Major Re-selection Advising and Academic Performance Deborah McKenzie, University of South Florida Tony Xing Tan, University of South Florida Edward C. Fletcher, University of South Florida Andrea Jackson-Williams, University of South Florida We sought to determine whether receiving major undergraduate years (Beggs et al., 2008; Gordon, re-selection (MRS) advising benefits undergrad- 2007) and a 6-year degree attainment rate below uate students’ grade-point averages (GPAs). We 60% among American college students who enroll used a quasi-experimental nonequivalent control in 4-year colleges (Bettinger, Boatman, & Long, group design to compare a treatment group (n ¼ 2013; Cuseo, 1991). 219) of undergraduates who changed their Academic advising designed to help students majors after receiving MRS advising with a transition from one major to another contributes to control group (n ¼ 206) who changed majors students’ academic progression, persistence with without advising during the same semester as the re-selected majors, and retention (Campbell & treatment group. Findings showed that, on Nutt, 2008; Gordon & Steele, 1992; Hunter & average, students who received MRS experienced White, 2004; Mayhall & Burg, 2002; Metzner, no change in their program GPA but an increase 1989; Steele, 1994; Steele, Kennedy, & Gordon, in their semester GPA; however, the control group 1993; Steingass & Sykes, 2008). For instance, in a experienced a decrease in program and semester recent study on the effect of centralized advising, GPAs. Multiple regression analysis confirmed Kot (2014) found that first-year students who that MRS advising had a positive effect on received centralized advising had earned higher posttest semester GPAs (b ¼.33, p , .001) and grade-point averages (GPAs) and experienced program GPAs (b ¼.28, p , .001). Implications lower attrition rates than peers who did not receive for student advising are discussed. any advising during the same period. Kot em- [doi:10.12930/NACADA-15-029] ployed the propensity score matching technique to estimate the impact of centralized academic KEY WORDS: academic performance, major advising on 2,745 undergraduates’ first-year GPAs changers, major re-selection advising, nonequiv- and second-year enrollment behaviors. Data from alent control group design students who accessed centralized advising were matched with those who received no advising over Research has shown that when selecting the same two semesters. Findings showed that academic majors, undergraduates take into consid- students who used centralized academic advising eration their academic interests, aptitude, the earned higher first-term, second-term, and first- psychological and social benefits associated with year cumulative GPAs and more enrolled for their a major, postgraduation employment prospects, second year than students who had not seen an and the appropriate education for their chosen advisor. occupations (Allen & Robbins, 2008; Beggs, The burden for receiving useful advising does Bantham, & Taylor, 2008). Changes in any of not fall solely to students. Some colleges and these factors might lead students to re-select an academic major. In an alternative scenario, some universities provide inadequate advising opportu- undergraduates declare a major after minimal nities to connect students’ interests (e.g., career considerations of relevant circumstances (Mor- goals) with appropriate academic majors (Feldt et timer, Zimmer-Gembeck, Holmes, & Shanahan, al., 2011). To provide an effective advising 2002). As a result of either situation, students may program, planners and administrators must recog- lack confidence in their original choice and nize that students at different stages of their commitment to their declared major such that they academic career need different types of advising. subsequently need to change to a different major. For instance, first-year students looking to declare Both of these decision-making processes may a major likely require different conversations and contribute to the 35–75% of undergraduates exercises than second- or third-year students who changing their majors at least once during their experienced failure in their selected program and NACADA Journal Volume 37(1) 2017 15 McKenzie et al. must find a new major to remain enrolled in who receive MRS advising outperform major college. changers who do not receive any advising? We Because students who need to re-select their included two groups of undergraduates who majors are particularly vulnerable for leaving matriculated at approximately the same time and college without a degree (e.g., dropping out or changed their majors at the same point in their academic dismissal), some postsecondary institu- college careers. However, without random group tions allocate academic advising resources to assignments, we did not have pretest sampling respond to the specific needs of major changers. data for the two groups. Students in the treatment A typical program features a centralized major re- group changed their majors after receiving MRS selection (MRS) advising office that provides advising. The students in the control group advising to students who request it; however, little changed their majors without receiving MRS research has been conducted to describe specific advising. This research design provided an characteristics of MRS advising and whether they opportunity to infer the effect of MRS advising benefit students who received it. Therefore, for the on students’ programs and term GPAs while current study, we described a centralized MRS as controlling for a host of covariates, including age, well as compare the academic performances of gender, transfer status, and racial background. undergraduates who changed their majors after receiving MRS advising with a peer group who Participants changed majors without receiving any advising. On Most participants were in their third year the basis of existing literature, we hypothesized (78.3%). The groups also included sophomores that students who selected majors after receiving (16.2%) and seniors (5.5%) during the 2013-2014 MRS advising would outperform their peers who academic year. The treatment group included all changed their majors without receiving advising. 219 students who received MRS advising during the summer and fall semesters of 2012. Prior to Methods receiving MRS advising, these students had Context completed an average of 28.9 credit hours (SD The study was conducted at a comprehensive, ¼ 10.5) and had formally declared an academic public, research university serving more than major at the university. Subsequent to receiving 48,000 students. The first-to-second year reten- MRS advising, all treatment group students had tion rate was 89%, and 67% had graduated within selected and declared a different major. The 6 years. Similar to descriptions in the literature control group was randomly drawn from the (e.g., Gordon & Steele, 1992; Osipow, 1983), at undergraduate population who had matriculated the studied university, second- and third-year at approximately the same time as students students in good academic standing (defined as a assigned to the treatment group. It included 206 2.0 GPA or higher) need MRS advising because undergraduates who had declared a major and they have discovered new interests or experienced then changed to a different major during the same one or more academic challenges (e.g., failure to period as the treatment group students; however, complete prerequisites for a declared major). control group students received no advising. Students who want or need to change their majors Similar to those in the treatment group, students are encouraged, but not required, to meet with an in the control group had completed an average of MRS advisor and to consult with advisors in both 28.7 credit hours (SD ¼8.9) when they changed their current college and the one(s) of interest. In their majors. other words, undergraduates may declare their major by completing a major declaration online Data Source or on paper by submitting the proper form to the Upon approval from the Institutional Review college of choice. After college staff process the Board, we obtained the following data directly information and update the student records from the university registrar reporting system for system, students may register for courses in their students in both groups: demographic informa- new college. tion (e.g., age, gender, ethnic and racial back- grounds); transfer status (i.e., whether or not the Research Design student transferred into the university); previously We used a quasi-experimental nonequivalent declared major and currently declared major; and control group design (per Fife-Schaw, 2012) to GPAs for each semester as well as for the address the research question: Do major changers students’ programs of study for each semester. 16 NACADA Journal Volume 37(1) 2017 Major Re-selection Advising In addition, students in the treatment group filled Handbook of Career Advising (Hughey, Nelson, out an in-take form that included a checklist of Damminger, & McCalla-Wriggins, 2009). Spe- reasons for major re-selection prior to meeting cifically, they exhibit a solid understanding of with their MRS advisor. The students could student development as well as learning and choose all the reasons that applied to them as career development. Furthermore, they apply well as write in additional reasons. No informa- extensive knowledge about all academic pro- tion was available on the reasons for major grams and curriculum requirements at the 13 change among those in the control group because colleges of this university rather than an individ- they did not request MRS advising. Finally, ual college or a program. Highly motivated, MRS information on the characteristics of the MRS advisors demonstrate effectiveness in working office was provided by the program manager of with students to achieve their goals. Advisors the MRS office. who handle other types of advising need might In data analyses, pretest semester GPAs were consider MRS advisors to be generalists. calculated by averaging the students’ GPAs from Philosophically, MRS advising is guided by all semesters before the time period the treatment the principles of developmental advising (e.g., group students received MRS advising (Summer Grites, 2013; Grites & Gordon, 2000) and the and Fall 2012). Posttest semester GPAs were notion that one discovers vocational options determined from students’ GPAs of the semester through a gradual process (Gottfredson, 2005). after receiving MRS advising (Spring 2013). In practice, the 3-I process—inquire, inform, Pretest program GPAs were calculated from integrate—proposed by Gordon (2006) was cumulative GPAs earned in program-specific incorporated into the advisors’ interactions with courses in all semesters before the students students. The MRS advisor carefully studies the received MRS advising. Posttest program GPAs in-take form (see Appendix) filled out by the were obtained from Spring 2013 semester grades student and then provides individualized, student- after students received MRS advising. centered, collaborative, and goal-orientated ad- vising. In addition to discussing the key infor- Results mation provided by the student on the in-take Characteristics of Major Re-selection Advising form, the MRS-trained advisor probes into According to the program manager, the MRS additional issues deemed important for engaging office is staffed with two full-time MRS advisors students in reflection on their academic history, and two part-time graduate assistants. The MRS strengths, and weaknesses and in evaluating steps advisors were trained to recognize that many necessary for their academic progress and second- and third-year students in need of new personal growth. Equally important, the MRS majors were at an elevated risk for leaving the advisor works with the students to consider more college without a degree (e.g., being dismissed or than the linear connection between an academic dropping out), and advisors accepted a vital role major and a postgraduation career and think in promoting student retention. Similar to other about gaining transferable skills (e.g., critical types of academic advisors, the MRS advisors thinking). only work with students who request advising to re-select majors and serve as liaisons between Demographics students and mental health counseling profes- Table 1 summarizes the demographics of the sionals (e.g., Kadar, 2001; Robbins, 2012). two groups. No significant differences in age, MRS advisors have acquired a set of skills gender distribution, or percentage of transfer unlike advisors who do not specialize in major students were found; however, a significant group changers. MRS advisors identified as seasoned difference was found in the distribution of ethnic staff members with training in both career and and racial backgrounds between the two groups mental health counseling. A requirement for (v 2 ¼13.60, p ¼.002). employment as an MRS advisor, a background Post hoc analyses showed a significantly in mental health counseling applies directly to the higher percentage of White students in the many students who arrive at the MRS office with treatment group (52.5%) than in the control a sense of urgency, frustration, defeat, and group (37.4%): v 2 ¼ 9.81, p ¼ .002. However, preexisting mental health conditions (e.g., de- the percentage of Black students in the treatment pression). MRS advisors also demonstrate key group (20.1%) was significantly lower than in the career advising competencies outlined in the control group (30.6%): v2 ¼6.20, p ¼.012. The NACADA Journal Volume 37(1) 2017 17 McKenzie et al. Table 1. Demographics of the treatment and control groups (N ¼425) Demographic Treatment Group (n ¼ 219) Control Group (n ¼ 206) Statistic Mean age (years) 22.7 (SD ¼ 6.0) 22.8 (SD ¼ 2.8) t ¼ .16 Gender n (%) n (%) v 2 ¼ 1.24 Female 136 (62.1) 117 (56.8) Male 73 (37.9) 89 (43.2) Race/Ethnicity v 2 ¼ 13.60** Asian 16 (7.3) 27 (13.1) Black 44 (20.1) 63 (30.6) Hispanic 44 (20.1) 39 (18.9) White 115 (52.5) 77 (37.4) Transfer student v2 ¼ .09 Yes 84 (38.4) 82 (39.1) No 135 (61.6) 124 (60.9) Note. **p , .01. percentage of Asian students was significantly the control group. The program GPA of the lower in the treatment group (7.3%) than in the treatment group (M ¼ 2.85, SD ¼ .60) was also control group (13.1%): v 2 ¼3.93, p ¼.047. significantly higher than that of the control group (M ¼2.75, SD ¼.46): t ¼2.07, p ¼.004. The mean Reasons for Major Re-selection and Mean GPAs for both groups correspond to a B� . GPAs Posttest GPA. The mean semester GPA for the According to information gathered from in- treatment group (M ¼ 2.86, SD ¼ .83) was take forms completed by students in the treatment significantly higher than that for the control group group, students need to change majors for (M ¼2.22, SD ¼.71): t ¼7.91, p , .001. These multiple reasons. Using techniques proposed by means correspond to a B� for the treatment group Creswell (2013), we applied content analysis to and a C for the control group. The mean program the treatment group’s reasons for major re- GPA for the treatment group (M ¼2.84, SD ¼.57) selection and to the self-identified barriers to was also significantly higher than that for the their academic progress. More specifically, we control group (M ¼2.48, SD ¼.36): t ¼7.85, p , identified recurring terms in student responses .001. These means correspond to a B� for the and used them as coding categories, which we treatment group and a Cþfor the control group. subsequently transformed into emerging themes. Changes in GPA after MRS. As shown in Results showed that loss of interest in the Figure 1, after receiving MRS advising, students in previous major (n ¼79; 40.1%), difficulties with the treatment group experienced a significant courses in the previous major (n ¼ 56; 28.4%), increase in semester GPAs: pretest, M ¼2.73, SD failure to meet minimum GPA requirements of ¼.67; posttest, M ¼2.86, SD ¼.83; paired t ¼2.39, the academic program (n ¼29; 14.7%), failure to p ¼.018. The GPAs correspond to Bs according to meet some or all of the prerequisites of a desired the university grading guidelines. However, the major (n ¼11; 5.58%), denial of admission into a treatment group experienced no changes in mean desired major (n ¼ 7; 3.55%), and other issues program GPAs: pretest, M ¼ 2.85, SD ¼ .60; (e.g., family finance, mental health; n ¼ 66; posttest, M ¼2.83, SD ¼.56; paired t ¼.61, p ¼.54. 33.5%) were primary reasons for changing On the contrary, students in the control group majors. Because the control group participants experienced a significant decrease in semester did not receive MRS, no information was GPAs: pretest, M ¼2.58, SD ¼.49; posttest, M ¼ available on their reasons for changing majors. 2.22, SD ¼.71; paired t ¼ 6.39, p ¼ .001. This Pretest GPA. The mean semester GPA of the corresponds to a decrease from Cþ to C. The treatment group was significantly higher (M ¼ control group also experienced a significant 2.73, SD ¼.67) than that of the control group (M ¼ decrease in program mean GPAs: pretest, M ¼ 2.58, SD ¼.49): t ¼2.70, p ¼.007. According to 2.74, SD ¼.46; posttest: M ¼2.47, SD ¼.35; paired university grading guidelines, the averages corre- t ¼10.76, p ¼.001. This mean average corresponds spond to a B� for the treatment group and a Cþfor to a drop from a B� to Cþ. 18 NACADA Journal Volume 37(1) 2017 Major Re-selection Advising Figure 1. Change in undergraduate GPAs between pretest and posttest Multiple Regression Analysis MRS advising, showed a higher posttest mean Simple correlation analyses revealed that program GPA (b ¼ .28, p , .001) than control semester GPAs were highly correlated with group students, who did not receive MRS. program GPAs prior to MRS advising (r ¼.85, Overall, these variables explained 56.6% of the p , .001) and after MRS advising (r ¼.74, p , variance in students’ posttest program GPAs. .001). However, the students’ pretest semester GPAs only moderately correlated with posttest Discussion semester GPAs (r ¼.35, p , .001). The control We examined the effect of MRS advising on group pretest program GPAs were highly corre- undergraduate semester and program GPAs. We lated with posttest program GPAs (r ¼.69, p , compared a group of undergraduates who changed .001). their majors after receiving MRS advising with a We conducted simultaneous multiple regres- group of randomly selected undergraduate major sion analyses for posttest semester GPAs and changers during the same period but who received program GPAs respectively, with group member- no advising. The study yielded several informative ship (treatment vs. control group) as the key findings. predictor. We controlled for students’ demograph- First, information from the MRS in-take ic profile information (age, gender, ethnic and obtained from the treatment group undergraduates, racial background), transfer status, and corre- who sought MRS advising before changing their sponding pretest semester and program GPAs majors, showed that loss of interest and poor (Table 2). academic performance with previous majors com- As presented in Table 2, regression results for prised the two main reasons for changing a major. posttest semester GPA showed that, with con- These factors likely influenced each other. If trolled demographic covariables and pretest GPA, interest proves an important factor in students’ students who received MRS had higher posttest major selection as suggested (e.g., DeMarie & semester GPAs (b ¼.35, p , .001) than students Aloise-Young, 2003; Malgwi, Howe, & Burnbay, who did not receive MRS. Overall, the variables 2005), then loss of interest might lead to academic explained 26.3% of the variance in students’ disengagement, which contributes to poor academ- posttest semester GPAs. Regression results ic performance. However, poor academic perfor- showed that, with controlled demographic vari- mance might also serve as a precursor for losing ables and pretest program GPA (b ¼ .67, p , interest as well as involuntary major re-selection .001), treatment group students, who had received (Allen & Robbins, 2008). In addition, Asian and NACADA Journal Volume 37(1) 2017 19 McKenzie et al. Table 2. Multiple regression predicting posttest semester and program GPAs (N ¼425) Posttest Semester GPA Posttest Program GPA Characteristics B b B b Age .004 .02 .004 .04 Female .12 .07 .04 .04 Male Ref.(0) Ref.(0) Ref.(0) Ref.(0) Nontransfer student �.19 �.11* �.03 �.03 Transfer student Ref.(0) Ref.(0) Ref.(0) Ref.(0) Asian .20 .07 �.02 �.01 Black .05 .02 �.04 �.04 Hispanic .02 .01 �.04 �.03 White Ref.(0) Ref.(0) Ref.(0) Ref.(0) Pretest GPA .46 .33*** .63 .67*** MRS advising (yes) .58 .35*** .28 .28*** MRS advising (no) Ref.(0) Ref.(0) Ref.(0) Ref.(0) F 21.06*** 54.88*** R2 .263 .566 Note. MRS ¼Major re-selection advising. For posttest semester GPA, corresponding pretest semester GPAs were used; for posttest program GPA, corresponding pretest program GPAs were used. *p , .05. **p , .01. ***p , .001. Black students who utilized MRS advising were advising strategies affect students’ academic per- underrepresented in the sample. Prior research has formances. shown students of different ethnic and racial Second, all undergraduates seeking it can backgrounds hold different perceptions on the receive MRS advising. Therefore, the students importance of academic advising (e.g., Kot, who chose to receive it before changing their 2014; Smith & Allen, 2006). However, more majors resemble those chosen by random sample research is needed to understand the factors with regard to the independent variable. Because associated with the underutilization of academic access did not affect either group, the higher mean advising services among Asian and Black students. pretest semester and program GPAs of the treatment group over those of the control group We obtained data on the control group, such as suggest nonaccess factors affected the choices to demographic information, previous and current use MRS or not. majors, pretest and posttest GPAs, from the According to the literature, students who registrar’s reporting system, but we could not demonstrate better academic performances may obtain qualitative data on students’ decisions about seek help more readily than those who perform less seeking advising when selecting their new majors well (Alexitch, 2002). They also may not doubt the or the ways this group made sense of declining quality of the advising (Metzner, 1989). Perhaps academic performances after changing their ma- those in the treatment group, with the higher mean jors. Because of the further decline in their GPAs, GPA, perceived that MRS advising could help the control group students may need to select them in selecting a new major. This speculation another major again in subsequent semesters, or comports with the literature suggesting that they may drop out of or be dismissed from the utilization of university resources are positively university. More research on their experiences associated with academic performance (e.g., Rob- would inform efforts to engage them proactively bins et al., 2009). Research has also shown that before they leave college by choice or by academic students possess widely different perceptions of the failure. In addition, because other intervention benefits of advising (Christian & Sprinkle, 2013). programs (e.g., academic assistance) have exerted Therefore, the GPA differences between the two significant and positive influences on students’ groups may reflect differences in the students’ GPAs and retention levels (e.g., Bahr, 2008; Pan, beliefs about the benefits of MRS. Furthermore, Guo, & Bai, 2008), future studies should expand the lower performance of the control group may the scope of this investigation into the ways other reflect other characteristics or issues (e.g., 20 NACADA Journal Volume 37(1) 2017 Major Re-selection Advising inadequate decision-making efficacy, poor academ- and advising. Because undergraduates at most 4- ic preparedness) (Firmin & MacKillop, 2008). year U.S. institutions must declare majors upon Third, treatment group t tests revealed a completing general education courses, advisors significant increase in semester GPA but no who proactively engage students making their difference in program GPA; control group t tests initial selection of major might reduce the revealed a significant decrease in both semester instances of subsequent major re-selection. This and program GPAs. However, multiple regression study also reinforces the need for specific strategies analyses, in which the pretest GPA and demo- for helpings students select a program of study. graphic variables were controlled, showed that Some identified in the academic advising literature students who received MRS had earned higher include assurances that students learn about posttest semester and program GPAs than students services available to assist them in selecting and who did not receive MRS. These findings changing academic majors. These types of pro- confirmed the hypothesis that MRS was associated grams may be of particular benefit to Asian and in a positive way with students’ GPAs. The positive Black students who may be unaware of these effect of advising has been well established (e.g., services. For students considered at a high risk for Steingass, & Sykes, 2008). Findings from our academic failure, targeted intrusive advising (e.g., study lend further support to this body of literature. Heisserer & Parette, 2002), instead of student- Because MRS advisors were trained to utilize a initiated voluntary advising, might yield better developmental advising approach with students outcomes. Proactively identifying at-risk individu- whose chosen majors were no longer viable, als who might benefit from MRS advising may students who interacted with MRS advisors likely also facilitate academic performance. selected new majors that fit well with their academic backgrounds, interests, and career aspi- References rations. Students’ corresponding pretest GPAs Alexitch, L. R. (2002). The role of help-seeking significantly predicted posttest GPAs, suggesting attitudes and tendencies in students’ prefer- that previous academic performance was a signif- ences for academic advising. 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Distinguishing the factors influencing college students’ choice of major. College Several limitations characterize this study. First the two groups were not matched on pretest GPA or Student Journal, 42, 381–394. ethnic and racial background. In an ideal design, Bettinger, E. P., Boatman, A., & Long, B. T. both groups of students with identical previous and (2013). Student supports: Developmental edu- current majors (e.g., all students changed their cation and other academic programs. The major from psychology to social work) would have Future of Children, 23(1), 93–115. allowed for a more straightforward interpretation of Campbell, S. M., & Nutt, C. L. (2008). Academic the effect (or lack thereof) of MRS advising on advising in the new global century: Supporting GPAs. In addition, limited qualitative data were student engagement and learning outcomes available for elucidating the reasons students in the achievement. 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Lent (Eds.), Career development and Psychotherapy, 26, 216–226. counseling: Putting theory and research to Robbins, S., Allen, J., Casillas, A., Akamigbo, work (pp. 71–100). Hoboken, NJ: John Wiley A., Saltonstall, M., Campbell, R., & Gore, P. & Sons. (2009). Associations of resource and service Grites, T. (2013). Developmental academic ad- utilization, risk level, and college outcomes. vising: A 40-year context. NACADA Journal, Research in Higher Education, 50(1), 101– 33(1), 5–15. 118. Grites, T., & Gordon, V. (2000). Developmental Smith, C., & Allen, J. (2006). Essential functions academic advising revisited. NACADA Jour- of academic advising: What students want and nal, 29(1), 12–15. get. NACADA Journal, 26(1), 56–66. 22 NACADA Journal Volume 37(1) 2017 Major Re-selection Advising Steele, G. E. (1994). Major-changers: A special Authors’ Notes type of undecided student In V. N. Gordon Deborah McKenzie is the Program Coordinator (Ed.), Issues in advising the undecided college for Major Re-selection at the University of student (Monograph Series No. 15; pp. 85– South Florida. Contact her at [email protected]. 92). Columbia: University of South Carolina, National Resource Center for The Freshman- Tony Xing Tan is a professor of Educational Year Experience. Psychology at the University of South Florida Steele, G. E., Kennedy, G. J., & Gordon, V. N. Edward C. Fletcher is an associate professor of (1993). The retention of major changers: A Career and Workforce Education at the Univer- longitudinal study. Journal of College Student sity of South Florida. Development, 34, 58–62. Steingass, S. J., & Sykes, S. (2008). Centralizing Andrea Jackson-Williams is a PhD student in advising to improve student outcomes. Peer Educational Psychology at the University of Review, 10(1), 18–20. South Florida. NACADA Journal Volume 37(1) 2017 23 McKenzie et al. Appendix. Major re-selection advising information form Welcome to the TRansitional Advising 1. Why did you originally choose this major? Center (TRAC)! Our advisors are here to help ______________________________________ you choose a new major based on your goals, 2. Who or what had any influence on your interests, and academic abilities. Most often, decision? _____________________________ students need to re-select a major because they 3. Why are you no longer pursuing this major? no longer meet the GPA requirement for their (Check all that apply) original major or their career goals and interests u Did not meet GPA requirements have changed. u Portfolio was denied Students with ‘‘MJ’’ holds are prevented from u Having difficulty with courses registering for classes until they declare a major. u Too many prerequisites/courses Choosing a new major requires active partici- u Loss of interest in the field pation by both the student and the advisor. u D/F Rule During the major re-selection process, your u Dismissal/ARC Petition advisor will explore the degree options available u Academic Probation to you and may refer you to campus resources u Other: that can further assist you in making an 4. How may the Major Re-Selection advisor informed decision. assist you? _____________________________ After you have decided on a major, your 5. What are your career goals?_____________ TRAC advisor will assist you with the declaration 6. Have you ever visited USF’s Career Center for process and provide contact information for your career exploration? new for your new major. If you have an ‘‘MJ’’ u Yes hold, it will be lifted after you officially declare u No your new major with the appropriate college. 7. How frequently have you been meeting with All degree plans and courses discussed with your academic advisor? __________________ your TRAC advisor must be confirmed by the 8. How would you describe your study habits? advisor for your new major. You are expected to ______________________________________ meet with your new advisor immediately upon 9. What could you do to improve? _________ declaring your new major. 10. Please describe any external factors that may Name: ________________________________ have interfered with your academic performance Student ID#: __________________________ (i.e., illness, family emergency, first time away E-mail address: ________________________ from home, etc.): _______________________ Phone: _______________________________ 11. Please cross off majors that you have no Current Cumulative GPA: ________________ interest in and rank remaining majors based on Previous Major: ________________________ your interest level 24 NACADA Journal Volume 37(1) 2017