Description
The purpose of this study is to identify which of factors are associated with student
performance in advanced accounting and auditing courses.
Accounting Research Journal
Factors associated with student performance in advanced accounting and auditing: An
empirical study in a public university
Mostafa M. Maksy Lin Zheng
Article information:
To cite this document:
Mostafa M. Maksy Lin Zheng, (2008),"Factors associated with student performance in advanced accounting
and auditing", Accounting Research J ournal, Vol. 21 Iss 1 pp. 16 - 32
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Tho Lai Mooi, (2006),"Self-efficacy and Student Performance in an Accounting Course", J ournal of
Financial Reporting and Accounting, Vol. 4 Iss 1 pp. 129-146http://dx.doi.org/10.1108/19852510680001586
Ervina Alfan, Nor Othman, (2005),"Undergraduate students' performance: the case of
University of Malaya", Quality Assurance in Education, Vol. 13 Iss 4 pp. 329-343 http://
dx.doi.org/10.1108/09684880510626593
Beverley J ackling, Paul de Lange, J on Phillips, J ames Sewell, (2012),"Attitudes towards accounting:
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Factors associated with student
performance in advanced
accounting and auditing
An empirical study in a public university
Mostafa M. Maksy
Northeastern Illinois University, Chicago, Illinois, USA, and
Lin Zheng
Mercer College, Atlanta, Georgia, USA
Abstract
Purpose – The purpose of this study is to identify which of factors are associated with student
performance in advanced accounting and auditing courses.
Design/methodology/approach – Students enrolled in a highly diversi?ed, commuter, public
university located in one of the largest cities in the USA provided responses to 12 questions used as
independent variables.
Findings – Of the three variables used as proxies for motivation, the grade the student would like to
make in the course was found to be signi?cantly associated with student performance, but intention to
take the CPA exam or attend graduate school were not. Additionally, the grade in intermediate
accounting II and grade point average (used as proxies for actual ability) were found to be strong
predictors of student performance. Self-perceived reading and listening abilities had moderate to
strong associations with student performance, but self-perceived writing and math abilities did not.
Finally, holding non-accounting-related jobs, working high numbers of hours per week, and taking on
higher course loads during the semester are factors which were, surprisingly, not signi?cantly
correlated with student performance.
Originality/value – No prior study that we are aware of has considered the associations between
motivation, actual ability, self-perceived ability, and distraction factors and student performance in
advanced level undergraduate accounting courses.
Keywords Students, Performance criteria, Accounting, Auditing, Education, Motivation (psychology)
Paper type Research paper
Introduction
As the review of prior research below indicates, many studies have explored various
factors that are associated with student performance in college-level accounting
courses. However, no prior study, that we are aware of, has considered the association
between motivation, prior actual ability, current self-perceived ability, and distraction
factors and student performance in advanced level undergraduate accounting courses.
This study considers the associations between these factors and student performance
in advanced accounting, and auditing courses.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1030-9616.htm
The authors would like to thank session attendants at the Midwest Region and the National
Meetings of the American Accounting Association as well as four anonymous reviewers for their
helpful comments and constructive feedback on earlier drafts of this paper.
ARJ
21,1
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Accounting Research Journal
Vol. 21 No. 1, 2008
pp. 16-32
qEmerald Group Publishing Limited
1030-9616
DOI 10.1108/10309610810891328
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The objective of the study is predicated on the assumption that identi?cation of
some factors that are associated with student performance and some factors that are
not may help us to emphasize those factors that improve student performance and
de-emphasize those factors that do not.
In the following parts of the paper we present a review of prior research, and we
describe the study variables, hypotheses, sample, statistical tests, and research results.
We end the paper with some conclusions, recommendations, study limitations, and
some suggestions for further research.
Review of prior research
Prior studies have explored various factors (e.g. aptitude, general academic
performance, prior exposure to accounting, prior exposure to mathematics, age, and
gender) that are associated with student performance in college-level accounting
courses. Grade point average (GPA) is used frequently as a proxy for aptitude and
prior academic performance. For example, researchers using US data ?nd evidence
supporting GPA as a signi?cant predictor of performance in accounting courses (Eckel
and Johnson, 1983; Hicks and Richardson, 1984; Ingram and Peterson, 1987; Eskew and
Faley, 1988; Doran et al., 1991). The US ?ndings are supported in Australia by Jackling
and Anderson (1998). However, using another measure, pre-university examination
performance, Gist et al. (1996) ?nd no signi?cant association between academic
performance and performance in university accounting courses.
Accounting is a subject area that requires accumulation of prior knowledge and
considerable quantitative skills. Therefore, several studies have investigated the
impact of prior exposure to accounting and mathematical background courses on
performance in college accounting courses. However, the results are inconclusive.
Some studies (Baldwin and Howe, 1982; Bergin, 1983; Schroeder, 1986) ?nd that
performance is not signi?cantly associated with prior exposure to high school
accounting education. However, some later studies (Eskew and Faley, 1988; Bartlett
et al., 1993; Gul and Fong, 1993; Tho, 1994; Rohde and Kavanagh, 1996) ?nd that prior
accounting knowledge, obtained through high school education, is a signi?cant
determinant of performance in college-level accounting courses. Con?icting results are
also observed about the association between student performance in introductory
accounting and their performance in non-introductory accounting courses. Canlar
(1986) ?nds evidence that college-level exposure to accounting is positively related to
student performance in the ?rst MBA-level ?nancial accounting course. However,
Doran et al. (1991) show that performance in the introductory accounting course has a
negative impact on performance in subsequent accounting courses. The in?uence of
mathematical background on performance in accounting courses is also ambiguous.
Eskew and Faley (1988) and Gul and Fong (1993) suggest that students with strong
mathematical backgrounds outperform students with weaker mathematical
backgrounds. However, a later study (Gist et al., 1996) does not report the same results.
Two demographic variables, age and gender, receive less attention than those
factors discussed above. Bartlett et al. (1993) and Koh and Koh (1999) suggest that
younger students have better performance, particularly at the senior university level.
Jenkins (1998) and Lane and Porch (2002) conclude that age is not a signi?cant
determinant for performance in auditing and management accounting courses.
There are studies indicating that male students perform better than female ones.
Student
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However, the results are either insigni?cant (Lipe, 1989) or only hold true for
introductory courses (Doran et al., 1991). One study ?nds that female students score
signi?cantly higher than male students (Mutchler et al., 1987). However, other studies
?nd no signi?cant differences in performance between male and female accounting
students. For example, Tyson (1989) and Buckless et al. (1991) demonstrate that gender
effect disappears when general academic ability is controlled for in the model.
One study shows that motivation and effort, among other factors, signi?cantly
in?uence individual performance in college (Pascarella and Terenzini, 1991). Other
studies have explored the association between effort and performance in the area of
?nance. For example, using self-reported data, Didia and Hasnat (1998) present
contra-intuitive evidence that the more time spent studying per week, the lower the
grade in the introductory ?nance course. However, another study (Nos?nger and Petry,
1999) also uses self-reported data and ?nds no signi?cant relationship between effort
and performance. Johnson et al. (2002) utilize computerized quizzes and analyze the
effect of objectively measured effort on student performance. Their evidence shows
that, after controlling for aptitude, ability, and gender, effort remains signi?cant in
explaining the differences in performance.
Study variables
We use two dependent variables and 12 independent variables in the study. Below we
list these variables starting with the abbreviation used for each variable in the
statistical models and ending with a de?nition or an explanation of the variable. For
each question representing an independent variable we list the possible responses in
parentheses “[ ]”.
Dependent variables
.
Points. The actual average number of points (including mid-term and ?nal
examinations, cases, term papers, class presentations, and other projects) a given
student received in a given course.
.
Grade. The letter grade (e.g. A, B, or C) a given student received in a given
course.
Independent variables
.
Grademk. The grade I would like to make in the course is [a. an A; b. at least a B;
c. a C is ?ne with me].
.
cpa. Do you intend to take the CPA exam? [a. Yes; b. No; c. Maybe].
.
grad. Do you intend to attend graduate school? [a. Yes, at this school; b. Yes, but
at another school; c. No; d. Maybe].
.
grade322. What was your grade for ACTG 322 (Intermediate Accounting II)?
[a. A; b. B; c.C].
.
gpac. What is your cumulative GPA? [__].
.
write. My writing ability is [a. Very good; b. Good; c. Average; d. Poor].
.
math. My math ability is [a. Very good; b. Good; c. Average; d. Poor].
.
read. My reading ability is [a. Very good; b. Good; c. Average; d. Poor].
.
listen. My listening ability is [a. Very good; b. Good; c. Average; d. Poor].
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job. My job outside of school is [a. Accounting; b. Business related (but not
accounting); c. Other].
.
hrs. In an average week, how many hours do you work at a job outside of school?
[___ hours].
.
load. How many courses are you taking this semester? [___ courses].
Categorization of independent variables
We classify the 12 independent variables into four categories of factors that may be
associated with students’ performance in advanced accounting and auditing courses as
following four categories:
(1) Motivation. Independent variables 1 through 3.
(2) Prior actual ability. Independent variables 4 and 5.
(3) Current self-perceived ability. Independent variables 6 through 9.
(4) Distraction. Independent variables 10 through 12.
Study hypotheses
We examine four categories – motivation, prior actual ability, current self-perceived
ability, and distraction – that may be associated with student performance in
advanced accounting and auditing courses. We discuss below the research hypotheses
under each of the four categories.
Motivation factors
The ?rst category, motivation, includes three variables:
The ?rst variable is the grade the student would like to make in the course. Our
hypothesis is that students who would like to make higher grades are motivated to
perform better to achieve their wish. On the other hand, students who report that “a C
is ?ne with them” are probably not that motivated. To eliminate redundancy we will
not give the null hypotheses but will state all our hypotheses in the alternate form as
shown below:
H
a1
. There is a positive association between the grade a given student would like
to make and that student’s performance in advanced accounting and auditing
courses.
The second variable is whether the student intends to take the CPA exam. Our
hypothesis is that students who intend to take the CPA exam are more motivated to
work hard to increase their chances of passing that exam and, therefore, they will earn
higher grades than students who do not intend to take the CPA exam:
H
a2
. There is an association between a student’s intention to take the CPA exam
and that student’s performance in advanced accounting and auditing courses.
The third motivation variable is whether the student intends to attend graduate school.
Our hypothesis is that students who have that intention are more motivated to work
hard to increase their chances of getting accepted at a good graduate school and,
therefore, they will earn higher grades than students who do not intend to go to
graduate school:
Student
performance
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H
a3
. There is an association between a student’s intention of attending graduate
school and that student’s performance in advanced accounting and auditing
courses.
Prior actual ability factors
The second category, prior actual ability, includes two variables:
The ?rst variable is the student’s grade in Intermediate Accounting II. Our
hypothesis is that students who earned higher grades in intermediate accounting II
(which is a prerequisite for advanced level accounting courses) will earn higher grades
in advanced accounting and auditing courses:
H
a4
. There is a positive association between a student’s grade in intermediate
accounting II and that student’s performance in advanced accounting and
auditing courses.
The second variable is the student’s cumulative GPA. Our hypothesis is that students
with higher cumulative GPAs will earn higher grades in advanced accounting and
auditing courses:
H
a5
. There is a positive association between a student’s cumulative GPA and that
student’s performance in advanced accounting and auditing courses.
Current self-perceived ability factors
The third category, current self-perceived ability, includes four variables.
These four variables represent students’ perceptions of their writing, math, reading,
and listening abilities. Our hypotheses are that students who perceive their writing,
math, reading, and listening abilities to be good or very good will earn higher grades in
advanced accounting and auditing courses than students who perceive their abilities in
these four areas to be average or poor:
H
a6
. There is a positive association between a student’s perception of his/her
writing ability and that student’s performance in advanced accounting and
auditing courses.
H
a7
. There is a positive association between a student’s perception of his/her math
ability and that student’s performance in Advanced Accounting and Auditing
courses.
H
a8
. There is a positive association between a student’s perception of his/her
reading ability and that student’s performance in advanced accounting and
auditing courses.
H
a9
. There is a positive association between a student’s perception of his/her
listening ability and that student’s performance in Advanced Accounting and
Auditing courses.
Distraction factors
The fourth category, distraction, includes three variables:
The ?rst variable is the student’s job type outside of school. Our hypothesis is that
students whose jobs outside of school are non-accounting-related will be distracted by
their jobs without gaining any understanding of accounting practice that might
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compensate for spending less time studying and will, therefore, end up earning lower
grades in advanced accounting and auditing courses than students whose jobs are
accounting related:
H
a10
. There is an association between a student’s type of job outside of school and
that student’s performance in Advanced Accounting and Auditing courses.
The second variable is the number of hours per week the student works outside of
school. Our hypothesis is that students who work more hours outside of school are
more distracted because they will spend less time studying and, therefore, will earn
lower grades than students who work fewer hours or who do not work at all:
H
a11
. There is a negative association between a student’s number of hours of work
per week outside of school and that student’s performance in advanced
accounting and auditing courses.
The third variable is the number of courses per semester the student is taking. Our
hypothesis is that students who are taking more courses than average are more
distracted because they spend less time studying per course and, therefore, will earn
lower grades than students who take fewer courses:
H
a12
. There is a negative association between a student’s course load and that
student’s performance in Advanced Accounting and Auditing courses.
Study sample
The study sample includes 104 students enrolled in advanced accounting and auditing
courses at a major metropolitan university. The university in which we conducted this
study is a commuter public university located in one of the largest cities in the USA
and enrolls about 12,500 students. The student body is very diverse as minority
students (mostly Hispanic and Asian) account for over 50 per cent. Most of the students
are the ?rst generation in their family to attend college. About 80 per cent of our
students work almost full time. They combine studying with working and raising a
family. We modi?ed a list of survey questions, from Ingram et al. (2002), to include,
besides the study variables, some demographic and other information, and distributed
it to students in advanced accounting and auditing courses. To increase the sample
size, we collected data over three consecutive semesters: Spring, Summer, and Fall of
2004. To avoid any possible instructor effect, we made sure that if a course is taught
more than once during the three semesters, it was taught by the same instructor.
Furthermore, to make sure that there are no signi?cant differences in responses from
semester to semester, we ran the statistical models using the responses for each
semester separately. We then compared the responses for each semester to the other
semesters, and we found no signi?cant differences. Our ?nal sample included 98 useful
responses (53 from the advanced accounting course and 45 from the auditing course).
Some students left some questions (independent variables) unanswered. Thus, 10 of the
12 variables have less than 98 observations each. However, most variables have 95
observations each.
Statistical tests and research results
At the beginning of this research project we de?ned the dependent variable, student
performance, only as the letter grade (e.g. A, B, etc.) a given student would receive for
Student
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the course. However, after discussions with the faculty teaching the two courses used
for the study, we realized that using the letter grade to operationally de?ne student
performance had three drawbacks:
(1) some faculty curve upward the average actual points received by every student
before they determine the letter grade;
(2) because we do not attach pluses or minuses to the letter grades at our school, the
letter grade treats a student receiving the lowest end of the grade range as
having the same exact performance as that of a student receiving the highest
end of the grade range (e.g. a student with actual average points of 80 and
another with actual average points of 89 would be considered having equal
performance since both students receive a B for the course); and
(3) the letter GPA of 4, 3, and 2 are not continuous and thus do not allow the use of
multivariate models to test the hypotheses.
As a result, in addition to using the grade to de?ne performance, we decided to use the
actual average number of points (including mid-term and ?nal examinations as well as
cases, papers and other projects) a given student received for the course before any
upward curving made by the faculty. All points used in the study were based on a
maximum total of 100 points. Some faculty members used total points of more than 100
to measure their students’ performance; however, they converted those points to a
number out of a maximum of 100 before giving them to us. We used the one-way
analysis of variance (ANOVA) statistical model to test our hypotheses with the
dependent variable de?ned as points. Table I presents the results of that test. Because
the dependent variable de?ned as “grade” is a categorical variable, we used the
Pearson and Spearman statistical tests instead of ANOVA. Table II presents the
Pearson and Spearman correlation coef?cients for “grade.” Because the prior actual
ability variables (the grade in intermediate accounting II and the cumulative GPA) may
derive most of the signi?cant associations that we obtain, we ran the Pearson and
Spearman partial correlation tests to control for these prior actual ability variables.
Table III presents these partial correlations.
Summary of results
Table IV presents a summary of the results of the study. This summary includes the
hypotheses, the independent variables, the association that we expected between each
independent variable and student performance de?ned either as “points” or “grade”,
the association that we actually obtained, and whether each of our 12 hypotheses was
supported or rejected.
As the last column of Table IVindicates, three hypotheses (1, 4 and 5) were supported
and seven hypotheses (2, 3, 6, 7, 10, 11 and 12) were rejected whether student
performance was de?ned as “points” or “grade.” The remaining two hypotheses (8 and 9)
were supported when student performance was de?ned as “points” and were rejected
when student performance was de?ned as “grade.” The three supported hypotheses
indicate that the grade the student would like to make in the course, the grade
in intermediate accounting II, and the GPA have signi?cant positive associations
withstudent performance whether it is de?ned as “points” or “grade.” The seven rejected
hypotheses indicate that intention to take the CPA exam or attend graduate school,
self-perceived writing and math abilities, type of job outside of school, number
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Source DF Sum of squares Mean square F-value Pr
Panel A: ANOVA for points using variable grademk
Grademk 2 2,482.05 1,241.02 9.56 0.00
Error 92 11,946.69 129.86
Corrected total 94 14,428.74
Panel B: ANOVA for points using variable cpa
Cpa 2 586.83 293.42 1.98 0.14
Error 96 14,213.17 148.05
Corrected total 98 14,800.00
Panel C: ANOVA for points using variable grad
Grad 3 874.26 291.42 1.97 0.12
Error 94 13,897.01 147.84
Corrected total 97 14,771.27
Panel D: ANOVA for points using variable grade322
grade322 2 3,195.35 1,597.68 13.16 ,0.0001
Error 94 11,412.46 121.41
Corrected total 96 14,607.81
Panel E: ANOVA for points using variable gpac
Gpac 2 1,626.87 813.43 5.78 0.00
Error 87 12,233.53 140.62
Corrected total 89 13,860.40
Panel F: ANOVA for points using variable write
Write 3 330.28 110.09 0.71 0.55
Error 92 14,242.21 154.81
Corrected total 95 14,572.49
Panel G: ANOVA for points using variable math
math 2 86.71 43.36 0.28 0.76
Error 92 14,469.02 157.27
Corrected total 94 14,555.73
Panel H: ANOVA for points using variable read
Read 3 2,341.30 780.43 5.87 0.00
Error 92 12,231.19 132.95
Corrected total 95 14,572.49
Panel I: ANOVA for points using variable listen
Listen 2 1,077.89 538.94 3.71 0.03
Error 93 13,494.60 145.10
Corrected total 95 14,572.49
Panel J: ANOVA for points using variable job
Job 3 502.44 167.48 1.13 0.34
Error 88 13,048.51 148.28
Corrected total 91 13,550.96
Panel K: ANOVA for points using variable hrs
Hrs 4 132.59 33.15 0.21 0.93
Error 91 14,451.37 158.81
Corrected total 95 14,583.96
Panel L: ANOVA for points using variable load
Load 5 627.23 125.45 0.82 0.54
Error 93 14,172.77 152.40
Corrected total 98 14,800.00
Table I.
Analysis of variance for
students’ performance
measured by points
Student
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a
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e
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a
d
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k
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a
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a
d
s
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r
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3
2
2
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p
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c
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e
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i
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n
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0
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1
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1
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0
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1
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2
0
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0
4
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0
9
2
0
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0
4
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1
5
0
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2
6
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H
r
s
0
.
0
8
2
0
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2
4
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0
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6
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2
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o
a
d
0
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1
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2
0
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3
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P
a
n
e
l
B
:
P
a
r
t
i
a
l
c
o
r
r
e
l
a
t
i
o
n
o
f
g
r
a
d
e
w
i
t
h
l
o
a
d
c
o
n
t
r
o
l
l
i
n
g
f
o
r
h
r
s
G
r
a
d
e
L
o
a
d
G
r
a
d
e
0
.
1
3
L
o
a
d
0
.
1
5
P
a
n
e
l
C
:
P
a
r
t
i
a
l
c
o
r
r
e
l
a
t
i
o
n
o
f
g
r
a
d
e
w
i
t
h
h
r
s
c
o
n
t
r
o
l
l
i
n
g
f
o
r
l
o
a
d
G
r
a
d
e
H
r
s
G
r
a
d
e
0
.
1
2
H
r
s
0
.
1
2
N
o
t
e
s
:
*
,
*
*
,
*
*
*
i
n
d
i
c
a
t
e
s
i
g
n
i
?
c
a
n
c
e
s
a
t
0
.
1
0
,
0
.
0
5
a
n
d
0
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0
1
l
e
v
e
l
.
a
P
e
a
r
s
o
n
c
o
r
r
e
l
a
t
i
o
n
c
o
e
f
?
c
i
e
n
t
s
a
r
e
a
b
o
v
e
t
h
e
d
i
a
g
o
n
a
l
a
n
d
S
p
e
a
r
m
a
n
c
o
r
r
e
l
a
t
i
o
n
c
o
e
f
?
c
i
e
n
t
s
a
r
e
u
n
d
e
r
t
h
e
d
i
a
g
o
n
a
l
Table II.
Correlation matrix
for grade
ARJ
21,1
24
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
5
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
P
a
n
e
l
A
:
P
a
r
t
i
a
l
P
e
a
r
s
o
n
a
n
d
S
p
e
a
r
m
a
n
c
o
r
r
e
l
a
t
i
o
n
c
o
e
f
?
c
i
e
n
t
s
f
o
r
g
r
a
d
e
a
c
o
n
t
r
o
l
l
i
n
g
f
o
r
g
r
a
d
e
3
2
2
a
n
d
g
p
a
c
G
r
a
d
e
G
r
a
d
e
m
k
C
p
a
G
r
a
d
s
W
r
i
t
e
M
a
t
h
R
e
a
d
L
i
s
t
e
n
J
o
b
H
r
s
L
o
a
d
G
r
a
d
e
0
.
3
3
*
*
*
0
.
0
1
2
0
.
2
9
*
*
0
.
0
4
0
.
0
4
2
0
.
1
3
2
0
.
0
1
2
0
.
1
7
0
.
0
7
0
.
0
7
G
r
a
d
e
m
k
0
.
3
2
*
*
*
2
0
.
1
7
2
0
.
0
3
2
0
.
1
8
0
.
1
6
2
0
.
1
3
0
.
0
6
2
0
.
3
2
*
*
*
2
0
.
2
5
*
*
0
.
0
1
C
p
a
2
0
.
0
3
2
0
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1
8
0
.
1
0
2
0
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1
0
2
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.
2
4
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*
2
0
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0
7
2
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2
5
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r
a
d
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1
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1
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5
2
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0
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0
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0
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1
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2
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1
2
W
r
i
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e
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0
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1
1
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1
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2
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0
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0
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2
9
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0
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1
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0
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1
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0
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3
3
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a
t
h
0
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0
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2
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2
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0
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4
8
*
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2
0
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0
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0
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2
1
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0
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1
6
R
e
a
d
2
0
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0
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2
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1
3
2
0
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0
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0
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0
6
0
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3
3
*
*
*
0
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1
1
0
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0
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0
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1
4
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1
0
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2
L
i
s
t
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n
2
0
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0
6
0
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1
5
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1
6
0
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1
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1
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1
2
2
0
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1
5
0
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0
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2
0
.
0
7
J
o
b
2
0
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1
7
2
0
.
3
3
*
*
*
0
.
0
4
0
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0
0
0
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1
8
0
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0
1
0
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1
6
2
0
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0
6
0
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1
4
0
.
2
6
*
*
H
r
s
0
.
0
7
2
0
.
2
7
*
*
2
0
.
0
1
2
0
.
2
5
*
*
0
.
3
1
*
*
*
2
0
.
2
3
*
0
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1
2
0
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0
3
0
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0
7
2
0
.
3
3
*
*
*
L
o
a
d
0
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1
1
0
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0
5
0
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0
2
0
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1
0
0
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0
3
0
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2
3
*
0
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0
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0
5
0
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2
7
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2
0
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3
8
*
*
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P
a
n
e
l
B
:
P
a
r
t
i
a
l
c
o
r
r
e
l
a
t
i
o
n
o
f
g
r
a
d
e
w
i
t
h
g
r
a
d
e
3
2
2
c
o
n
t
r
o
l
l
i
n
g
f
o
r
g
p
a
c
G
r
a
d
e
G
r
a
d
e
3
2
2
G
r
a
d
e
0
.
3
6
*
*
*
G
r
a
d
e
3
2
2
0
.
3
2
*
*
*
P
a
n
e
l
C
:
P
a
r
t
i
a
l
c
o
r
r
e
l
a
t
i
o
n
o
f
g
r
a
d
e
w
i
t
h
g
p
a
c
c
o
n
t
r
o
l
l
i
n
g
f
o
r
g
r
a
d
e
3
2
2
G
r
a
d
e
G
p
a
c
G
r
a
d
e
0
.
3
2
*
*
*
G
p
a
c
0
.
2
3
*
*
N
o
t
e
s
:
*
,
*
*
,
*
*
*
i
n
d
i
c
a
t
e
s
i
g
n
i
?
c
a
n
c
e
s
a
t
0
.
1
0
,
0
.
0
5
a
n
d
0
.
0
1
l
e
v
e
l
.
a
P
e
a
r
s
o
n
c
o
r
r
e
l
a
t
i
o
n
c
o
e
f
?
c
i
e
n
t
s
a
r
e
a
b
o
v
e
t
h
e
d
i
a
g
o
n
a
l
a
n
d
S
p
e
a
r
m
a
n
c
o
r
r
e
l
a
t
i
o
n
c
o
e
f
?
c
i
e
n
t
s
a
r
e
u
n
d
e
r
t
h
e
d
i
a
g
o
n
a
l
Table III.
Correlation matrix
for grade
Student
performance
25
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
5
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
E
x
p
e
c
t
e
d
a
s
s
o
c
i
a
t
i
o
n
w
i
t
h
s
t
u
d
e
n
t
p
e
r
f
o
r
m
a
n
c
e
d
e
?
n
e
d
a
s
:
O
b
t
a
i
n
e
d
a
s
s
o
c
i
a
t
i
o
n
w
i
t
h
s
t
u
d
e
n
t
p
e
r
f
o
r
m
a
n
c
e
d
e
?
n
e
d
a
s
:
H
y
p
o
t
h
e
s
i
s
S
u
p
p
o
r
t
e
d
(
S
)
o
r
R
e
j
e
c
t
e
d
(
R
)
w
h
e
n
s
t
u
d
e
n
t
p
e
r
f
o
r
m
a
n
c
e
i
s
d
e
?
n
e
d
a
s
:
H
y
p
o
t
h
e
s
i
s
N
o
.
I
n
d
e
p
e
n
d
e
n
t
v
a
r
i
a
b
l
e
s
l
i
s
t
e
d
u
n
d
e
r
e
a
c
h
f
a
c
t
o
r
“
P
o
i
n
t
s
”
“
G
r
a
d
e
”
“
P
o
i
n
t
s
”
“
G
r
a
d
e
”
“
P
o
i
n
t
s
”
“
G
r
a
d
e
”
F
a
c
t
o
r
1
:
M
o
t
i
v
a
t
i
o
n
1
G
r
a
d
e
s
t
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Table IV.
Summary of results
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of hours of work per week, and number of courses taken per semester have no
associations with student performance whether it is de?ned as “points” or “grade.” The
two remaining hypotheses that are partially supported and partially rejected indicate
that self-perceived reading and listening abilities have signi?cant positive association
with student performance de?ned as “points” but have no associations with student
performance de?ned as “grade.”
The Appendix provides a further discussion of the speci?c statistical results shown
in Tables I-III.
Conclusions and recommendations
One general conclusion of the study is that motivated students earn higher grades
in advanced accounting and auditing courses than students who are not motivated.
More speci?cally, the study provides evidence that the majority of students who
responded that they would like to make high grades in these courses ended up
making high grades. The result obtained in this study, that motivated students earn
higher grades than students who are not motivated, con?rms the results obtained in
some prior studies (Pascarella and Terenzini, 1991). Probably, there are various
reasons that are motivating the students to want to make high grades. This study
looked at two possible reasons: students’ intensions to take the CPA exam and
attend graduate schools. Our results show that neither of these is a good motivating
variable for the students in our school. Intention to take the CPA exam has no
signi?cant association with student performance de?ned either as “points” or
“grade.” Furthermore, intension to attend graduate school has no signi?cant
association with student performance de?ned as “points,” and worse yet, it has a
signi?cant negative association with student performance de?ned as “grade.” The
obtained association between intension to attend graduate school and student
performance seems to be counter-intuitive since Table I shows no signi?cant
association and Tables II and III show signi?cant negative association (at the 0.01
and 0.05 levels). One possible reason for this is the fact that student performance is
de?ned as “points” in Table I and as “grade” in Tables II and III. The latter
de?nition has several drawbacks as explained earlier. One other possible reason for
the signi?cant negative association between intension to attend graduate school and
student performance de?ned as “grade” is the fact that we assumed that students
who intend to attend graduate school at a university other than ours are more
motivated and, thus, will earn higher grades than students who intend to attend
graduate school at our university. This assumption was based on the general
perception as well as our own knowledge that the other graduate schools in town
are ranked higher academically than our school. As it turned out, from an analysis
of the frequency tables of responses (which are available from the authors upon
request) our students, particularly those with low grades, apparently thought that
our undergraduate school is too dif?cult and our graduate school will be even more
dif?cult. Thus, even though many of them reported that they intend to attend
graduate school, the majority reported that they would attend at another school. For
example, of the 22 students who intended to attend graduate school at another
university (i.e., those we thought would earn the highest grades), 15 (or 68 percent)
earned the grade of C, six (or 27 percent) earned the grade of B, and only one
student (or 5 percent) earned the grade of A.
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In light of this general conclusion, we recommend that college of business faculty in
general and accounting faculty in particular should ?nd ways (whatever these may be)
to motivate students to work hard and earn high grades. We realize that some faculty
may already be doing this; thus our recommendation is for those who may not be.
Another general conclusion of the study is that, as expected, students with high
prior actual ability end up earning higher grades in advanced accounting and auditing
courses than students with low prior actual ability. Speci?cally, the study provides
strong evidence that student performance in intermediate accounting II and their
cumulative GPA are strong predictors of student performance in advanced accounting
and auditing courses. This study’s result that student performance in intermediate
accounting II is a strong predictor of student performance in more advanced
undergraduate accounting courses is in agreement with the results in some prior
studies showing that prior accounting knowledge obtained through high school
education is a strong predictor of performance in college-level accounting courses
(Eskew and Faley, 1988; Bartlett et al., 1993; Gul and Fong, 1993; Tho, 1994; Rohde and
Kavanagh, 1996), and that college-level exposure to accounting is positively related to
student performance in the ?rst MBA-level accounting course (Canlar, 1986).
Furthermore, This study’s result that GPA is a strong predictor of student performance
in advanced accounting and auditing courses con?rms the results in some prior studies
showing that GPA is a strong predictor of performance in accounting courses (Eckel
and Johnson, 1983; Hicks and Richardson, 1984; Ingram and Peterson, 1987; Eskew and
Faley, 1988; Doran et al., 1991; Jackling and Anderson, 1998).
In light of this general conclusion, we recommend that faculty encourage their
students to work hard to get high grades in all the courses they take to increase their
GPA. We further recommend that faculty who teach intermediate accounting II
encourage their students to work hard and try to do well in that course by emphasizing
that research shows that students who get high grades in that course will most likely
get high grades in advanced accounting and auditing courses.
A third general conclusion of this study is that self-perceived abilities in reading
and listening are strong predictors of student performance (de?ned as “points”) in
advanced accounting and auditing courses. More speci?cally, the study provides
evidence those students who reported that their reading and listening abilities are good
or very good earned higher grades than those who reported that their reading and
listening abilities are average or poor. Incidentally, only six students (or roughly
6 percent of the sample) reported that their reading and/or listening abilities are poor.
In light of this general conclusion, we recommend that accounting faculty encourage
their students to concentrate on improving their reading and listening skills by
informing them that research has shown that there is a strong correlation between
good reading and listening skills and student performance (de?ned as the actual points
received for the course) in advanced accounting and auditing. Again, we realize that
some faculty may already be encouraging their students to improve their reading and
listening skills; thus our recommendation is for those who may not be.
The fact that this study shows no signi?cant association between self-perceived
writing and math abilities and student performance de?ned as “points,” or between
self-perceived writing, math, reading and listening abilities and student performance
de?ned as “grade” is puzzling. One explanation for this may be that students tend to
over-estimate their abilities, and that their self-perceptions of their abilities in these
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areas are not accurate representations of their actual abilities. However, we may note
here that the result obtained in this study, showing no association between students’
mathematical ability and their performance in advanced accounting and auditing
courses, con?rms the result in at least one prior study (Gist et al., 1996) that showed
that students with strong mathematical background did not outperform students with
weaker mathematical background in accounting courses.
A fourth general conclusion of this study is that the distraction variables
(i.e. working too many hours per week, even in non-accounting related jobs, and taking
too many courses per semester) have no signi?cant negative associations with student
performance. That is, they are not distracting the students and preventing them from
earning high grades
In light of this conclusion we recommend that accounting faculty need not
encourage their students to work as few hours as possible to earn high grades. And if
the students have to work many hours anyway to support their families, accounting
faculty need not encourage those students to take as few courses per semester as
possible to earn high grades in advanced accounting and auditing courses.
Study limitations and suggestions for further research
Our study is subject to some limitations. One limitation is that our school is a public
university and, therefore, we do not know if the results will be the same for private
schools. So, one suggestion for further research is to replicate the study in a private
school. Another limitation is that our school is a commuter school and, therefore, we do
not know if the results will be the same for residential schools. Accordingly, another
suggestion for further research is to replicate the study in a residential school. A third
limitation is that our student body is highly diversi?ed and, therefore, we do not know
if the results will be the same for much less diversi?ed schools. Thus, a third
suggestion for further research is to replicate the study in a much less diversi?ed
school. A fourth limitation of this study is that about 80 percent of our students work
almost full time while going to school and, therefore, we do not know if the results will
be the same for schools where a much less percentage of the students work full time.
Therefore, a fourth suggestion for further research is to replicate the study in other
schools where a much smaller percentage of the students work full time. A ?fth
limitation of the study is that the results are based on a small sample size and, thus, are
not as robust as they could have been if the sample size were at least 20 percent larger.
Hence, a ?fth suggestion for future research is to replicate the study using a larger
sample.
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Bartlett, S.M., Peel, J. and Pendlebury, M. (1993), “From fresher to ?nalist: a three-year study of
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Buckless, F.A., Lipe, M.G. and Ravenscroft, S.P. (1991), “Do gender effects on accounting course
performance persist after controlling for general academic aptitude?”, Issues in Accounting
Education, Vol. 6, pp. 248-61.
Canlar, M. (1986), “College-level exposure to accounting study and its effect on student
performance in the ?rst MBA-level ?nancial accounting course”, Issues in Accounting
Education, Vol. 1, pp. 13-23.
Didia, D. and Hasnat, B. (1998), “The determinants of performance in the univeresity
introductory ?nance course”, Financial Practice and Education, Vol. 1, pp. 102-7.
Doran, B., Bouillon, M.L. and Smith, C.G. (1991), “Determinants of student performance in
accounting principles I and II”, Issues in Accounting Education, Vol. 6, pp. 74-84.
Eckel, N. and Johnson, W.A. (1983), “A model for screening and classifying potential”,
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Eskew, R.K. and Faley, R.H. (1988), “Some determinants of student performance in the ?rst
college-level ?nancial accounting course”, The Accounting Review, January, pp. 137-47.
Gist, W.E., Goedde, H. and Ward, B.H. (1996), “The in?uence of mathematical skills and other
factors on minority student performance in principles of accounting”, Issues in Accounting
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Gul, F.A. and Fong, S.C. (1993), “Predicting success for introductory accounting students: some
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Hicks, D.W. and Richardson, F.M. (1984), “Predicting early success in intermediate accounting:
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pp. 61-7.
Ingram, R.W. and Peterson, R.J. (1987), “An evaluation of AICPA tests for predicting the
performance of accounting majors”, The Accounting Review, January, pp. 215-23.
Ingram, R.W., Albright, T.L. and Baldwin, A.B. (2002), Financial Accounting: ABridge to Decision
Making, Thomson South-Western, Cincinnatti, OH.
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accounting: a research note”, Accounting Education: An International Journal, Vol. 1,
pp. 33-42.
Jenkins, E.K. (1998), “The signi?cant role of critical thinking in predicting auditing students’
performance”, Journal of Education for Business, Vol. 5, pp. 274-80.
Johnson, D.L., Joyce, P. and Sen, S. (2002), “An analysis of student effort and performance in the
?nance principles course”, Journal of Applied Finance, Fall/Winter, pp. 67-72.
Koh, M.Y. and Koh, H.C. (1999), “The determinants of performance in an accountancy degree
course”, Accounting Education: An International Journal, Vol. 1, pp. 13-29.
Lane, A. and Porch, M. (2002), “The impact of background factors on the performance of
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a research note”, Accounting Education, Vol. 1, pp. 109-18.
Lipe, M.G. (1989), “Further evidence on the performance of female versus male accounting
students”, Issues in Accounting Education, Vol. 1, pp. 144-52.
Mutchler, J.E., Turner, T.H. and Williams, D.D. (1987), “The performance of female versus male
accounting students”, Issues in Accounting Education, Vol. 1, pp. 103-11.
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Tho, L.M. (1994), “Some determinants of student performance in the University of Malaya
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Appendix. A further discussion of the statistical results in Tables I-III
We provide below a bit more elaborate analysis of the statistical results of the study by the type
of factors associated or not associated with student performance.
Motivation factors associated with student performance
As Table I indicates, of the three motivation variables, only one, the grade the student would like
to make in the course, is signi?cantly associated (at the 0.01 level) with the student’s performance
de?ned as “points.” The remaining two motivation variables have no signi?cant associations
with the student’s performance de?ned as “points.” As Table II indicates, of the three motivation
variables, one variable, the grade the student would like to make in the course, is signi?cantly
associated (at the .01 level in both Pearson and Spearman tests) with the student’s performance
de?ned as “grade.” One other variable, whether the student intends to take the CPA exam, has no
signi?cant association with student performance. The third variable, whether the student
intends to attend graduate school, has a signi?cant negative association (at the 0.05 level in both
Pearson and Spearman tests) with the student’s performance. These results remained the same
even after we controlled for the prior actual ability factors (the grade in Intermediate Accounting
II and the cumulative GPA). In fact, as Table III indicates, the negative association between
student’s intension of attending graduate school and student performance becomes even more
signi?cant (at the 0.01 level) under Spearman’s test.
Prior actual ability factors associated with students’ performance
As Tables I and II indicate, the two variables representing prior actual ability have signi?cant
associations (at the 0.01 level) with student performance de?ned either as the grade or the
average actual points received for the course.
Current self-perceived ability factors associated with student performance
As Table I indicates, of the four self-perceived ability variables, one variable, the student’s
reading ability, is signi?cantly associated (at the 0.01 level) with the student’s performance
de?ned as “points.” One other variable, the student’s listening ability, is signi?cantly associated
(at the 0.05 level) with the student’s performance de?ned as “points.” The other two variables
have positive but not signi?cant associations with student performance. As Table II indicates,
none of the four variables representing self-perceived ability has any signi?cant association with
student performance de?ned as grade. As Table III indicates, these results remained the same
even after we controlled for the prior actual ability factors (the grade in Intermediate
Accounting II and the cumulative GPA). Thus, based only on the results shown in Table I, we can
generally state that students’ self-perceived reading and listening abilities have signi?cant
associations with their performance de?ned as the average actual points received for the course.
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Based only on the results shown in Table II, we can generally state that students’ self-perceived
writing, math, reading and listening abilities have no signi?cant associations with their
performance de?ned as the “grade” received for the course. The contradiction between the
results in Table I and those in Table II may be attributed to using two different de?nitions of
student performance, points and grade, with the latter having some drawbacks as discussed
earlier. The non-signi?cant results could also be due the possibility that students, particularly
those earning low grades, overestimated their reading, math, writing, and listening abilities.
Distraction factors associated with student performance
As Table I indicates, the variables representing distraction factors have no signi?cant negative
associations with student performance de?ned as the average actual points received for the
course. As Table II indicates, the type of job has a negative but not signi?cant association with
student performance, whereas the number of hours of work outside of school, and the course load
have positive but not signi?cant association with student performance de?ned as the grade
received for the course.
Corresponding author
Mostafa M. Maksy can be contacted at: [email protected]
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doc_595738992.pdf
The purpose of this study is to identify which of factors are associated with student
performance in advanced accounting and auditing courses.
Accounting Research Journal
Factors associated with student performance in advanced accounting and auditing: An
empirical study in a public university
Mostafa M. Maksy Lin Zheng
Article information:
To cite this document:
Mostafa M. Maksy Lin Zheng, (2008),"Factors associated with student performance in advanced accounting
and auditing", Accounting Research J ournal, Vol. 21 Iss 1 pp. 16 - 32
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Beverley J ackling, Paul de Lange, J on Phillips, J ames Sewell, (2012),"Attitudes towards accounting:
differences between Australian and international students", Accounting Research J ournal, Vol. 25 Iss 2 pp.
113-130http://dx.doi.org/10.1108/10309611211287305
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Factors associated with student
performance in advanced
accounting and auditing
An empirical study in a public university
Mostafa M. Maksy
Northeastern Illinois University, Chicago, Illinois, USA, and
Lin Zheng
Mercer College, Atlanta, Georgia, USA
Abstract
Purpose – The purpose of this study is to identify which of factors are associated with student
performance in advanced accounting and auditing courses.
Design/methodology/approach – Students enrolled in a highly diversi?ed, commuter, public
university located in one of the largest cities in the USA provided responses to 12 questions used as
independent variables.
Findings – Of the three variables used as proxies for motivation, the grade the student would like to
make in the course was found to be signi?cantly associated with student performance, but intention to
take the CPA exam or attend graduate school were not. Additionally, the grade in intermediate
accounting II and grade point average (used as proxies for actual ability) were found to be strong
predictors of student performance. Self-perceived reading and listening abilities had moderate to
strong associations with student performance, but self-perceived writing and math abilities did not.
Finally, holding non-accounting-related jobs, working high numbers of hours per week, and taking on
higher course loads during the semester are factors which were, surprisingly, not signi?cantly
correlated with student performance.
Originality/value – No prior study that we are aware of has considered the associations between
motivation, actual ability, self-perceived ability, and distraction factors and student performance in
advanced level undergraduate accounting courses.
Keywords Students, Performance criteria, Accounting, Auditing, Education, Motivation (psychology)
Paper type Research paper
Introduction
As the review of prior research below indicates, many studies have explored various
factors that are associated with student performance in college-level accounting
courses. However, no prior study, that we are aware of, has considered the association
between motivation, prior actual ability, current self-perceived ability, and distraction
factors and student performance in advanced level undergraduate accounting courses.
This study considers the associations between these factors and student performance
in advanced accounting, and auditing courses.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1030-9616.htm
The authors would like to thank session attendants at the Midwest Region and the National
Meetings of the American Accounting Association as well as four anonymous reviewers for their
helpful comments and constructive feedback on earlier drafts of this paper.
ARJ
21,1
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Accounting Research Journal
Vol. 21 No. 1, 2008
pp. 16-32
qEmerald Group Publishing Limited
1030-9616
DOI 10.1108/10309610810891328
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The objective of the study is predicated on the assumption that identi?cation of
some factors that are associated with student performance and some factors that are
not may help us to emphasize those factors that improve student performance and
de-emphasize those factors that do not.
In the following parts of the paper we present a review of prior research, and we
describe the study variables, hypotheses, sample, statistical tests, and research results.
We end the paper with some conclusions, recommendations, study limitations, and
some suggestions for further research.
Review of prior research
Prior studies have explored various factors (e.g. aptitude, general academic
performance, prior exposure to accounting, prior exposure to mathematics, age, and
gender) that are associated with student performance in college-level accounting
courses. Grade point average (GPA) is used frequently as a proxy for aptitude and
prior academic performance. For example, researchers using US data ?nd evidence
supporting GPA as a signi?cant predictor of performance in accounting courses (Eckel
and Johnson, 1983; Hicks and Richardson, 1984; Ingram and Peterson, 1987; Eskew and
Faley, 1988; Doran et al., 1991). The US ?ndings are supported in Australia by Jackling
and Anderson (1998). However, using another measure, pre-university examination
performance, Gist et al. (1996) ?nd no signi?cant association between academic
performance and performance in university accounting courses.
Accounting is a subject area that requires accumulation of prior knowledge and
considerable quantitative skills. Therefore, several studies have investigated the
impact of prior exposure to accounting and mathematical background courses on
performance in college accounting courses. However, the results are inconclusive.
Some studies (Baldwin and Howe, 1982; Bergin, 1983; Schroeder, 1986) ?nd that
performance is not signi?cantly associated with prior exposure to high school
accounting education. However, some later studies (Eskew and Faley, 1988; Bartlett
et al., 1993; Gul and Fong, 1993; Tho, 1994; Rohde and Kavanagh, 1996) ?nd that prior
accounting knowledge, obtained through high school education, is a signi?cant
determinant of performance in college-level accounting courses. Con?icting results are
also observed about the association between student performance in introductory
accounting and their performance in non-introductory accounting courses. Canlar
(1986) ?nds evidence that college-level exposure to accounting is positively related to
student performance in the ?rst MBA-level ?nancial accounting course. However,
Doran et al. (1991) show that performance in the introductory accounting course has a
negative impact on performance in subsequent accounting courses. The in?uence of
mathematical background on performance in accounting courses is also ambiguous.
Eskew and Faley (1988) and Gul and Fong (1993) suggest that students with strong
mathematical backgrounds outperform students with weaker mathematical
backgrounds. However, a later study (Gist et al., 1996) does not report the same results.
Two demographic variables, age and gender, receive less attention than those
factors discussed above. Bartlett et al. (1993) and Koh and Koh (1999) suggest that
younger students have better performance, particularly at the senior university level.
Jenkins (1998) and Lane and Porch (2002) conclude that age is not a signi?cant
determinant for performance in auditing and management accounting courses.
There are studies indicating that male students perform better than female ones.
Student
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However, the results are either insigni?cant (Lipe, 1989) or only hold true for
introductory courses (Doran et al., 1991). One study ?nds that female students score
signi?cantly higher than male students (Mutchler et al., 1987). However, other studies
?nd no signi?cant differences in performance between male and female accounting
students. For example, Tyson (1989) and Buckless et al. (1991) demonstrate that gender
effect disappears when general academic ability is controlled for in the model.
One study shows that motivation and effort, among other factors, signi?cantly
in?uence individual performance in college (Pascarella and Terenzini, 1991). Other
studies have explored the association between effort and performance in the area of
?nance. For example, using self-reported data, Didia and Hasnat (1998) present
contra-intuitive evidence that the more time spent studying per week, the lower the
grade in the introductory ?nance course. However, another study (Nos?nger and Petry,
1999) also uses self-reported data and ?nds no signi?cant relationship between effort
and performance. Johnson et al. (2002) utilize computerized quizzes and analyze the
effect of objectively measured effort on student performance. Their evidence shows
that, after controlling for aptitude, ability, and gender, effort remains signi?cant in
explaining the differences in performance.
Study variables
We use two dependent variables and 12 independent variables in the study. Below we
list these variables starting with the abbreviation used for each variable in the
statistical models and ending with a de?nition or an explanation of the variable. For
each question representing an independent variable we list the possible responses in
parentheses “[ ]”.
Dependent variables
.
Points. The actual average number of points (including mid-term and ?nal
examinations, cases, term papers, class presentations, and other projects) a given
student received in a given course.
.
Grade. The letter grade (e.g. A, B, or C) a given student received in a given
course.
Independent variables
.
Grademk. The grade I would like to make in the course is [a. an A; b. at least a B;
c. a C is ?ne with me].
.
cpa. Do you intend to take the CPA exam? [a. Yes; b. No; c. Maybe].
.
grad. Do you intend to attend graduate school? [a. Yes, at this school; b. Yes, but
at another school; c. No; d. Maybe].
.
grade322. What was your grade for ACTG 322 (Intermediate Accounting II)?
[a. A; b. B; c.C].
.
gpac. What is your cumulative GPA? [__].
.
write. My writing ability is [a. Very good; b. Good; c. Average; d. Poor].
.
math. My math ability is [a. Very good; b. Good; c. Average; d. Poor].
.
read. My reading ability is [a. Very good; b. Good; c. Average; d. Poor].
.
listen. My listening ability is [a. Very good; b. Good; c. Average; d. Poor].
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job. My job outside of school is [a. Accounting; b. Business related (but not
accounting); c. Other].
.
hrs. In an average week, how many hours do you work at a job outside of school?
[___ hours].
.
load. How many courses are you taking this semester? [___ courses].
Categorization of independent variables
We classify the 12 independent variables into four categories of factors that may be
associated with students’ performance in advanced accounting and auditing courses as
following four categories:
(1) Motivation. Independent variables 1 through 3.
(2) Prior actual ability. Independent variables 4 and 5.
(3) Current self-perceived ability. Independent variables 6 through 9.
(4) Distraction. Independent variables 10 through 12.
Study hypotheses
We examine four categories – motivation, prior actual ability, current self-perceived
ability, and distraction – that may be associated with student performance in
advanced accounting and auditing courses. We discuss below the research hypotheses
under each of the four categories.
Motivation factors
The ?rst category, motivation, includes three variables:
The ?rst variable is the grade the student would like to make in the course. Our
hypothesis is that students who would like to make higher grades are motivated to
perform better to achieve their wish. On the other hand, students who report that “a C
is ?ne with them” are probably not that motivated. To eliminate redundancy we will
not give the null hypotheses but will state all our hypotheses in the alternate form as
shown below:
H
a1
. There is a positive association between the grade a given student would like
to make and that student’s performance in advanced accounting and auditing
courses.
The second variable is whether the student intends to take the CPA exam. Our
hypothesis is that students who intend to take the CPA exam are more motivated to
work hard to increase their chances of passing that exam and, therefore, they will earn
higher grades than students who do not intend to take the CPA exam:
H
a2
. There is an association between a student’s intention to take the CPA exam
and that student’s performance in advanced accounting and auditing courses.
The third motivation variable is whether the student intends to attend graduate school.
Our hypothesis is that students who have that intention are more motivated to work
hard to increase their chances of getting accepted at a good graduate school and,
therefore, they will earn higher grades than students who do not intend to go to
graduate school:
Student
performance
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a3
. There is an association between a student’s intention of attending graduate
school and that student’s performance in advanced accounting and auditing
courses.
Prior actual ability factors
The second category, prior actual ability, includes two variables:
The ?rst variable is the student’s grade in Intermediate Accounting II. Our
hypothesis is that students who earned higher grades in intermediate accounting II
(which is a prerequisite for advanced level accounting courses) will earn higher grades
in advanced accounting and auditing courses:
H
a4
. There is a positive association between a student’s grade in intermediate
accounting II and that student’s performance in advanced accounting and
auditing courses.
The second variable is the student’s cumulative GPA. Our hypothesis is that students
with higher cumulative GPAs will earn higher grades in advanced accounting and
auditing courses:
H
a5
. There is a positive association between a student’s cumulative GPA and that
student’s performance in advanced accounting and auditing courses.
Current self-perceived ability factors
The third category, current self-perceived ability, includes four variables.
These four variables represent students’ perceptions of their writing, math, reading,
and listening abilities. Our hypotheses are that students who perceive their writing,
math, reading, and listening abilities to be good or very good will earn higher grades in
advanced accounting and auditing courses than students who perceive their abilities in
these four areas to be average or poor:
H
a6
. There is a positive association between a student’s perception of his/her
writing ability and that student’s performance in advanced accounting and
auditing courses.
H
a7
. There is a positive association between a student’s perception of his/her math
ability and that student’s performance in Advanced Accounting and Auditing
courses.
H
a8
. There is a positive association between a student’s perception of his/her
reading ability and that student’s performance in advanced accounting and
auditing courses.
H
a9
. There is a positive association between a student’s perception of his/her
listening ability and that student’s performance in Advanced Accounting and
Auditing courses.
Distraction factors
The fourth category, distraction, includes three variables:
The ?rst variable is the student’s job type outside of school. Our hypothesis is that
students whose jobs outside of school are non-accounting-related will be distracted by
their jobs without gaining any understanding of accounting practice that might
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compensate for spending less time studying and will, therefore, end up earning lower
grades in advanced accounting and auditing courses than students whose jobs are
accounting related:
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a10
. There is an association between a student’s type of job outside of school and
that student’s performance in Advanced Accounting and Auditing courses.
The second variable is the number of hours per week the student works outside of
school. Our hypothesis is that students who work more hours outside of school are
more distracted because they will spend less time studying and, therefore, will earn
lower grades than students who work fewer hours or who do not work at all:
H
a11
. There is a negative association between a student’s number of hours of work
per week outside of school and that student’s performance in advanced
accounting and auditing courses.
The third variable is the number of courses per semester the student is taking. Our
hypothesis is that students who are taking more courses than average are more
distracted because they spend less time studying per course and, therefore, will earn
lower grades than students who take fewer courses:
H
a12
. There is a negative association between a student’s course load and that
student’s performance in Advanced Accounting and Auditing courses.
Study sample
The study sample includes 104 students enrolled in advanced accounting and auditing
courses at a major metropolitan university. The university in which we conducted this
study is a commuter public university located in one of the largest cities in the USA
and enrolls about 12,500 students. The student body is very diverse as minority
students (mostly Hispanic and Asian) account for over 50 per cent. Most of the students
are the ?rst generation in their family to attend college. About 80 per cent of our
students work almost full time. They combine studying with working and raising a
family. We modi?ed a list of survey questions, from Ingram et al. (2002), to include,
besides the study variables, some demographic and other information, and distributed
it to students in advanced accounting and auditing courses. To increase the sample
size, we collected data over three consecutive semesters: Spring, Summer, and Fall of
2004. To avoid any possible instructor effect, we made sure that if a course is taught
more than once during the three semesters, it was taught by the same instructor.
Furthermore, to make sure that there are no signi?cant differences in responses from
semester to semester, we ran the statistical models using the responses for each
semester separately. We then compared the responses for each semester to the other
semesters, and we found no signi?cant differences. Our ?nal sample included 98 useful
responses (53 from the advanced accounting course and 45 from the auditing course).
Some students left some questions (independent variables) unanswered. Thus, 10 of the
12 variables have less than 98 observations each. However, most variables have 95
observations each.
Statistical tests and research results
At the beginning of this research project we de?ned the dependent variable, student
performance, only as the letter grade (e.g. A, B, etc.) a given student would receive for
Student
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the course. However, after discussions with the faculty teaching the two courses used
for the study, we realized that using the letter grade to operationally de?ne student
performance had three drawbacks:
(1) some faculty curve upward the average actual points received by every student
before they determine the letter grade;
(2) because we do not attach pluses or minuses to the letter grades at our school, the
letter grade treats a student receiving the lowest end of the grade range as
having the same exact performance as that of a student receiving the highest
end of the grade range (e.g. a student with actual average points of 80 and
another with actual average points of 89 would be considered having equal
performance since both students receive a B for the course); and
(3) the letter GPA of 4, 3, and 2 are not continuous and thus do not allow the use of
multivariate models to test the hypotheses.
As a result, in addition to using the grade to de?ne performance, we decided to use the
actual average number of points (including mid-term and ?nal examinations as well as
cases, papers and other projects) a given student received for the course before any
upward curving made by the faculty. All points used in the study were based on a
maximum total of 100 points. Some faculty members used total points of more than 100
to measure their students’ performance; however, they converted those points to a
number out of a maximum of 100 before giving them to us. We used the one-way
analysis of variance (ANOVA) statistical model to test our hypotheses with the
dependent variable de?ned as points. Table I presents the results of that test. Because
the dependent variable de?ned as “grade” is a categorical variable, we used the
Pearson and Spearman statistical tests instead of ANOVA. Table II presents the
Pearson and Spearman correlation coef?cients for “grade.” Because the prior actual
ability variables (the grade in intermediate accounting II and the cumulative GPA) may
derive most of the signi?cant associations that we obtain, we ran the Pearson and
Spearman partial correlation tests to control for these prior actual ability variables.
Table III presents these partial correlations.
Summary of results
Table IV presents a summary of the results of the study. This summary includes the
hypotheses, the independent variables, the association that we expected between each
independent variable and student performance de?ned either as “points” or “grade”,
the association that we actually obtained, and whether each of our 12 hypotheses was
supported or rejected.
As the last column of Table IVindicates, three hypotheses (1, 4 and 5) were supported
and seven hypotheses (2, 3, 6, 7, 10, 11 and 12) were rejected whether student
performance was de?ned as “points” or “grade.” The remaining two hypotheses (8 and 9)
were supported when student performance was de?ned as “points” and were rejected
when student performance was de?ned as “grade.” The three supported hypotheses
indicate that the grade the student would like to make in the course, the grade
in intermediate accounting II, and the GPA have signi?cant positive associations
withstudent performance whether it is de?ned as “points” or “grade.” The seven rejected
hypotheses indicate that intention to take the CPA exam or attend graduate school,
self-perceived writing and math abilities, type of job outside of school, number
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Source DF Sum of squares Mean square F-value Pr
Panel A: ANOVA for points using variable grademk
Grademk 2 2,482.05 1,241.02 9.56 0.00
Error 92 11,946.69 129.86
Corrected total 94 14,428.74
Panel B: ANOVA for points using variable cpa
Cpa 2 586.83 293.42 1.98 0.14
Error 96 14,213.17 148.05
Corrected total 98 14,800.00
Panel C: ANOVA for points using variable grad
Grad 3 874.26 291.42 1.97 0.12
Error 94 13,897.01 147.84
Corrected total 97 14,771.27
Panel D: ANOVA for points using variable grade322
grade322 2 3,195.35 1,597.68 13.16 ,0.0001
Error 94 11,412.46 121.41
Corrected total 96 14,607.81
Panel E: ANOVA for points using variable gpac
Gpac 2 1,626.87 813.43 5.78 0.00
Error 87 12,233.53 140.62
Corrected total 89 13,860.40
Panel F: ANOVA for points using variable write
Write 3 330.28 110.09 0.71 0.55
Error 92 14,242.21 154.81
Corrected total 95 14,572.49
Panel G: ANOVA for points using variable math
math 2 86.71 43.36 0.28 0.76
Error 92 14,469.02 157.27
Corrected total 94 14,555.73
Panel H: ANOVA for points using variable read
Read 3 2,341.30 780.43 5.87 0.00
Error 92 12,231.19 132.95
Corrected total 95 14,572.49
Panel I: ANOVA for points using variable listen
Listen 2 1,077.89 538.94 3.71 0.03
Error 93 13,494.60 145.10
Corrected total 95 14,572.49
Panel J: ANOVA for points using variable job
Job 3 502.44 167.48 1.13 0.34
Error 88 13,048.51 148.28
Corrected total 91 13,550.96
Panel K: ANOVA for points using variable hrs
Hrs 4 132.59 33.15 0.21 0.93
Error 91 14,451.37 158.81
Corrected total 95 14,583.96
Panel L: ANOVA for points using variable load
Load 5 627.23 125.45 0.82 0.54
Error 93 14,172.77 152.40
Corrected total 98 14,800.00
Table I.
Analysis of variance for
students’ performance
measured by points
Student
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r
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k
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0
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a
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0
5
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1
8
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0
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1
2
2
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2
2
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1
5
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2
3
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0
6
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r
a
d
2
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2
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9
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r
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2
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7
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1
6
0
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0
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4
6
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9
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2
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7
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0
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0
4
0
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0
9
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p
a
c
0
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4
5
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3
1
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1
4
2
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1
0
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4
9
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3
2
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1
6
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3
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8
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r
i
t
e
0
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1
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0
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7
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1
4
0
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2
7
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0
5
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a
t
h
0
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0
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0
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1
6
2
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4
0
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3
5
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.
0
2
0
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1
4
2
0
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0
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0
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0
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2
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0
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2
0
.
2
4
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0
.
1
5
R
e
a
d
0
.
0
2
2
0
.
0
5
2
0
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1
1
0
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0
4
0
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0
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0
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1
2
0
.
3
7
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0
.
1
0
0
.
1
1
0
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0
8
0
.
0
9
0
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0
0
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i
s
t
e
n
2
0
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0
9
0
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1
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1
1
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1
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2
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1
1
2
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0
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0
3
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o
b
2
0
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0
5
2
0
.
2
7
*
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0
.
0
7
0
.
1
0
0
.
1
7
0
.
0
1
0
.
1
6
2
0
.
0
4
0
.
0
9
2
0
.
0
4
0
.
1
5
0
.
2
6
*
*
H
r
s
0
.
0
8
2
0
.
2
4
*
*
0
.
0
7
2
0
.
1
6
0
.
0
1
2
0
.
0
2
0
.
2
6
*
*
2
0
.
2
5
*
*
0
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1
0
2
0
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0
5
0
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0
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2
0
.
2
6
*
*
L
o
a
d
0
.
1
1
0
.
1
0
2
0
.
0
1
0
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1
2
0
.
0
9
0
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0
4
0
.
0
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0
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2
0
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0
.
0
4
2
0
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0
1
0
.
2
5
*
*
2
0
.
3
0
*
*
*
P
a
n
e
l
B
:
P
a
r
t
i
a
l
c
o
r
r
e
l
a
t
i
o
n
o
f
g
r
a
d
e
w
i
t
h
l
o
a
d
c
o
n
t
r
o
l
l
i
n
g
f
o
r
h
r
s
G
r
a
d
e
L
o
a
d
G
r
a
d
e
0
.
1
3
L
o
a
d
0
.
1
5
P
a
n
e
l
C
:
P
a
r
t
i
a
l
c
o
r
r
e
l
a
t
i
o
n
o
f
g
r
a
d
e
w
i
t
h
h
r
s
c
o
n
t
r
o
l
l
i
n
g
f
o
r
l
o
a
d
G
r
a
d
e
H
r
s
G
r
a
d
e
0
.
1
2
H
r
s
0
.
1
2
N
o
t
e
s
:
*
,
*
*
,
*
*
*
i
n
d
i
c
a
t
e
s
i
g
n
i
?
c
a
n
c
e
s
a
t
0
.
1
0
,
0
.
0
5
a
n
d
0
.
0
1
l
e
v
e
l
.
a
P
e
a
r
s
o
n
c
o
r
r
e
l
a
t
i
o
n
c
o
e
f
?
c
i
e
n
t
s
a
r
e
a
b
o
v
e
t
h
e
d
i
a
g
o
n
a
l
a
n
d
S
p
e
a
r
m
a
n
c
o
r
r
e
l
a
t
i
o
n
c
o
e
f
?
c
i
e
n
t
s
a
r
e
u
n
d
e
r
t
h
e
d
i
a
g
o
n
a
l
Table II.
Correlation matrix
for grade
ARJ
21,1
24
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
5
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
P
a
n
e
l
A
:
P
a
r
t
i
a
l
P
e
a
r
s
o
n
a
n
d
S
p
e
a
r
m
a
n
c
o
r
r
e
l
a
t
i
o
n
c
o
e
f
?
c
i
e
n
t
s
f
o
r
g
r
a
d
e
a
c
o
n
t
r
o
l
l
i
n
g
f
o
r
g
r
a
d
e
3
2
2
a
n
d
g
p
a
c
G
r
a
d
e
G
r
a
d
e
m
k
C
p
a
G
r
a
d
s
W
r
i
t
e
M
a
t
h
R
e
a
d
L
i
s
t
e
n
J
o
b
H
r
s
L
o
a
d
G
r
a
d
e
0
.
3
3
*
*
*
0
.
0
1
2
0
.
2
9
*
*
0
.
0
4
0
.
0
4
2
0
.
1
3
2
0
.
0
1
2
0
.
1
7
0
.
0
7
0
.
0
7
G
r
a
d
e
m
k
0
.
3
2
*
*
*
2
0
.
1
7
2
0
.
0
3
2
0
.
1
8
0
.
1
6
2
0
.
1
3
0
.
0
6
2
0
.
3
2
*
*
*
2
0
.
2
5
*
*
0
.
0
1
C
p
a
2
0
.
0
3
2
0
.
1
8
0
.
1
0
2
0
.
1
0
2
0
.
2
4
*
*
2
0
.
0
7
2
0
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2
5
*
*
0
.
0
3
2
0
.
0
2
0
.
0
4
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r
a
d
2
0
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3
1
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*
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2
0
.
0
1
0
.
0
9
2
0
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1
0
0
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5
2
*
*
*
0
.
0
6
0
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1
0
0
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0
1
2
0
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2
4
*
*
0
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1
2
W
r
i
t
e
0
.
0
0
2
0
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2
0
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2
0
.
1
1
2
0
.
1
0
2
0
.
0
8
0
.
2
9
*
*
0
.
1
2
0
.
1
6
0
.
3
3
*
*
*
0
.
0
2
M
a
t
h
0
.
0
5
0
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1
9
2
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2
2
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0
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4
8
*
*
*
2
0
.
0
9
0
.
0
4
0
.
0
7
2
0
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0
1
2
0
.
2
1
*
0
.
1
6
R
e
a
d
2
0
.
0
7
2
0
.
1
3
2
0
.
0
8
0
.
0
6
0
.
3
3
*
*
*
0
.
1
1
0
.
0
3
0
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1
4
0
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1
0
0
.
0
2
L
i
s
t
e
n
2
0
.
0
6
0
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1
5
2
0
.
1
6
0
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1
5
0
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1
2
0
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1
0
0
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1
2
2
0
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1
5
0
.
0
9
2
0
.
0
7
J
o
b
2
0
.
1
7
2
0
.
3
3
*
*
*
0
.
0
4
0
.
0
0
0
.
1
8
0
.
0
1
0
.
1
6
2
0
.
0
6
0
.
1
4
0
.
2
6
*
*
H
r
s
0
.
0
7
2
0
.
2
7
*
*
2
0
.
0
1
2
0
.
2
5
*
*
0
.
3
1
*
*
*
2
0
.
2
3
*
0
.
1
2
0
.
0
3
0
.
0
7
2
0
.
3
3
*
*
*
L
o
a
d
0
.
1
1
0
.
0
5
0
.
0
2
0
.
1
0
0
.
0
3
0
.
2
3
*
0
.
0
5
2
0
.
0
5
0
.
2
7
*
*
2
0
.
3
8
*
*
*
P
a
n
e
l
B
:
P
a
r
t
i
a
l
c
o
r
r
e
l
a
t
i
o
n
o
f
g
r
a
d
e
w
i
t
h
g
r
a
d
e
3
2
2
c
o
n
t
r
o
l
l
i
n
g
f
o
r
g
p
a
c
G
r
a
d
e
G
r
a
d
e
3
2
2
G
r
a
d
e
0
.
3
6
*
*
*
G
r
a
d
e
3
2
2
0
.
3
2
*
*
*
P
a
n
e
l
C
:
P
a
r
t
i
a
l
c
o
r
r
e
l
a
t
i
o
n
o
f
g
r
a
d
e
w
i
t
h
g
p
a
c
c
o
n
t
r
o
l
l
i
n
g
f
o
r
g
r
a
d
e
3
2
2
G
r
a
d
e
G
p
a
c
G
r
a
d
e
0
.
3
2
*
*
*
G
p
a
c
0
.
2
3
*
*
N
o
t
e
s
:
*
,
*
*
,
*
*
*
i
n
d
i
c
a
t
e
s
i
g
n
i
?
c
a
n
c
e
s
a
t
0
.
1
0
,
0
.
0
5
a
n
d
0
.
0
1
l
e
v
e
l
.
a
P
e
a
r
s
o
n
c
o
r
r
e
l
a
t
i
o
n
c
o
e
f
?
c
i
e
n
t
s
a
r
e
a
b
o
v
e
t
h
e
d
i
a
g
o
n
a
l
a
n
d
S
p
e
a
r
m
a
n
c
o
r
r
e
l
a
t
i
o
n
c
o
e
f
?
c
i
e
n
t
s
a
r
e
u
n
d
e
r
t
h
e
d
i
a
g
o
n
a
l
Table III.
Correlation matrix
for grade
Student
performance
25
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
5
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
E
x
p
e
c
t
e
d
a
s
s
o
c
i
a
t
i
o
n
w
i
t
h
s
t
u
d
e
n
t
p
e
r
f
o
r
m
a
n
c
e
d
e
?
n
e
d
a
s
:
O
b
t
a
i
n
e
d
a
s
s
o
c
i
a
t
i
o
n
w
i
t
h
s
t
u
d
e
n
t
p
e
r
f
o
r
m
a
n
c
e
d
e
?
n
e
d
a
s
:
H
y
p
o
t
h
e
s
i
s
S
u
p
p
o
r
t
e
d
(
S
)
o
r
R
e
j
e
c
t
e
d
(
R
)
w
h
e
n
s
t
u
d
e
n
t
p
e
r
f
o
r
m
a
n
c
e
i
s
d
e
?
n
e
d
a
s
:
H
y
p
o
t
h
e
s
i
s
N
o
.
I
n
d
e
p
e
n
d
e
n
t
v
a
r
i
a
b
l
e
s
l
i
s
t
e
d
u
n
d
e
r
e
a
c
h
f
a
c
t
o
r
“
P
o
i
n
t
s
”
“
G
r
a
d
e
”
“
P
o
i
n
t
s
”
“
G
r
a
d
e
”
“
P
o
i
n
t
s
”
“
G
r
a
d
e
”
F
a
c
t
o
r
1
:
M
o
t
i
v
a
t
i
o
n
1
G
r
a
d
e
s
t
u
d
e
n
t
w
o
u
l
d
l
i
k
e
t
o
m
a
k
e
i
n
t
h
e
c
o
u
r
s
e
S
P
A
S
P
A
S
P
A
S
P
A
S
S
2
I
n
t
e
n
t
i
o
n
t
o
t
a
k
e
t
h
e
C
P
A
E
x
a
m
S
P
A
S
P
A
N
A
N
A
R
R
3
I
n
t
e
n
t
i
o
n
t
o
a
t
t
e
n
d
g
r
a
d
.
S
c
h
o
o
l
S
P
A
S
P
A
N
A
S
N
A
R
R
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Table IV.
Summary of results
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of hours of work per week, and number of courses taken per semester have no
associations with student performance whether it is de?ned as “points” or “grade.” The
two remaining hypotheses that are partially supported and partially rejected indicate
that self-perceived reading and listening abilities have signi?cant positive association
with student performance de?ned as “points” but have no associations with student
performance de?ned as “grade.”
The Appendix provides a further discussion of the speci?c statistical results shown
in Tables I-III.
Conclusions and recommendations
One general conclusion of the study is that motivated students earn higher grades
in advanced accounting and auditing courses than students who are not motivated.
More speci?cally, the study provides evidence that the majority of students who
responded that they would like to make high grades in these courses ended up
making high grades. The result obtained in this study, that motivated students earn
higher grades than students who are not motivated, con?rms the results obtained in
some prior studies (Pascarella and Terenzini, 1991). Probably, there are various
reasons that are motivating the students to want to make high grades. This study
looked at two possible reasons: students’ intensions to take the CPA exam and
attend graduate schools. Our results show that neither of these is a good motivating
variable for the students in our school. Intention to take the CPA exam has no
signi?cant association with student performance de?ned either as “points” or
“grade.” Furthermore, intension to attend graduate school has no signi?cant
association with student performance de?ned as “points,” and worse yet, it has a
signi?cant negative association with student performance de?ned as “grade.” The
obtained association between intension to attend graduate school and student
performance seems to be counter-intuitive since Table I shows no signi?cant
association and Tables II and III show signi?cant negative association (at the 0.01
and 0.05 levels). One possible reason for this is the fact that student performance is
de?ned as “points” in Table I and as “grade” in Tables II and III. The latter
de?nition has several drawbacks as explained earlier. One other possible reason for
the signi?cant negative association between intension to attend graduate school and
student performance de?ned as “grade” is the fact that we assumed that students
who intend to attend graduate school at a university other than ours are more
motivated and, thus, will earn higher grades than students who intend to attend
graduate school at our university. This assumption was based on the general
perception as well as our own knowledge that the other graduate schools in town
are ranked higher academically than our school. As it turned out, from an analysis
of the frequency tables of responses (which are available from the authors upon
request) our students, particularly those with low grades, apparently thought that
our undergraduate school is too dif?cult and our graduate school will be even more
dif?cult. Thus, even though many of them reported that they intend to attend
graduate school, the majority reported that they would attend at another school. For
example, of the 22 students who intended to attend graduate school at another
university (i.e., those we thought would earn the highest grades), 15 (or 68 percent)
earned the grade of C, six (or 27 percent) earned the grade of B, and only one
student (or 5 percent) earned the grade of A.
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In light of this general conclusion, we recommend that college of business faculty in
general and accounting faculty in particular should ?nd ways (whatever these may be)
to motivate students to work hard and earn high grades. We realize that some faculty
may already be doing this; thus our recommendation is for those who may not be.
Another general conclusion of the study is that, as expected, students with high
prior actual ability end up earning higher grades in advanced accounting and auditing
courses than students with low prior actual ability. Speci?cally, the study provides
strong evidence that student performance in intermediate accounting II and their
cumulative GPA are strong predictors of student performance in advanced accounting
and auditing courses. This study’s result that student performance in intermediate
accounting II is a strong predictor of student performance in more advanced
undergraduate accounting courses is in agreement with the results in some prior
studies showing that prior accounting knowledge obtained through high school
education is a strong predictor of performance in college-level accounting courses
(Eskew and Faley, 1988; Bartlett et al., 1993; Gul and Fong, 1993; Tho, 1994; Rohde and
Kavanagh, 1996), and that college-level exposure to accounting is positively related to
student performance in the ?rst MBA-level accounting course (Canlar, 1986).
Furthermore, This study’s result that GPA is a strong predictor of student performance
in advanced accounting and auditing courses con?rms the results in some prior studies
showing that GPA is a strong predictor of performance in accounting courses (Eckel
and Johnson, 1983; Hicks and Richardson, 1984; Ingram and Peterson, 1987; Eskew and
Faley, 1988; Doran et al., 1991; Jackling and Anderson, 1998).
In light of this general conclusion, we recommend that faculty encourage their
students to work hard to get high grades in all the courses they take to increase their
GPA. We further recommend that faculty who teach intermediate accounting II
encourage their students to work hard and try to do well in that course by emphasizing
that research shows that students who get high grades in that course will most likely
get high grades in advanced accounting and auditing courses.
A third general conclusion of this study is that self-perceived abilities in reading
and listening are strong predictors of student performance (de?ned as “points”) in
advanced accounting and auditing courses. More speci?cally, the study provides
evidence those students who reported that their reading and listening abilities are good
or very good earned higher grades than those who reported that their reading and
listening abilities are average or poor. Incidentally, only six students (or roughly
6 percent of the sample) reported that their reading and/or listening abilities are poor.
In light of this general conclusion, we recommend that accounting faculty encourage
their students to concentrate on improving their reading and listening skills by
informing them that research has shown that there is a strong correlation between
good reading and listening skills and student performance (de?ned as the actual points
received for the course) in advanced accounting and auditing. Again, we realize that
some faculty may already be encouraging their students to improve their reading and
listening skills; thus our recommendation is for those who may not be.
The fact that this study shows no signi?cant association between self-perceived
writing and math abilities and student performance de?ned as “points,” or between
self-perceived writing, math, reading and listening abilities and student performance
de?ned as “grade” is puzzling. One explanation for this may be that students tend to
over-estimate their abilities, and that their self-perceptions of their abilities in these
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areas are not accurate representations of their actual abilities. However, we may note
here that the result obtained in this study, showing no association between students’
mathematical ability and their performance in advanced accounting and auditing
courses, con?rms the result in at least one prior study (Gist et al., 1996) that showed
that students with strong mathematical background did not outperform students with
weaker mathematical background in accounting courses.
A fourth general conclusion of this study is that the distraction variables
(i.e. working too many hours per week, even in non-accounting related jobs, and taking
too many courses per semester) have no signi?cant negative associations with student
performance. That is, they are not distracting the students and preventing them from
earning high grades
In light of this conclusion we recommend that accounting faculty need not
encourage their students to work as few hours as possible to earn high grades. And if
the students have to work many hours anyway to support their families, accounting
faculty need not encourage those students to take as few courses per semester as
possible to earn high grades in advanced accounting and auditing courses.
Study limitations and suggestions for further research
Our study is subject to some limitations. One limitation is that our school is a public
university and, therefore, we do not know if the results will be the same for private
schools. So, one suggestion for further research is to replicate the study in a private
school. Another limitation is that our school is a commuter school and, therefore, we do
not know if the results will be the same for residential schools. Accordingly, another
suggestion for further research is to replicate the study in a residential school. A third
limitation is that our student body is highly diversi?ed and, therefore, we do not know
if the results will be the same for much less diversi?ed schools. Thus, a third
suggestion for further research is to replicate the study in a much less diversi?ed
school. A fourth limitation of this study is that about 80 percent of our students work
almost full time while going to school and, therefore, we do not know if the results will
be the same for schools where a much less percentage of the students work full time.
Therefore, a fourth suggestion for further research is to replicate the study in other
schools where a much smaller percentage of the students work full time. A ?fth
limitation of the study is that the results are based on a small sample size and, thus, are
not as robust as they could have been if the sample size were at least 20 percent larger.
Hence, a ?fth suggestion for future research is to replicate the study using a larger
sample.
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performance persist after controlling for general academic aptitude?”, Issues in Accounting
Education, Vol. 6, pp. 248-61.
Canlar, M. (1986), “College-level exposure to accounting study and its effect on student
performance in the ?rst MBA-level ?nancial accounting course”, Issues in Accounting
Education, Vol. 1, pp. 13-23.
Didia, D. and Hasnat, B. (1998), “The determinants of performance in the univeresity
introductory ?nance course”, Financial Practice and Education, Vol. 1, pp. 102-7.
Doran, B., Bouillon, M.L. and Smith, C.G. (1991), “Determinants of student performance in
accounting principles I and II”, Issues in Accounting Education, Vol. 6, pp. 74-84.
Eckel, N. and Johnson, W.A. (1983), “A model for screening and classifying potential”,
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Eskew, R.K. and Faley, R.H. (1988), “Some determinants of student performance in the ?rst
college-level ?nancial accounting course”, The Accounting Review, January, pp. 137-47.
Gist, W.E., Goedde, H. and Ward, B.H. (1996), “The in?uence of mathematical skills and other
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Gul, F.A. and Fong, S.C. (1993), “Predicting success for introductory accounting students: some
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Hicks, D.W. and Richardson, F.M. (1984), “Predicting early success in intermediate accounting:
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performance of accounting majors”, The Accounting Review, January, pp. 215-23.
Ingram, R.W., Albright, T.L. and Baldwin, A.B. (2002), Financial Accounting: ABridge to Decision
Making, Thomson South-Western, Cincinnatti, OH.
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accounting: a research note”, Accounting Education: An International Journal, Vol. 1,
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performance”, Journal of Education for Business, Vol. 5, pp. 274-80.
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?nance principles course”, Journal of Applied Finance, Fall/Winter, pp. 67-72.
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Appendix. A further discussion of the statistical results in Tables I-III
We provide below a bit more elaborate analysis of the statistical results of the study by the type
of factors associated or not associated with student performance.
Motivation factors associated with student performance
As Table I indicates, of the three motivation variables, only one, the grade the student would like
to make in the course, is signi?cantly associated (at the 0.01 level) with the student’s performance
de?ned as “points.” The remaining two motivation variables have no signi?cant associations
with the student’s performance de?ned as “points.” As Table II indicates, of the three motivation
variables, one variable, the grade the student would like to make in the course, is signi?cantly
associated (at the .01 level in both Pearson and Spearman tests) with the student’s performance
de?ned as “grade.” One other variable, whether the student intends to take the CPA exam, has no
signi?cant association with student performance. The third variable, whether the student
intends to attend graduate school, has a signi?cant negative association (at the 0.05 level in both
Pearson and Spearman tests) with the student’s performance. These results remained the same
even after we controlled for the prior actual ability factors (the grade in Intermediate Accounting
II and the cumulative GPA). In fact, as Table III indicates, the negative association between
student’s intension of attending graduate school and student performance becomes even more
signi?cant (at the 0.01 level) under Spearman’s test.
Prior actual ability factors associated with students’ performance
As Tables I and II indicate, the two variables representing prior actual ability have signi?cant
associations (at the 0.01 level) with student performance de?ned either as the grade or the
average actual points received for the course.
Current self-perceived ability factors associated with student performance
As Table I indicates, of the four self-perceived ability variables, one variable, the student’s
reading ability, is signi?cantly associated (at the 0.01 level) with the student’s performance
de?ned as “points.” One other variable, the student’s listening ability, is signi?cantly associated
(at the 0.05 level) with the student’s performance de?ned as “points.” The other two variables
have positive but not signi?cant associations with student performance. As Table II indicates,
none of the four variables representing self-perceived ability has any signi?cant association with
student performance de?ned as grade. As Table III indicates, these results remained the same
even after we controlled for the prior actual ability factors (the grade in Intermediate
Accounting II and the cumulative GPA). Thus, based only on the results shown in Table I, we can
generally state that students’ self-perceived reading and listening abilities have signi?cant
associations with their performance de?ned as the average actual points received for the course.
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Based only on the results shown in Table II, we can generally state that students’ self-perceived
writing, math, reading and listening abilities have no signi?cant associations with their
performance de?ned as the “grade” received for the course. The contradiction between the
results in Table I and those in Table II may be attributed to using two different de?nitions of
student performance, points and grade, with the latter having some drawbacks as discussed
earlier. The non-signi?cant results could also be due the possibility that students, particularly
those earning low grades, overestimated their reading, math, writing, and listening abilities.
Distraction factors associated with student performance
As Table I indicates, the variables representing distraction factors have no signi?cant negative
associations with student performance de?ned as the average actual points received for the
course. As Table II indicates, the type of job has a negative but not signi?cant association with
student performance, whereas the number of hours of work outside of school, and the course load
have positive but not signi?cant association with student performance de?ned as the grade
received for the course.
Corresponding author
Mostafa M. Maksy can be contacted at: [email protected]
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