Understanding the Factors that Contribute to Graduate Student Success: A Study of Wingate University s MBA Program



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Understanding the Factors that Contribute to Graduate Student Success: A Study of Wingate University s MBA Program Lisa Schwartz, Wingate University Kristin Stowe, Wingate University Patricia Sendall, Merrimack College ABSTRACT MBA programs search for ways to identify candidates who will be successful in their programs. Several studies have been done that have analyzed the relationship between graduate grade point average and factors that contribute to academic performance, such as Graduate Management Aptitude Test (GMAT) scores, undergraduate GPA, gender and business experience. This paper addresses the relationship between graduate GPA and the traditional variables; however, it will use actual years of business experience instead of a proxy, the method used in other papers. This paper will also look at how enrollment in a one semester prerequisite course for students without undergraduate business degree impacts graduate GPA. A second goal of the study is to analyze students who withdrew from the MBA program before completion. The authors will compare data of these students to students who successfully completed the program to look for potential risk indicators. The analysis shows a significant positive relationship between graduate GPA and GMAT, particularly the quantitative score. INTRODUCTION Wingate University is a small, private institution located in North Carolina. The School of Business offers bachelor s degrees as well as a Master of Business Administration (MBA) degree. Both the undergraduate and MBA programs are ACBSP accredited. The institution began offering MBA courses in the fall of 1991, and the first graduate degrees were awarded in May 1993. The School of Business has kept records, including original applications, for all students since the program s inception. The School of Business uses a standard criterion for evaluating MBA admissions applications: undergraduate grade point average (UG GPA), GMAT score, work experience and letters of recommendation. An index number is calculated for each student of GMAT + 200*Undergraduate GPA. Students with an index number below 1100 may be admitted on probationary status. Students are also required to have at least 2 years of business experience, although many students have been admitted without meeting this requirement. Overall, the school has a fairly open admissions policy. Applicants are usually given a chance to prove themselves in the classroom.

LITERATURE REVIEW Since the late 1970 s, beginning with a study by Deckro and Woudenberg (1977), researchers have sought to understand MBA admission criteria and if or how we can predict an applicant s success through the admission process. Numerous studies have been done over the past 30 years, but the results are varied. A question this study seeks to answer is whether the standard criteria, specifically GMAT score and undergraduate GPA, have a high value in predicting an applicant s success in an MBA program. Deckro and Woundenberg (1977) concluded that, Total GMAT score remains the most significant single criterion for admission. In addition to GMAT score, they established that previous undergraduate study and GPA averages were acceptable predictors of academic success. Other studies have had similar conclusions. Wright and Palmer (1994) sorted students into four groups based on their graduate GPAs. GMAT scores and undergraduate GPAs were significant predictors for students in the middle groups but not for low performers. Wright and Palmer (1997) later found that the Verbal GMAT score is the most important variable when separating students at risk of not graduating (GPA<3.3) from students on track for graduation. According to Talento-Miller and Rudner (2008), Overall, the GMAT total score is the best individual predictor, and its validity coefficient is similar to the combination of the Verbal and Quantitative scores. They also found that the highest validity coefficients come from a combination of the GMAT factors in combination with undergraduate GPA. However, the GMAT-V and GMAT-Q have a higher predictive validity than undergraduate GPA alone. Their report summarized the results of 273 studies involving 41,338 students conducted from 1997 to 2004 using the Graduate Management Admission Council s (GMAC) Validity Study Service (VSS). Sobol (1984) used the background, activities, and personal qualities (BAPQ) scale to help improve graduate admissions decisions. This scale was used along with UG GPA and GMAT to forecast graduate GPA (GGPA). She concluded that only GMAT and GPA were useful predictors of MBA student success. Elkin and Sneyd (1989) concluded that the combined UG GPA and GMAT score is effective in predicting the achievement of students during the MBA program. Fisher and Resnick (1990) found that GMAT was the single best predictor of first year graduate GPA and concluded that a combination of GMAT plus GPA is the best available indicator of success. In a 2006 study conducted by Sireci, the results indicated that GMAT verbal and quantitative scores had substantial predictive validity, accounting for 16% of the variance in graduate GPA beyond that predicted by undergraduate GPA. When undergraduate GPA was factored in, they accounted for approximately 25% of the variation in first-year graduate GPA. As a result, GMAT quantitative and verbal scores are good predictors of first-year GPA in graduate school. In addition, he found that criteria such as GPA alone are not perfect measures of graduate school success. However, he also concluded that many other variables play a role in graduate school success, such as diligence, and cannot be measured by standardized tests. Other authors have also found that UG GPA and GMAT scores predict student success in other graduate degree programs. Siegert (2008) concluded that researchers and educators could - 1 -

effectively use UG GPA and GMAT scores in combination to choose students who would perform well in an executive [MBA] program. Using a variety of empirical Bayes regression, Zwick (1993) conducted a validity study to examine the degree to which GMAT scores and undergraduate GPA (UG GPA) could predict first-year GPA and final GPA in a business doctoral programs. She found that using UG GPA alone as a predictor tended to be more accurate than using GMAT verbal (GMATV) and GMAT quantitative (GMATQ) scores together. Including all three predictors was more effective than using only UG GPA. However, some schools have stopped using the GMAT (for example, Harvard Business School from 1985 to 1996) because its results had been shown to be poor predictors of success after graduate school and in the workplace (R. D. Bretz as cited in Peiperl and Trevelyan, 1997). Paolillo (1982) found undergraduate grades better than standardized test scores at predicting success in several graduate programs. Clayton and Cate (2004) concluded that traditional indicators of success, GPA and GMAT scores, played no significant role in the classification. Their study showed that dummy variables rather than the more standard numeric ones proved to be the most useful in both analyses. They asserted that GMAT scores and previous GPAs may not adequately predict success and may unfairly deny admission to some qualified students. Ahmadi, Raiszadeh and Helms (1997) study concurs; they found that standardized tests do not accurately measure an individual s ability, critical thinking skills, or competency and that GMAT scores and previous GPAs may not adequately predict success and may unfairly deny admission to some qualified students. Standardized tests put the test taker in a passive, reactive position often ignoring knowledge and student performance expectations. They are not written to measure a student s capacity to solve structured tasks, generate ideas, or to solve problems (Darling-Hammond as cited in Ahmadi, et. al, 1997). Hedlund, Wilt, Nebel, Ashford, and Sternberg (2006) argue that standard admission methods that only consider UG GPA and GMAT do not consider a student s full range of abilities that are important for success. The authors have shown that that Practical Intelligence (PI) 1 measures have the potential to improve the prediction of success in business school and in the workplace. PI attributes include personality, motivation, interpersonal skills and prior experience or noncognitive factors that relate to performance. Can gender help admission representatives predict the success of a student entering into an MBA degree program? Some studies do show some differences in the predictive value of factors for male and for female applicants, while others do not. Hancock (1999) found that MBA performance was essentially the same for men and for women even though the men had significantly higher GMAT scores. He observed that, though women performed significantly lower on the GMAT there was no discernible difference in overall MBA performance (graduate GPA). Hancock also found that, the average GGPA of those women scoring below 520 was virtually indistinguishable from either the men or women who scored 520 and above. Ahmadi, Raiszadeh and Helms (1997) used regression analysis to study factors including GMAT score, undergraduate GPA, age, race and gender. Neither race nor gender was significant in predicting graduate GPA while the other factors were. However, Sireci (2006) found that GMAT-Q and 1 Practical Intelligence (PI) is a component of a broader definition of intelligence, which also includes creative and analytical intelligence. (Hedlund, et. al, 2006) - 2 -

GMAT-V scores are valid predictors that do not appear to be biased against women or minorities. In addition to GMAT scores, Peiperl and Trevelyan (1997) considered age, gender, language proficiency, marital status and work experience as predictors of performance. They concluded that there was no indication that either women or men perform better in MBA programmes. Sulaiman and Mohezar (2006) also found that gender had no bearing on academic performance. Some studies have shown that women, relative to their male counterparts, are underperforming on the GMAT standardized tests, yet at the same time women perform as well or better than men with similar credentials. (Gropper, 2007). Deckro and Woudenberg (1977) concluded the women candidates on the average do better academically than their male peers. According to Hancock (1999), MBA admission strictly by GMAT score may disadvantage female candidates who are both qualified and vital to the future of business management. This study also seeks to answer whether or not business experience before entering a graduate degree program positively influences a student s ability to graduate and graduate GPA. Clayton and Cate (2004) used discriminate analysis to separate MBA no-shows from successful graduates. The most useful indicators were dummy variables such as full- or part-time status, instate residency and whether the admission application was complete. The authors also noted that unless they had a high UG GPA, non-business majors are at a disadvantage in the MBA program. Adams and Hancock (2000) sampled 269 MBA graduates using ANOVA and correlation analysis to show that amount of work experience prior to enrolling in the program is a predictor of success. They concluded that work experience is a better predictor of success than the GMAT score or UG GPA. They also found the years of experience variable is significant for both genders collectively, the effect is stronger for males than it is for females. The authors measured the work experience variable by a proxy, that is, years between the completion of the bachelor's degree and the first semester in the MBA program. The authors of this study used the same methodology when measuring work experience of the population used in this analysis. Not all scholars agree that work experience can be used as a predictor of success. A 1994 study done by Cooksey and Rindfuss concluded that entering the MBA program right after a student s bachelor s degree is completed is actually more desirable than seeking employment between degree programs. They found that work interruption between degrees leads to a higher likelihood of part-time enrollment, and a consequent lower probability of completing the degree program in a timely fashion. Sulaiman and Mohezar (2006) concluded that work experience was not related to MBA performance. A 2000 study carried out by Dreher and Ryan found little support that previous work experience leads to higher levels of academic achievement. Prior work experience was found to account for only a small proportion of the variance in first-semester grades. They also found that pre-mba work experience was unrelated to academic performance in the second semester. They wrote, Students with less than two years of previous work experience were performing as well as their more experienced counterparts by the end of the second semester in graduate school. There is no evidence that more than 5 years of work experience provided an advantage in either the first or second semester. - 3 -

In a follow-up study, Dreher and Ryan (2002) concluded that MBAs without prior work experience were more satisfied, had received more promotions, and earned more cash compensation than some of their more experienced counterparts. Other authors have suggested using unconventional tools to predict MBA student success. Naik and Ragothaman (2004) used neural network techniques to classify applicants into marginal and successful student pools. They included factors such as UG GPA, GMAT scores, undergraduate major, age and other relevant data. They concluded that the neural network tool predicts MBA student performance as well as other statistical models. Finally, Nilsson (1995) concluded that GMAT yielded a weaker relationship to GGPA than did the GRE exam. Considering the questions we raise in this study and the existing research on factors that attempt to predict the success of an MBA student, we hypothesize: H1: GMAT score will be a factor in predicting student performance H2: GMAT-Q is a better predictor of student success in the MBA program H3: GMAT + UG GPA is a better predictor of MBA GPA success than GMAT score alone H4: Gender will be a factor in predicting student performance H5: Work experience will be a factor in predicting student performance H6: The pre-requisite course will be a factor in predicting the performance of non-business majors entering the MBA degree program. DATA ANALYSIS One hundred seventy-five (175) students received the MBA degree from the program s inception in 1991 through summer 2007. Sixty-four (64), or 37%, of the graduates are women. Forty-one (41), or 23%, of the graduates entered the MBA program without an undergraduate business degree; they completed an undergraduate-level prerequisite course as required of nonbusiness majors by the University. This one semester, six hour course, BUS 500, covers principles of algebra, statistics, microeconomics, macroeconomics, accounting, finance, management and marketing. In addition to the 175 graduates, there were an additional 79 students who were admitted to the program who did not graduate. Of that group, thirty (38%) of the drop-outs are women. Twenty-three (23), or 29%, entered without an undergraduate business degree and enrolled in BUS 500. Students with a range of academic credentials are admitted to the program. A minimum GPA of 3.0 is required for graduation. As Table 1 shows, censoring of GMAT scores is not an issue here as in some studies. Work experience is taken from each student s admission application. We did not have to use age or years since graduation as a proxy for experience as have some studies. Table 1: Summary Statistics MBA GPA GMAT Undergraduate GPA Mean 3.46 463 2.99 8.33 Years of Work Experience - 4 -

Minimum 0 230 2.00 0 Maximum 4.00 720 4.00 35 This paper analyzes MBA student success two ways. For students who graduated, it identifies factors that increased the student s grade point average. For students who withdrew from the program before graduation, it uses the same variables to distinguish between graduates and non graduates. This paper will also compare the performance of male students to female students since many other authors have raised the question. MBA grade point average (MBA GPA) is the GPA the student had at the time of graduation or at the time of withdraw from the program. It is expected that the MBA GPA will be higher for graduates than non graduates. Undergraduate grade point average (UG GPA) is also expected to be higher for graduates, and should positively affect student success. The Wingate MBA program strongly recommends at least two years of professional experience. It is expected that business experience (Years Exp) should have a positive effect on student success. Many students apply for the MBA program without undergraduate business prerequisite courses. The BUS 500 course covers all foundation business courses. If the course is not a sufficient substitution for taking the individual courses, then it should show a negative effect on student success. Total GMAT is analyzed as well as the individual component scores: quantitative score (Quant Score), verbal score (Verbal Score) and analytical score (Analytical Score). It is predicted that higher GMAT scores will have a positive effect on student success. Gender is the final variable assessed. It is not expected to have an effect on student success. QUANTITATIVE RESULTS In comparing the variable means for MBA graduates and non graduates, several were found to be significantly different. As shown in Table 2, there is a significant difference in MBA GPA between students who graduate and those who withdrew from the program. As expected, MBA GPA is higher for graduates than non graduates. Since students must maintain a 3.0 GPA with only one C to remain in the program, students whose grades are too low are likely to drop out of the program. Overall GMAT scores were significantly higher for graduates than non graduates. Standardized testing is sometimes considered an inferior way to gauge graduation success. This study shows that it actually is an important indicator of graduate success. When analyzing the individual components of the GMAT, quantitative scores and analytical percentile ranking are significantly different for graduates and non graduates. The % below variables indicate the percentage of test takers who scored below the student. For example, an analytical % below of 40 says that a student scored above 40%, and below 60%, of the people who took that particular exam. Graduates have higher quantitative scores and analytical rankings. This MBA program includes several quantitative courses so students who demonstrate higher skills are more likely to graduate. The BUS 500 course does not significantly affect student success. Students taking the one semester prerequisite course do not have lower MBA GPAs and are not more likely to drop out than students who come into our program with individual prerequisite courses. This is an important result for the School of Business, as it is evidence that students who complete the BUS 500 course fare no differently than students with an undergraduate business degree. - 5 -

Undergraduate GPA and years of experience are not significantly different for graduates and non graduates. These factors were expected to positively affect student success. Gender was also not a factor and was not expected to affect graduation. Table 2: Test for Equality of Means, Graduates & Drop-Outs Mean Z MBA GPA Graduate 3.59-5.38 *** Drop-Out 3.02 UG GPA Graduate 3.02-1.64 Drop-Out 2.92 Years Exp. Graduate 7.93-1.32 Drop-Out 9.31 BUS 500 Graduate 24% -1.19 Drop-Out 31% % Females Graduate 37% -0.17 Drop-Out 38% Quant Score Graduate 27.19-2.29 * Drop-Out 23.92 Verbal Score Graduate 27.33-1.56 Drop-Out 26.43 Analytical Score Graduate 3.95-1.84 Drop-Out 3.58 GMAT Graduate 472.11-2.33 * Drop-Out 433.77 Analytical% Below Graduate 43.02-2.35 * Drop-Out 33.49 Total % Below Graduate 35.28-1.68 Drop-Out 30.32 Quant % Below Graduate 28.76-1.97 * Drop-Out 24.38 Verbal % Below Graduate 47.27-1.67 Drop-Out 40.92 * p <.05 ** p <.01 *** p <.001 Due to the differences in means, regressions were run on MBA graduates and non graduates. The results are shown in Table 3. The dependent variable was MBA GPA. For students who graduate, years of experience, GMAT quantitative score and GMAT verbal score significantly affected MBA GPA. The relationship between all the variables and MBA GPA is positive, meaning more experience and higher test scores resulted in higher graduate GPAs. For students who withdrew from the program, none of the variables was significant in determining MBA GPA. Obviously this is an area for further research. - 6 -

Table 3: Regression Analysis, Graduates and Non Graduates Dependent Variable: MBA GPA Students who Graduated Students who Dropped Out Coefficient Std. Error Coefficient Std Error (Constant) 2.523 0.162 *** 2.786 1.389 * UG GPA 0.700 0.043-0.163 0.501 Years Exp. 0.014 0.003 *** -0.006 0.042 BUS 500 0.017 0.047-0.338 0.484 Gender 0.065 0.043 0.041 0.533 Quant Score 0.009 0.003 ** 0.026 0.035 Verbal Score 0.011 0.003 ** 0.012 0.020 Analytical Score 0.038 0.026 0.004 0.204 Adjusted R square 0.239 0.160 * p <.05 ** p <.01 *** p <.001 There is some discussion in the literature as to whether female students have different standardized test scores and classroom performance than do male students. Table 4 shows there are several variables for which the male and female students have significantly different means. MBA GPA is not one of the variables. Women applicants have significantly fewer years of business experience and significantly lower overall GMAT and quantitative GMAT scores. Both MBA graduates and non graduates are included in this table. Table 4: Test for Equality of Means, Males and Females Mean Z MBA GPA Females 3.47-0.20 Males 3.45 UG GPA Females 3.03-1.28 Males 2.96 Years Exp. Females 7.31-1.16 Males 8.97 BUS 500 Females 31% -1.22 Males 24% Quant Score Females 23.87-3.74 *** Males 27.88 Verbal Score Females 26.78-0.94 Males 27.31 Analytical Score Females 4.00-1.35 Males 3.81-7 -

GMAT Females 443.37-2.71 ** Males 474.55 Analytical% below Females 44.37-0.95 Males 39.29 Total % below Females 29.59-2.45 * Males 36.62 Quant % Below Females 21.49-3.62 *** Males 31.19 Verbal % Below Females 43.85-0.98 Males 46.84 * p <.05 ** p <.01 *** p <.001 We also ran separate regressions for male and female students. Both graduates and non graduates are included. The regression results for males and females in Table 5 do show some differences. Quantitative score positively affects MBA GPA for both males and females. Business experience and analytical score also positively affect MBA GPA for females. Verbal score positively affects MBA GPA for males. This information could be used at the time of the admissions decision by placing more emphasis on verbal score for marginal male applicants and more emphasis on work experience and analytical score for marginal female applicants. Table 5: Regression Analysis, Females and Males Dependent Variable: MBA GPA Female Students Std. Male Students Std Error Coefficient Error Coefficient (Constant) 2.028 0.311 * 2.623 0.281 * UG GPA 0.119 0.087-0.012 0.076 Years Exp. 0.022 0.009 * 0.004 0.006 BUS 500-0.020 0.094 0.020 0.086 Quant Score 0.023 0.007 * 0.016 0.005 * Verbal Score 0.000 0.007 0.013 0.005 * Analytical Score 0.113 0.051 * 0.027 0.044 Adjusted R square 0.336 0.199 * p <.05 ** p <.01 *** p <.001-8 -

CONCLUSIONS These results confirm some prior findings in the literature on gender and academic performance. Women do have significantly lower standardized test scores than do males, but only on the quantitative portion of the GMAT exam. There was no significant difference in classroom GPA between the male and female students. The regression results do have differences in variables that are significant predictors of MBA GPA for males and females. This information could be used at the time of the admissions decision by placing more emphasis on verbal score for marginal male applicants and more emphasis on work experience and analytical score for marginal female applicants. The results show no significant difference in MBA GPA between students who have taken the BUS 500 course and those who did not. This is important for the University s business school. The unique prerequisite course does not put students at a disadvantage. The results on work experience are mixed. Mean work experience is not significantly different between graduates and non graduates. However, work experience is a significant variable in the regression analysis of the factors that contribute positively to MBA GPA for graduates. The results of this study show that the GMAT quantitative score is the most consistent predictor of student success. It was the only factor to show up as significant in all of the testing. WORKS CITED Adams, Arthur J. and Hancock, Terence. Work Experience as a Predictor of MBA Performance, College Student Journal, June 2000, Vol. 34, No. 2, 211-216. Ahmadi, Mohammad; Raiszadeh, Farhad; and Helms, Marilyn. An Examination of the Admission Criteria for the MBA Programs: A Case Study, Education, Summer 1997, 540-546. Clayton, Gary and Cate, Tom. Predicting MBA No-Shows and Graduation Success with Discriminate Analysis, International Advances in Economic Research, August 2004, 235-243. Cooksey, Elizabeth C. and Rindfuss, Ronald R. Prior Activities and Progress in MBA Programs, Research in Higher Education, November, 1994, Vol. 36, No. 6, 647-668. Deckro, Richard F. and Woundenberg, Henry W. M.B.A. Admission Criteria and Academic Success, Decision Sciences, October 1977, Vol. 8, No. 4, 765-769. Dobson, Paul, Krapljan-Barr, Pavica and Vielba, Carol. An Evaluation of the Validity and Fairness of the Graduate Management Admissions Test (GMAT) Used for MBA Selection in a UK Business School, International Journal of Selection and Assessment, December 2002, Vol. 7, No. 4, 196-202. Dreher, George F. and Ryan, Katherine C. Prior Work Experience and Academic Achievement Among First-Year MBA Students, Research in Higher Education, 2000, Vol. 41, No. 4, 505-525. - 9 -

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Sireci, Stephen G., Evaluating the Predictive Validity of Graduate Management Admission Test Scores, Educational and Psychological Measurement, 2006, Vol. 66, No. 2, 305-317. Sobol, Marian G. GPA, GMAT and Scale: A Method for Quantification of Admissions Criteria, Research in Higher Education, 1984, Vol. 20, No.1, 77-88. Sulaiman, Ainin and Mohezar, Suhana. Student Success Factors: Identifying Key Predictors, The Journal of Education for Business, July-August 2006, Vol. 81, No. 6, 328-333. Talento-Miller, Eileen and Rudner, Lawrence M. The Validity of Graduate Management Admission Test Scores: A Summary of Studies Conducted from 1997 to 2004, Educational and Psychological Measurement, February 2008, Vol. 68, No. 1, 129-138. Wright, Robert and Palmer, John. Examining Performance Predictors for Differentially Successful MBA Students, College Student Journal, June 1997, 276-282. Wright, Robert and Palmer, John. GMAT Scores and Undergraduate GPAs as Predictors of Performance in Graduate Business Programs, Journal of Education for Business, July/August 1994, 344-349. Zwick, Rebecca. The Validity of the GMAT for the Prediction of Grades in Doctoral Study in Business and Management: An Empirical Bayes Approach, Journal of Educational and Behavioral Statistics, 1993, Vol. 18, No. 1, 91-107. - 11 -