2008 - Marketing Educators' Association

Variable Operationalization
Our variables were constructed from the grades that
students received on each of their polished and final
analyses. The writing consultant and instructor
provided detailed feedback and a score, based on a
grade point evaluation scheme. They provided an
overall writing score and an analysis score – the
maximum a student could receive on each of these
was a 4.0 translating to an A. In addition, the writing
consultant provided a breakdown of the writing score
on the following five components: argument,
evidence, format, writing rules and appendices.
Each of these components received a grade-based
score as well. The construction of the criteria is
explained in Exhibit 2. We used only the argument
and evidence components since the other
components were aimed at writing style rather than
toward developing logical thinking. In addition, we
collected information on the students’ gender, with a
binary variable, 1 if female, 0 if male; the number of
transfer hours; their earned GPA on required
university writing classes (prior to business major
admission); and on the business required writing
class (subsequent to admission to the business
major).
Sample Description
In general, we had fewer female students, 20
percent, which was representative of the population
at the Business School. Our students joined the
university with an average of 34 transfer hours and
tended to transfer from a variety of institutions, two-
and four-year colleges as well as nationally
recognized research universities. The student grade
point average (GPA) in the required university
writing class taken prior to admission as a business
major, as well as the required Business Writing
class, was 3.61 and 3.79, respectively. Although this
seemed to indicate that our students were prepared
for writing and had done well in their writing classes,
receiving grades of B+ to A-, our assessment was
that the high GPAs represented grade inflation
rather than a representation of student ability to
write. This was further confirmed by the lower
averages on the writing and analysis scores, as well
as the components of argument and evidence
received on the cases that ranged from 2.39 to 3.16,
suggesting that student writing ability was in the C to
B range. Our statistics did indicate an improvement
due to the feedback provided on the polished draft;
all final draft scores, writing, analysis, argument and
evidence, were consistently higher than the
respective polished draft scores
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Findings
We ran three sets of regressions to explore the key
influences on student writing ability. The lack of
consistent records across students and across
semesters led to samples of different sizes across
the three regressions. Our first set of regressions
explored the effect of student characteristics of
gender, transfer hours and GPA on prior writing
courses. The second set of regressions examined
the effects of student learning by regressing the
scores received on the first case analyses on the
scores received on the second case analyses. The
third set determined the value of revision and
rewriting a case analysis by comparing the polished
draft and final draft scores. We first discuss the
effects of student characteristics on writing ability
(Table 2).
TABLE 2
Effect of Student Characteristics on Writing
Scores and Analysis Scores
Dependent Variable
Independent Variables
Writing
Score
Model 1
Analysis
Score
Model 2
Gender 0.2720@ 0.4231**
(0.1365) (0.1592)
Transfer hours -0.0015 -0.0013
(0.0016) (0.0018)
GPA in required university
writing course
GPA in required business
school writing course
0.4904**
(0.1505)
0.0234
(0.2057)
0.5596**
(0.1756)
0.2504
(0.24)
F statistic 3.6327 4.7332
R-squared 0.1679 0.2082
N = 77
Standard errors in parentheses
@ p