling may be infused with academic and personal and social counseling for school counselors, counselor educators may consider infusing career counseling concepts throughout other courses and experiences during a training program. Counselor educators could model this authentic type of integration. Counselor educators could talk more about various career clusters and the value of career counseling throughout a training program rather than just in one specific course. Counselor educators may also facilitate discussions with counselors-in-training about their own career counseling experiences, allowing trainees time to reflect on their experience. In addition, trainees could talk about how they have worked with people in roles other than a counselor through the career exploration and planning process.

Counselors need to consider ways to utilize and increase the support of administration and teachers to identify what needs to change in order for them to reallocate their time so they are able to provide more career counseling. Providing evidence of the positive impact of their work may be an effective strategy. There are many approaches to this, such as utilizing current research studies to communicate support for the value of career counseling efforts. In addition, school counselors can gather data from current students, parents, and alumni regarding their perception of and desire for career counseling services through surveys or focus groups. Once specific programs are implemented, school counselors can evaluate the outcomes of the career counseling efforts through both formal and informal assessment procedures with students, teachers, and parents. Administrators should continue to express support for the career counseling efforts of school counselors and show support by advocating for more personnel in order for students to receive adequate career counseling and to meet the demand of the non-counseling tasks that counselors are assigned.


The findings should be considered in light of the limitations of the study. Because of the nature of instruments that involve self-report, the results are based on the current perception of the participants and not objective assessments of the effectiveness of their work. Also, it may be more socially and professionally desirable to have confidence in personal abilities and, therefore, some participants may have answered the way they thought they should. This study was limited to those middle school counselors who had publically available e-mail addresses and were working in Virginia. Non-respondents and middle school counselors outside of Virginia are not represented in these findings; therefore, generalizing the findings should be considered with caution. Furthermore, the 406 non-respondents and the 18 respondents who did not complete the entire survey may be systematically different from the 143 respondents who were included.


This study has provided important new information about the self-efficacy of school counselors in the middle school setting as related to career counseling. Career counseling self-efficacy was high overall, with specific areas of deficit related to gender, ethnicity, and sexual orientation. Those school counselors who had previous teaching experience had even higher career counseling self-efficacy than those who did not. High self-efficacy in school counselors had little or no impact on the time spent providing career counseling services. Tailoring continuing education opportunities in career counseling and providing clear administrative leadership would further strengthen practicing school counselor self-efficacy. Utilizing support personnel for non-counseling–related duties may allow school counselors to use their career counseling skills and training to help middle school students explore and connect with careers, thereby improving academic and life outcomes.

Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest or funding contributions for the development of this manuscript.


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Carrie Sanders is a visiting assistant professor at Virginia Tech. Laura E. Welfare, NCC, is an associate professor at Virginia Tech. Steve Culver is Director of Assessment and Analytics at North Carolina A&T State University. Correspondence may be addressed to Carrie Sanders, 1750 Kraft Drive, Suite 2005, Blacksburg, VA 24061, cbrill@vt.edu.

School Counselors’ Perceptions of Competency in Career Counseling

Leann Wyrick Morgan, Mary Ellen Greenwaldt, Kevin P. Gosselin

The National Office for School Counselor Advocacy stated that secondary students need better support from professional school counselors when making decisions regarding their postsecondary education and career. The present qualitative study explored school counselors’ perceptions of competence in the area of career counseling, and resulted in the following themes: challenges to delivery, opportunity, self-doubt, reliance on colleagues, and the use of technology. Recommendations for college and career readiness best practice were incorporated with the findings from the National Office for School Counselor Advocacy report.

Keywords: school counselor, career counseling, competence, postsecondary education, qualitative study


No step in life, unless it may be the choice of a husband or wife, is more important than the choice of a vocation. . . . These vital problems should be solved in a careful, scientific way, with due regard to each person’s aptitudes, abilities, ambitions, resources, and limitations, and the relations of these elements to the conditions of success in different industries. (Parsons, 1909, p. 3)

Young people exploring career decisions are often left to their own searches to find direction in this complex process. Ninety-five percent of high school seniors expect to attain some form of college education, yet more and more are delaying entry after high school, frequently changing colleges or majors when they do enter, or taking time off throughout their programs (Altbach, Gumport, & Berdahl, 2011). According to The College Board National Office for School Counselor Advocacy (NOSCA), professional school counselors need to better support students during the decision-making process in order to streamline their progress toward postsecondary education and career readiness (Barker & Satcher, 2000; Bridgeland & Bruce, 2014). School counselors must balance this heady task with accountability in other areas, such as academic achievement, social and emotional development, and related administrative duties.

The American School Counselor Association (ASCA) National Model for School Counseling (ASCA Model) was developed and recently updated by the Recognized ASCA Model Program (RAMP), which supports school counselors and counselor educators by standardizing and enhancing the practices of these professionals (ASCA, 2012). With the release of NOSCA’s survey results, a new movement in school counselor reform emerged, which calls for standardization of practices involving college access for all students. According to The College Board (Bridgeland & Bruce, 2014), this reform is necessary to highlight the lack of support students receive in their pursuit of higher educational goal attainment.

School counselors have historically lacked a clear identity in role and function (Bridgeland & Bruce, 2014; Clemens, Milsom, & Cashwell, 2009; Dodson, 2009; Johnson, Rochkind, & Ott, 2010; Reiner, Colbert, & Pérusse, 2009), and in response, many states have adopted the use of some form of the ASCA Model as a guide for practicing school counselors (Martin & Carey, 2012; Martin, Carey, & DeCoster, 2009). Not all states provide such guidance for their school counselors and, as a result, some school counselors are left with little continuity among schools, even within the same school district. Some counselor educators have called for more support and supervision for school counselors (Brott, 2006; DeVoss & Andrews, 2006; Somody, Henderson, Cook, & Zambrano, 2008); however, a gap between education and professional responsibility, and consequently liability, has remained apparent (Foster, Young, & Hermann, 2005; Pérusse & Goodnough, 2005). It is important to note that the aforementioned reform is linked directly to the roles and functions of school counselors (Clemens, Milsom, & Cashwell, 2009; Pérusse & Goodnough, 2005). According to NOSCA, 71% of school counselors surveyed stated that they believed academic planning related to college and career readiness was important, but only 31% believed their school was successful in fulfilling students’ needs in that area (Bridgeland & Bruce, 2014). The gap between what they believe to be important and how they deliver information and assist students in using the information is critical.

To successfully bridge the gap and provide students with a consistent avenue for college and career readiness, more attention must be directed toward training school counselors and clearly defining the roles and functions of school counselors to other school professionals (Dodson, 2009; Mason & McMahon, 2009; McMahon, Mason, & Paisley, 2009; Reiner, Colbert, & Pérusse, 2009). Further inquiry is necessary to determine the possible impact of revised training and practice on the profession as well as on school counselors’ relationships with students, parents and the school community stakeholders. Counselor educators are not solely responsible for the role development of the school counselors they train; however, they have an increased personal responsibility as well (Paisley & Milsom, 2007; Pérusse & Goodnough, 2005). Consistent dialogue between counselor educators and school counselors-in-training regarding role competence in career development may provide an avenue to overall effectiveness.

Currently, professional school counselors are expected to offer comprehensive, well-balanced, developmental, evidence-based school counseling programs that target social and emotional supportive services, educational and academic planning, and vocational education for all students (ASCA, 2003; Campbell & Dahir, 1997; Dugger & Boshoven, 2010; Foster et al., 2005; Martin & Carey, 2012; Martin et al., 2009; Pérusse & Goodnough, 2005). However, high school counselors continue to be scrutinized in light of the poor marks they receive from high school students and graduates regarding the counselors’ involvement in their respective postsecondary planning processes (Gibbons, Borders, Wiles, Stephan, & Davis, 2006; Johnson et al., 2010).

School counselors serve in multiple­—and often demanding—educational and counseling roles. In addition, school counselors are asked to further the academic and educational missions of the school, seek teacher and administrator buy-in to an integrated comprehensive guidance program, and act in a proactive manner that will enhance collaboration among all facets of the school and community (Brown, 2006; Dodson, 2009; Green & Keys, 2001; Walsh, Barrett, & DePaul, 2007). Keeping these functions in mind, one can see how critical it is for school counselors to develop particular skills in order to provide services, to promote a strong professional identity, and to obtain regular supervision and consultation (McMahon et al., 2009).

In many cases, school counselors develop competencies in their roles while performing the duties assigned by their administrators or counseling supervisors; however, the basic educational training that occurs preservice can vary dramatically. In the field of counselor education, many issues impact the curriculum and philosophy of school counselor training programs including (a) the accreditation of the program by the Council for Accreditation of Counseling and Related Educational Programs (CACREP) and (b) the degree to which programs offer training in how to utilize the ASCA Model (ASCA, 2003). The CACREP training standards have gained popularity among state certification and licensure boards (such as those in Louisiana and New Jersey), and some boards now require all candidates seeking certification or licensure to have completed CACREP-accredited counseling programs in order to be eligible for professional certification or licensure. Certainly, not all counselor training programs are CACREP-accredited, and those that are CACREP-accredited likely vary in how they address the standards. Yet, many school counselor trainees will encounter similar standards presented in the newly revised ASCA Model as they pursue state certification or become involved in ASCA as a student or professional member (ASCA, 2012).

The ASCA Model provides a tool for school counselors to design, coordinate, implement, manage and evaluate school counseling programs, but the specifics on how school counselors address each area varies (ASCA, 2012). School counselors are expected to demonstrate competency in the areas of academic achievement, social and emotional development, and career counseling. However, career counseling competency is often minimized in relation to other areas because the accountability measures are not fully developed. Also, the results cannot be determined until years after students leave high school (Belasco, 2013; McDonough, 2005), and due to so many commitments falling upon school counselors, their time to provide specific career interventions can be limited (Bryan, Moore-Thomas, Day-Vines, & Holcomb-McCoy, 2011; Deil-Amen & Tevis, 2010).

The leaders of ASCA (2012) have encouraged secondary school counselors to spend at least 40% of their day conducting career assessment, engaging in development and planning postsecondary activities with students (e.g., individual student responsive services, group guidance activities, college and career indirect services); yet, according to Clinedinst, Hurley, and Hawkins (2011), high school counselors devote only 23% of their time to this cause. School counselor education programs minimally address this disparity (Foster et al., 2005). Most programs offer one course in general career development theory, assessment and counseling, which would translate to roughly 6% of students’ training within a 48-hour program, and only 5% for programs requiring 60 credit hours of graduate work. Although CACREP (2009) has called for counselor educators to infuse career development throughout the program curricula, school counselors have reported they did not feel competent in the delivery of career programs (Bridgeland & Bruce, 2014).

Given the convergence of an increased number of school counselor education programs seeking accreditation (Urofsky, personal communication, March 28, 2014), increased calls for accountability in school counseling programs (Wilkerson, Pérusse, & Hughes, 2013), and the growing influence of the ASCA Model (Martin et al., 2009), it seems imperative that school counselors be prepared to address the vocational and transitional needs of the secondary student. A gap exists between what is expected and suggested by the national standards for a comprehensive guidance program and what is actually being taught in school counselor preparation programs, specifically in the area of college and career readiness (Bridgeland & Bruce, 2014; Clinedinst et al., 2011; Engberg & Gilbert, 2014; McDonough, 2005). School counselors must have an appropriate cache of career counseling techniques in order to be effective leaders, not just possess a basic understanding of career development theories (Zunker, 2012). Osborn and Baggerly (2004) suggested the following:

High school is a crucial time for students to make career and/or postsecondary training decisions. If there were any group of school counselors who needed to have a large proportion of their time devoted to career counseling, it would be high school counselors. (p. 55)

Bridgeland and Bruce (2014) stated in the NOSCA report that “counselors are also largely enthusiastic about supporting college and career readiness initiatives, but here again, do not think they have the support and resources to successfully promote their students’ postsecondary achievement” (p. 12).

Hines & Lemons (2011) proposed refocusing university training programs for school counselors to emphasize educational access, opportunity and equity in college, and career readiness, with an increased focus on interns utilizing college and career readiness curricula with students in their schools. They also recommended the revision of school counselor job descriptions to focus on postsecondary planning, the use of performance evaluations connected to student academic outcomes and college and career readiness standards, and the need for persistent professional development in order to cultivate effective college and career readiness counseling programs.

By continuing to examine school counselor training and consequent job competency standards, it may be possible to determine gaps in training and how counselors compensate for their lack of knowledge in serving their students. Career counseling theory and application play a role in how school counselors work with students in postsecondary planning, and where a lack of knowledge exists, a lack of services exists as well (Perrone, Perrone, Chan, & Thomas, 2000). The rising costs of higher education, paired with students’ lack of concise college and career planning, make the school counselor’s role more important than in past decades.


School Counseling

Borders and Drury (1992) determined that “school counseling interventions have a substantial impact on students’ educational and personal development. Individual and small-group counseling, classroom guidance, and consultation activities seem to contribute directly to students’ success in the classroom and beyond” (p. 495). School counselors have shared responsibility for students acquiring knowledge necessary for successful mastery of essential developmental skills at the secondary level (Myrick, 1987; Sears, 1999). The need for appropriate and relevant training of secondary school counselors is critical to ensure that the students they serve receive challenging academic paths that will impact their quality of life long after they leave high school (Erford, 2010).

The CACREP standards for counselor training serve as a guide for counselor education programs to include when determining elements and experiences essential for training competent school counselors. However, the standards were not established to provide any support or structure for the postgraduate professional working in the schools (Campbell & Dahir, 1997; Pérusse, Goodnough, & Noel, 2001). ASCA provides professional school counselors with support through the National Model to administer appropriate programming to students at the secondary level, including career planning. The question remains whether counselors-in-training receive access to the appropriate coursework and relevant experiences to adequately prepare them to fulfill their role in the schools, as suggested by historical perspectives (e.g., the vocational needs of students) and the current national standards for the profession.

The area of career development and postsecondary planning is one in which counselors-in-training may not receive adequate instruction or supervision (Barker & Satcher, 2000; Foster et al., 2005). With the acceptance of the 2016 CACREP standards revisions, counselor education programs would be required to demonstrate how they assess students’ competencies using data “gathered at multiple points and using multiple measures” (CACREP, 2014, p. 6). Counselor educators must determine how to measure competency in career development throughout their programs. Some programs offer one course in career counseling, development or assessment, while other programs may choose to meet the standards in other ways. While students may gain training experience in career counseling through internship hours at the master’s level, career development is not a required part of the internship experience. Through the use of standardized tests that measure students’ knowledge of career counseling theory (e.g., Counselor Preparation Comprehensive Examination, National Counselor Examination), counselor education programs would be partially meeting the requirements for CACREP accreditation under the new standards. Testing graduate students on their knowledge of career counseling theory, however, does not provide an indicator of the students’ ability to provide comprehensive career counseling programs upon graduation. Using multiple measures of competency throughout the program may be a more effective way to accurately measure professional skill and readiness to provide career services to students.

A recent review of the counseling and education literature yielded several articles confirming the deficiencies in school counselor training and the increased need for additional competence among school counselors to provide college and career readiness programming to students, including information on financial literacy and the cost of higher education (Belasco, 2013; Bridgeland & Bruce, 2014; Engberg & Gilbert, 2014). Some educators may argue that the standards have been infused throughout their school counselor training program curriculum, yet there is no evidence within the professional literature of a consistent standard of practice. As a result, the question remains: Can counselor educators provide the necessary curriculum and expect that counselors-in-training will retain enough information to be able to provide services competently to students?

The educational recommendations versus the professional expectations imposed upon the school counselor may seem unrealistic, and at times, inappropriate (Brott, 2006; Clinedinst et al., 2011; Foster et al., 2005). An inconsistency between the amount of preparation and the expectations of school counselors’ work roles is apparent (Dodson, 2009; Reiner, Colbert, & Pérusse, 2009) and is highlighted in the NOSCA report (Bridgeland & Bruce, 2014). One might wonder how and where school counselors obtain adequate preparation for their professional roles. The authors in this study attempted to explore and document this information within the context of the schools in which the participants worked. Once again, the need to reform school counselor education programs is evident, and the voices of these counselors may help identify the specific areas in which to begin.



The research questions proposed in this study were addressed using a qualitative research design. A phenomenological research inquiry (Creswell, 2013) was used to assess participants’ experiences, preparedness and perceptions of competency related to career counseling with high school students. The goals of using this approach stem from the core ideals of phenomenological research (Colaizzi, 1978; Osborne, 1990; Wertz, 2005), which seeks to understand “how human beings make sense of experience and transform experience into consciousness, both individually and as shared meaning” (Patton, 1990, p. 104). Based on the premise that human beings by nature strive for a sense of self in the world of work and the knowledge that they have to use in their work (Crotty, 1998), it was imperative to develop an awareness of the relationship between the data and the participants within the context of the study (McCroskey, 1997; Merriam, 1998). With this goal in mind, participant responses were assessed using the methodological processes of grounded theory, and shared meanings grounded in the data were further derived (Corbin & Strauss, 2008).


Participants were chosen using a purposeful and convenience criteria sampling method (Collins, Onwuegbuzie, & Jiao, 2007), and identified from the first author’s community network of school counselor colleagues located in two Midwestern states. These counselors referred other secondary school counselors in their communities to the current authors for potential participation in the study. To select the participants, the authors previewed a convenience sample of 18 secondary school counselors from urban, suburban and rural public schools. They chose specific participants based on differences in age, ethnicity, gender, number of years of experience as a high school counselor, and those who hold master’s degrees from both CACREP and non-CACREP programs. In an effort to diversify the sample, the authors did not select participants with similar characteristics. The authors directly contacted the identified school counselors, and the nine participants agreed to participate in the study (see Table 1 for identifying characteristics). Each participant and school name was changed to protect identity.


Table 1

School Counselor Participant Information and School Information

Participant Name

Participant Description

Graduate Program

Years of Experience

School Description


White female in her late 20s



Shermer High School: urban; public; 2000 students; 45% F/R lunch*; 41% White, 31.8% Asian, 18.8% Hispanic, 7.4% Black, .8% American Indian; 6 other counselors

White female in her mid-40s



Shermer High School: urban; public; 2000 students; 45% F/R lunch*; 41% White, 31.8% Asian, 18.8% Hispanic, 7.4% Black, .8% American Indian; 6 other counselors

White male in his late 50s



High Bridge High School: suburban; public; 2301 students; 18.4% F/R lunch*; 65.7% White, 16.3% Hispanic, 10.3% Asian, 5.7% Black, 1.8% Multiracial, .1% American Indian, .1% Native Hawaiian/Pacific Islander; 11 other counselors

White female in her early 50s



High Bridge High School: suburban; public; 2301 students; 18.4% F/R lunch*; 65.7% White, 16.3% Hispanic, 10.3% Asian, 5.7% Black, 1.8% Multiracial, .1% American Indian, .1% Native Hawaiian/Pacific Islander; 11 other counselors

White male in his early 30s



High Bridge High School: suburban; public; 2301 students; 18.4% F/R lunch*; 65.7% White, 16.3% Hispanic, 10.3% Asian, 5.7% Black, 1.8% Multiracial, .1% American Indian, .1% Native Hawaiian/Pacific Islander; 11 other counselors

White male in his early 60s



Mayfield High School: urban; public; 2058 students; 27% F/R lunch*; 45% White, 39% Black, 12% Hispanic, 2% Asian, 2% American Indian; 5 other counselors

Hispanic female in her late 30s



Ridgemont Jr./Sr. High School: rural; public; 222 students; 54% F/R lunch*; 65% Hispanic, 31% White, 3% Asian, 1% American Indian, 0% Black; no other school counselors in building

White female in her early 30s



Bedford High school: rural; public; 645 students; 10% F/R lunch*, 85% White, 12% Hispanic, 2% Asian, 1% American Indian, 0% Black; one other counselor

Hispanic female in her early 30s



Hill Valley High School: rural; public; 401 students; 52% Hispanic, 45% White, 2% American Indian, 1% Black, 0% Asian/Pacific Islander; no other counselor in building

 Note. All participant and school information has been changed to protect identities.

*Students receive free or reduced-fee lunch based on household income.


Procedures and Data Collection

As part of the data collection process, a personal audit trail (Merriam, 1998) was utilized to minimize and account for specific feelings or opinions formed by the primary investigator. As a former school counselor, the first author had areas of training, and professional and personal experiences that were similar to, or different from those of the research participants. The journal served as an appropriate place for the primary investigator to document feelings regarding these issues and issues of counselor training.

Merriam (1998) suggested that researchers share a common language with the participants of the study; to that end, in-depth, face-to-face, semi-structured interviews lasting 45–55 minutes were completed. The following nine research questions were asked:

Tell me about your overall experience in your counselor training program.

Tell me about your experiences in that program with regard to instruction you received in career development delivery models with high school students.

How has the training you received in career development prepared you for your work with students?

What type of continuing education training have you received in the area of career development since finishing your degree program?

Describe your level of confidence in your ability to provide students with career development information and guidance.

In what areas, if any, do you feel unsure (or less sure) of the information you are providing?

What would have aided you in attaining competency in career development and postsecondary planning?

How much career counseling did you do during your internship?

How did you see your preparedness in career development in relation to your colleagues’ preparedness?

The first author for the study recorded the interviews electronically and then transcribed or typed the interviews using a traditional word processing program. The information obtained from the transcripts was compiled into one data set, which represents the voices of all nine participants. This author also obtained official transcripts from the participants’ master’s degree programs in school counseling to track the number of courses they took in career counseling and development. The participants provided information regarding the accreditation status of their training program as CACREP or non-CACREP at the time they obtained their degrees. At the conclusion of each interview, the first author immediately moved to another location in order to write initial thoughts (i.e., field notes) regarding any physical or nonverbal responses of the participants. The first author wrote notes in a research journal regarding any personal researcher biases that emerged (Creswell, 2013). The field notes, transcript and program accreditation status served as additional data that were shared with the research team for triangulation purposes, specifically to enrich the data collected during each interview.



Interview data were subjected to a rigorous phenomenological reduction. Also known as bracketing (Husserl, 1977), this is the process of extracting significant statements from the actual, transcribed interviews with the participants. The authors utilized Denzin’s (1989) suggestions to extract statements, including (a) locating the key phrases and statements that speak directly to the phenomenon in question; (b) interpreting the meanings of these phrases as an informed reader; (c) obtaining the subjects’ interpretations of these phrases; (d) inspecting the meanings for what they reveal about the essential, recurring features of the phenomenon being studied; and (e) offering a tentative statement, or definition, of the phenomenon in terms of the essential recurring features (see Figure 1 for steps in analysis process).                    

Figure 1. Interview data steps

A total of 543 significant statements were analyzed and coded for inclusion in the theme-building process (Corbin & Strauss, 2008; Curry & Bickmore, 2012). The nine counselors’ statements were then grouped into categories as similarities emerged among them. This process gave each statement equal weight in contributing to the final analysis, regardless of which participant made the statement (Patton, 1990). New categories were formed until each statement had been grouped, totaling 17 in all. At the conclusion, the sample was determined rich enough to reach saturation. According to Creswell (2013), saturation occurs when pieces of information are put into categories and the researcher begins to see repetition among the data being categorized.



Once saturation was reached, the first author’s epoche (journal) was utilized to control for bias, and member checking was used to confirm the trustworthiness of the data. The act of member checking includes obtaining confirmation from the participants that the extracted statements from the interviews were accurate and inclusive (Creswell, 2013). Each of the nine participants reviewed their statements via e-mail and confirmed the accuracy and true representation of their thoughts and feelings. Triangulation of the data (i.e., comparing the researcher’s journal to the participants’ verified statements) further confirmed the results. At that point, imaginative variation and thematic reduction were employed to provide an organized, rich description of the participants’ experiences (Creswell, 2013).

Imaginative variation. The process of imaginative variation (Denzin, 1989) asks the researcher to horizontalize the data, or place the extracted significant statements of each participant side by side to compare, group and organize the statements into comprehensive ideas. The first author collected overall themes by physically cutting the statements out and dividing them into groups of similar statements. This process gave “each statement equal weight” in contributing to the final analysis, regardless of which participant made a particular statement (Patton, 1990). The deconstructed data set made the meanings of the participants’ stories clearer.

Thematic reduction: School counselor themes. The meanings derived from the counselors’ statements were grouped into common themes. The authors read and examined the counselors’ statements until words or phrases surfaced that represented patterns of feelings or thoughts that were repeated consistently throughout. These common words or phrases were grouped into major thematic areas that represented the collective voice of the participants.



Four themes emerged that indicated school counselors experienced feelings of under-preparedness in helping students plan for postsecondary pursuits, including (a) awareness (subtheme: feelings of incompetence), (b) theory versus reality (subtheme: disconnect of formal education), (c) acquiring competence (subthemes: colleague networks and technology), and (d) training needs (counselor education programs).

Awareness: Incompetence versus competence. Positive or desirable characteristics of a competent school counselor, particularly in the area of career development, were compiled to create a textural portrayal that illustrated the picture of a highly competent school counselor. Collectively, the participants indicated that a competent school counselor would have the following characteristics: (a) the ability to secure accurate information and provide it to students quickly, (b) active membership in state or national school counseling organizations, (c) use of professional networks for professional development, (d) well-maintained connections with students in spite of large caseloads, (e) outreach to marginalized student populations, and (f) personal respect and reflection of the role of a professional school counselor.

When the more specific themes were examined, the counselors described characteristics of the competency levels they possessed; however, they believed they were not living up to self-imposed standards. Most of the counselors’ statements referred to their perceived lack of competency in performing their roles in the schools, as opposed to positive feelings of competency. One of the participants, Vivian, stated, “A kid would come in and I would think, please, let’s talk about suicide or something because I am not so hot in this [career counseling] area.” This counselor considered herself more prepared to assess a student’s risk for self-harm than to help guide him or her toward a career path. Vivian believed that her training had inadequately prepared her, and did not remember what she was supposed to do to help students look beyond high school. She expressed frustration and the need for more tailored training, specifically on how to deliver comprehensive career and postsecondary planning curricula. Another participant, Noah, stated, “I am sure those kids know way more what their plans are going to be and what their options are than I do, and that is not the way it is supposed to work. It is something that I should know.” This counselor had become aware that he lacked the skills necessary to work with students, and his perceived helplessness prevented him from being engaged in the process. This school counselor needed resources to fill the gap and help him reach his students.

Theory versus reality. Throughout the dialogue with the participants, one common thread was that the formal instruction and implementation suggestions from their graduate training were inadequate. One participant, Noah, strongly voiced his concern with these training deficiencies by stating, “I don’t feel like I had enough [career training], it goes back to . . . well, they gave us theories. I did not get any specifics on how to use them.” Another counselor, Alan, stated, “We had a very good understanding of the theoretical [career counseling] model. It was very lacking in how to convey it to the kids or how you work with kids. This is where I think it came up short.” The voices of all the participants reflected this type of statement. Some of the participants believed that they had been introduced to career counseling theory and some assessment tools; however, they noted that they had not received sufficient instruction on how to apply these concepts when working with students. In addition, none of the participants were able to recall a particular standard for career assessment or planning for secondary school counseling that they might use as a guide when working in the schools.

Colleague networks. In order to combat the noted deficiencies, participants reported forming both formal and informal networks with other colleagues to gain competence in the area of career development. Noah stated, “Luckily I had a friend or two . . . who were good counselors and . . . I learned a lot from them.” The idea of learning how to create and implement career development programming on the job resonated throughout the participants. Diane stated, “I still know that at any time I can call somebody who will know something,” and Vivian said, “Thank God for other counselors because I wouldn’t know where to start.” The importance of colleague networks to the perceived competency of each counselor was made apparent by all the participants, not just the ones represented here. They seemed to rely on one another most often to supplement the gaps in information, more so than consulting other resources available to them.

Utilizing technology. The school counselors made numerous statements regarding the use of technology at their jobs. They mentioned the use of specific programs, and the consensus seemed to reflect that everyone used computer technology in some capacity. Some counselors believed that particular programs purchased by their districts were not useful to them, while others pointed to the use of computers as a resource for gaining competency in providing career development counseling to their students. Vivian stated, “We finally decided to go with the . . . [career development online program], which now has been probably the most used resource by our kids, by our staff, and by the counseling office simply because it is so easily accessible.” Alan also noted the following:

We got it [the online career development program] not only for the kids . . . but for the parents, the community, PR, and making ourselves a viable part of their development. . . . This has been a big plus for us because it forces contact with every kid in an easy, very positive type conference.

A third participant, Kimberly, recalled, “I can point them in the right direction now. The computer is so much easier and the students respond to it.”

The technology-based career development programs appeared to be used more readily by the counselors than any other counseling tool. Some of the benefits of technology-based programs include the following: Students can access information independently (autonomy), students can access career information from any computer at the school or from their homes (accessibility), and counselors can provide answers to students’ questions quickly (time-sensitivity). The computer-based, Internet programs gave confidence to the counselors that the information was up-to-date and accurate. They used the computer and Internet-based programs to work more efficiently and provide students with consistent, research-based career development programming. This resource provided school counselors with confidence where they lacked it prior to using these tools.

Training needs. Participants were forthcoming about what they needed; for example, they would have benefited from specialized training prior to starting their roles as professional school counselors. Throughout the interviews, the counselors interjected their dissatisfaction with their preparedness upon completing their master’s degree programs, to varying degrees. Interestingly, the statements grouped into the training needs category were not gathered in response to a particular question, but rather as they naturally occurred throughout the interviews. Even the participants who stated they were satisfied with their training overall offered suggestions for improving school counselor training programs based on their unique experiences in the field.

Vanessa stated the following:

I think as school counselors, the counseling part one-on-one we see once [in] awhile, but it is geared more towards career and preparing the kids. . . . I think one thing that would have helped me a lot was maybe having college recruiters or admission counselors come into the class and talk about what they look for on an application or in essay questions. I think that would have helped me help my seniors this year.

Similarly, Diane said that it would have been helpful to know “just the day-to-day what does a career counseling program look like or what does a career counseling program in a high school look like?” Other participants did not identify specific training areas that would have helped them; but they acknowledged that continuing education was necessary based on what was provided in their graduate programs. Kimberly reflected, “I would say that out of the 75 kids that we have [grades] 9–12, I would say maybe 20% have a skill that they can use if they were to drop out of school. It is one area that I am really not comfortable in right now.” School counselors carry the responsibility to prepare students for post-graduation, but how they accomplish this task is left to the specific counselor, school or school district.

Jane’s statement reflects her desire for more specific training curricula:

I think that training programs hopefully will evolve and will begin to become more specialized . . . it [career development] is definitely an area that needs more than one class. Three credit hours when 55 are required? It is probably one of the most important things for school counselors to know.

Few counselors echoed this call for more coursework, but specialized training in and out of the classroom was seen as a necessary part of gaining competency for all participants. While a number of the participants were passionate about the idea of increasing training in career development within counseling training programs, the collective voice of the counselors’ statements demonstrated the variety of struggles and frustrations the participants encountered, and still encounter, along the way.



The purpose of this study was to understand how school counselors view their roles, and how they understand and deliver career counseling curricula to students. Nine counselors made statements consistent with feelings of inadequacy and incompetence in their ability to provide adequate career development programming to their students, as well as unpreparedness upon completion of their counselor education programs. The findings are consistent with the reviewed literature, given that even those counselors who made positive statements regarding their overall experiences in their programs clearly reflected uncertainty regarding their competence level in career development in general (Bridgeland & Bruce, 2014; McDonough, 2005), but especially in how to deliver useful career programs to students (Clinedinst et al., 2011; Johnson et al., 2010). The particular training programs that these counselors completed to obtain licensure differed. Additionally, the secondary data collected from participants (i.e., CACREP vs. non-CACREP degree programs) indicate that accreditation and the completion of a course in career theory and application appear irrelevant regarding the participants’ perceptions of overall competency.

The authors noticed that the agitation in the counselors’ voices subsided when they discussed the steps they took to gain competency in this area. For some participants, it was a friendly colleague who showed them the way it had always been done, or the discovery of a new online resource that helped them quickly provide answers to their students’ questions. The counselors identified specific strategies that they used to improve their competency, but said that they relied heavily on their professional networks for support.

The three urban counselors reported that they were more prepared than their colleagues were in terms of providing career development programming that utilized technology. The three rural and three suburban counselors believed that they were close to or at the same level of competency as their colleagues. Additionally, all three urban counselors believed that funding or political obstacles within their respective districts prevented their success. Some participants also noted that they relied on technology because it had been purchased by their schools and was the only resource available. For a number of the participants, the isolation and lack of connection to other counselors furthered their sense of frustration and disconnectedness.

Participants employed professional mentoring and consultation in some cases; however, these counselors reported that they utilized informal, personal networking extensively. They described these relationships as casual, question-and-answer partnerships. These relationships were not formally structured with specific goals as in mentoring relationships, but rather were formed out of necessity for team building and information sharing among colleagues. The counselors valued these contacts more than any other resource they had acquired since completion of their degree programs.

The big picture of what it means to be a competent school counselor resonated loudly through the voices of the participants. They uniformly reported that despite their struggle to achieve competency, there was an overarching sense that their efforts were not enough. The counselors’ feelings of incompetence in the area of career development significantly impacted their ability to address the needs of students. The quiet desperation resonating in their statements magnified their perceptions of how they lacked what they needed to help prepare students for life after high school. School counselors have an understanding of who they would like to be in the schools, but oftentimes they believe they fall short (Scarborough & Culbreth, 2008). Many school counselors lack the confidence or competence to navigate the college counseling process effectively, thus leading to overall perceptions of incompetence in career development (Clinedinst et al., 2011; Engberg & Gilbert 2014).

The lack of competency in career development that these school counselors expressed may imply that a certain degree of insecurity and real or perceived incompetence are expected when one starts out in the field. However, if the degree of preparedness among these participants is at all representative, it may indicate that more focus on career development practice is needed in counselor education programs. According to Hill (2012), it is important to emphasize counselor-initiated strategies for college and career readiness interventions­­—something this group of school counselors found challenging. Addressing this need is a critical issue for school counselor educators as they design training curricula and experiences. Again, participants stated that they had received valuable information in their programs regarding the specifics of what career development is, but not how to use it with students. The missing link between knowledge and know-how for these counselors is palpable. School counselor educators and supervisors must take note and develop career counseling curricula that address the needs of their counselors-in-training, as well as the needs of the future students they will serve.



As a result of the information obtained from this study and with the support of the NOSCA report and other studies published in recent years, a need clearly exists for career development training standards to be integrated into graduate programs for school counselors (Bridgeland & Bruce, 2014; Clinedinst et al., 2011; Engberg & Gilbert, 2014). Specifically, counselor educators may adequately identify deficiencies in the overall training model by isolating the differences between anticipated transitions, role adoption and professional development. Participants in the present study believe that they and future school counselors would benefit from a more applied, community-based experience, much like the professional development schools model suggested by Clark and Horton-Parker (2002), and a standard of practice to better serve their students.

The plan outlined by NOSCA includes implementing a process by which all secondary school counselors follow a set of standards while working with students on college readiness from academic, social and career perspectives (Bridgeland & Bruce, 2014). Ideally, these standards would be consistent among school counselors across the country to ensure all students access to adequate college preparation and postsecondary planning. Graduate-level courses offered in the form of additional electives, such as counseling the college-bound student or career and technical education, would provide opportunities for growth in areas not currently available in most graduate counseling programs. In response to the growing need for high school counselor competency in postsecondary planning, some states are now offering an additional licensure endorsement for school counselors; for example, in Colorado, school counselors complete two graduate-level courses already offered within CACREP programs (i.e., individual counseling, career development) and one additional two-credit course in career and technical education, offered through the Colorado Community College System. Upon completion of the three courses, school counselors may then apply for the additional endorsement in career and technical education (Colorado Department of Education, 2014). This effort supports the Common Core Curriculum implementation in Colorado and many other states where school counselors are now expected to provide academic advising to directly reflect their students’ career cluster interests.

With the recent passing of the Langevin-Thompson Amendment to the Success and Opportunity through Quality Charter Schools Act (H.R. 10, 2014), school counselors working in charter schools will now be asked to provide documentation of their comprehensive career counseling programs in order for schools to obtain priority status when applying for federal funding. This movement, which currently applies only to charter schools, may begin to find its way into all public school funding requests, thus making career counseling curriculum development and implementation a priority for all school counselors. With the support of ASCA, the Association for Career and Technical Education, the National Education Association, the American Federation of Teachers, and the National Alliance for Public Charter Schools, this movement will continue to grow, and the need for well-trained school counselors who are able to provide comprehensive career counseling programs will increase.



In this study, the authors used several measures in order to preserve the internal validity of the study, such as researcher epoche, triangulation and member checking. In keeping with the tradition of qualitative research, the participants were not studied in isolation but in environments in which the studied phenomenon continues to occur. It is safe to assume that the participants’ statements were not without bias, because few inquiries involving human interactions and perceptions are without bias. The authors selected nine participants from a convenience sample of high school counselors from rural, suburban and urban areas within two Midwestern states in the United States. The relationship of the counselors to the first author, although limited, may have reflected a need to please or demonstrate competency where little may have existed. Despite the limitations of the study, the findings contribute to the literature regarding school counselors’ perceptions of their abilities to effectively deliver career counseling programs. Also, the findings further emphasize the need to reform the training methods through which school counselors provide college and career readiness services to students.



Given the results of this study, it would be negligent to ignore the possibility that school counselors may be placed in positions with less than adequate training in career development. Counselor education programs have an obligation to prepare school counselors in more role-specific areas (e.g., college and career readiness), given that the national average ratio of students to school counselor is 471:1, which is well above ASCA’s recommended ratio of 250:1 (http://www.schoolcounselor.org/asca/media/asca/home/ratios10-11.pdf). Doing more with less has always been a challenge for school leaders, and preparing school counselors more effectively to meet the needs of their students may empower a new generation of counselors to lead students into the 21st century workforce.

The authors acknowledge that this particular study includes only the voices of nine school counselors; however, their voices loudly echo NOSCA’s findings and support the need for school counselor standardization of practice in promoting, teaching and facilitating career and postsecondary planning for all students (Bridgeland & Bruce, 2014). Currently, most school counselor education programs do not highlight this area, yet this area represents the very heart of school counseling services at the secondary level. ASCA (2012) has deemed this area important enough to provide school counselors with standards with which to guide their daily activities, but training programs offer limited exposure to actual planning and implementation of career services. This study exposes a disconnection between training and practice standards in school counselor education, which has led to feelings of incompetence and discouragement in these nine school counselors. Regardless of how the counselors compensate for this lack of training, this phenomenon exists. Whether they graduated from CACREP or non-CACREP programs, all of the participants in this study believed that they were equally incompetent in providing career development programming to students. Therefore, future CACREP standards and ASCA Model revisions, as well as state credentialing boards, must include guidelines by which school counselors are trained, specifically reflecting their appropriate job duties and responsibilities in college and career readiness programming. Future school counselors may be better equipped to address the needs of their students, parents and communities if this area of training is expanded and integrated as an essential component of counselor education programs.


Conflict of Interest and Funding Disclosure

The authors reported no conflict of  interest or funding contributions for the development of this manuscript.



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Leann Wyrick Morgan is an assistant professor at the University of Colorado, Colorado Springs. Mary Ellen Greenwaldt is a family case worker for Licking County Job and Family Services, Children Services Division, in Newark, OH. Kevin P. Gosselin is an associate professor and assistant dean of research at Texas A&M Health Sciences Center. Correspondence can be addressed to Leann Wyrick Morgan, University of Colorado at Colorado Springs, College of Education, 1420 Austin Bluffs Parkway, Colorado Springs, CO 80918, lmorgan7@uccs.edu.

Career Development of Women in Academia: Traversing the Leaky Pipeline

Courtney E. Gasser, Katharine S. Shaffer

Women’s experiences in academia are laden with a fundamental set of issues pertaining to gender inequalities. A model reflecting women’s career development and experiences around their academic pipeline (or career in academia) is presented. This model further conveys a new perspective on the experiences of women academicians before, during and after their faculty appointments and can help in career counseling. Specifically, this model provides career counselors with a framework to conceptualize the concerns of women clients who work in academic environments. Other implications for career counseling as well as limitations and future directions also are discussed.

Keywords: women, academia, career development, pipeline, career counseling

There is a documented trend of women prematurely leaving higher education and academia. In a groundbreaking contribution spearheaded by women academicians, the Massachusetts Institute of Technology (MIT) Special Edition Newsletter reported on the experiences of women faculty, stating that “the pipeline leaks at every stage of career” (MIT, 1999, p. 8). Pipeline refers to careers in academia, which often require many years of education and training prior to entry to the pipeline. More recent work has supported and deepened this assertion with empirical investigation (e.g., Goulden, Mason, & Frasch, 2011; Wang & Degol, 2013). Researchers have approached the question of why this is the case from a myriad of research perspectives, including sociological, psychological and cultural. The existing body of literature investigating women’s experiences as academicians addresses the issue of women’s struggle for equality in the institution, but does not comprehensively address how female faculty develop their career aspirations and expectations, how the essential component of career development influences their experiences within the pipeline, and how counselors and institutions might address women’s career outcomes.


In this article, the authors first discuss the process of scholarly questioning, which guided the authors’ choice to examine certain bodies of literature that seemed relevant to women in academia. Second, a brief literature review identifies different variables that influence how women choose careers as academicians, how they decide whether to stay in those careers and how institutions have been called to respond to women’s experiences. Next, the authors present a model combining issues relevant to women in academia from the perspectives of several bodies of scholarly literature (i.e., sociology, women’s studies, psychology). The authors also make predictions based on the model, and address limitations and implications for counselors.


The idea for this article originated from a limited review of literature that addressed women as a cultural minority in a career field. Upon reviewing articles that centered on women in academia, the present authors observed that the vocational, cultural, social and psychological variables investigated in these studies focused substantially on women’s present experiences in academia—a realm often referred to as the pipeline. The present authors wondered how women’s life experiences before and after their faculty appointments influence their pipeline experiences.


The idea for the proposed model grew out of the literature review process itself. Through examining the available research on the subject of women in academia, it became clear that there were a multitude of perspectives on how and why women’s experiences exist as they do in the academic world. However, it also was apparent that these perspectives were not linked systematically to the overall literature. The primary goal of creating this model was to better understand and organize constructs that explain how women’s experiences before their career in academia, as well as how women experience that career. By organizing and linking these ideas into a model, the authors offer professional counselors a working model to refer to when helping academicians with career issues.




The authors utilized a qualitative research methodology in which they combined largely quantitative data with a qualitative analysis called grounded theory. According to Tesch (1990), grounded theory involves the “identifying and categorizing of elements and explanation of their connections” (p. 63), wherein one sorts the data into categories, compares their content, “defines properties of the categories” and then “relates categories to each other” (p. 64). The present authors modified their grounded theory approach by using published literature comprised mostly of quantitative studies as their data. As stated in the rationale for this paper in the previous section, the authors wanted to understand how women’s experiences leading up to and resulting in a career in academia, as well as how women experience that academic career. As is typical in qualitative research, these general questions served as their guide, and led to a generative process by which they surveyed the relevant literature of career development and gender as well as women’s academic careers. More precisely, the authors conducted the initial explorations of the literature using the key search terms women, academia or academe, faculty or professors, career development, and pipeline in various combinations to yield the largest body of results. The review process consisted of eliminating all articles concerning the academic experiences of women outside the United States, as this paper focuses exclusively on women within U.S. institutions. Throughout this process, the authors met weekly for at least 4 months and, beyond that, met 1–2 times a month for a minimum of 1 year. Also, two graduate student researchers made the initial classifications and the faculty subject matter expert reviewed those classifications, checking for consistency and accuracy.


The authors began by engaging in the strategy of inquiry called grounded theory. When reading through the collected literature, they noticed patterns in which variables (and later, themes) tended to appear again and again. Thus, the first major critical themes emerged through an inductive process, reflecting the grounded theory methods first championed by Glaser (Kelle, 2005). Glaser’s work focused on identifying similar codes whose content is gathered and organized into larger groups or concepts, and these groups or concepts form themes or categories (Kelle, 2005). Utilizing this approach in their exploration, the authors separated the articles into three groups based on their relevance to women across the career life span: early career development (preacademic appointment, which included experiences up to graduate school when some graduate students start participating in faculty and faculty-like roles), the pipeline (graduate school through academic job/career) and postpipeline (e.g., transitioning to a different career, retirement). It seemed important that these ideas present throughout the literature become more connected, and thus the present authors decided to create a model to show how person and environment interact to mold women’s expectations and experiences regarding education and career in academia. From this point forward, they carefully recorded the theoretical constructs and variables investigated by each research article and entered them into a spreadsheet. Once this process was complete, they critically reviewed the list of variables and constructs and collapsed some categories within each section together in order to capture both the broadest and the most succinct picture of the variables within the literature. Through this process, the authors were able to isolate the variables that were addressed by multiple articles (generally four or more), and these variables became the basis for the model.


Finally, the authors found that the variables tended to cluster together logically in each section. Through dialogue, critical thinking and specific knowledge within the field of vocational psychology, the authors categorized the variables into groups based on their similarity to and difference from one another, and created themes for the groups of variables within each section. These labels served to organize the variables into manageable concepts and tie the model together. In addition, these themes separated the larger social, psychological and systemic processes in ways that reflect how these concepts function for women in the world.


This literature review of over 120 articles revealed that, to the authors’ knowledge, no existing model binds career development and outcomes to the concepts of women’s career development and the leaky pipeline. Given the magnitude of such a project, the authors felt that it was best to create the model based on the research and resources that already exist in each area of scholarly inquiry. The variables and themes that exist in their model reflect their interpretation of the literature as well as their conceptualization of how these constructs interact with one another.


Variables Underlying Women Academicians’ Career Processes


Previous researchers have identified many variables related to women academicians’ career processes before, during and after their decision to pursue an academic job. The current authors reviewed and organized these variables by superordinate labels into the following three categories: career development, pipeline influences and pipeline outcomes.


Part I: Career Development

Excellent reviews of the literature on women’s general career development have been published (e.g., Betz, 2005; Fitzgerald, Fassinger, & Betz, 1995; Phillips & Imhoff, 1997). The current authors described variables important to women’s career development while they avoided recreating what others have already explored. Continuing with their modified grounded theory approach detailed above, for organizational purposes, the authors created five categories of variables and gave each category a superordinate label. The categories are cognitive, coping, environmental, personality and relational.


Cognitive theme. These variables were considered to be cognitive in nature: career aspirations, career choice, career expectations, intellectual abilities and liberal gender role attitudes.


Career aspirations. Career aspirations, or one’s dreams for one’s career, are important in career development and choice (Astin, 1984; Farmer, 1985; Gottfredson, 1981). Women’s career aspirations are affected by verbal ability, support from teachers, race, age and social class (Farmer, 1985); a desire for work–family balance and an intrinsic valuing of occupations (Frome, Alfeld, Eccles, & Barber, 2006); and parental influence (Li & Kerpelman, 2007).


     Career choice. Fitzgerald et al. (1995) addressed career choice by considering how it can be limited as a result of being female, pointing out how stereotyping of occupations and women’s compromised career aspirations work to limit women’s career choices.


     Career expectations. Brooks and Betz (1990) demonstrated that college student expectations for success in pursuing a job path, obtaining a job and advancing in that work, as well as preferences for a given type of work, explained 12%–41% of the variance in choosing a job. Men tended to have higher levels of expectations for more traditionally male occupations, whereas women tended to exhibit higher levels for more traditionally female occupations.


     Intellectual abilities. Women’s career development can be promoted with higher verbal and math abilities (Fassinger, 1990; O’Brien & Fassinger, 1993). Ceci, Williams, and Barnett (2009) found that women with high math abilities were more likely than men to also have high verbal abilities, resulting in a greater range of career choices.


Liberal gender role attitudes. Fassinger (1990) and O’Brien and Fassinger (1993) found that having more liberal attitudes toward one’s gender role regarding one’s roles in the family and in the workforce was related to and predictive of career choice. Flores and O’Brien (2002) found that liberal gender role attitudes were predictive of Mexican American adolescent women’s self-efficacy for nontraditional careers. Liberal gender role attitudes can increase women’s perceived career options, leading them to consider both traditional and nontraditional gender career choices.


Coping theme. The following variables involve coping: career decision-making coping, career maturity and adaptability, career self-efficacy, and self-esteem.


Career decision-making coping. Career decision-making coping can be defined as one’s perceived confidence (self-efficacy) and/or coping skills when making career decisions. O’Hare and Beutell (1987) examined gender differences in career decision-making coping with undergraduate college students. Men had significantly higher scores than women on career decision-making self-efficacy behavior, or “a constructive, positive sense of control over the decision” (O’Hare & Beutell, 1987, p. 177). However, women scored significantly higher on reactive behavior, wanting “to be superorganized and do all that is expected,” as well as support-seeking behavior (p. 177). Men tended to be more confident, likely because they are socialized to appear strong and confident to others. On the other hand, women tended to place importance on maintaining a relational style and reacting to situations as opposed to being proactive. Also, Betz, Hammond, and Multon (2005) found that career decision-making self-efficacy was negatively related to career indecision and positively related to career identity.


     Career maturity and adaptability. Career maturity means making good career decisions during adolescence (Super, 1977). King (1989) showed that career maturity determinants can differ by gender: for girls, family cohesion, locus of control, age and cultural participation were most important; however, for boys, age, locus of control, family cohesion and parental aspirations mattered more. Career adaptability is a postadolescence extension of career maturity, and has been linked with career self-efficacy, career interests and problem-solving ability (Rottinghaus, Day, & Borgen, 2005).


Career self-efficacy. Believing in one’s ability to perform career behaviors has been found to predict the number of career options considered (Betz & Hackett, 1981; Hackett, 1985), and is related to (r = .59) and predictive of career interests (Rottinghaus, Larson, & Borgen, 2003). Lower career self-efficacy beliefs predict women’s more traditional career choices (Hackett & Betz, 1981), while higher career self-efficacy beliefs predict career achievement (Betz, 2005).


     Self-esteem. Self-esteem affects career development and achievement, and “increases occupational prestige   . . . and income” (Kammeyer-Mueller, Judge, & Piccolo, 2008, p. 204). Self-esteem aids in persistence when one is confronted with career barriers (Richie et al., 1997).


Environmental theme. This group impacts one’s environment and includes the following: availability of resources and opportunities, low status of traditionally female jobs, previous work experience, social class and socioeconomic status, and socialization influences.


   Availability of resources and opportunities. Astin’s (1984) career choice model describes major concepts affecting women’s careers: work motivation, with the driving needs of survival, pleasure and contribution; gender role socialization; and structure of opportunity, which includes elements such as job availability, barriers to work opportunities and economic considerations. Astin suggested that differences in gender socialization produce different work expectations, ultimately limiting women’s career opportunities by what is seen as appropriate women’s work. However, some opportunities provide women with a greater range of work–family alternatives (e.g., reproductive technologies).


    Low status of traditionally female jobs. So-called women’s work has been devalued in terms of status and equitable pay. In paid work, there is a well-documented gap between women’s and men’s wages (e.g., Bielby & Bielby, 1992; Corbett & Hill, 2012). A number of authors have formed postulations about the low status of traditionally female jobs and career processes (e.g., England, 2010; Fassinger, 1990; O’Brien & Fassinger, 1993). For example, in order for women to advance socioculturally (e.g., economically), they must consider work in male-dominated fields, such as academia; higher status jobs in U.S. culture are jobs traditionally held by men (England, 2010).


     Previous work experience. Previous work experience during adolescence is predictive of career aspirations and career choice (Betz & Fitzgerald, 1987).


     Social class and socioeconomic status. Social class can shape career aspirations (Farmer, 1985). For example, social class privilege for European American adolescent women served to increase their perceptions of having many career options, as well as narrow the range of options they considered (Lapour & Heppner, 2009).


     Socialization influences. Exposure to environmental learning, or socialization, can shape an individual’s career processes. For instance, Gottfredson’s (1981) model of circumscription and compromise in career development describes how one’s environment and heredity impact his or her career. Leung, Ivey, and Suzuki (1994) found Asian American women more likely than European American women to consider nontraditional gender role careers in order to pursue higher prestige occupations—that is, prestige was most important to these women, as opposed to compromising based on gender role fit or perceived gender typing of certain jobs. For example, an Asian American woman might choose a career in engineering over a career in teaching, as the engineering career would have greater prestige but would be a less traditional career for women than teaching.


Personality theme. Personality variables include achievement motivation, career interests, instrumentality and other personality variables, and valuing graduate education.


   Achievement motivation. Achievement motivation refers to the impetus toward seeking career attainments and accomplishments. Two major models of women’s career development address achievement. In explaining gender differences in achievement by focusing on women’s decision making, Eccles (1987) proposed that the decisions women make regarding the work–family balance may be based on the subjective valuing of tasks as per socialization and stereotypes. Eccles suggested that some women may choose to focus more on family than work because other work is less satisfying to them than nurturing a family. In a different, empirically supported model, Farmer (1985) considered achievement motivation in career development to be influenced by cultural, personality and environmental factors. Achievement motivation culminates in the creation of career aspirations, motivation to pursue mastery experiences, and commitment to a career (Farmer, 1985).


     Career interests. Women are more likely to have higher career interest scores for artistic and social domains and lower scores for realistic and investigative domains, when compared with men (Betz, 2005; Fitzgerald et al., 1995). Additionally, Evans and Diekman (2009) investigated how the presence of gendered beliefs about careers predicted differences in career goals and career interests along traditional gender lines. Women and men who thought about careers in a gender-stereotypical manner were less likely to endorse career interests in gender-atypical fields (Evans & Diekman, 2009).


     Instrumentality and other personality variables. Instrumentality, which is defined as the ability to make decisions with confidence, was examined by O’Brien and Fassinger (1993) in their test of the Fassinger (1990) career model. The authors concluded that “young women who possess liberal gender role attitudes, are instrumental and efficacious with regard to math and careers, and exhibit moderate degrees of attachment and independence from their mothers tend to value their career pursuits” (O’Brien & Fassinger, 1993, p. 466).


     Valuing graduate education. Battle and Wigfield (2002) found that college women with a strong career orientation had more positive views of graduate education, evidencing that the perceived usefulness of attending graduate school, a sense of attainment, and intrinsic motivation to pursue graduate studies were major reasons behind women’s graduate school plans.


Relational theme. The following variables have a central relationship component: dual roles of marital and parental status, perceived encouragement, psychosocial needs, relationships with parents and presence of role models, and rewards and costs of career and parenthood.


     Dual roles of marital and parental status. As Fassinger (1990) pointed out, past research has supported a negative relationship between being both a wife and mother and developing one’s career. However, having liberal gender role attitudes helps women engage more fully in their own career development as opposed to more traditional attitudes (Betz & Fitzgerald, 1987; Fassinger, 1990; Flores & O’Brien, 2002). Morrison, Rudd, and Nerad (2011) found that parenting young children was a barrier at all levels of the pipeline for women, and that married men advanced faster through the tenure process than married women.


     Perceived encouragement. Parents, role models, teachers and supportive others may offer women perceived encouragement regarding their career options (e.g., Fassinger, 1990; Leslie, 1986), ultimately facilitating women’s choice and attainment of both traditional and nontraditional careers (e.g., Hackett, Esposito, & O’Halloran, 1989). Perceived encouragement is especially important for the educational expectations and work identity of African American and Mexican American college students (Fisher & Padmawidjaja, 1999).


   Psychosocial needs. Although psychosocial needs may be individually defined, women share needs for survival, satisfaction and pleasure (see Eccles, 1987; Farmer, 1985). Work can provide important sources of satisfaction and pleasure as well as meet survival needs, and underutilization of abilities has been associated with lower levels of mental health (Betz, 2005).


     Relationships with parents and presence of role models. For college women, the positive influence of female teachers and high performance self-esteem (i.e., agency, or a feeling of being able to be autonomous) was most predictive of career salience (i.e., the importance of one’s career relative to one’s other roles) and educational aspirations (i.e., aspirations to pursue different levels of education). Also, having the positive influences of fathers and male teachers, as well as high performance self-esteem, predicted women wanting to pursue less traditional careers (Hackett et al., 1989).


     Rewards and costs of career and parenthood. Leslie (1986) found that the daughters of homemakers had more positive feelings toward employment when mothers were not satisfied with homemaking and the children helped more with housework. Daughters of employed mothers viewed employment more positively when they perceived their mothers as happy and busy with their work. Daughters of homemakers indicated most concern with the costs of work and the costs of having children in the future, whereas the daughters of employed mothers also were concerned with the rewards of work. Also, Campione (2008) found that depression stemmed from family issues (e.g., caring for a disabled family member) and work issues (e.g., working irregular hours at a job), and working shifts during odd hours was associated with marital stress and family difficulties.


Conclusion of Part I: Career Development. In Part I, the current authors reviewed evidence on variables pertinent to a woman developing her career as an academician, or having access to developing a job or career as an academician. The next section focuses on the pipeline.


Part II: Pipeline Influences

The present authors conceptualize the pipeline, or the route to an academic career and the academic career itself, as beginning in graduate school and extending through all stages of a career in academia. The career development literature focuses heavily on undergraduates, whose experiences the present authors consider to be separate from graduate student experiences, which are conceptually more proximal to and overlap with the concerns of academic careers. Thus, for the authors’ purposes, once a woman decides to pursue a graduate-level degree, her experiences are characterized as part of the pipeline. Again, the authors have grouped variables using superordinate labels. The themes include academic duties, academic environment, individually centered, resources and social variables.


Academic duties theme. In this section the authors describe variables associated with women’s status within the academic institution, including administrative-level representation, institutional housekeeping and service-oriented activities, teaching and research productivity, and tenure-track versus nontenure-track status.


     Administrative-level representation. Quite simply, women are not represented at the administrative level of academic institutions as frequently as men (Kimball, Watson, Canning, & Brady, 2001). Women’s underrepresentation can be associated with the amount of effort they have invested in teaching, mentoring and service, along with an inability to decline projects, which may compromise women’s career trajectory toward higher levels of authority within the institution. Kimball et al. (2001) suggested that women may not understand how to effectively negotiate the male-dominated and hierarchical structure of academia in order to fulfill broader career advancement desires.


     Institutional housekeeping and service-oriented activities. Bird, Litt, and Wang (2004) defined institutional housekeeping as “the invisible and supportive labor of women to improve women’s situation within the institution” (p. 195), based on Valian’s (1998) work. Valian (2005) described these activities as “low-visibility, low-power, low-reward, and labor-intensive” (p. 205). Women may often be called upon to participate on committees or in groups that bolster the department or institution with regard to advising and teaching, or even issues pertinent to women in the academy. Providing service work may detract from time performing research, which is often the most heavily weighted criterion for tenure decisions (Misra, Lundquist, Holmes, & Agiomavritis, 2011). On the other hand, service activities are recently gaining more recognition as an important component of tenure decisions (Sampson, Driscoll, Foulk, & Carroll, 2010).


     Teaching and research productivity. Data gathered for the MIT (1999) report on women faculty members revealed “inequitable distributions” regarding “teaching assignments” (p. 8). Women, by cultural standard, bear the weight of the more relational processes involved in academia (e.g., teaching, advising, mentoring), so research and administration are areas still disproportionately male dominated. A more recent study of university deans focused on what was considered important in achieving tenure, and supported the salience of research productivity above other faculty contributions such as service and, to some extent, teaching (Balogun, Sloan, & Germain, 2007). Furthermore, “heavy teaching workloads may be detrimental to the chances of obtaining tenure” (Balogun, Sloan, & Germain, 2006, p. 532).


     Tenure track versus nontenure track. Harper, Baldwin, Gansneder, and Chronister (2001) found stark differences between men and women faculty members in both the tenure-track and nontenure-track categories. Generally, they found that men spent the fewest number of hours teaching, with more time spent on administrative, research and other activities, while women in all categories spent a slightly larger percentage of their time teaching. Differences also were found between the tenure-track categories and the relative amounts of time spent teaching undergraduate courses, with nontenure-track faculty spending a majority of their time teaching undergraduate courses versus tenure-track faculty who are teaching graduate courses more (Harper et al., 2001). Generally speaking, women make up a much larger percentage of nontenure-track faculty (e.g., August & Waltman, 2004; Equal Rights Advocates [ERA], 2003). Often the issue of tenure is complicated for women due to role conflict related to childcare and its incompatibility with the demands of the tenure process (Comer & Stites-Doe, 2006; O’Laughlin & Bischoff, 2005; Stinchfield & Trepal, 2010). In addition, there are other complex processes that influence women’s ability to gain tenure, an overview of which is outside the scope of this article (see American Association of University Women [AAUW], 2004; Marchant, Bhattacharya, & Carnes, 2007; Park, 2007; Rudd, Morrison, Sadrozinski, Nerad, & Cerny, 2008).


     Academic environment theme. This theme focuses on variables that pertain to the college or university environment, and the literature is reviewed regarding departmental climate, isolation and invisibility, and transparency of departmental decision making (including tenure).


     Departmental climate. Various authors have described departmental climates within institutions as “hostile” (ERA, 2003, p. 3), “challenging and chilly” (August & Waltman, 2004, p. 179), and “toxic” (Hill, Leinbaugh, Bradley, & Hazler, 2005, p. 377). These authors also pointed out how the lack of a supportive departmental climate contributes to other issues women face as academicians, such as having less access to resources or feeling isolated.


     Isolation and invisibility. Winkler (2000) asserted that women faculty themselves define the limits of their productivity (which tends to be the largest factor in salary increase and tenure decisions) based on “feelings of exclusion, disconnectedness, marginalization, intellectual and social isolation, and limited access to resources” (p. 740). She also argued that women more than men tend to have more rigid and higher standards for quality over quantity in research, and that women may be more perfectionistic in research activities, which leads to a lower overall rate of publication.


     Transparency of departmental decision making (including tenure). August and Waltman (2004) investigated job satisfaction of faculty members and found that women at different levels of the tenure process were influenced by different job satisfaction criteria. All faculty women surveyed reported being impacted by the following: having a supportive relationship with the head or chair of the department, having a perceived ability to influence decisions made within their department and receiving an equitable salary as compared to others within the department. Tenured women rated the equitable salary and departmental influence variables as more significant. For nontenured women, level of influence was also significant.


     Individually centered theme. These psychosociocultural variables pertain to women as individuals, and include academic self-concept, age, and race and ethnicity, as well as gender schemas and feminism, and personal power and self-promoting behavior.


     Academic self-concept. Guidelines for mentorship posed by Williams-Nickelson (2009) include specific action components aimed at bolstering a woman graduate student’s academic self-concept, or an individual’s conception of herself as a student. Mentors should “facilitate independent thinking” and encourage mentees to “develop self-assurance,” “be mentored” and “be receptive to autonomy and divergence” (Williams-Nickelson, 2009, p. 289). Ülkü-Steiner, Kurtz-Costes, and Kinlaw (2000) found that women’s academic self-concept and mentor support (regardless of the mentor’s gender) in graduate programs best predicted women graduate students’ career commitment. In addition, women and men who were attending graduate school in a male-dominated department reported lower levels of academic self-concept than those in more gender-balanced programs (Ülkü-Steiner et al., 2000).


     Age. For women entering the academy 20 or more years ago, being an older student (after having children or supporting a partner through his or her career) could be a barrier to entrance into graduate school; some women, however, reported positive effects of being leaders and mentors as older graduate students (Bronstein, 2001). In addition, women reported feeling marginalized, being overlooked, being seen as a mom, and being overtly discriminated against in academia (Bronstein, 2001). Junior and senior women faculty also may experience rifts with one another based on different feelings about discrimination and inclusion (MIT, 1999). Furthermore, Jacobs and Winslow (2004) compiled data on faculty ages, tenure track, tenure status and job satisfaction, and found that the high-end child-bearing years for women (late 30s through early 40s) are spent working toward tenure, which complicates the work–family balance.


     Race and Ethnicity. There has been “no growth in the percentage of minority students receiving doctoral degrees since 1999” (Maton, Kohout, Wicherski, Leary, & Vinokurov, 2006, p. 126). Women of color are at a disadvantage before the pipeline even begins, a problem that persists through the academic career level, where they may experience marginalization, discrimination and microaggressions (Marbley, Wong, Santos-Hatchett, Pratt, & Jaddo, 2011). Thomas, Mack, Williams, and Perkins (1999) studied the effects of personal fulfillment (or an individual’s sense of meaning and/or satisfaction in life) on the research agendas of academicians who are women of color. Often, women of color who assume an outsider within­ stance (a professional orientation toward using one’s personal experiences and interests to fuel one’s research) may be disadvantaged for scholarly recognition and promotion, though researching topics of personal multicultural concern can increase one’s level of personal fulfillment (Thomas et al., 1999).


     Gender schemas and feminism. Gender schemas exist that work against women in male-dominated professional environments (Valian, 2005). Lynch (2008) touched on clashing life roles for women in the early pipeline. One recurring theme for the participants was women graduate students’ feeling that they had traded off their feminist ideals and independence by getting married and/or having children, and by being financially dependent on their husbands during their time in graduate school. Krefting (2003) discussed ambivalent sexism, which essentially contrasts the concepts of having “perceived competence” (i.e., masculine) and being “likeable” (i.e., feminine; p. 269). The intersection of these two concepts for women in competitive academic environments can be a conundrum: How does a woman garner respect for her competence when likability is the trait with which students and colleagues are most concerned?


     Personal power and self-promoting behavior. Kimball et al. (2001) posited that previous research has shown that women place more emphasis on “external attributions” than men (p. 136). That is, although men and women both believe that internal attributes such as intelligence and ambition contribute to one’s career success in academia, women place much greater weight on their social capital—for instance, the people they know and the prestige of their educating institution. These authors also discussed the fact that many women feel uncomfortable with the self-promoting behavior that may facilitate advancement in academia.


     Resources theme. This theme includes variables related to resources within institutions that impact women’s career paths as academicians, including access to resources; financial issues; and salary, rewards, and recognition.


     Access to resources. Krefting (2003) conceptualized women’s access to resources as an uphill climb. Whereas men are included in the network of those expected to succeed within academia, women are fighting for both inclusion and the resources to make them worthy of inclusion. Winkler (2000) also echoed Krefting’s (2003) notion that resources (and subsequently, productivity) flow from being included in “the networks in which ideas are generated and evaluated, in which human and material resources circulate, and in which advantages are exchanged” (2000, p. 740). MIT’s (1999) seminal report on women’s experiences as academics in its own School of Science uncovered “inequitable distributions . . . involving space, amount of 9-month salary paid from individual research grants, teaching assignments, awards and distinctions, inclusion on important committees and assignments within the department” (p. 7).


     Financial issues. Students in psychology doctoral programs tend to graduate with student loan amounts that exceed $75,000 (Williams-Nickelson, 2009). Springer, Parker, & Leviten-Reid (2009) discussed a multitude of stressors for graduate student parents, including lack of financial support, a struggle to afford childcare and FMLA leave issues. Lynch (2008) reported that the most common complaint of women graduate student mothers is a lack of financial support from their academic departments.


     Salary, rewards and recognition. August and Waltman’s (2004) survey uncovered that tenured women faculty’s career satisfaction was heavily influenced by their “salary comparable to similar peers” (p. 188). Harper et al. (2001) conducted a cross-discipline analysis of men’s and women’s experiences in academia and reported that “overall, men’s salaries appear to be more related to their disciplines and responsibilities while women’s salaries are more related to their tenure status and the degree they hold” (p. 248). In addition, Harper et al. (2001) noted that women tend to earn less because they are often employed in academic positions that pay less (e.g., nontenure track, assistant professor).


     Social theme. This theme subsumes the influence of family, work and peer relationship variables, including peer and mentor relationships; presence of women in the field and the decision to pursue a doctorate; and work and family issues such as parenthood, marriage and the division of responsibility.


Peer and mentor relationships. Several articles review or note the positive impact of supportive peer relationships on female graduate student success (Lynch, 2008; Ülkü-Steiner et al., 2000; Williams-Nickelson, 2009). Also, mentoring and advising relationships provide essential resources to women graduate students, including elements such as emotional support and professional guidance (Williams-Nickelson, 2009). Hill et al. (2005) outlined the importance of supportive peers and social/teaching environments as a factor of satisfaction in their study of women faculty members in counselor education. Also, Pruitt, Johnson, Catlin, and Knox (2010) found that women counseling psychology associate professors who were seeking promotion to full professor indicated that having the support of a current mentor was helpful. Compared to men, women typically place a higher value on a supportive work environment and may often find these types of relationships through service-oriented work in the institution (Bird et al., 2004; Kimball et al., 2001).


     Presence of women in the field and the decision to pursue a doctorate. Women are more likely to leak from the educational pipeline before doctoral completion, and they still earn less than men in the world of work (Ülkü-Steiner et al., 2000; Winkler, 2000). Ülkü-Steiner et al. (2000) found that the mere presence of women faculty in any academic department bolstered career commitment and academic self-concept for men and women doctoral students. Similarly, Winkler (2000) reported that women academicians benefit from relationships with female students and that female students tend to graduate more quickly when female faculty are present within the department. However, because women tend to be underrepresented as faculty members in general, there is an overall shortage of role models for women wishing to pursue doctoral education and become academicians themselves (August & Waltman, 2004; Harper et al., 2001).


     Work and family issues: Parenthood, marriage and division of responsibility. Springer et al. (2009) and Lynch (2008) discussed the unique role conflicts that occur early in the pipeline for women graduate students who also are mothers. These women often find themselves caught between their desire to excel in graduate school and to be a mother, and also experience challenges with respect to finding peer support from their non-mother peers.


Wolfinger, Mason, and Goulden (2008) conceptualized family and marriage as having a direct effect on the leaky pipeline when women are trying to earn tenure. Generally speaking, when family issues and domestic responsibilities are at stake, women academics receive less support from their male partners than men academics do from their female partners (Bird et al., 2004). However, evidence for the effect that children and marriage have on scholarly productivity paints a different picture. Winkler (2000) reviewed the literature and found that though women on the whole publish less than men, single women are less productive in publication than married women. Krefting (2003) reported that “neither marriage nor parenthood seems to affect women’s productivity (or men’s, Valian, 1998)” (p. 264).


Conclusion of Part II: Pipeline Influences. This section discussed the themes and variables that are relevant to women’s experiences in the pipeline as graduate students and as academicians. The final section addresses key outcomes.


Part III: Pipeline Outcomes

     The following section examines academic women’s career outcomes and satisfaction as well as institutional responses to women’s issues. The literature search for this section included the search terms women’s career satisfaction, women in academia, and university (or college) response.


     Women’s career outcomes and satisfaction. As discussed previously, fewer women are granted tenure than their male counterparts. As one travels through the pipeline, chances of leaking out are greater for women at all stages of their career than for men (Mason & Goulden, 2004; Winkler, 2000; Wolfinger et al., 2008). In August and Waltman’s (2004) study, women’s career satisfaction was predicted by “departmental climate; the quality of student relationships and such related activities as mentoring and advising students . . . ; a supportive relationship with the unit chairperson; and the level of influence within the department or unit” (p. 187). In addition, for tenured women faculty, “comparable salary and the importance of departmental influence” rose to the forefront (p. 187). Harper et al. (2001) found that both tenured and tenure-track women were “least satisfied with their authority to make other job decisions . . . and the time they have available to advise students. . . . Non-tenure-track women as a group were the least satisfied with their authority to decide which courses they teach” (p. 251).


     Institutional response. The call for institutional change to address the needs of women academicians is a direct result of research conducted on this topic in the past several decades. Although a full review of institutional initiatives on behalf of changing women’s experiences in academia is beyond the scope of this article, the current authors have highlighted some recommendations for change that exist in the literature.


Many authors have called for higher education institutions to implement initiatives to address the issues that women academics face (e.g., AAUW, 2004; ERA, 2003; MIT, 1999; Stinchfield & Trepal, 2010). Generally speaking, these initiatives include, but are not limited to the following: (a) changing hiring practices to seek out women and people of color for all faculty positions, especially tenure-track positions; (b) encouraging mentorship programs for faculty; (c) instituting policies in which the tenure clock may be stopped and restarted; (d) adjusting views on career commitment to accommodate academicians’ family and other responsibilities; (e) promoting women to higher-level administrative positions; (f) eliminating gender discrimination regarding salary and access to resources; (g) revising the tenure review process to include merits for service-oriented work; (h) making evaluation standards for tenure clear and transparent; (i) expanding understanding of the psychosociocultural variables that influence academicians differently; (j) conducting research on institutional policy and its effects on faculty members; (k) being active beyond hiring practices by encouraging women and people of color to pursue careers as academicians; and (l) being vigilant of and punitive toward gender discrimination taking place within the institution (Bird et al., 2004; Bronstein, 2001; ERA, 2003; Harper et al., 2001; Jacobs & Winslow, 2004; MIT, 1999; Thomas et al., 1999; Valian, 2005; Winkler, 2000).


Conclusion of Part III: Pipeline Outcomes. This section provided an overview of career outcomes and satisfaction among women academicians and how institutions have been called to respond to these issues. The following section reviews the authors’ model for women’s career processes in academia.


A Model for the Career Process of Women in Academia


Women’s career development is related to a variety of psychological, social and cultural influences. Researchers have studied many of these influences with girls and women, demonstrating the powerful effects shaping women’s career aspirations, choices and development. In the present authors’ model, career development influences, pipeline influences (factors affecting entry into academia), and pipeline outcomes (outcomes of a career in academia) are addressed. Here, the authors explain the structure of and rationales behind each section of the model (see Figure 1 and Table 1).


Overview of the Model

To promote parsimony of the literature and model coherence, the authors organized women’s career development influences into five major groups of variables: cognitive, coping, environmental, personality and relational. Each of these major themes is present within the top portion of Figure 1. These five domains of career development lead up to a decision to pursue a graduate degree, labeled “pursue terminal degree” in the model. The authors used the phrase “terminal degree” for the sake of simplicity, even though some employers and fields do not require a doctorate (e.g., school psychology).


While previous collegiate accomplishments certainly facilitate matriculation into a graduate program, the authors consider the pipeline as beginning in graduate school and continuing with women taking academic positions. The numerous variables affecting women’s experiences in academia are grouped into the following categories: academic duties, academic environments, individually centered, resources and social.


The pipeline is considered to be one piece, since the literature seemed to indicate this understanding and it resulted in the most parsimonious interpretation. However, future evidence may lead to consideration of the pipeline in two pieces, in which there is an early pipeline that focuses on graduate students and a midpipeline that pertains to women in academic positions. For example, some variables may not be relevant to graduate students (e.g., tenure-track versus nontenure-track), which lends support to the idea of breaking the pipeline into two groups. However, many variables have been found to be a consideration for both graduate students and academicians (e.g., age, work, family issues). Also, some variables that are currently considered part of one group may actually show evidence of salience with the other group (e.g., academic self-concept, financial issues). For now, since the themes seem interwoven with the experiences of both graduate students and academicians, the current authors have considered them together as one group.


Once a woman decides to pursue a graduate degree, a host of psychosociocultural factors begin to influence both her educational experiences and her experiences in academia. As the model shows, women may leak out of the pipeline at different points of their academic careers (i.e., early, mid- or late career), with early leaking meaning that one might never enter academe. The final section of the model indicates two major outcomes of women’s career development and the academic pipeline. First, women may report different levels of career satisfaction. Second, institutional responses to women’s issues within the academy may vary.

Figure 1. The Leaky Pipeline: Career Development of Women in Academia Before, During, and After Careers in Academia



Table 1


Themes and Variables Comprising the Career Development and Leaky Pipeline Experiences of Women in Academia


Model Predictions

Based on the literature review and the resulting model, the authors can make several predictions to describe the processes involved in women entering, traversing and exiting the pipeline.


Entry into the Pipeline. As women begin their careers as faculty members they bring their career development history with them, which in turn influences their education and career. The interaction of these factors creates a unique experience for women in faculty positions. Specifically, the career development variables are relevant to entry into the pipeline. First, the authors predict that the cognitive theme affects career trajectory in that women must have career aspirations, career choices and career expectations that are compatible with an academic career, as well as sufficient intellectual abilities and liberal gender role attitudes to endure and succeed in graduate school and beyond. Second, the coping theme also facilitates pipeline entrance, as women must have career decision-making coping, career maturity and adaptability, career self-efficacy, and self-esteem to transition effectively from graduate school into academic careers. Third, the authors predict that lower social class and socioeconomic status diminish the likelihood that a woman will enter an academic career (environmental theme), because lower social class and socioeconomic status tend to be associated with less access to opportunity structures such as those afforded by the educational attainment required for many academic careers. Fourth, the authors predict that having high achievement motivation, possessing career interests that complement an academic path, exhibiting high instrumentality and valuing graduate education facilitate an academic career (personality theme). Fifth, the authors hypothesize that the presence of perceived encouragement and supportive relationships with parents and role models facilitate these career paths (relational theme).


In addition, pipeline variables like feminism, personal power and self-promoting behavior have been evidenced as beneficial to women, and the present authors predict that these trends will likely remain consistent. For instance, academic self-concept can be a facilitative variable for women’s futures as academicians when that self-concept is consistent with an academic career and when women attend graduate programs that are more gender balanced than male dominated.


Traversing and Exiting the Pipeline. Once a woman enters graduate school, she is officially in the pipeline, and must maintain a level of teaching and research productivity commensurate with the expectations of the institution. Women academicians may leak out of the pipeline if they are denied tenure due to a lack of research productivity as a result of spending a disproportionate amount of time performing unrecognized service-oriented activities, particularly in research-intensive institutions (Misra et al., 2011). However, there is some evidence that institutions are recognizing service activities more frequently (Sampson et al., 2010). The current authors predict that experiencing a hostile departmental climate, feeling isolated and invisible, and encountering little or no transparency in departmental decision making facilitate conditions that increase the likelihood of a woman leaking from the pipeline before, during and after tenure decisions are made.


In addition, the authors predict that women leave their academic careers behind due to feeling stuck in positions with little hope for meaningful promotion, having restricted access to resources, dealing with financial issues or feeling dissatisfied with their salaries, rewards or level of recognition. Posttenure, the authors predict that a lack of administrative-level representation leads some women to leave academia because they are not able to realize administrative-level career goals, or because they may have less support (e.g., lack of available mentors) and more career challenges (e.g., greater isolation and invisibility) within institutions that lack women in these positions.




As the authors have shown through the model and its explanation, women academicians experience a unique set of personal and career challenges. Socialization and educational and career development processes stack the deck early, especially against women entering traditionally male-dominated fields. When one adds these processes to the existing structure of the academic system, it becomes clear that there are inherent systemic disadvantages for women in academic fields, which contribute to the leaks during each stage of the academic pipeline. The influences that women experience as children and young adults, and the discrepancies between women in different positions within academia, point to the necessity of a more holistic understanding of how women choose and navigate the complex path that leads them to and through academia.


It is the authors’ contention that each section of the model builds the groundwork for the next stage of the model in such a way that women in later stages of their careers have a multiplicity of additive strains that inhibit their career and personal satisfaction. To be sure, there are women who feel happy and fulfilled in their academic careers. At the same time, the present authors believe that this picture of satisfaction or dissatisfaction is supported by achievements and growth that occurs in different ways and for different reasons than it does for men. The authors hope to understand these influences and encourage responses at individual, societal and systemic levels. There exist numerous implications of this model, and here the authors highlight a few key points.



     Barriers for women. Women receive opportunities in the work world in ways that constrain their choices from a young age (e.g., Gottfredson, 1981; Gottfredson & Lapan, 1997; Mello, 2008; Riegle-Crumb, Moore, & Ramos-Wada, 2011). Factors such as low self-efficacy, little perceived encouragement and few role models can create barriers for career choice. However, some women do pursue academic careers, succeeding in their efforts and finding the work enjoyable and satisfying. Identifying a combination of protective factors that help women to succeed in academia could help offset some of these barriers. Also, career and mental health counselors can help women to develop these strategies and traits for themselves.


Women seem to struggle throughout the lifespan with perfectionism that inhibits their ability to feel fulfilled by their endeavors as well as their ability to produce academic work at the same rates as their male peers. It may be that women decide to leave the pressure of the academic environment because they experience burnout, working tirelessly and too meticulously toward a goal that men may reach more easily since they may be less influenced by perfectionistic tendencies. It is the authors’ hope that graduate training programs, mentors, counselors and academic institutions will continue to work together to provide women with guidance, support and psychoeducation in order to cultivate new perspectives on achievement in academia.


     Gender role socialization. How women glean messages from the dominant U.S. culture regarding what types of jobs are suitable for women and gendered expectations for behavior influence and constrain young women’s career interests, self-efficacy, view of parenthood and achievement motivation. Should a woman find herself with the resources necessary to enter graduate school with aspirations of an academic career, these socialization processes could potentially continue to restrain her because she may find herself with fewer female than male mentors and professors. If she has children, she also may find that the role strain between graduate student and mother is exhausting. If she is successful and becomes an academic, she may find herself balancing feelings of marginalization, isolation and frustration regarding her work and collegial relationships with the expectation that she be more “likeable” than “competent” (Krefting, 2003, p. 269). Often she may be called upon to perform activities in service of the institution that reinforce the gendered nature of “housework” for the institution (Valian, 2005, p. 205). Depending on the institution, performing service-oriented activities for the institution may help (Sampson et al., 2010) or hurt (Misra et al., 2011) her progress toward promotion and tenure. Hence, women may leak from the pipeline. For those women who do not leak, there are lingering discriminatory practices and beliefs that may flavor each day they spend pursuing their career goals and navigating the male-dominated terrain of the U.S. academic institution. The authors hope that this model will inspire others to consider the tangible reality of gender discrimination and combat its very specific effects on women academicians.


     Role models and mentors. Women’s experiences with role models in early life affect how these women aspire to and place importance upon career success (Hackett et al., 1989). In addition, girls’ decisions about work and family are influenced in part by their perception of their mothers’ work behavior, both inside and outside the home; by their emerging gender role attitudes; and by sociocultural messages regarding the gendered nature of careers and opportunities that exist. The work–family issue does not dissipate as women age, but is consistently present throughout women’s lives in the pipeline. It seems logical to conclude that some women with doctoral degrees and families decide to leave the pipeline due to the strain that academic jobs place on them. Providing more modern and family-friendly practices within institutions, such as daycare services and paternity leave, might well encourage women to enter or remain in academia.



One limitation to the model presented here pertains to its broad overview of some of the variables relevant to women’s career development in academia and job satisfaction. The variables in this model are by no means the only contributing variables, and thus the authors welcome feedback, extensions and rearrangement of this model based on other scholarly bodies of knowledge and research findings.


Also, an important consideration for future researchers and scholars is the question of how best to represent the model itself, specifically regarding the academic pipeline. Two major issues that arose for the authors involved (a) the troublesome nature of conceptualizing women’s academic career paths as linear in the form of this pipeline, and (b) whether to conceptualize women graduate students and women academicians as representing different phases of pipeline processes. With more study, conceptualization of these variables and how they fit together may lead to shifts in the current model. Finally, the authors’ review has been limited in that a comprehensive survey of this voluminous literature was not possible given the realities of publication space limitations.


Implications for Counselors and Other Future Directions


The model has many potential applications for counselors. First, counselors can utilize the model to conceptualize women academicians’ career development issues, using Figure 1 and Table 1 as quick reference tools. Also, counselors can assist women with career decision making and coping with their academic careers, which may help alleviate leaks in the pipeline. For example, expanding this model may help to guide the development of career counseling interventions for girls and young women during their career development and college or graduate school years. In addition, women academicians can benefit from interventions designed to explicate their experiences in a male-dominated career field, help them find support and challenge institutions for policy changes. In addition, the model can guide further research and interventions. Expanding, reframing or finding supportive or contradictory evidence for the model and its variables can be informative for academicians who conduct research in vocational psychology, women’s issues or other areas, as this information can guide future research, theory, and clinical practice. Finally, career counselors can act as advocates working in partnership with academic institution administrators, who may benefit from this model by looking critically at their own practices and policies and working with departments and faculty members to address critical issues that influence women’s decisions to pursue, remain in or leave academic careers.




The authors have merged and organized several bodies of literature regarding women in academia before, during and after their faculty appointments. Women’s unique career development and socialization experiences are the foundation for understanding how women navigate careers in academia. Barriers do exist for women that constrain career development, yet resources such as counseling and mentoring can counteract these barriers. In addition to highlighting the obstacles within the leaky pipeline, the authors hope to encourage the adjustment and repair of the pipeline itself.





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Courtney E. Gasser, NCC, is an assistant professor at the University of Baltimore. Katharine S. Shaffer is a doctoral candidate at the University at Albany, State University of New York. Correspondence can be addressed to Courtney E. Gasser, Division of Applied Behavioral Sciences, University of Baltimore, 1420 North Charles Street, Baltimore, MD 21201, cgasser@ubalt.edu.


The authors wish to acknowledge Dr. Deborah Kohl, Division of Applied Behavioral Sciences, University of Baltimore, for her feedback on this manuscript; Sean D. Lough, Morgan State University, for preparing and revising their model graphic; and Angela Brant, Krissa M. Jackson, Alexandra Mattern-Roggelin and Christina Pimble, University of Baltimore, for their research assistance.