Manajemen | Fakultas Ekonomi Universitas Maritim Raja Ali Haji joeb.80.4.236-239
Journal of Education for Business
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
The Validity of the Graduate Management
Admissions Test for Non-U.S. Students
Daniel J. Koys
To cite this article: Daniel J. Koys (2005) The Validity of the Graduate Management Admissions
Test for Non-U.S. Students, Journal of Education for Business, 80:4, 236-239, DOI: 10.3200/
JOEB.80.4.236-239
To link to this article: http://dx.doi.org/10.3200/JOEB.80.4.236-239
Published online: 07 Aug 2010.
Submit your article to this journal
Article views: 35
View related articles
Citing articles: 11 View citing articles
Full Terms & Conditions of access and use can be found at
http://www.tandfonline.com/action/journalInformation?journalCode=vjeb20
Download by: [Universitas Maritim Raja Ali Haji]
Date: 12 January 2016, At: 22:38
INTERNATIONAL PERSPECTIVE
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:38 12 January 2016
The Validity of the Graduate
Management Admissions Test
for Non-U.S. Students
DANIEL J. KOYS
DePaul University
Chicago, Illinois
T
here is a great deal of evidence that
the Graduate Management Admissions Test (GMAT) is a valid predictor
of academic performance for U.S. students in U.S. MBA programs. However,
there is very little evidence that the
GMAT predicts performance for nonU.S. students. I conducted this research
to determine whether the GMAT would
predict academic performance for a
sample of MBA students in Bahrain, the
Czech Republic, and Hong Kong.
I used the predictive validation
approach. In almost all of the previous
validation studies of the GMAT, a concurrent validation approach has been
used. Although both approaches are
acceptable, the predictive approach provides a more accurate estimate of the
validity of a test because the predictive
approach does not suffer from a restriction of range on the predictor score.
In the concurrent approach to validation, researchers examine the current
students of a program. This approach
involves the following four steps:
1. Applicants take the GMAT.
2. Admissions decisions are made
through use of the GMAT and other
predictors, usually undergraduate grade
point average (GPA) and sometimes
years of full-time work experience.
3. Students take classes and receive
grades.
236
Journal of Education for Business
ABSTRACT. In this study, the author
examined the validity of the Graduate
Management Admissions Test (GMAT)
for non-U.S. students (N = 75)
through a predictive validation procedure in which applicants were given
the predictor test but the test results
were not used to admit students. The
author’s business school admitted students to three overseas MBA programs. The author then gathered academic performance data (MBA
grades) and correlated the predictor
(GMAT) with the criterion (MBA
GPA). The findings showed that the
correlation between the two was .64
(p < .001), meaning that 41% of the
variance in MBA academic performance was explained by the GMAT.
This number is higher than the corresponding one for U.S. students. The
findings indicate that the GMAT was
a valid predictor of academic performance in an MBA program for these
non-U.S. students.
4. Researchers calculate the correlation between the GMAT score and the
overall GPA in the MBA program. The
range of predictor scores (GMAT
scores) is restricted because hardly any
applicants with very low GMAT scores
are admitted. The relationship between
the predictor and the criterion may
therefore be weaker than is actually the
case because data from the less qualified
applicants are not used in the analysis.
The predictive validation approach
involves the same set of steps, with the
exception of a different Step 2. In Step 2
of this approach, applicants are admitted regardless of their scores on the
GMAT. Note that some people with low
GMAT scores will be admitted to the
program. The prediction is that the less
qualified students will do poorly in the
MBA program and that the students
who scored high on the GMAT will do
well in the program (as measured by
GPA in the MBA program).
Many articles have been published on
the validity of the GMAT for U.S. students. In some of these studies, GMAT
score was used as a single predictor of
academic performance. In some of
them, GMAT score and undergraduate
GPA (UGPA) were considered as joint
predictors of academic performance. In
additional studies, GMAT scores and
other variables were combined as multiple predictors of academic performance.
GMAT as an Individual Predictor of
Academic Performance
In several studies, researchers have
found a statistically significant correlation between GMAT scores and the
MBA GPA. If we square the correlation
coefficient, we can see the degree to
which one can use changes in one variable to explain changes in another variable. Wright and Palmer (1994) found
that GMAT scores explained 18% of the
variance in MBA GPA. Gayle and Jones
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:38 12 January 2016
(1973) found similar results; the GMAT
scores explained 17% of the variance in
MBA GPA. My own unpublished analysis of data on our domestic MBA students showed that GMAT scores
explained 14% of the variance in MBA
GPA when I used a concurrent validation approach (Koys, 2004).
In two other studies, researchers
found statistically significant correlations, although one could argue that
those correlations were not practically
significant. Nilsson (1995) reported that
the GMAT scores explained 5% of the
variance in MBA GPA, and Hancock
(1999) found that the GMAT scores
explained 5% of the MBA GPA for
women and 8% for men. I found only
one published study that failed to show
a significant relationship between
GMAT scores and MBA GPA (Benson,
1983).
GMAT and Undergraduate GPA as
Predictors of Academic Performance
Business school admissions officers
commonly use both the GMAT and
undergraduate GPA to make admissions
decisions. Some researchers have used
multiple regression analysis to test the
combined relationship of these two predictors with the criterion of MBA GPA.
In one study, the GMAT and undergraduate GPA together explained 17% of the
variance in MBA GPA (Paolillo, 1982);
in two others, GMAT and undergraduate
GPA together explained 15% of the variance in academic performance (Deckro
& Woundenberg, 1977; Sobol, 1984).
The results of another study indicated
that the quantitative and verbal subscores of the GMAT along with the
undergraduate GPA explained 20% of
the variance in MBA GPA (Hoefer &
Gould, 2000). My own unpublished
multiple regression analysis of data on
our U.S. students showed that GMAT
score and undergraduate GPA together
explained 22% of the variance in MBA
GPA when I used a concurrent validation approach (Koys, 2004).
In the past, some business schools
used a formula that combined the
GMAT score with the undergraduate
GPA. In that formula, the undergraduate
GPA was multiplied by 200 and then
added to the GMAT score (i.e., GMAT +
[200 × UGPA]). If the composite score
was above a certain number, then an
applicant would be admitted. For example, a school might set the cut-off at 950.
One applicant could be admitted by
scoring a 450 on the GMAT and by having an undergraduate GPA of 2.5.
Another applicant could be admitted
with a GMAT score of 350 and an
undergraduate GPA of 3.0. In the only
published study that I found on this
composite score, the composite score
was not found to be significantly related
to academic performance (Carver &
King, 1994). However, my own unpublished study of our U.S. students showed
that this composite score explained 20%
of the variance in MBA GPA when I
used the concurrent approach to validation. This is similar to my regression
analysis in which I used the GMAT
score and the undergraduate GPA as
predictors of MBA GPA (Koys, 2004).
GMAT and Other Variables as
Predictors of Academic Performance
Researchers have explored other variables that might increase validity beyond
that obtained by the GMAT score and
the undergraduate GPA. The results of
one study showed that work experience,
GMAT score, and undergraduate GPA
explained 21% of the variance in MBA
GPA (Carver & King, 1994). A scale
measuring various background activities
(e.g., campus activities, work experience, technical background, references,
goals) combined with GMAT score and
undergraduate GPA to explain 19% of
the variance in MBA GPA (Sobol,
1984).
In all of the studies that I reviewed for
the current article, U.S. students were
used as subjects. In the current study, I
used non-U.S. students in an MBA program taught in English. Therefore, English skills may be an important predictor
of MBA GPA. A commonly used measure of English skills is the Test of English as a Foreign Language (TOEFL). An
unpublished study from the Educational
Testing Service (ETS) (Wilson, 1985)
showed that 5% of the variance in 1styear MBA GPA was explained by the
TOEFL score. That study found that the
verbal subscore of the GMAT explained
2.5% of the variance in 1st-year MBA
GPA. The same study reported that
TOEFL scores and the verbal subscore of
the GMAT were strongly correlated with
each other in data obtained from students
of English as a Second Language (r =
.68). Wilson (1985) also reported that the
correlation between TOEFL scores and
the GMAT total scores was only slightly
lower (r = .64).
ETS also did some multiple regression analyses (Wilson, 1985). When
ETS used the GMAT’s verbal subscore
and the GMAT’s quantitative subscore
to predict 1st-year MBA GPA, it
obtained a multiple correlation of .30
(R2 = .09). When ETS added the TOEFL
score to the multiple regression equation, it obtained a multiple correlation
of .32 (R2 = .10). Note that using the
GMAT plus the TOEFL was slightly
better at predicting MBA GPA than was
the GMAT alone. Because the TOEFL
is correlated with the GMAT’s verbal
subscore, ETS also ran a regression
analysis in which the TOEFL score and
the GMAT’s quantitative subscore were
the predictors of 1st-year MBA GPA.
The resulting multiple correlation was
.29 (R2 = .08) (Wilson).
Summary of the Literature
In the studies that I have cited,
GMAT scores either alone or together
with other predictors explained between
0% and 22% of the variance in MBA
academic performance. If we look at the
16 correlations between GMAT (either
alone or along with other predictors)
and academic performance in the studies cited, the predictor variables explain
an average of 13% of the variance in
academic performance. When the
GMAT was studied in conjunction with
other predictors, it was always the
strongest predictor.
There were some limitations to the
cited studies. The concurrent approach
to validation was used in all of them.
That is, current students who had been
admitted to MBA programs partially on
the basis of their GMAT scores served
as the study population. This produced a
restriction of range on the predictor
variable. It is possible that the GMAT
may explain a greater percentage of the
variance in academic performance if a
predictive validation approach is used.
March/April 2005
237
In the current study, I used the predictive validation approach.
Another limitation of the cited studies
is that almost all of them relied on U.S.
students as subjects. The one exception
was Hancock (1999), who involved nonU.S. students but analyzed their data
together with U.S. students’ data. In my
study, I used non-U.S. students.
graduate GPAs ranged from 1.59 to 4.00
on a 4-point scale; again there was no
restriction of range. I computed an additional variable by using the formula
GMAT + (200 × UGPA); this composite
variable ranged from 630 to 1420. The
criterion was overall MBA GPA.
Because it ranged from 1.54 to 4.00,
there was very little restriction of range
on this criterion variable.
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:38 12 January 2016
Method
In this study, I examined students in
three overseas MBA programs run by a
U.S. business school; one program was
in Bahrain, one program was in the
Czech Republic, and one program was
in Hong Kong. All were part-time programs with students taking classes either
in the evening or on the weekend. All
classes were taught in a compressed format (courses usually taught over a 10week quarter in the United States are
delivered in about 3 weeks in the overseas locations). Twelve of the 16 courses
in each program were the same. The
other 4 courses represented a concentration; the concentrations were slightly
different across the three programs. The
students in all programs were working
full time while going to school part time.
The faculty members were from the U.S.
business school.
I used the predictive validation procedure to avoid the problem of restricting
the range of the predictor variables.
That is, applicants took the GMAT and
submitted undergraduate transcripts.
Applicants were admitted as long as
they had the equivalent of a 4-year U.S.
bachelor’s degree and had good English
skills (as measured by an oral interview). The students then took courses
and received grades. I then correlated
the GMAT scores with the overall GPA
in the MBA program. Although there
was a total of 112 students, I had complete data on only 75 of them. I conducted all of my analyses by using data
from those 75 students.
The predictor variables in this study
were the GMAT score and the undergraduate GPA. GMAT scores can run
from a low of 200 to a high of 800. The
GMAT scores for my sample ranged
from 200 to 680. Thus, one can safely
say that there was very little restriction
of range on this variable. The under238
Journal of Education for Business
indicate that the GMAT itself is the best
predictor of academic performance.
In Table 2, I show the results of a multiple regression analysis. The GMAT and
the undergraduate GPA produced a multiple correlation of .651 (R2 = .424).
Notice that this equation explains slightly
more variance (42.4%) than does GMAT
score alone (41.2%). However, the
GMAT score has the only statistically
significant beta weight.
Results
In Table 1, I show the descriptive statistics and the correlation matrix. The
overall MBA GPA was strongly correlated with the GMAT score; the GMAT
score explained 41.2% of the variance in
MBA academic performance. The MBA
GPA was also significantly correlated
with undergraduate GPA, but not as
strongly; the undergraduate GPA
explained 8.6% of the variance in MBA
academic performance. The MBA GPA
was also significantly correlated with the
composite variable (that is, GMAT plus
200 times the undergraduate GPA); it
explained 31.5% of the variance in MBA
academic performance. These results
Discussion
The results of my study show that the
GMAT is a valid predictor of MBA academic performance for our non-U.S. students in Bahrain, the Czech Republic,
and Hong Kong. The simple correlation
between the GMAT score and the MBA
GPA is .642 (p < .001), indicating that
the GMAT explains 41.2% of the variance in MBA academic performance. (I
obtained similar results when I analyzed
each country’s data separately. I do not
report those results in this article
because breaking the data down by location would give small sample sizes.) The
correlations are stronger than those
TABLE 1. Descriptive Statistics and Correlation Matrix
Variable
1. GMAT score
2. Undergraduate GPA
3. GMAT + (200 x UGPA)
4. MBA GPA
M
SD
1
2
3
436.80
2.87
1,011.04
3.50
108.82
.65
192.35
.47
.298**
.766***
.642***
.842***
.294**
.561***
Note. GMAT = Graduate Management Aptitude Test.
**p < .01. ***p < .001.
TABLE 2. Results of Multiple Regression Analysis
Variable
Coefficient
GMAT score beta weight
Undergraduate GPA beta weight
R2
Adjusted R 2
F
.609***
.113
.424
.408
26.521***
Note. GMAT = Graduate Management Aptitude Test.
**p < .01. ***p < .001.
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:38 12 January 2016
reported in the literature for U.S. MBA
students. This means that the GMAT can
be used in admissions decisions in these
three countries.
To add strength to the results, I used a
predictive approach to validation,
whereas almost all previous studies
relied on a concurrent approach to validation. This alone may explain why my
results were stronger than those reported
in the literature. The predictive approach
does not suffer from a restriction of
range on the GMAT, as does the concurrent approach.
I found evidence that the undergraduate GPA is also a valid predictor of
MBA academic performance (r = .294,
p < .01). I conducted two different
analyses to see whether the GMAT
score and the undergraduate GPA
together would be more valid than the
GMAT alone. First, regression analysis
showed that the two variables explained
42.4% of the variance in MBA GPA.
Second, a composite variable based on
the formula GMAT + (200 × UGPA)
explained 31.4% of the variance in
MBA academic performance. Both of
these results were statistically significant. This finding means that one can
use the GMAT and the undergraduate
GPA to admit non-U.S. students into
MBA programs in Bahrain, the Czech
Republic, and Hong Kong.
Because undergraduate GPA has a
smaller correlation with MBA GPA (r =
.294) than does the GMAT score (r =
.642), the composite variable might be
more useful if it gave less weight to the
undergraduate GPA. If it is computed as
GMAT score plus 50 times the undergraduate GPA, then the correlation
between MBA GPA and the revised
combination variable is .649 (r2 = .421),
which is basically the same as the .651
(r2 = .424) obtained via the regression of
MBA GPA onto GMAT score and
undergraduate GPA. However, the formula of GMAT + (200 × UGPA) has
been used by many schools. I do not
advocate changing the formula unless
future research in other countries confirms the results that I obtained for
Bahrain, the Czech Republic, and Hong
Kong.
One limitation of this research is that
I did not collect scores on the Test of
English as a Foreign Language
(TOEFL). Given that previous research
shows that TOEFL scores are highly
correlated with GMAT scores (r = .64),
I do not think that this is a serious limitation. However, I suggest that future
research on the validity of the GMAT
for non-U.S. students include the
TOEFL score.
My conclusion is that the GMAT is an
extremely valid predictor of performance
in our MBA programs in Bahrain, the
Czech Republic, and Hong Kong.
REFERENCES
Benson, G. (1983). GMAT—Fact or fiction: A look
at the validity of the exam (Tech. Rep. ED2482
74). Casper, WY: University of Wyoming.
Carver, M. R., & King, T. E. (1994). An empirical
investigation of the MBA admission criteria for
nontraditional programs. Journal of Education
for Business, 70, 95–98.
Deckro, R., & Woundenberg, H. (1977). MBA
admission criteria and academic success. Decision Sciences, 8, 765–769.
Gayle, J., & Jones, T. (1973). Admissions standards for graduate study in management. Decision Sciences, 4, 421–425.
Hancock, T. (1999). The gender difference: Validity of standardized admission tests in predicting
MBA performance. Journal of Education for
Business, 75, 91–93.
Hoefer, P., & Gould, J. (2000). Assessment of
admission criteria for predicting students’ academic performance in graduate programs. Journal of Education for Business, 76, 225–229.
Koys, D. (2004). GMAT scores and undergraduate GPA as predictors of part-time MBA academic performance (working paper). Chicago, IL:
College of Commerce, DePaul University.
Nilsson, J. E. (1995). The GRE and the GMAT: A
comparison of their correlations to GGPA. Educational & Psychological Measurement, 55,
637–640.
Paolillo, J. (1982). The predictive validity of
selected admissions variables relative to grade
point average earned in a master of business
administration program. Educational and Psychological Measurement, 42, 1,153–1,162.
Sobol, M. G. (1984). GPA, GMAT, and SCALE:
A method for quantification of admissions criteria. Research in Higher Education, 20, 77–88.
Wilson, K. M. (1985). Factors affecting GMAT
predictive validity for foreign MBA students: An
exploratory study (Tech. Rep.). Princeton, NJ:
Educational Testing Service.
Wright, R. E., & Palmer, J. C. (1994). GMAT
scores and undergraduate GPAs as predictors of
performance in graduate business programs.
Journal of Education for Business, 69, 344–348.
March/April 2005
239
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
The Validity of the Graduate Management
Admissions Test for Non-U.S. Students
Daniel J. Koys
To cite this article: Daniel J. Koys (2005) The Validity of the Graduate Management Admissions
Test for Non-U.S. Students, Journal of Education for Business, 80:4, 236-239, DOI: 10.3200/
JOEB.80.4.236-239
To link to this article: http://dx.doi.org/10.3200/JOEB.80.4.236-239
Published online: 07 Aug 2010.
Submit your article to this journal
Article views: 35
View related articles
Citing articles: 11 View citing articles
Full Terms & Conditions of access and use can be found at
http://www.tandfonline.com/action/journalInformation?journalCode=vjeb20
Download by: [Universitas Maritim Raja Ali Haji]
Date: 12 January 2016, At: 22:38
INTERNATIONAL PERSPECTIVE
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:38 12 January 2016
The Validity of the Graduate
Management Admissions Test
for Non-U.S. Students
DANIEL J. KOYS
DePaul University
Chicago, Illinois
T
here is a great deal of evidence that
the Graduate Management Admissions Test (GMAT) is a valid predictor
of academic performance for U.S. students in U.S. MBA programs. However,
there is very little evidence that the
GMAT predicts performance for nonU.S. students. I conducted this research
to determine whether the GMAT would
predict academic performance for a
sample of MBA students in Bahrain, the
Czech Republic, and Hong Kong.
I used the predictive validation
approach. In almost all of the previous
validation studies of the GMAT, a concurrent validation approach has been
used. Although both approaches are
acceptable, the predictive approach provides a more accurate estimate of the
validity of a test because the predictive
approach does not suffer from a restriction of range on the predictor score.
In the concurrent approach to validation, researchers examine the current
students of a program. This approach
involves the following four steps:
1. Applicants take the GMAT.
2. Admissions decisions are made
through use of the GMAT and other
predictors, usually undergraduate grade
point average (GPA) and sometimes
years of full-time work experience.
3. Students take classes and receive
grades.
236
Journal of Education for Business
ABSTRACT. In this study, the author
examined the validity of the Graduate
Management Admissions Test (GMAT)
for non-U.S. students (N = 75)
through a predictive validation procedure in which applicants were given
the predictor test but the test results
were not used to admit students. The
author’s business school admitted students to three overseas MBA programs. The author then gathered academic performance data (MBA
grades) and correlated the predictor
(GMAT) with the criterion (MBA
GPA). The findings showed that the
correlation between the two was .64
(p < .001), meaning that 41% of the
variance in MBA academic performance was explained by the GMAT.
This number is higher than the corresponding one for U.S. students. The
findings indicate that the GMAT was
a valid predictor of academic performance in an MBA program for these
non-U.S. students.
4. Researchers calculate the correlation between the GMAT score and the
overall GPA in the MBA program. The
range of predictor scores (GMAT
scores) is restricted because hardly any
applicants with very low GMAT scores
are admitted. The relationship between
the predictor and the criterion may
therefore be weaker than is actually the
case because data from the less qualified
applicants are not used in the analysis.
The predictive validation approach
involves the same set of steps, with the
exception of a different Step 2. In Step 2
of this approach, applicants are admitted regardless of their scores on the
GMAT. Note that some people with low
GMAT scores will be admitted to the
program. The prediction is that the less
qualified students will do poorly in the
MBA program and that the students
who scored high on the GMAT will do
well in the program (as measured by
GPA in the MBA program).
Many articles have been published on
the validity of the GMAT for U.S. students. In some of these studies, GMAT
score was used as a single predictor of
academic performance. In some of
them, GMAT score and undergraduate
GPA (UGPA) were considered as joint
predictors of academic performance. In
additional studies, GMAT scores and
other variables were combined as multiple predictors of academic performance.
GMAT as an Individual Predictor of
Academic Performance
In several studies, researchers have
found a statistically significant correlation between GMAT scores and the
MBA GPA. If we square the correlation
coefficient, we can see the degree to
which one can use changes in one variable to explain changes in another variable. Wright and Palmer (1994) found
that GMAT scores explained 18% of the
variance in MBA GPA. Gayle and Jones
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:38 12 January 2016
(1973) found similar results; the GMAT
scores explained 17% of the variance in
MBA GPA. My own unpublished analysis of data on our domestic MBA students showed that GMAT scores
explained 14% of the variance in MBA
GPA when I used a concurrent validation approach (Koys, 2004).
In two other studies, researchers
found statistically significant correlations, although one could argue that
those correlations were not practically
significant. Nilsson (1995) reported that
the GMAT scores explained 5% of the
variance in MBA GPA, and Hancock
(1999) found that the GMAT scores
explained 5% of the MBA GPA for
women and 8% for men. I found only
one published study that failed to show
a significant relationship between
GMAT scores and MBA GPA (Benson,
1983).
GMAT and Undergraduate GPA as
Predictors of Academic Performance
Business school admissions officers
commonly use both the GMAT and
undergraduate GPA to make admissions
decisions. Some researchers have used
multiple regression analysis to test the
combined relationship of these two predictors with the criterion of MBA GPA.
In one study, the GMAT and undergraduate GPA together explained 17% of the
variance in MBA GPA (Paolillo, 1982);
in two others, GMAT and undergraduate
GPA together explained 15% of the variance in academic performance (Deckro
& Woundenberg, 1977; Sobol, 1984).
The results of another study indicated
that the quantitative and verbal subscores of the GMAT along with the
undergraduate GPA explained 20% of
the variance in MBA GPA (Hoefer &
Gould, 2000). My own unpublished
multiple regression analysis of data on
our U.S. students showed that GMAT
score and undergraduate GPA together
explained 22% of the variance in MBA
GPA when I used a concurrent validation approach (Koys, 2004).
In the past, some business schools
used a formula that combined the
GMAT score with the undergraduate
GPA. In that formula, the undergraduate
GPA was multiplied by 200 and then
added to the GMAT score (i.e., GMAT +
[200 × UGPA]). If the composite score
was above a certain number, then an
applicant would be admitted. For example, a school might set the cut-off at 950.
One applicant could be admitted by
scoring a 450 on the GMAT and by having an undergraduate GPA of 2.5.
Another applicant could be admitted
with a GMAT score of 350 and an
undergraduate GPA of 3.0. In the only
published study that I found on this
composite score, the composite score
was not found to be significantly related
to academic performance (Carver &
King, 1994). However, my own unpublished study of our U.S. students showed
that this composite score explained 20%
of the variance in MBA GPA when I
used the concurrent approach to validation. This is similar to my regression
analysis in which I used the GMAT
score and the undergraduate GPA as
predictors of MBA GPA (Koys, 2004).
GMAT and Other Variables as
Predictors of Academic Performance
Researchers have explored other variables that might increase validity beyond
that obtained by the GMAT score and
the undergraduate GPA. The results of
one study showed that work experience,
GMAT score, and undergraduate GPA
explained 21% of the variance in MBA
GPA (Carver & King, 1994). A scale
measuring various background activities
(e.g., campus activities, work experience, technical background, references,
goals) combined with GMAT score and
undergraduate GPA to explain 19% of
the variance in MBA GPA (Sobol,
1984).
In all of the studies that I reviewed for
the current article, U.S. students were
used as subjects. In the current study, I
used non-U.S. students in an MBA program taught in English. Therefore, English skills may be an important predictor
of MBA GPA. A commonly used measure of English skills is the Test of English as a Foreign Language (TOEFL). An
unpublished study from the Educational
Testing Service (ETS) (Wilson, 1985)
showed that 5% of the variance in 1styear MBA GPA was explained by the
TOEFL score. That study found that the
verbal subscore of the GMAT explained
2.5% of the variance in 1st-year MBA
GPA. The same study reported that
TOEFL scores and the verbal subscore of
the GMAT were strongly correlated with
each other in data obtained from students
of English as a Second Language (r =
.68). Wilson (1985) also reported that the
correlation between TOEFL scores and
the GMAT total scores was only slightly
lower (r = .64).
ETS also did some multiple regression analyses (Wilson, 1985). When
ETS used the GMAT’s verbal subscore
and the GMAT’s quantitative subscore
to predict 1st-year MBA GPA, it
obtained a multiple correlation of .30
(R2 = .09). When ETS added the TOEFL
score to the multiple regression equation, it obtained a multiple correlation
of .32 (R2 = .10). Note that using the
GMAT plus the TOEFL was slightly
better at predicting MBA GPA than was
the GMAT alone. Because the TOEFL
is correlated with the GMAT’s verbal
subscore, ETS also ran a regression
analysis in which the TOEFL score and
the GMAT’s quantitative subscore were
the predictors of 1st-year MBA GPA.
The resulting multiple correlation was
.29 (R2 = .08) (Wilson).
Summary of the Literature
In the studies that I have cited,
GMAT scores either alone or together
with other predictors explained between
0% and 22% of the variance in MBA
academic performance. If we look at the
16 correlations between GMAT (either
alone or along with other predictors)
and academic performance in the studies cited, the predictor variables explain
an average of 13% of the variance in
academic performance. When the
GMAT was studied in conjunction with
other predictors, it was always the
strongest predictor.
There were some limitations to the
cited studies. The concurrent approach
to validation was used in all of them.
That is, current students who had been
admitted to MBA programs partially on
the basis of their GMAT scores served
as the study population. This produced a
restriction of range on the predictor
variable. It is possible that the GMAT
may explain a greater percentage of the
variance in academic performance if a
predictive validation approach is used.
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237
In the current study, I used the predictive validation approach.
Another limitation of the cited studies
is that almost all of them relied on U.S.
students as subjects. The one exception
was Hancock (1999), who involved nonU.S. students but analyzed their data
together with U.S. students’ data. In my
study, I used non-U.S. students.
graduate GPAs ranged from 1.59 to 4.00
on a 4-point scale; again there was no
restriction of range. I computed an additional variable by using the formula
GMAT + (200 × UGPA); this composite
variable ranged from 630 to 1420. The
criterion was overall MBA GPA.
Because it ranged from 1.54 to 4.00,
there was very little restriction of range
on this criterion variable.
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:38 12 January 2016
Method
In this study, I examined students in
three overseas MBA programs run by a
U.S. business school; one program was
in Bahrain, one program was in the
Czech Republic, and one program was
in Hong Kong. All were part-time programs with students taking classes either
in the evening or on the weekend. All
classes were taught in a compressed format (courses usually taught over a 10week quarter in the United States are
delivered in about 3 weeks in the overseas locations). Twelve of the 16 courses
in each program were the same. The
other 4 courses represented a concentration; the concentrations were slightly
different across the three programs. The
students in all programs were working
full time while going to school part time.
The faculty members were from the U.S.
business school.
I used the predictive validation procedure to avoid the problem of restricting
the range of the predictor variables.
That is, applicants took the GMAT and
submitted undergraduate transcripts.
Applicants were admitted as long as
they had the equivalent of a 4-year U.S.
bachelor’s degree and had good English
skills (as measured by an oral interview). The students then took courses
and received grades. I then correlated
the GMAT scores with the overall GPA
in the MBA program. Although there
was a total of 112 students, I had complete data on only 75 of them. I conducted all of my analyses by using data
from those 75 students.
The predictor variables in this study
were the GMAT score and the undergraduate GPA. GMAT scores can run
from a low of 200 to a high of 800. The
GMAT scores for my sample ranged
from 200 to 680. Thus, one can safely
say that there was very little restriction
of range on this variable. The under238
Journal of Education for Business
indicate that the GMAT itself is the best
predictor of academic performance.
In Table 2, I show the results of a multiple regression analysis. The GMAT and
the undergraduate GPA produced a multiple correlation of .651 (R2 = .424).
Notice that this equation explains slightly
more variance (42.4%) than does GMAT
score alone (41.2%). However, the
GMAT score has the only statistically
significant beta weight.
Results
In Table 1, I show the descriptive statistics and the correlation matrix. The
overall MBA GPA was strongly correlated with the GMAT score; the GMAT
score explained 41.2% of the variance in
MBA academic performance. The MBA
GPA was also significantly correlated
with undergraduate GPA, but not as
strongly; the undergraduate GPA
explained 8.6% of the variance in MBA
academic performance. The MBA GPA
was also significantly correlated with the
composite variable (that is, GMAT plus
200 times the undergraduate GPA); it
explained 31.5% of the variance in MBA
academic performance. These results
Discussion
The results of my study show that the
GMAT is a valid predictor of MBA academic performance for our non-U.S. students in Bahrain, the Czech Republic,
and Hong Kong. The simple correlation
between the GMAT score and the MBA
GPA is .642 (p < .001), indicating that
the GMAT explains 41.2% of the variance in MBA academic performance. (I
obtained similar results when I analyzed
each country’s data separately. I do not
report those results in this article
because breaking the data down by location would give small sample sizes.) The
correlations are stronger than those
TABLE 1. Descriptive Statistics and Correlation Matrix
Variable
1. GMAT score
2. Undergraduate GPA
3. GMAT + (200 x UGPA)
4. MBA GPA
M
SD
1
2
3
436.80
2.87
1,011.04
3.50
108.82
.65
192.35
.47
.298**
.766***
.642***
.842***
.294**
.561***
Note. GMAT = Graduate Management Aptitude Test.
**p < .01. ***p < .001.
TABLE 2. Results of Multiple Regression Analysis
Variable
Coefficient
GMAT score beta weight
Undergraduate GPA beta weight
R2
Adjusted R 2
F
.609***
.113
.424
.408
26.521***
Note. GMAT = Graduate Management Aptitude Test.
**p < .01. ***p < .001.
Downloaded by [Universitas Maritim Raja Ali Haji] at 22:38 12 January 2016
reported in the literature for U.S. MBA
students. This means that the GMAT can
be used in admissions decisions in these
three countries.
To add strength to the results, I used a
predictive approach to validation,
whereas almost all previous studies
relied on a concurrent approach to validation. This alone may explain why my
results were stronger than those reported
in the literature. The predictive approach
does not suffer from a restriction of
range on the GMAT, as does the concurrent approach.
I found evidence that the undergraduate GPA is also a valid predictor of
MBA academic performance (r = .294,
p < .01). I conducted two different
analyses to see whether the GMAT
score and the undergraduate GPA
together would be more valid than the
GMAT alone. First, regression analysis
showed that the two variables explained
42.4% of the variance in MBA GPA.
Second, a composite variable based on
the formula GMAT + (200 × UGPA)
explained 31.4% of the variance in
MBA academic performance. Both of
these results were statistically significant. This finding means that one can
use the GMAT and the undergraduate
GPA to admit non-U.S. students into
MBA programs in Bahrain, the Czech
Republic, and Hong Kong.
Because undergraduate GPA has a
smaller correlation with MBA GPA (r =
.294) than does the GMAT score (r =
.642), the composite variable might be
more useful if it gave less weight to the
undergraduate GPA. If it is computed as
GMAT score plus 50 times the undergraduate GPA, then the correlation
between MBA GPA and the revised
combination variable is .649 (r2 = .421),
which is basically the same as the .651
(r2 = .424) obtained via the regression of
MBA GPA onto GMAT score and
undergraduate GPA. However, the formula of GMAT + (200 × UGPA) has
been used by many schools. I do not
advocate changing the formula unless
future research in other countries confirms the results that I obtained for
Bahrain, the Czech Republic, and Hong
Kong.
One limitation of this research is that
I did not collect scores on the Test of
English as a Foreign Language
(TOEFL). Given that previous research
shows that TOEFL scores are highly
correlated with GMAT scores (r = .64),
I do not think that this is a serious limitation. However, I suggest that future
research on the validity of the GMAT
for non-U.S. students include the
TOEFL score.
My conclusion is that the GMAT is an
extremely valid predictor of performance
in our MBA programs in Bahrain, the
Czech Republic, and Hong Kong.
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