Major Re-selection Advising and Academic Performance
We sought to determine whether receiving major re-selection (MRS) advising benefits undergraduate students' grade-point averages (GPAs). We used a quasi-experimental nonequivalent control group design to compare a treatment group (n = 219) of undergraduates who changed their majors after receiving MRS advising with a control group (n = 206) who changed majors without advising during the same semester as the treatment group. Findings showed that, on average, students who received MRS experienced no change in their program GPA but an increase in their semester GPA; however, the control group experienced a decrease in program and semester GPAs. Multiple regression analysis confirmed that MRS advising had a positive effect on posttest semester GPAs (β = .33, p < .001) and program GPAs (β = .28, p < .001). Implications for student advising are discussed.
Research has shown that when selecting academic majors, undergraduates take into consideration their academic interests, aptitude, the psychological and social benefits associated with a major, postgraduation employment prospects, and the appropriate education for their chosen occupations (Allen & Robbins, 2008; Beggs, Bantham, & Taylor, 2008). Changes in any of these factors might lead students to re-select an academic major. In an alternative scenario, some undergraduates declare a major after minimal considerations of relevant circumstances (Mortimer, Zimmer-Gembeck, Holmes, & Shanahan, 2002). As a result of either situation, students may lack confidence in their original choice and commitment to their declared major such that they subsequently need to change to a different major. Both of these decision-making processes may contribute to the 35–75% of undergraduates changing their majors at least once during their undergraduate years (Beggs et al., 2008; Gordon, 2007) and a 6-year degree attainment rate below 60% among American college students who enroll in 4-year colleges (Bettinger, Boatman, & Long, 2013; Cuseo, 1991).
Academic advising designed to help students transition from one major to another contributes to students' academic progression, persistence with re-selected majors, and retention (Campbell & Nutt, 2008; Gordon & Steele, 1992; Hunter & White, 2004; Mayhall & Burg, 2002; Metzner, 1989; Steele, 1994; Steele, Kennedy, & Gordon, 1993; Steingass & Sykes, 2008). For instance, in a recent study on the effect of centralized advising, Kot (2014) found that first-year students who received centralized advising had earned higher grade-point averages (GPAs) and experienced lower attrition rates than peers who did not receive any advising during the same period. Kot employed the propensity score matching technique to estimate the impact of centralized academic advising on 2,745 undergraduates' first-year GPAs and second-year enrollment behaviors. Data from students who accessed centralized advising were matched with those who received no advising over the same two semesters. Findings showed that students who used centralized academic advising earned higher first-term, second-term, and first-year cumulative GPAs and more enrolled for their second year than students who had not seen an advisor.
The burden for receiving useful advising does not fall solely to students. Some colleges and universities provide inadequate advising opportunities to connect students' interests (e.g., career goals) with appropriate academic majors (Feldt et al., 2011). To provide an effective advising program, planners and administrators must recognize that students at different stages of their academic career need different types of advising. For instance, first-year students looking to declare a major likely require different conversations and exercises than second- or third-year students who experienced failure in their selected program and must find a new major to remain enrolled in college.
Because students who need to re-select their majors are particularly vulnerable for leaving college without a degree (e.g., dropping out or academic dismissal), some postsecondary institutions allocate academic advising resources to respond to the specific needs of major changers. A typical program features a centralized major re-selection (MRS) advising office that provides advising to students who request it; however, little research has been conducted to describe specific characteristics of MRS advising and whether they benefit students who received it. Therefore, for the current study, we described a centralized MRS as well as compare the academic performances of undergraduates who changed their majors after receiving MRS advising with a peer group who changed majors without receiving any advising. On the basis of existing literature, we hypothesized that students who selected majors after receiving MRS advising would outperform their peers who changed their majors without receiving advising.
Methods
Context
The study was conducted at a comprehensive, public, research university serving more than 48,000 students. The first-to-second year retention rate was 89%, and 67% had graduated within 6 years. Similar to descriptions in the literature (e.g., Gordon & Steele, 1992; Osipow, 1983), at the studied university, second- and third-year students in good academic standing (defined as a 2.0 GPA or higher) need MRS advising because they have discovered new interests or experienced one or more academic challenges (e.g., failure to complete prerequisites for a declared major). Students who want or need to change their majors are encouraged, but not required, to meet with an MRS advisor and to consult with advisors in both their current college and the one(s) of interest. In other words, undergraduates may declare their major by completing a major declaration online or on paper by submitting the proper form to the college of choice. After college staff process the information and update the student records system, students may register for courses in their new college.
Research Design
We used a quasi-experimental nonequivalent control group design (per Fife-Schaw, 2012) to address the research question: Do major changers who receive MRS advising outperform major changers who do not receive any advising? We included two groups of undergraduates who matriculated at approximately the same time and changed their majors at the same point in their college careers. However, without random group assignments, we did not have pretest sampling data for the two groups. Students in the treatment group changed their majors after receiving MRS advising. The students in the control group changed their majors without receiving MRS advising. This research design provided an opportunity to infer the effect of MRS advising on students' programs and term GPAs while controlling for a host of covariates, including age, gender, transfer status, and racial background.
Participants
Most participants were in their third year (78.3%). The groups also included sophomores (16.2%) and seniors (5.5%) during the 2013-2014 academic year. The treatment group included all 219 students who received MRS advising during the summer and fall semesters of 2012. Prior to receiving MRS advising, these students had completed an average of 28.9 credit hours (SD = 10.5) and had formally declared an academic major at the university. Subsequent to receiving MRS advising, all treatment group students had selected and declared a different major. The control group was randomly drawn from the undergraduate population who had matriculated at approximately the same time as students assigned to the treatment group. It included 206 undergraduates who had declared a major and then changed to a different major during the same period as the treatment group students; however, control group students received no advising. Similar to those in the treatment group, students in the control group had completed an average of 28.7 credit hours (SD = 8.9) when they changed their majors.
Data Source
Upon approval from the Institutional Review Board, we obtained the following data directly from the university registrar reporting system for students in both groups: demographic information (e.g., age, gender, ethnic and racial backgrounds); transfer status (i.e., whether or not the student transferred into the university); previously declared major and currently declared major; and GPAs for each semester as well as for the students' programs of study for each semester. In addition, students in the treatment group filled out an in-take form that included a checklist of reasons for major re-selection prior to meeting with their MRS advisor. The students could choose all the reasons that applied to them as well as write in additional reasons. No information was available on the reasons for major change among those in the control group because they did not request MRS advising. Finally, information on the characteristics of the MRS office was provided by the program manager of the MRS office.
In data analyses, pretest semester GPAs were calculated by averaging the students' GPAs from all semesters before the time period the treatment group students received MRS advising (Summer and Fall 2012). Posttest semester GPAs were determined from students' GPAs of the semester after receiving MRS advising (Spring 2013). Pretest program GPAs were calculated from cumulative GPAs earned in program-specific courses in all semesters before the students received MRS advising. Posttest program GPAs were obtained from Spring 2013 semester grades after students received MRS advising.
Results
Characteristics of Major Re-selection Advising
According to the program manager, the MRS office is staffed with two full-time MRS advisors and two part-time graduate assistants. The MRS advisors were trained to recognize that many second- and third-year students in need of new majors were at an elevated risk for leaving the college without a degree (e.g., being dismissed or dropping out), and advisors accepted a vital role in promoting student retention. Similar to other types of academic advisors, the MRS advisors only work with students who request advising to re-select majors and serve as liaisons between students and mental health counseling professionals (e.g., Kadar, 2001; Robbins, 2012).
MRS advisors have acquired a set of skills unlike advisors who do not specialize in major changers. MRS advisors identified as seasoned staff members with training in both career and mental health counseling. A requirement for employment as an MRS advisor, a background in mental health counseling applies directly to the many students who arrive at the MRS office with a sense of urgency, frustration, defeat, and preexisting mental health conditions (e.g., depression). MRS advisors also demonstrate key career advising competencies outlined in the Handbook of Career Advising (Hughey, Nelson, Damminger, & McCalla-Wriggins, 2009). Specifically, they exhibit a solid understanding of student development as well as learning and career development. Furthermore, they apply extensive knowledge about all academic programs and curriculum requirements at the 13 colleges of this university rather than an individual college or a program. Highly motivated, MRS advisors demonstrate effectiveness in working with students to achieve their goals. Advisors who handle other types of advising need might consider MRS advisors to be generalists.
Philosophically, MRS advising is guided by the principles of developmental advising (e.g., Grites, 2013; Grites & Gordon, 2000) and the notion that one discovers vocational options through a gradual process (Gottfredson, 2005). In practice, the 3-I process—inquire, inform, integrate—proposed by Gordon (2006) was incorporated into the advisors' interactions with students. The MRS advisor carefully studies the in-take form (see Appendix) filled out by the student and then provides individualized, student-centered, collaborative, and goal-orientated advising. In addition to discussing the key information provided by the student on the in-take form, the MRS-trained advisor probes into additional issues deemed important for engaging students in reflection on their academic history, strengths, and weaknesses and in evaluating steps necessary for their academic progress and personal growth. Equally important, the MRS advisor works with the students to consider more than the linear connection between an academic major and a postgraduation career and think about gaining transferable skills (e.g., critical thinking).
Demographics
Table 1 summarizes the demographics of the two groups. No significant differences in age, gender distribution, or percentage of transfer students were found; however, a significant group difference was found in the distribution of ethnic and racial backgrounds between the two groups (χ2 = 13.60, p = .002).
Post hoc analyses showed a significantly higher percentage of White students in the treatment group (52.5%) than in the control group (37.4%): χ2 = 9.81, p = .002. However, the percentage of Black students in the treatment group (20.1%) was significantly lower than in the control group (30.6%): χ2 = 6.20, p = .012. The percentage of Asian students was significantly lower in the treatment group (7.3%) than in the control group (13.1%): χ2 = 3.93, p = .047.
Reasons for Major Re-selection and Mean GPAs
According to information gathered from in-take forms completed by students in the treatment group, students need to change majors for multiple reasons. Using techniques proposed by Creswell (2013), we applied content analysis to the treatment group's reasons for major re-selection and to the self-identified barriers to their academic progress. More specifically, we identified recurring terms in student responses and used them as coding categories, which we subsequently transformed into emerging themes. Results showed that loss of interest in the previous major (n = 79; 40.1%), difficulties with courses in the previous major (n = 56; 28.4%), failure to meet minimum GPA requirements of the academic program (n = 29; 14.7%), failure to meet some or all of the prerequisites of a desired major (n = 11; 5.58%), denial of admission into a desired major (n = 7; 3.55%), and other issues (e.g., family finance, mental health; n = 66; 33.5%) were primary reasons for changing majors. Because the control group participants did not receive MRS, no information was available on their reasons for changing majors.
Pretest GPA
The mean semester GPA of the treatment group was significantly higher (M = 2.73, SD = .67) than that of the control group (M = 2.58, SD = .49): t = 2.70, p = .007. According to university grading guidelines, the averages correspond to a B− for the treatment group and a C+ for the control group. The program GPA of the treatment group (M = 2.85, SD = .60) was also significantly higher than that of the control group (M = 2.75, SD = .46): t = 2.07, p = .004. The mean GPAs for both groups correspond to a B−.
Posttest GPA
The mean semester GPA for the treatment group (M = 2.86, SD = .83) was significantly higher than that for the control group (M = 2.22, SD = .71): t = 7.91, p < .001. These means correspond to a B− for the treatment group and a C for the control group. The mean program GPA for the treatment group (M = 2.84, SD = .57) was also significantly higher than that for the control group (M = 2.48, SD = .36): t = 7.85, p < .001. These means correspond to a B− for the treatment group and a C+ for the control group.
Changes in GPA after MRS
As shown in Figure 1, after receiving MRS advising, students in the treatment group experienced a significant increase in semester GPAs: pretest, M = 2.73, SD = .67; posttest, M = 2.86, SD = .83; paired t = 2.39, p = .018. The GPAs correspond to Bs according to the university grading guidelines. However, the treatment group experienced no changes in mean program GPAs: pretest, M = 2.85, SD = .60; posttest, M = 2.83, SD = .56; paired t = .61, p = .54. On the contrary, students in the control group experienced a significant decrease in semester GPAs: pretest, M = 2.58, SD = .49; posttest, M = 2.22, SD = .71; paired t = 6.39, p = .001. This corresponds to a decrease from C+ to C. The control group also experienced a significant decrease in program mean GPAs: pretest, M = 2.74, SD = .46; posttest: M = 2.47, SD = .35; paired t = 10.76, p = .001. This mean average corresponds to a drop from a B− to C+.
Citation: NACADA Journal 37, 1; 10.12930/NACADA-15-029
Multiple Regression Analysis
Simple correlation analyses revealed that semester GPAs were highly correlated with program GPAs prior to MRS advising (r = .85, p < .001) and after MRS advising (r = .74, p < .001). However, the students' pretest semester GPAs only moderately correlated with posttest semester GPAs (r = .35, p < .001). The control group pretest program GPAs were highly correlated with posttest program GPAs (r = .69, p < .001).
We conducted simultaneous multiple regression analyses for posttest semester GPAs and program GPAs respectively, with group membership (treatment vs. control group) as the key predictor. We controlled for students' demographic profile information (age, gender, ethnic and racial background), transfer status, and corresponding pretest semester and program GPAs (Table 2).
As presented in Table 2, regression results for posttest semester GPA showed that, with controlled demographic covariables and pretest GPA, students who received MRS had higher posttest semester GPAs (β = .35, p < .001) than students who did not receive MRS. Overall, the variables explained 26.3% of the variance in students' posttest semester GPAs. Regression results showed that, with controlled demographic variables and pretest program GPA (β = .67, p < .001), treatment group students, who had received MRS advising, showed a higher posttest mean program GPA (β = .28, p < .001) than control group students, who did not receive MRS. Overall, these variables explained 56.6% of the variance in students' posttest program GPAs.
Discussion
We examined the effect of MRS advising on undergraduate semester and program GPAs. We compared a group of undergraduates who changed their majors after receiving MRS advising with a group of randomly selected undergraduate major changers during the same period but who received no advising. The study yielded several informative findings.
First, information from the MRS in-take obtained from the treatment group undergraduates, who sought MRS advising before changing their majors, showed that loss of interest and poor academic performance with previous majors comprised the two main reasons for changing a major. These factors likely influenced each other. If interest proves an important factor in students' major selection as suggested (e.g., DeMarie & Aloise-Young, 2003; Malgwi, Howe, & Burnbay, 2005), then loss of interest might lead to academic disengagement, which contributes to poor academic performance. However, poor academic performance might also serve as a precursor for losing interest as well as involuntary major re-selection (Allen & Robbins, 2008). In addition, Asian and Black students who utilized MRS advising were underrepresented in the sample. Prior research has shown students of different ethnic and racial backgrounds hold different perceptions on the importance of academic advising (e.g., Kot, 2014; Smith & Allen, 2006). However, more research is needed to understand the factors associated with the underutilization of academic advising services among Asian and Black students.
We obtained data on the control group, such as demographic information, previous and current majors, pretest and posttest GPAs, from the registrar's reporting system, but we could not obtain qualitative data on students' decisions about seeking advising when selecting their new majors or the ways this group made sense of declining academic performances after changing their majors. Because of the further decline in their GPAs, the control group students may need to select another major again in subsequent semesters, or they may drop out of or be dismissed from the university. More research on their experiences would inform efforts to engage them proactively before they leave college by choice or by academic failure. In addition, because other intervention programs (e.g., academic assistance) have exerted significant and positive influences on students' GPAs and retention levels (e.g., Bahr, 2008; Pan, Guo, & Bai, 2008), future studies should expand the scope of this investigation into the ways other advising strategies affect students' academic performances.
Second, all undergraduates seeking it can receive MRS advising. Therefore, the students who chose to receive it before changing their majors resemble those chosen by random sample with regard to the independent variable. Because access did not affect either group, the higher mean pretest semester and program GPAs of the treatment group over those of the control group suggest nonaccess factors affected the choices to use MRS or not.
According to the literature, students who demonstrate better academic performances may seek help more readily than those who perform less well (Alexitch, 2002). They also may not doubt the quality of the advising (Metzner, 1989). Perhaps those in the treatment group, with the higher mean GPA, perceived that MRS advising could help them in selecting a new major. This speculation comports with the literature suggesting that utilization of university resources are positively associated with academic performance (e.g., Robbins et al., 2009). Research has also shown that students possess widely different perceptions of the benefits of advising (Christian & Sprinkle, 2013). Therefore, the GPA differences between the two groups may reflect differences in the students' beliefs about the benefits of MRS. Furthermore, the lower performance of the control group may reflect other characteristics or issues (e.g., inadequate decision-making efficacy, poor academic preparedness) (Firmin & MacKillop, 2008).
Third, treatment group t tests revealed a significant increase in semester GPA but no difference in program GPA; control group t tests revealed a significant decrease in both semester and program GPAs. However, multiple regression analyses, in which the pretest GPA and demographic variables were controlled, showed that students who received MRS had earned higher posttest semester and program GPAs than students who did not receive MRS. These findings confirmed the hypothesis that MRS was associated in a positive way with students' GPAs. The positive effect of advising has been well established (e.g., Steingass, & Sykes, 2008). Findings from our study lend further support to this body of literature. Because MRS advisors were trained to utilize a developmental advising approach with students whose chosen majors were no longer viable, students who interacted with MRS advisors likely selected new majors that fit well with their academic backgrounds, interests, and career aspirations. Students' corresponding pretest GPAs significantly predicted posttest GPAs, suggesting that previous academic performance was a significant predictor of subsequent academic performance.
Taking these findings together, we concluded that MRS advising exerted a positive influence on students' GPAs. However, we caution against generalizing the findings, but point out that they add support to the literature showing that underutilization of resources and services is associated with lower academic performance of undergraduates considered academically at risk (Robbins et al., 2009).
Limitations and Recommendations for Practice
Several limitations characterize this study. First the two groups were not matched on pretest GPA or ethnic and racial background. In an ideal design, both groups of students with identical previous and current majors (e.g., all students changed their major from psychology to social work) would have allowed for a more straightforward interpretation of the effect (or lack thereof) of MRS advising on GPAs. In addition, limited qualitative data were available for elucidating the reasons students in the control group chose not to utilize MRS advising services.
Nonetheless, findings from our study offer some implications for undergraduate education and advising. Because undergraduates at most 4-year U.S. institutions must declare majors upon completing general education courses, advisors who proactively engage students making their initial selection of major might reduce the instances of subsequent major re-selection. This study also reinforces the need for specific strategies for helpings students select a program of study. Some identified in the academic advising literature include assurances that students learn about services available to assist them in selecting and changing academic majors. These types of programs may be of particular benefit to Asian and Black students who may be unaware of these services. For students considered at a high risk for academic failure, targeted intrusive advising (e.g., Heisserer & Parette, 2002), instead of student-initiated voluntary advising, might yield better outcomes. Proactively identifying at-risk individuals who might benefit from MRS advising may also facilitate academic performance.
Change in undergraduate GPAs between pretest and posttest
Contributor Notes
Deborah McKenzie is the Program Coordinator for Major Re-selection at the University of South Florida. Contact her at dmajor@usf.edu.
Tony Xing Tan is a professor of Educational Psychology at the University of South Florida
Edward C. Fletcher is an associate professor of Career and Workforce Education at the University of South Florida.
Andrea Jackson-Williams is a PhD student in Educational Psychology at the University of South Florida.
