Abstract
Research suggests that career development courses have positive impacts on college students’ career development outputs. What is less established is the impact of these career courses on educational outcomes like retention, graduation rate, and academic performance. This study compared two groups of undergraduate students: one that successfully completed a career development course (n = 3,546) and a matched group of students who did not take the career course (n = 3,510). The groups were compared on graduation rate, time to graduation, course withdrawals, and cumulative grade point averages (GPAs). The career development course was not a significant predictor of graduation within 6 years, the number of semesters to graduate, or the number of withdrawals incurred. However, the career development course did significantly predict the total number of credits (participants graduated with about five more credits) and cumulative GPA at graduation (participants graduated with higher GPAs).
For over 90 years, colleges and universities across the United States have been offering formal career education and vocational guidance to assist their students in the complex process of career preparation and decision-making (Maverick, 1926). One particularly effective vocational intervention is offering a credit-bearing academic course in career development and exploration. These courses have been implemented with a number of purposes in mind: to promote psychological well-being, to increase retention to graduation, to contribute to economic efficiency by reducing the number of course and semester withdrawals of students and ultimately to speed up the graduation process, and finally to utilize the dynamic benefits of group interventions for individual students.
With the first career courses appearing in colleges and universities in the early 1900s, the last century has produced an abundance of research evaluating the impact of these courses on various variables. Folsom and Reardon (2003) in a comprehensive literature review on the subject distinguished between what they termed outputs and outcomes of career interventions. This heuristic proves helpful in navigating the career course literature. “In this model, outputs refer to the skills, knowledge, and attitudes acquired by participants as the result of an intervention” (Folsom and Reardon, 2003, p. 427). Some examples of common outputs in studies looking at career courses include increased career maturity, more positive career-related thoughts, and increased career decision-making skills. “In contrast, outcomes of career service interventions refer to the resultant effects occurring at some later point in time” (p. 427). For example, common outcomes of interest when studying career courses include deciding on an academic major and efficient time to graduation. While the clear majority of studies conducted have examined the immediate outputs of career courses—such as career decision-making and confidence—few studies have looked at the long-term effects of career courses on variables such as time to graduation.
In their review of career course literature, Reardon, Folsom, Lee, and Clark (2011) examined 74 articles dealing with the effectiveness of career planning courses in colleges and universities throughout the country. In those 74 articles, Reardon et al. isolated 61 findings dealing with output effects, compared to 21 findings addressing outcome effects. The major theme of the output studies is that career courses tend to positively impact output variables including, vocational identity, career maturity, career decision-making, and cognitive development. While some studies have found that career courses also positively impact outcome variables, the nature of this influence is not always clear. Outcome studies sometimes conflict (e.g., Folsom, 2000; Goodson, 1982; Smith-Keller, 2005) with some reporting significant differences between students who participated in a career course and those who did not on certain outcome variables (like retention to graduation and credits at graduation) and others finding no significant differences on those outcome variables but significant differences in other outcome variables (such as course withdrawals and time to graduation).
As the works of Folsom and Reardon (2003) and Reardon et al. (2011) have confirmed, there is no shortage of research suggesting that the use of career courses in the university setting has strong, positive impact on students’ career decision-making ability and other output variables. What is lacking, however, is consistent and convincing evidence of the outcomes of these courses. Put another way, while the immediate positive impact of career courses on individual students seems clearly established, the long-term effects of these courses on broader, macro-level variables like retention, graduation rate, and academic performance are not known. Since universities devote significant resources to the teaching of career development courses, it would be important to determine what kind of long-term impact these courses have on students.
While a handful of studies have examined long-term outcome variables like retention, graduation rate, and academic performance in relation to career development courses (Folsom, 2000; Goodson, 1982; Smith-Keller, 2005), the results have been unclear and at times contradictory. For example, Smith-Keller (2005) reported a significant difference between course participants and noncourse participants in terms of persisting to graduation and taking a different amount of credits to graduate (with course participants graduating with fewer credits than noncourse participants), but Folsom (2000) found no such significant differences on those variables but did find a significant difference in terms of course withdrawals. Additional research in the form of replicating the Folsom (2000) study would provide much needed information in clarifying and confirming past studies.
The purpose of this research was to expand upon past research and replicate a study (Folsom, 2000) that examined the impact of a career course on outcome variables of interest including graduation, graduation rate, and academic performance. That is, in a general way, the purpose of this research is to contribute to a growing body of literature concerning the effectiveness of career courses at universities and colleges across the United States, in a way that is particularly needed (by examining outcome rather than output of the course). In a more context-specific way, the purpose of this research is to determine what impact a college career development class has on student outcome variables.
This study addressed the following research questions:
Method
In order to outline the method of this study, we first identify the research design we used. Next, we discuss participants, comprising two groups (one experimental and one quasi control), and describe the setting in which this study took place, including the particulars of the career development course which acted as the independent variable of the study. Finally, we address both data collection and data analysis and identify appropriate statistical analyses for each of the five research questions.
Research Design
This study used an ex post facto design in which archival data were accessed and analyzed to answer the aforementioned research questions. The study included two samples of students from an 8-year span (2000–2007): (a) those who completed the career course during that time and (b) a statistically comparable sample of students who did not take the career course to act as the comparison group. The independent variable in this study was the career course. Those students who enrolled in and completed the class were included in the experimental or treatment condition. The dependent variables were persistence to graduation (measured by graduation in 6 years), graduation rate (time to graduation), credits taken to graduate, and the number of course withdrawals executed by students. A cohort of students who did not enroll in the career class served as the comparison group.
Participants
Both groups in our sample were comprised of students at a large private university during the years 2000–2007. One group included students who enrolled in and successfully passed the career development class (with a grade of C-minus or better), and the other group included students who did not take the career development class. The comparison, nonclass participant sample was initially drawn from the population in a mostly random fashion (the only constraint being that the student could never have taken a career course). This yielded a significantly unbalanced comparison sample in terms of year in school with freshmen and sophomores comprising 75.7% of the career course group and only 28.5% of the nonclass participant group. It was thus decided to pull the data again but to match the nonclass participant group to the career class group on the variable year in school. No additional demographic information was used to match the groups to allow for as random a draw as possible and with the intention to control for group differences in the main analysis should they appear.
The combined total number of participants from the two groups was 7,056 undergraduates, 3,430 women (48.6%), and 3,626 men (51.4%). About 85% of the participants were classified as freshmen and sophomores and approximately 90% were White. Other ethnic groups represented included Hispanic (4.1%), Asian (2.6%), Hawaiian/Pacific Islander (1.8%), American Indian (0.8%), and Black (0.7%) with 29 participants listed as “other” (0.4%). About one third of participants (n = 2,255, 32%) were listed as “open major,” while the other two thirds (68%) had declared a major.
Group 1
The first group was comprised of 3,546 undergraduates who had enrolled in and successfully passed (with a grade of at least a C-minus or better) the career course from the year 2000 to 2007. This group, considered as the treatment group in the study, was referred to as the career course group, and students in this group were referred to as course participants. Categorical demographic information for this group (and the second group) is presented in Table 1.
Descriptive Statistics Comparing the Categorical Variables of the Career Course and Noncourse Participant Groups.
Group 2
The second group of participants was comprised of 3,510 students who did not take the career course and were matched to the career course group on the variable year in school. This group was considered the quasi-control group of the study and is referred to as the comparison group; students in this group were referred to as noncourse participants. Demographic information representing continuous variables for this group (and the career course group) are presented in Table 2.
Descriptive Statistics Comparing the Continuous Variables of the Career Course and Noncourse Participant Groups.
Note. HS GPA = high school grade point average.
Within the major variable, the largest proportion of students in both groups was “open major.” To simplify the analysis, a new variable was dummy-coded in which open majors were coded as 0 and students who had a major were coded as 1. Similarly, within the ethnicity variable, the largest proportion of students in both groups was “White/Caucasian.” Since no remarkable trend was noted other than the discrepancy between Whites and all other ethnicities, a new variable was created in which Whites/Caucasians, considered in this context to be students in the ethnic majority, were coded 0, and all other ethnicities (those in the ethnic minority) were coded 1. Table 3 depicts the frequencies in the two groups (career course and noncourse participants) of these collapsed variables.
Descriptive Statistics Comparing the Dummy-Coded Variables of the Career Course and Noncourse Participant Groups.
Career exploration course
The career course examined in this study is typical of career development courses in postsecondary settings. The University Catalog provides the following description for the course: “Applying theories of individual, academic, and career development to the university student. Exploring university opportunities and college majors; graduation planning.” In addition to this description, four learning outcomes for the course are identified thus: Increase knowledge of college majors, career options, and additional world-of-work factors that influence career choice. Develop greater awareness of personal qualities, interests, skills, and values that play a role in career-decision making. Demonstrate increased confidence and ability to make decisions as well as progress toward making career decisions. Display an awareness of and ability to access educational and career information resources.
This course is taught by many individuals, including professors, psychologists, career specialists, and graduate students. While a common curriculum unites the various sections, the teachers are fairly free to adapt the lessons to their interest and the needs of the class. All sections subscribed to the same learning outcomes, and we can reasonably assume that all students who completed the career class engaged in similar processes and content regardless of the section in which they were enrolled.
Data analysis
The first task of the data analysis was to test our two groups for similarity based on the identified comparison criteria (i.e., year in school, race, gender, high school GPA, and American College Testing [ACT] score). Following the methodological example of Folsom (2000) whose study we aimed to replicate, we used a χ2 test of independence to compare between-group frequencies for the race, gender, and year in school variables since these data were categorical in nature. Independent t-tests were used to compare group means when it came to high school GPA and ACT scores. The null hypothesis in each of these tests was that there was no significant difference between the two groups on each factor. In the event that significant differences between the groups were found, we treated those particular variables as covariates during the main data analysis.
For the first research question concerning whether students who take the career class graduate at a rate significantly different from those who do not, dummy-coding was employed to create a new variable that represented whether students graduated in 6 years or not. As Smith-Keller (2005) described, “students who persisted to graduation within six years of matriculation into university were coded ‘1’ and those students who did not persist to graduation within the six-year time frame were coded ‘0’” (p. 43). A binary logistic regression was computed (since the dependent variable is categorical/dichotomous) to determine whether the career development course with covariates was a significant predictor (at the .05 level) of persistence to graduation.
The second research question (which asks about differences in time to graduation) was answered using multiple regression. For this research question, time was measured in terms of semesters (with a term being considered half a semester). Then, the multiple regression was able to assess whether the career development course significantly predicted (at the .05 level) students’ time to graduation in the presence of other covariates.
The third research question, concerning credits to graduation, was answered by employing multiple regression. Doing so determined whether participation in the career development course was a significant predictor (at the .05 level) of students’ total credits at graduation in the presence of the other covariates.
The fourth research question regarding course withdrawals was answered by calculating means and standard deviations using the total number of course withdrawals executed by those who did persist to graduation in the two groups. Using multiple regression, it was determined whether between-group differences (at the .05 level) in terms of number of course withdrawals were accurately predicted by the career development course.
The fifth and final research question concerning cumulative GPA was also answered using multiple regression to determine whether there were significant differences (at the .05 level) between the treatment and control groups. Specifically, the career course was examined to see whether it was a significant predictor of group differences in cumulative GPA.
Results
The purpose of this research was twofold: (a) to determine what impact college career development courses have on student outcome variables and (b) to contribute to a growing body of literature concerning the effectiveness of career courses at universities and colleges across the United States, in a way that is particularly needed (by examining outcome rather than output of the course). Specifically, we examined the long-term impacts of completing a credit-bearing career exploration course on student and institutional outcomes of specified interest including student retention, time taken to graduate (measured in terms of both semesters and credits), number of course withdrawals, and overall academic success (measured by total cumulative GPA at graduation). To examine the impact of the career development course, a group of students who did not take the class was used as a comparison sample and assessed on all of the same outcome variables.
Results to each of the research questions will be detailed below. However, before addressing the five research questions, the results of the statistical analyses used to determine whether the two groups (the experimental or career course group and the quasi-control or comparison group) were reasonably matched will be presented.
Group Comparisons
Given that the quasi-control sample (the group of students who did not take the career course) was only matched to the experimental group (encompassing the group of students who did take the career course) on one criterion (year in school), the two groups were statistically compared on each of the other matching criteria (gender, ethnicity, major, high school GPA, and ACT score), in order to assess whether or not the groups were reasonably matched before proceeding to answer the main research questions. These six dimensions were identified from the Folsom (2000) and Smith-Keller (2005) studies and replicated here to maintain consistency and attempt to control for potentially confounding variables. Results to each of these six criteria-based comparisons will be discussed in turn.
Year in school
After initially pulling an unrestrained random sample of the students available who had not taken the career course, it was discovered that the two groups were significantly mismatched in terms of year in school, with the nonclass participants being much more heavily weighted toward juniors and seniors (freshmen = 431, sophomores = 700, juniors = 846, seniors = 1,995), while the career course group contained (predictably) many more freshmen and sophomores proportionately (freshmen = 2,090, sophomores = 2,389, juniors = 1,094, seniors = 343). A χ2 test of independence was calculated comparing the class level of the career course participants and noncourse participants. A significant interaction was found, χ2(3) = 2,945.908, p < .001, indicating that there was a significant difference between the two groups in terms of year in school compared to what would be expected proportionately. In an effort to procure a comparison group that was reasonably similar to the career course group in terms of year in school, the data were pulled again, this time by using the year in school makeup of the career course group to match the quasi-control group. For example, for every x number of freshman students in a given year who passed the career course (with a C-minus or better), the registry was queried for that same number of freshman students in that year who did not take the career course (these students were also checked to ensure that they never enrolled in the course during their time at the university). With the new data set, after excluding students who were identified as visiting students or otherwise nontraditional students, another χ2 test of independence was computed, and no significant relationship was found, χ2(3) = .034, p = .998. It was thus concluded that there was no significant difference between the two groups in terms of class standing (freshman, sophomore, junior, or senior).
Gender
Considering that year in school was the only criterion used to match the two groups at the time of the data pull, the rest of the identified criteria were used to statistically assess for group similarity between the two groups (course participants and noncourse participants). The next criterion used to compare the two groups for similarity was gender. A χ2 test of independence was calculated comparing the proportion of males to females in each of the two groups. No significant relationship was found, χ2(1) = 3.768, p >.05, and it was concluded that the two groups were reasonably matched in terms of gender. That is, both groups contained proportionately similar numbers of males and females.
Ethnicity
Ethnicity was initially coded into seven groups (White/Caucasian, American Indian, Asian, Black, Hawaiian/Pacific Islander, Hispanic, and other). To simplify the analysis, these groups were collapsed into two broader categories: students considered to be in the minority (American Indian, Asian, Black, Hawaiian/Pacific Islander, Hispanic, and other) and those in the majority (White/Caucasian). A χ2 test of independence was calculated comparing the proportion of students in the minority to those in the majority both in the career class group and in the quasi-control group. A significant interaction was found, χ2(1) = 17.607, p < .001, indicating that groups were significantly different in terms of ethnicity. Specifically, students in the minority were found in the career course participants more than what would be expected based on proportions. In light of this finding, ethnicity was treated as a covariate in the main analysis.
Major
Because the largest proportion of students in both the group of course participants and the noncourse participants had undeclared majors, participants were categorized as either undeclared major or declared major. A χ2 test of independence was calculated comparing the frequency of undeclared major students and declared major students in the career course and noncourse participants groups. A significant interaction was found, χ2(1) = 524.996, p < .001, indicating that the two groups were significantly different in terms of major status. There were fewer students with an undeclared major in the quasi-control group than was proportionately expected. Given this difference between groups, students’ major status was treated as a covariate in the main statistical analysis.
High school GPA
Another criterion used to compare the two groups was high school GPA. An independent samples t-test was calculated comparing the mean high school GPA of the career course participants to the mean high school GPA of noncourse participants. No significant difference was found, t(6886) = 1.434, p > .05. The mean of the career course participants (M = 3.6671, SD = 0.34222) was not significantly different from the mean of noncourse participants (M = 3.6788, SD = 0.33494), indicating that two groups were reasonably similar in terms of high school GPA.
ACT score
The final criterion used to compare the two groups was ACT score. An independent samples t-test comparing the mean ACT scores of the career course group and the quasi-control group found a significant difference between the means of the two groups, t(7016) = 6.925, p < .001. The mean ACT score of the career course group was significantly lower (M = 25.96, SD = 3.737) than the mean ACT score of the noncourse participants (M = 26.55, SD = 3.474). Since this criterion was found to be significantly different between the two groups, ACT score was added to the list of covariates to be controlled for in the main analysis.
Given that the quasi-control group was pulled in a mostly random fashion (matched only on the variable year in school), we are able to make some observations about the composition of these groups at the outset which would not be possible if the groups were made to be as similar as possible. For example, it is interesting (though perhaps unsurprising) to note that the major variable was a point of marked difference between the groups. It can thus be inferred that, in general, course participants have a much higher proportion of undecided students than noncourse participants. The same can be said for the other significant differences between groups, ethnicity, and entering ACT score: Overall, the career course generally contains higher than expected minority students, and the career course participants have lower ACT scores than noncourse participants. It bears repeating, however, that these differences, while interesting, were treated as covariates in the data analysis, and thus, their potentially confounding effects were controlled for statistically.
Research Questions
Having determined the degree to which the two groups (course participants and noncourse participants) were matched, the main research questions were addressed using the appropriate statistical analysis, treating major, ethnicity, and ACT score as covariates.
Retention to graduation in 6 years
A χ2 test of independence was calculated comparing the retention to graduation within 6 years in the two groups (the class cohort and nonclass cohort). No significant relationship was found, χ2(1) = .691, p = .423, indicating that there was no significant difference between the class cohort and nonclass cohort in terms of graduation within 6 years.
To control for the potential confounding effect of the covariates (ACT score, ethnicity, and major), a binary logistic regression was also computed to determine whether participation in the career class could significantly predict whether participants graduated within 6 years or not (a dichotomous variable) in the presence of the covariates. A test of the full model against a constant only model was statistically significant, indicating that the predictors (participation in the career class and the covariates, ACT score, ethnicity, and major) as a set reliably distinguished between those who did graduate within 6 years and those who did not (χ2 = 73.907, p < .001, with df = 4). Within the model, the career course variable was not a significant predictor of graduation. Table 4 shows the logistic regression coefficient, Wald test, and odds ratio for each of the predictors.
Logistic Regression Predicting Graduation in 6 Years From Career Course, Major/Minority Status, and ACT Score.
Employing a .05 criterion of statistical significance, minority status and ACT score had significant partial β weights. Participation in the career course was not a significant predictor of graduation within 6 years. It was thus concluded that there was no significant difference between the experimental and quasi-control groups in terms of retention to graduation (as measured by graduation in 6 years).
Time to graduation in semesters
The second research question asked whether students who complete the career course graduate in a different amount of time (measured in semesters) than those who do not take the course. A multiple linear regression was calculated predicting students’ semesters to graduation based on being in the career course and the covariates (major status, minority status, and ACT score). A significant regression equation was found, F(4, 7017) = 24.945, p < .001, with an R 2 of .014. However, the career course did not significantly predict differences in students’ semesters taken to graduate (β = .021, t = .411, p = .681). It was thus concluded that there was no significant difference between the course and noncourse participants in terms of the amount of time (in semesters) it took for them to graduate.
Time to graduation in credits
The third research question had to do with whether students in the career class take a different amount of credits to graduate than those who do not take the course. A multiple linear regression was calculated to predict participants’ total credits at graduation based on the career course and the covariates (major status, minority status, and ACT score). A significant regression equation was found, F(4, 7017) = 153.050, p < .001, with an R 2 of .080. Participants’ predicted total credits are equal to 91.113 + 4.78 (career course) + 3.828 (minority) + 2.239 (ACT), where career course is coded as 0 = no, 1 = yes; minority is coded as 0 = majority, 1 = minority; and ACT is a continuous score. Career course, minority, and ACT were all significant predictors. It was concluded that students who take the career course differ significantly from the noncourse participants in terms of total credits at graduation. Students who took the career course graduated with 4.78 more credits than those who do not take the class.
Number of course withdrawals
The fourth research question that was posed was whether students who take the career course withdraw from courses differently from those who do not. A multiple linear regression was calculated predicting students’ number of withdraws based on being in the career course and the covariates (major status, minority status, and ACT score). A significant regression equation was found, F(4, 7017) = 8.804, p < .001, with an R 2 of .005. However, the career course did not significantly predict differences in students’ number of withdraws (β = −.055, t = −1.366, p = .172). It was thus concluded that there was no significant difference between the course and noncourse participants in terms of the number of withdrawals students incurred.
Total cumulative GPA at graduation
The fifth and final research question of this study asked whether students who took the career course had significantly different cumulative GPAs than students who did not take the course. A multiple linear regression was calculated to predict participants’ total cumulative GPAs at graduation based on the career course and the covariates (major status, minority status, and ACT score). A significant regression equation was found, F(4, 7017) = 350.411, p < .001, with an R 2 of .167. Participants’ predicted total GPA is equal to 2.357 + .035 (SD 117) − 0.091 (minority) + .039 (ACT), where career course is coded as 0 = no, 1 = yes; Minority is coded as 0 = majority, 1 = minority, and ACT is a continuous score. Career course, minority, and ACT were all significant predictors. It was concluded that students who took the career course differed significantly from the noncourse participants in terms of total cumulative GPA at graduation. Students who took the career course graduated with cumulative GPAs 0.035 higher than students who did not take the course.
In conclusion, it was found that while the two groups (career course participants and noncourse participants) were similar in terms of gender and high school GPA, they significantly differed in terms of major, ethnicity, and entering ACT score. Controlling for the effects of the covariates, the career course was not a significant predictor of whether or not students graduated in 6 years, the number of semesters it took students to graduate, and the number of withdrawals students incurred. However, in the presence of the covariates, the career course did significantly predict the total number of credits (with course participants graduating with about five more credits than the noncourse participants) and cumulative GPA at graduation (with course participants graduating with higher GPAs than the comparison group).
Discussion
This study examined the impact of a university credit-bearing career exploration course on measures of academic outcomes (retention, time to graduation, and withdraws) and achievement (cumulative GPA). It was found that participation in the course did not make a significant difference in terms of retention, as measured by students’ rates of graduation (within 6 years), time to graduation (in terms of semesters), and the number of withdraws. However, the course was found to significantly predict students’ total credits at graduation and their overall academic performance (measured by cumulative GPA).
Each research question with its accompanying results will be discussed in turn below. This discussion will address how the findings from this study compare with previous research (particularly Folsom, 2000; Goodson, 1982; Smith-Keller, 2005).
Integration of Findings
Retention to graduation in 6 years
Results indicated no significant difference between the career course group and the noncourse participants in terms of graduation within 6 years. This finding mirrors that of Folsom (2000) who also found no significant difference. However, it differs from the results of Smith-Keller (2005) who found that students who had taken the career course at that university persisted to graduation at a rate significantly higher than those who did not take the class. Although it is unclear whether Goodson (1982) was measuring retention to graduation, a significant difference was found between the students who took the career class and those who did not in terms of the percentage of students completing 4 years of college. It was reported that 67% of students who took the class completed 4 years of college at the time of the 10-year follow-up, compared to 57% of students who did not.
While the career course was not found to predict a significant difference in terms of students graduating within 6 years, it should be noted that the graduation rates in that time for both the course participants (86.6%) and the comparison group (85.7%) were much higher than the national average of 59% (U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics, 2015). Graduation rates are predictably different when one considers the type and acceptance rate of the institution—universities with less stringent admissions tend to have lower graduation rates, while those with higher admission standards tend to have higher graduation rates. Given that the site institution had an acceptance rate of 48.7% in Fall 2013 (U.S. News and World Report, 2015) and 55.0% in Fall 2014 (Brigham Young University Admissions, 2015), these numbers are also higher than the national average for nonprofit institutions that accept between 25.0% and 49.9% of applicants (77.5%) and these same institutions that accept between 50.0% and 74.9% of applicants (62.3%).
Time to graduation in semesters
Results indicated no significant difference between the career course group and the comparison group in terms of time to graduation (measured in semesters). Course participants on average graduated in 10.26 semesters, while students in the comparison group graduated in 10.15 semesters. This finding provided evidence that even in the presence of other covariates (major, ethnicity, and ACT score), participation in the career course did not significantly predict the time it took students to graduate (as measured by semesters). Similar to the results of the first research question, this finding again reflected Folsom’s (2000) study, as he likewise found no significant difference between the two groups in his study on this variable (although time in that case was measured in months, not in semesters). However, Smith-Keller’s (2005) study did show a significant difference on this variable of time to graduation reporting that “students who had not taken the career course took significantly less time to complete their degrees and graduate, compared to students who took the course” (p. 64).
Time to graduation in credits
Time to graduation measured in terms of credits was one of two outcome variables for which there was a significant finding. Results indicated that the two groups differed significantly in the total number of credits at graduation with the career course group graduating with 4.78 more credits than the comparison sample, in the presence of the covariates. While noncourse participants took 151.23 credits to graduate on average, students who took the career course graduated with 154.74 credits. Although this difference in means is 3.51, the multiple regression equation, which took into account the combined effects of the covariates, yielded a difference of 4.78 credits. This finding showed a trend similar to that found in Folsom (2000) who reported that “the adjusted mean number of credit hours taken to graduate by course participants was (M = 110.85),” and the “adjusted mean number of credit hours taken to graduate among non-participants was (M = 109.90)” (p. 108). In other words, in both studies, career course participants graduated with more credit hours than students who did not take a career course. Smith-Keller (2005), on the other hand, found that students who took the career course graduated with significantly less credit hours than those who did not.
While, taken alone, this finding may seem to suggest that career course participants took longer time to graduate, it is important to again note that there was no significant difference between the groups in terms of semesters taken to graduate. Taken together then, it appears to bode well that while the students who took career exploration may have taken a few more credits to graduate, they did so in the same amount of time (semesters) as their nonclass peers. It bears noting as well that although there was a difference of 4.78 credits between the course participants and the noncourse participants, the career exploration course itself accounted for two of those credits. Career courses are hypothesized by some (Folsom, 2000; Reardon, Folsom, Lee, & Clark, 2011; Smith-Keller, 2005) to serve an efficiency function—that is, that career courses help students determine what they want to major in and thus enable them to take courses more intentionally geared toward their major requirements from an earlier point in their education—it may also be that career courses empower students to use their courses as opportunities to explore different major and career options. This may explain in part why students who took career exploration graduated with more credits than noncourse participants.
Number of course withdrawals
Interest in this outcome variable stemmed in part from the desire to replicate Folsom (2000) and in part as an alternative to another variable of interest, the number of major changes to which we did not have access. The university does not have a central way of tracking if and how many times students change their majors. Folsom (2000) stated that the number of course withdraws was of interest in studies of this nature because “if career course participants gain a clearer career focus, then one possible outcome is less within-course starting and stopping and hence less course withdrawals executed in comparison with students who did not complete the career development course” (p. 110). Contrary to Folsom, results of this study indicated no significant difference between course participants and noncourse participants in the number of course withdrawals executed. This supported the conclusion that students who take career courses withdraw from classes at a rate similar to students who do not take the career course. Smith-Keller (2005) likewise found no significant difference between what she called the class cohort and nonclass cohort in terms of course drops.
Total cumulative GPA at graduation
The fifth and final outcome variable we examined was total cumulative GPA at graduation. Results indicated that the two groups were significantly different in terms of total GPA at graduation and that students in the career course group graduated with higher cumulative GPAs than the comparison group. While the difference in GPAs was marginal (.035), it remains a meaningful finding that even in the presence of the covariates (major, ethnicity, and ACT score), the career course significantly contributed to the outcome variable, cumulative GPA at graduation. That is, students who enrolled in and successfully completed the career class (with a grade of C-minus or better) graduated with a .035 higher cumulative GPA than students who did not take the class.
Limitations
This study is limited in its scope due to several factors that ultimately constrain the generalizability of the results. These factors include variability across the teachers of the course, data collection occurring entirely at one, somewhat unique university, differences between the quasi-experimental and the comparison groups, and the presence of nontraditional students in the sample.
Variability across teachers
The career course was taught by different teachers, who were generally free to adapt the course to their interests and style. While the stated learning outcomes of the course were consistent and did not vary by teacher, individual teacher’s approaches to teaching did vary and this may have introduced variability.
One university
It should be noted that the scope of this study (and the generalizability of the results) is limited by the fact that it only examined one career course at one university. While the sample is large and this course seems to be similar in content and process to other career development courses at other universities, future research should examine the impact of various career courses at multiple sites.
Between-group differences
Although the effect of between-group differences was controlled for in the data analysis, there is one significant group difference that should be kept in mind as a potential confound. As was presented in Table 4, the quasi-experimental group and the comparison groups were significantly different in terms of major status. Specifically, nearly half of the students in the career exploration group were open majors (44.6%) compared to less than a fifth of students in the comparison group (19.2%)—meaning that over 80% of the comparison group had declared a major compared to only 55.4% of the career exploration group. While this difference was statistically controlled for in the analysis—this variable was treated as a covariate in the data analysis—it raises the question of whether having more similarly matched groups might have strengthened the study.
Nontraditional students in sample
Failure to collect the demographic variable of age of the students made it difficult to track which students might be nontraditional students. This can be seen as a potential confound in that nontraditional students take varied paths to graduation, and the research questions motivating this study were more focused on the traditional, entering first time freshmen and whether taking the career course made a difference to those students on certain outcome variables. Given that these students comprised less than 2% of the sample as a whole, it is not likely that they represented a significant confound in the study.
Implications for Future Research
This study has implications for future studies. First, this study and other studies like this (Folsom, 2000; Goodson, 1982; Smith-Keller, 2005) were each conducted at one university and examined the impact of one career development course. Future research should consider a multisite approach in which multiple, similarly structured career development courses are assessed simultaneously for these same outcome variables of interest. In addition, future research should seek to compare one-credit career courses with two-credit and three-credit career courses. This study examined a two-credit hour course, Folsom’s (2000) study examined a three-credit hour course, Smith-Keller (2005) reported on a one-credit hour course, and Goodson’s (1982) study reported on a non-credit-bearing career course. These differences should be studied empirically to determine whether career courses of different credit configurations impact student outcomes differently.
In connection with one of this study’s limitations, future research might look at only students who received a grade of B-minus or better in the career course (Folsom, 2000). As it can likely be assumed that career courses in general do not carry the same academic rigor as other classes, it may even be worthwhile to include only students who got an A grade or A-minus in the career course to more discriminately delineate between students who presumably benefited most from the class and those who did not meet learning objectives. In addition, the variability between the course teachers might be more effectively addressed by standardizing curriculum and/or investigating the outcomes of a course taught by a single individual.
Implications for Practitioners
The practitioners for whom this study is relevant are not only those in career counseling, and those who teach the course, but also personnel in higher education more generally and anyone who interacts with college students and can make recommendations to those students. It is not only helpful to know that a career development course is an option for undecided students; it is also validating to be able to show that this course has a significant impact on student outcomes (e.g., students who took the class graduated with significantly higher GPAs than those in the comparison group). Perhaps it makes little difference to students that those who pass the career development class tend to graduate with five more credits in the same amount of time (semesters) as students who do not take the course. But as we start to consider what those five credits represent—conceding that two of the credits account for the career development course itself—additional credits can be seen to represent not only additional coursework but the added knowledge and educational experience that coursework provides. What is more, these credits were accumulated in the same amount of semesters as the comparison group, which suggests that this additional coursework is being completed in an efficient manner that does not incur the unnecessary financial cost of extra semester(s) of tuition and living expenses.
In addition, it is worth noting that while this course seems to be drawing generally equally from men and women (recall that our two groups were not significantly different in terms of gender), there was a higher than expected proportion of minority students in the career development course, and this can be seen to have implications for those who work with ethnically diverse students. It appears that this class is being recommended to or pursued more by diverse students, which further justifies its continued implementation as it is reaching a historically marginalized and underserved population of students.
It also bears highlighting that the groups were originally found to be significantly different in terms of entering ACT score (with students in the career course having lower ACT scores than their noncourse participant peers). Given this between-group difference, it appears all the more noteworthy that course participants graduated with significantly higher cumulative GPAs than those in the comparison group. Put another way, assuming that ACT scores and GPAs measure some part of what they purport to measure, course participants who had a lower readiness for college to begin with (as measured by their ACT scores) graduated in the end with higher academic performance (as measured by total GPA at graduation) than noncourse participants. Extrapolating some, one could argue that although initially comprising a group of students, some might expect to underperform compared to their peers (whether that be considering their significantly different composition in terms of race or in terms of ACT score), students taking the career course ended up performing at equal or higher levels on multiple dimensions (i.e., comprising both significant findings of no difference and significant findings in which the career course group could be said to have outperformed the comparison group, this includes time to graduation measured in semesters, retention to graduation as measured by graduated in 6 years, the number of course withdrawals incurred, and total cumulative GPA at graduation).
Conclusions
This study adds to the growing body of literature concerning the effectiveness of career courses at universities and colleges across the United States, in a way that is particularly needed (by examining outcome rather than output of the course). This was accomplished by replicating portions of Folsom’s (2000) and Smith-Keller’s (2005) studies in an attempt to provide needed clarity surrounding their conflicting findings. Specifically, a two-credit, career development course entitled was treated as the independent variable in the study, while the following outcome variables were identified as dependent variables of interest: retention to graduation (within 6 years), time to graduation (measured by semesters and credits), the number of course withdrawals, and overall academic success (measured by cumulative GPA at time of graduation). To try to isolate the impact of the course, a comparison group comprising students who did not take the class was likewise assessed on each outcome variable.
Results revealed no significant differences between the two groups in terms of retention to graduation (within 6 years), semesters to graduate, and the number of course withdrawals. However, results indicated statistically significant differences between the quasi-experimental group and the comparison group in terms of credits taken to graduate (with course participants graduating with more credits than noncourse participants) and cumulative GPA (with course participants graduating with higher cumulative GPAs than noncourse participants).
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.