08832323.2015.1014458
Journal of Education for Business
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
Illusion Versus Reality: An Empirical Study of
Overconfidence and Self Attribution Bias in
Business Management Students
Vinky Sharma & Moonis Shakeel
To cite this article: Vinky Sharma & Moonis Shakeel (2015) Illusion Versus Reality: An Empirical
Study of Overconfidence and Self Attribution Bias in Business Management Students, Journal
of Education for Business, 90:4, 199-207, DOI: 10.1080/08832323.2015.1014458
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Date: 11 January 2016, At: 19:17
JOURNAL OF EDUCATION FOR BUSINESS, 90: 199–207, 2015
Copyright Ó Taylor & Francis Group, LLC
ISSN: 0883-2323 print / 1940-3356 online
DOI: 10.1080/08832323.2015.1014458
Illusion Versus Reality: An Empirical Study
of Overconfidence and Self Attribution Bias
in Business Management Students
Vinky Sharma and Moonis Shakeel
Downloaded by [Universitas Maritim Raja Ali Haji] at 19:17 11 January 2016
Jaypee Institute of Information Technology, Noida, India
Students often exhibit overconfidence and self-attribution bias (SAB). The authors report the
findings of a survey of management students across gender. They found why students fail to
understand the fact that their performance was actually dismal while their belief about their
ability to perform well was high. The results imply that all students irrespective of gender
tend to be overconfident. It was also observed that a larger percentage of the female students
had a tendency to be overconfident. Existence of SAB among management students was also
observed. However, a gender-wise breakdown of the students depicted that more female
students portrayed SAB specifically when poor grades were received.
Keywords: management, overconfidence, self-attribution bias, students
The way individuals think about themselves has been an
important research topic for a long time. In that sense,
there is evidence for a variety of behaviors or behavioral outcomes when people assess their characters more
favorably. These behaviors also include overconfidence
and self-attribution bias (SAB). Overconfidence is the
tendency of people to overestimate the accuracy of their
knowledge. There is a substantial literature in psychology, which suggests that, people are apparently overconfident about their own knowledge (Keren, 1991; Yates,
1990). This behavior is particularly observed in students, where they tend to overestimate their grades. Psychologists have also long known that people, in general,
and students, in particular, tend to overestimate their
abilities. In an educational context, this tendency toward
overconfidence is exacerbated among the people who
exhibit the lowest skill in recognizing their own incompetence (Kruger & Dunning, 1999).
Philosophers and writers have long tried to raise the
awareness about the difficulty of balancing confidence
with realism, yet the consequences of unsupportable
confidence continues specifically when it comes down
to gender differences. A number of studies have documented a gender difference in overconfidence, with
Correspondence should be addressed to Vinky Sharma, Jaypee Institute
of Information Technology, Jaypee Business School, Noida, India. E-mail:
vinky.sharma@rediffmail.com
men being more overconfident than women in a wide
variety of domains related to mathematics, science, and
technology (Niederle & Vesterlund, 2007; O’Laughlin
& Brubaker, 1998; Pajares & Miller, 1994). In addition, men more often initiate unprovoked attacks and
wars than by women because men are more overconfident about their expectations of success in conflict
(Johnson et al., 2006).
Another behavior, which is depicted by people, is
SAB. It is a tendency for people to attribute successes
or good outcomes to their own abilities, while blaming
failures on circumstances beyond their control, which
can lead to increase in over confidence (Miller & Ross,
1975). One possibility that tilt attribution is the cognitive factors, suggesting that self-serving bias stems
mainly from certain tendencies in the way people process social information (Ross, 1977). In contrast,
another explanation emphasizes the role of motivation.
This explanation suggests that the self-serving bias
stems from people’s need to protect and enhance their
self-esteem or related desire to look good to others
(Greenberg, Pyszczynski, & Solomon, 1983).
In the present study we tried to investigate the presence
of overconfidence and SAB from empirical data collected
using a survey questionnaire on management students. The
paper also examines, using appropriate statistical tests, to
find out if there exists a gender difference in overconfidence
and SAB.
200
V. SHARMA AND M. SHAKEEL
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LITERATURE SURVEY
Overconfidence has been explained by variety of ways,
ranging from a tendency to favor positive above negative
evidence (Koriat, Linchtenstein, & Fischhoff, 1980) or confirmatory bias (Rabin & Schrag, 1990) to a lack of complete, immediate, and accurate feedback (Arkes, 2001).
People often appear overconfident for questions where they
possess a self-declared expertise (Heath & Tversky, 1991).
Camerer and Lovallo (1991) also found strong evidence of
overconfidence in an experimental market entry game. An
overconfident person, whose average probability judgment
exceed the proportions of items he or she answers correctly
(Yates, Lee, & Shinotsuka, 1996), tends to makes decision
based on faulty assumptions, resulting in less than optimal
decisions (Lee at al., 1995). In the same way students, in
particular, often exhibit overconfident grade expectations
and tend to overestimate the actual course grade at the completion of a course (Nowell & Alston, 2007).
Millea and Grimes (2002) reported that both expected
grades and actual grades influence students’ evaluations.
The average of student evaluations of teaching are higher
in classes where students expect higher grades, but they
found that it is “the gap between expected grade and cumulative grade point average” rather than expected grade, per
se, that is the relevant explanatory variable (Isley & Singh,
2005, p. 28). Seifert (2004) and Bandura (1993) suggested
that for achievement-oriented students, who set goals and
adjust their behavior to reach them, overconfidence may
result in allocating less time to studying than would be the
case if their grade expectations were more accurate.
Yates et al. (1992) proposed that the overconfidence
observed in most Asian countries, relative to western countries, reflects differences in the number of arguments typically recruited in those countries. Western methods of
education (i.e., constructive approach) result in the recruitment of more arguments than do Asian methods (i.e., direct
instruction approach). The more arguments he or she
recruits, the more a person is in doubt about any decision. It
is noted that students consistently overestimate the grades
they would actually receive. Falchikov and Boud (1989)
and Grimes (2002) also suggested that overconfidence may
vary systematically with student characteristics and academic discipline.
The most pervasive finding in the body of literature on
overconfidence is that individuals are overconfident across
a wide variety of tasks (Fischhoff & Slovic, 1980), response
modes (Fischhoff, Slovic, & Lichtenstien, 1977), subject
populations (Philips and Wright, 1977), and contexts (e.g.,
banking, engineering, clinical psychology). Notably, the
overconfidence bias does not vary as a function of intelligence or other personality measures, though the results
relating to expertise are maximized and mixed.
Langer and Roth (1975) argued that skill attribution is
determined early in sequence of outcomes suggesting that
overconfidence develops quickly. Brockner and Weisenfeld
(1996) used attribution theory to explain the process x outcome interaction pattern by looking at two different aspects
of the theory. The first explanation focuses on basic internal
and external causes for the process and outcome while the
second explanation focuses on behavior or motivational
aspects of attribution theory.
An early review of self-serving bias suggests that selfserving bias can be interpreted in nonmotivational, information-processing terms (Miller & Ross, 1975). In this
view of self- serving bias, individuals restrict their attention
to the information available to them so that flawed information processing leads to self-serving bias. A different view
suggests that self-serving bias can be interpreted in motivational terms such that individuals desire to think positively
of themselves so they attribute successful outcomes to
themselves and negative outcomes to others (Bradley,
1978). This view assumes that people need to protect or
enhance their feelings of personal worth, so that self-serving attributions can be made to confirm the individual’s
self-esteem.
In an attempt to reconcile the two different viewpoints,
some researchers have suggested that cognitive and motivational aspects may be operating concurrently. Pyszcynski,
Greenberg, and LaPrelle (1985), for example, argued that
an extensive information search that occurs after a failure
experience may be a reaction to self-threat, and motivates
the individual to find information consistent with a selfserving attribution. The individual would only engage in
the extensive information search, however, if he or she
expected to confirm a self-serving conclusion. In this situation, elements of both motivational and information-processing theory are used to account for self-serving bias.
A field experiment conducted by Taylor and Reiss
(1989) concluded that self-serving bias may not occur in
natural settings, and the authors suggested that previous
studies (particularly laboratory experiments) may not generalize to field settings as expected. In contrast, however,
most reviews on self-serving bias have concluded that selfserving bias does exist albeit with certain caveats.
Problem Statement(s)
Given the significance of overconfidence and SAB among
students, in the present study we attempted an empirical
examination of the presence of the same among management students by conducting a comparative analysis on
gender. The objectives of the study were (a) to find out the
presence of overconfidence among management students
across gender; and (b) to explore the existence of SAB
among management students across gender.
Hypotheses
Study hypotheses follow:
ILLUSION VERSUS REALITY
Hypothesis 1 (H1): To test the differences in actual and
expected frequencies on the variable ability to understand MBA courses (for overall sample; and based on
gender):
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H0 (Overall Sample): Actual frequency (ability to understand)
would be equal to expected frequency (ability to
understand)
H0 (Gender D Male): Actual frequency (ability to understand)
would be equal to expected frequency (ability to
understand)
H0 (Gender D Female): Actual frequency (ability to understand) would be equal to expected frequency (ability to
understand)
H2: To test the presence of differences on ability to understand, grade perception, and actual grade across
gender:
H0: Male perception (ability to understand) would be
equal to female perception (ability to understand)
H0: Male perception (grade perception) would be equal to
female perception (grade perception)
H0: Male perception (actual grade) would be equal to
female perception (actual grade)
Significance of the Study
It would be worthwhile to know if a gender difference in
overconfidence exists within the management students.
Such a gender difference could have far-reaching consequences; among other things, it could explain why students
fail to understand the fact that their performance was actually dismal while their belief about their ability to perform
well was actually high. Overconfidence may lead to discouragement among such students; hence, it becomes
imperative for the institutions to have periodic counseling
sessions for the students in order to make them understand
the differences in their performances and how to recover
from the same. This would help them prevent from entering
into SAB and make them understand the difference
between illusion and reality.
RESEARCH PHILOSOPHY
This research problem required an intense research process
that used both interpretivist (qualitative) and positivist
(quantitative) approaches to research. Both quantitative and
qualitative methods were needed to provide the information
required for sound and effective analysis. Each approach
can inform the other with a study of an issue following a
circular course through a qualitative-quantitative or quantitative-qualitative sequence. In this sense the research
201
process was both inductive (bottom-up) and deductive (topdown) in nature.
In the first phase of the study, inductive approach was
used to describe and explain the research problem. To do
this, observations were collected and patterns were identified to formulate the hypothesis. Once this was done, the
second phase of the study used the deductive approach,
wherein the hypotheses were tested using the collected
observations. The empirical results obtained in the second
phase were unexpected and hard to explain. Therefore, we
had to resort to inductive approach to substantiate the findings from other researches (Burns & Burns, 2008).
Questionnaire Design
Primary data were collected from postgraduate management
students with the help of a structured questionnaire, which
contained three questions, wherein question 1 was designed
to capture overconfidence and question 2 for capturing SAB.
Question 3 was incorporated to validate their claims.
The first question was regarding how they rate themselves
on their ability to understand management courses. The
responses were taken using a 5-point Likert-type scale ranging from 1 (highly able) to 5 (highly unable). The second
question was about their grade perception (good or bad).
This particular question was divided into two parts: if the
student thinks that the grades that he or she has scored are
good then, they would fill part (a) or else part (b). The third
question was about their actual grade earned (or cumulative
grade point average [CGPA]).
Data Collection Procedure and Processing
The questionnaire was administered to the students separately; that is, the students were asked to give the response
to the first question and the responses were collected. Then
the second question was provided and the responses were
collected. Finally, the third question was given to get the
responses. This was intentionally done to avoid biased
responses mainly because response to one question could
have influenced the response to the next question, and we
did not want the students to know what the next question
was. All the questions were coded with the same number
and it was ensured that the same questionnaire goes to the
same student.
Before giving the response to the first question, the
respondent was asked to check the box against male or
female. In order to make CGPA comparable on Likert-type
scale, the CGPA was categorized from 1 (highest existing
grade [i.e., 8.1–10]) to 4 (lowest existing grade [i.e., < 4]).
The data were collected over a period of two years (2012
and 2013; i.e., for two different master of business administration batches). Thus, the sample size was 320 management students. Of the total number of students surveyed
202
V. SHARMA AND M. SHAKEEL
TABLE 1
Difference in Ability Perception
h2
df
p
289.531
137.852
153.351
4
4
4
.000
.000
.000
Ability to understand
Ability to understand (overall)
Ability to understand (male)
Ability to understand (female)
TABLE 3
Ability to Understand
TABLE 2
Gender Differences Across Questions
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Item
Ability to understand
Grade perception
Actual grade
Mann-Whitney U
Wilcoxon W
Z
p
12358.000
11590.000
9558.000
21538.000
20770.000
18738.000
¡0.173
¡1.269
¡3.588
.862
.205
.000
over the period of two years, 58% (n D 185) were female
respondents and 42% (n D 135) were male respondents.
Ability
Valid highly able
Moderately able
Neither able nor unable
Moderately unable
Highly unable
Total
n
%
Valid %
Cumulative %
115
156
37
4
8
320
35.9
48.8
11.6
1.2
2.5
100.0
35.9
48.8
11.6
1.2
2.5
100.0
35.9
84.7
96.2
97.5
100.0
observation by conducting cross-frequency tables to substantiate the findings.
The data used for the study are multidimensional
(nominal), therefore it was apt to use chi-square statistic
to test whether the variables are independent of each
other. Further, the Mann-Whitney test was applied to
conduct the independent samples test to confirm whether
the significant difference exist on a particular variable
based on gender.
Statistical Techniques
Our research was inductive, as it starts with analysis followed by specific observations and descriptions that produced explanation of the results generated. Therefore, this
research was qualitative in nature as it developed a picture
of what is occurring, generating tentative conjectures and
determining the feasibility and sense of direction for more
rigorous follow-up. Given this background, we have used
nonparametric tests (quantitative approach) such as chisquare and Mann-Whitney and then dived deep for specific
FINDINGS
To illustrate the existence of difference in overconfidence among the management students in general, and
across gender, we conducted a chi-square analysis. We
used it here to determine whether there was equal number of students within the five categories of ability perception by testing the differences between the observed
and expected frequencies. Previous research has
TABLE 4
Gender £ Ability to Understand Cross-Tabulation
Ability to understand
Gender
Count
Expected count
% within gender
% within ability to understand
% of total
Male
Count
Expected count
% within gender
% within ability to understand
% of total
Total
Count
Expected count
% within gender
% within ability to understand
% of total
Highly able
Moderately able
Neither able nor unable
Moderately unable
Highly unable
Total
68
66.5
36.8%
59.1%
21.2%
86
90.2
46.5%
55.1%
26.9%
21
21.4
11.4%
56.8%
6.6%
3
2.3
1.6%
75.0%
0.9%
7
4.6
3.8%
87.5%
2.2%
185
185.0
100.0%
57.8%
57.8%
47
48.5
34.8%
40.9%
14.7%
70
65.8
51.9%
44.9%
21.9%
16
15.6
11.9%
43.2%
5.0%
1
1.7
0.7%
25.0%
0.3%
1
3.4
0.7%
12.5%
0.3%
135
135.0
100.0%
42.2%
42.2%
115
115.0
35.9%
100.0%
35.9%
156
156.0
48.8%
100.0%
48.8%
37
37.0
11.6%
100.0%
11.6%
4
4.0
1.2%
100.0%
1.2%
8
8.0
2.5%
100.0%
2.5%
320
320.0
100.0%
100.0%
100.0%
203
ILLUSION VERSUS REALITY
TABLE 5
Grade Range £ Ability to Understand £ Grade Perception Cross-Tabulation
Ability to understand
Grade perception
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Bad grade range
8.1–10
6.1–8
4.1–6
Total
Good grade range
6.1–8
4.1–6
Total
Highly able
Moderately able
Neither able nor unable
Moderately unable
Highly unable
Total
2
10
38
50
4
30
45
79
0
2
17
19
0
1
2
3
0
0
4
4
6
43
106
155
7
58
65
14
63
77
1
17
18
0
1
1
0
4
4
22
143
165
suggested that there exists a difference in overconfidence among male and female students and they often
exhibit overconfident grade expectations that tend to
overestimate the actual course grade at the completion
of the course (Nowell & Alston, 2007). Our chi-square
result suggests an expected frequency of 64 in each of
the categories in the ability question; however, given
the actual frequencies the test suggest that there is a significant difference between them (x2 p D .000). The
same test was then applied on ability perception based
on gender to know further whether these differences
also present in male and female students separately. The
result shows that there is also a significant difference
(x2 p D .000) for male and female students, respectively
(see Table 1).
As mentioned in research methodology, Mann-Whitney test was then applied to substantiate the above
results. The test depicts that there is no significant difference (p D .862) on their perception about their ability
to understand the management courses (see Table 2).
This reflects that both the genders are equally overconfident when it comes to their ability. These results are in
line with previous studies (Clayson, 2005; Kennedy,
Lawton, & Plummee, 2002).
At the microlevel, we also investigated the first objective
of the study, that is, overconfidence among management
students. Simple frequency tables were used for the first
variable on the ability to understand management courses.
Of the total students, a majority of the students considered
themselves to be moderately to highly able. If we consider
only those students who opted for highly able, then they are
around 36% (see Table 3); of this, 59% (68 of 115) were
women and 41% (47 of 115) were men (see Table 3). This
depicts that higher number of female students displayed
overconfidence than male students.
When we link this perception of the students about themselves on ability to understand management courses with
their perception about grades and their actual grades, then
we can decipher whether they have a tendency to overestimate their ability or not. As shown in Table 5, exactly half
of the students have actually scored bad grades but they still
consider their grades good, which displays their
TABLE 6
Ability to Understand £ Grade Range Cross-Tabulation
Grade range
Item
Ability to understand
Highly able
Count
% within ability to understand
% within grade range
% of total
Moderately able
Count
% within ability to understand
% within grade range
% of total
Neither able nor unable
Count
% within ability to understand
% within grade range
% of total
;Moderately unable
Count
% within ability to understand
% within grade range
% of total
Highly unable
Count
% within ability to understand
% within grade range
% of total
Total
Count
% within ability to understand
% within grade range
% of total
8.1–10
6.1–8
4.1–6
Total
2
1.7%
33.3%
0.6%
17
14.8%
26.2%
5.3%
96
83.5%
38.6%
30.0%
115
100.0%
35.9%
35.9%
4
2.6%
66.7%
1.2%
44
28.2%
67.7%
13.8%
108
69.2%
43.4%
33.8%
156
100.0%
48.8%
48.8%
0
0%
0%
0%
3
8.1%
4.6%
0.9%
34
91.9%
13.7%
10.6%
37
100.0%
11.6%
11.6%
0
0%
0%
0%
1
25.0%
1.5%
0.3%
3
75.0%
1.2%
0.9%
4
100.0%
1.2%
1.2%
0
0%
0%
0%
0
0%
0%
0%
8
100.0%
3.2%
2.5%
8
100.0%
2.5%
2.5%
6
1.9%
100.0%
1.9%
65
20.3%
100.0%
20.3%
249
77.8%
100.0%
77.8%
320
100.0%
100.0%
100.0%
204
V. SHARMA AND M. SHAKEEL
TABLE 7
Gender £ Ability to Understand £ Grade Range Cross-Tabulation
Ability to understand
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Grade range
4.1–6
Gender
Female
Count
Expected count
% within gender
% within ability to understand
% of total
Male
Count
Expected count
% within gender
% within ability to understand
% of total
Total
Count
Expected count
% within gender
% within ability to understand
% of total
6.1–8
Gender
Female
Count
Expected count
% within gender
% within ability to understand
% of total
Male
Count
Expected count
% within gender
% within ability to understand
% of total
Total
Count
Expected count
% within gender
% within ability to understand
% of total
8.1–10
Gender
Female
Count
Expected count
% within gender
% within ability to understand
% of total
Male
Count
Expected count
% within gender
% within ability to understand
% of total
Total
Count
Expected count
% within gender
% within ability to understand
% of total
Highly able
Moderately able
Neither able nor unable
Moderately unable
Highly unable
Total
58
60.1
37.2%
60.4%
23.3%
70
67.7
44.9%
64.8%
28.1%
18
21.3
11.5%
52.9%
7.2%
3
1.9
1.9%
100.0%
1.2%
7
5.0
4.5%
87.5%
2.8%
156
156.0
100.0%
62.7%
62.7%
38
35.9
40.9%
39.6%
15.3%
38
40.3
40.9%
35.2%
15.3%
16
12.7
17.2%
47.1%
6.4%
0
1.1
0%
0%
0%
1
3.0
1.1%
12.5%
0.4%
93
93.0
100.0%
37.3%
37.3%
96
96.0
38.6%
100.0%
38.6%
108
108.0
43.4%
100.0%
43.4%
34
34.0
13.7%
100.0%
13.7%
3
3.0
1.2%
100.0%
1.2%
8
8.0
3.2%
100.0%
3.2%
249
249.0
100.0%
100.0%
100.0%
9
7.1
33.3%
52.9%
13.8%
15
18.3
55.6%
34.1%
23.1%
3
1.2
11.1%
100.0%
4.6%
0
.4
0%
0%
0%
27
27.0
100.0%
41.5%
41.5%
8
9.9
21.1%
47.1%
12.3%
29
25.7
76.3%
65.9%
44.6%
0
1.8
0%
0%
0%
1
.6
2.6%
100.0%
1.5%
38
38.0
100.0%
58.5%
58.5%
17
17.0
26.2%
100.0%
26.2%
44
44.0
67.7%
100.0%
67.7%
3
3.0
4.6%
100.0%
4.6%
1
1.0
1.5%
100.0%
1.5%
65
65.0
100.0%
100.0%
100.0%
1
.7
50.0%
50.0%
16.7%
1
1.3
50.0%
25.0%
16.7%
2
2.0
100.0%
33.3%
33.3%
1
1.3
25.0%
50.0%
16.7%
3
2.7
75.0%
75.0%
50.0%
4
4.0
100.0%
66.7%
66.7%
2
2.0
33.3%
100.0%
33.3%
4
4.0
66.7%
100.0%
66.7%
6
6.0
100.0%
100.0%
100.0%
205
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ILLUSION VERSUS REALITY
overconfidence. Splitting this result based on gender depicts
that, of 58 students 41% of the male students had a tendency to overestimate their ability, which is less than that
of female students, 59% (see Table 4). One reason for this
could be that young men often grow up expecting to work
and take over the responsibility of their family while
females are still less likely to grow up believing they must
support their family (Duffy & Atwater, 2011). Therefore,
the conjecture that could be made is that even though the
marks of more female students were bad they considered
them good and was otherwise for male students. On the
other hand, there were 33% of the students who had actually earned bad grades and considered their grades bad.
However, they perceived themselves to be highly able. This
displays their psychological thought process that it was not
the lack of ability due to which they got bad grades; rather
there were other factors that might have been the reasons
for their grades such as those mentioned in question 2 of
the questionnaire (Appendix; see Table 5).
Another analysis was conducted on ability to understand and actual grade scored by the students. It was
found that majority of the total population, irrespective
of gender, considered themselves to be moderately to
highly able on understanding management courses.
However, when the actual grades were seen, 78% of the
students have scored the lowest grade (see Table 6).
When the same analysis was conducted gender wise,
84% (156 of 185) of the female students were found to
be lying in the lowest grade category. Interestingly, of
these 156 female students, 82% rated themselves to be
highly to moderately able. Similarly, 68% (93 of 135)
of the male students were found to be lying in the lowest grade category. Of these 93 male students, 81%
rated themselves to be highly to moderately able (see
Table 7).
These results were substantiated by the Mann-Whitney
test. It was found that there was no significant difference in
grade perception, and ability perception; however, ironically there was a significant difference in the actual grades
scored by male and female students. Thus, it can be inferred
that female students are more over-confident compared to
the male students.
To investigate the second objective of the study that is,
SAB among management students, cross-tabulation was
first conducted on actual bad grade scored. It was found
that in 50% of the total students, SAB was missing. Comparing male students with the female students, 35% of the
male students depicted SAB, while 63% of the females
showed SAB (see Table 8).
Surprisingly when the same analysis was conducted on
actual good grade scored, again among 50% of the total students, SAB was found. Comparing male students with
female students almost equal percentages of the male and
female students displayed SAB (see Table 9).
CONCLUSION AND RECOMMENDATIONS
The results imply that majority of the students considered
themselves to be highly able. Almost equal numbers of
male and female students thought the same. However, more
of the male students seemed to be modest relative to the
female students. A negligible number of students underrated themselves. This can further be supported by comparing their ability with their grade perception or by
comparing their ability perception with their actual grades.
The analysis depicts that almost half of the sample size
considered their grades to be bad. Wherein from this it can
be deduced that there are two observations; first, that these
students have actually scored good grades but this may not
TABLE 8
Gender £ Bad Grade Cross-Tabulation
Bad grade
Gender
Male
Count
% within gender
% within bad grade
% of total
Female
Count
% within gender
% within bad grade
% of total
Total
Count
% within gender
% within bad grade
% of total
Teacher taught badly
Difficult course
I did not work hard
Not attentive
Tough paper
Strict checking
Total
6
8.5%
28.6%
3.9%
12
16.9%
38.7%
7.8%
33
46.5%
56.9%
21.4%
13
18.3%
68.4%
8.4%
6
8.5%
37.5%
3.9%
1
1.4%
11.1%
0.6%
71
100.0%
46.1%
46.1%
15
18.1%
71.4%
9.7%
19
22.9%
61.3%
12.3%
25
30.1%
43.1%
16.2%
6
7.2%
31.6%
3.9%
10
12.0%
62.5%
6.5%
8
9.6%
88.9%
5.2%
83
100.0%
53.9%
53.9%
21
13.6%
100.0%
13.6%
31
20.1%
100.0%
20.1%
58
37.7%
100.0%
37.7%
19
12.3%
100.0%
12.3%
16
10.4%
100.0%
10.4%
9
5.8%
100.0%
5.8%
154
100.0%
100.0%
100.0%
206
V. SHARMA AND M. SHAKEEL
TABLE 9
Gender £ Good Grade Cross-Tabulation
Good grade
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Gender
Male
Count
% within gender
% within good grade
% of total
Female
Count
% within gender
% within good grade
% of total
Total
Count
% within gender
% within good grade
% of total
Teacher taught well
Easy course
I work hard
Not attentive
Easy paper
Lenient checking
Total
16
25.0%
39.0%
9.7%
11
17.2%
35.5%
6.7%
22
34.4%
41.5%
13.3%
11
17.2%
37.9%
6.7%
4
6.2%
44.4%
2.4%
0
0%
0%
0%
64
100.0%
38.8%
38.8%
25
24.8%
61.0%
15.2%
20
19.8%
64.5%
12.1%
31
30.7%
58.5%
18.8%
18
17.8%
62.1%
10.9%
5
5.0%
55.6%
3.0%
2
2.0%
100.0%
1.2%
101
100.0%
61.2%
61.2%
41
24.8%
100.0%
24.8%
31
18.8%
100.0%
18.8%
53
32.1%
100.0%
32.1%
29
17.6%
100.0%
17.6%
9
5.5%
100.0%
5.5%
2
1.2%
100.0%
1.2%
165
100.0%
100.0%
100.0%
correspond to their actual ability to understand management
courses. Second, that these students have actually scored
bad grades, which depicts that they are overestimating the
accuracy of their knowledge (i.e., overconfidence). It is
also observed that more of the female students have a tendency of being overconfident.
While comparing ability to understand management
courses with the actual grades of the students, it was again
substantiated that management students are overconfident.
As a majority of the students who rated their ability to
understand was high, a major chunk of the students actually
scored the lowest grades, ranging between 4.1 and 6.
It was also observed that there exists a SAB among management students. However, gender-wise breakup of the
students those who displayed SAB depicted that more
female (almost double) students portrayed SAB specifically
when bad grades were scored. On the other hand, when
good grades were scored by female students, this percentage declined to the percentage of male students, which
increased in this case. Therefore, it can be said that in case
of female students when something bad happens to them
SAB becomes more prominent.
This study was an attempt to find out the presence of
overconfidence and SABs among management students.
The results indicate the presence of both. Although, it
gets different when gender-wise comparisons were
made.
The results of this study could have significant implications, given an insight into the fact that most of the management students are still lacking in certain skills, which they
do not realize and hence are not employable. Therefore,
there is a need for students and institutions to understand
the existence of overconfidence and SAB and to take measures such as to come up with the counseling sessions and/or
foundation courses before the students actually begin their
classes formally. Students indeed can be trained to perform
better.
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APPENDIX: QUESTIONNAIRE
Gender: Male: __________
Female: __________
Q1: How would you rate yourself on the ability to understand Management courses? (Please tick your response)
Highly able: __________
Moderately able: __________
Neither able nor unable: _____ Moderately unable: ______
Highly unable: __________
Q2(a): If you got bad grades/marks then the reason that you
attribute to this is: - (Please tick only one option from the
followings):
1. Teacher/s taught badly.
2. The course/s was difficult.
3. I did not work hard.
4. I was not attentive in the class.
5. The paper was tough.
6. Paper checking was strict.
(OR)
Q2(b): If you got good grades/marks then the reason that
you attribute to this is (Please tick only one option from the
followings):
1. Teacher/s taught very well.
2. The course/s was easy.
3. I worked hard.
4. I was attentive in the class.
5. The paper was easy.
6. Paper checking was lenient.
Please write down your commutative grades (CGPA) up to
the last semester you passed.
Grades: __________
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
Illusion Versus Reality: An Empirical Study of
Overconfidence and Self Attribution Bias in
Business Management Students
Vinky Sharma & Moonis Shakeel
To cite this article: Vinky Sharma & Moonis Shakeel (2015) Illusion Versus Reality: An Empirical
Study of Overconfidence and Self Attribution Bias in Business Management Students, Journal
of Education for Business, 90:4, 199-207, DOI: 10.1080/08832323.2015.1014458
To link to this article: http://dx.doi.org/10.1080/08832323.2015.1014458
Published online: 16 Mar 2015.
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Date: 11 January 2016, At: 19:17
JOURNAL OF EDUCATION FOR BUSINESS, 90: 199–207, 2015
Copyright Ó Taylor & Francis Group, LLC
ISSN: 0883-2323 print / 1940-3356 online
DOI: 10.1080/08832323.2015.1014458
Illusion Versus Reality: An Empirical Study
of Overconfidence and Self Attribution Bias
in Business Management Students
Vinky Sharma and Moonis Shakeel
Downloaded by [Universitas Maritim Raja Ali Haji] at 19:17 11 January 2016
Jaypee Institute of Information Technology, Noida, India
Students often exhibit overconfidence and self-attribution bias (SAB). The authors report the
findings of a survey of management students across gender. They found why students fail to
understand the fact that their performance was actually dismal while their belief about their
ability to perform well was high. The results imply that all students irrespective of gender
tend to be overconfident. It was also observed that a larger percentage of the female students
had a tendency to be overconfident. Existence of SAB among management students was also
observed. However, a gender-wise breakdown of the students depicted that more female
students portrayed SAB specifically when poor grades were received.
Keywords: management, overconfidence, self-attribution bias, students
The way individuals think about themselves has been an
important research topic for a long time. In that sense,
there is evidence for a variety of behaviors or behavioral outcomes when people assess their characters more
favorably. These behaviors also include overconfidence
and self-attribution bias (SAB). Overconfidence is the
tendency of people to overestimate the accuracy of their
knowledge. There is a substantial literature in psychology, which suggests that, people are apparently overconfident about their own knowledge (Keren, 1991; Yates,
1990). This behavior is particularly observed in students, where they tend to overestimate their grades. Psychologists have also long known that people, in general,
and students, in particular, tend to overestimate their
abilities. In an educational context, this tendency toward
overconfidence is exacerbated among the people who
exhibit the lowest skill in recognizing their own incompetence (Kruger & Dunning, 1999).
Philosophers and writers have long tried to raise the
awareness about the difficulty of balancing confidence
with realism, yet the consequences of unsupportable
confidence continues specifically when it comes down
to gender differences. A number of studies have documented a gender difference in overconfidence, with
Correspondence should be addressed to Vinky Sharma, Jaypee Institute
of Information Technology, Jaypee Business School, Noida, India. E-mail:
vinky.sharma@rediffmail.com
men being more overconfident than women in a wide
variety of domains related to mathematics, science, and
technology (Niederle & Vesterlund, 2007; O’Laughlin
& Brubaker, 1998; Pajares & Miller, 1994). In addition, men more often initiate unprovoked attacks and
wars than by women because men are more overconfident about their expectations of success in conflict
(Johnson et al., 2006).
Another behavior, which is depicted by people, is
SAB. It is a tendency for people to attribute successes
or good outcomes to their own abilities, while blaming
failures on circumstances beyond their control, which
can lead to increase in over confidence (Miller & Ross,
1975). One possibility that tilt attribution is the cognitive factors, suggesting that self-serving bias stems
mainly from certain tendencies in the way people process social information (Ross, 1977). In contrast,
another explanation emphasizes the role of motivation.
This explanation suggests that the self-serving bias
stems from people’s need to protect and enhance their
self-esteem or related desire to look good to others
(Greenberg, Pyszczynski, & Solomon, 1983).
In the present study we tried to investigate the presence
of overconfidence and SAB from empirical data collected
using a survey questionnaire on management students. The
paper also examines, using appropriate statistical tests, to
find out if there exists a gender difference in overconfidence
and SAB.
200
V. SHARMA AND M. SHAKEEL
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LITERATURE SURVEY
Overconfidence has been explained by variety of ways,
ranging from a tendency to favor positive above negative
evidence (Koriat, Linchtenstein, & Fischhoff, 1980) or confirmatory bias (Rabin & Schrag, 1990) to a lack of complete, immediate, and accurate feedback (Arkes, 2001).
People often appear overconfident for questions where they
possess a self-declared expertise (Heath & Tversky, 1991).
Camerer and Lovallo (1991) also found strong evidence of
overconfidence in an experimental market entry game. An
overconfident person, whose average probability judgment
exceed the proportions of items he or she answers correctly
(Yates, Lee, & Shinotsuka, 1996), tends to makes decision
based on faulty assumptions, resulting in less than optimal
decisions (Lee at al., 1995). In the same way students, in
particular, often exhibit overconfident grade expectations
and tend to overestimate the actual course grade at the completion of a course (Nowell & Alston, 2007).
Millea and Grimes (2002) reported that both expected
grades and actual grades influence students’ evaluations.
The average of student evaluations of teaching are higher
in classes where students expect higher grades, but they
found that it is “the gap between expected grade and cumulative grade point average” rather than expected grade, per
se, that is the relevant explanatory variable (Isley & Singh,
2005, p. 28). Seifert (2004) and Bandura (1993) suggested
that for achievement-oriented students, who set goals and
adjust their behavior to reach them, overconfidence may
result in allocating less time to studying than would be the
case if their grade expectations were more accurate.
Yates et al. (1992) proposed that the overconfidence
observed in most Asian countries, relative to western countries, reflects differences in the number of arguments typically recruited in those countries. Western methods of
education (i.e., constructive approach) result in the recruitment of more arguments than do Asian methods (i.e., direct
instruction approach). The more arguments he or she
recruits, the more a person is in doubt about any decision. It
is noted that students consistently overestimate the grades
they would actually receive. Falchikov and Boud (1989)
and Grimes (2002) also suggested that overconfidence may
vary systematically with student characteristics and academic discipline.
The most pervasive finding in the body of literature on
overconfidence is that individuals are overconfident across
a wide variety of tasks (Fischhoff & Slovic, 1980), response
modes (Fischhoff, Slovic, & Lichtenstien, 1977), subject
populations (Philips and Wright, 1977), and contexts (e.g.,
banking, engineering, clinical psychology). Notably, the
overconfidence bias does not vary as a function of intelligence or other personality measures, though the results
relating to expertise are maximized and mixed.
Langer and Roth (1975) argued that skill attribution is
determined early in sequence of outcomes suggesting that
overconfidence develops quickly. Brockner and Weisenfeld
(1996) used attribution theory to explain the process x outcome interaction pattern by looking at two different aspects
of the theory. The first explanation focuses on basic internal
and external causes for the process and outcome while the
second explanation focuses on behavior or motivational
aspects of attribution theory.
An early review of self-serving bias suggests that selfserving bias can be interpreted in nonmotivational, information-processing terms (Miller & Ross, 1975). In this
view of self- serving bias, individuals restrict their attention
to the information available to them so that flawed information processing leads to self-serving bias. A different view
suggests that self-serving bias can be interpreted in motivational terms such that individuals desire to think positively
of themselves so they attribute successful outcomes to
themselves and negative outcomes to others (Bradley,
1978). This view assumes that people need to protect or
enhance their feelings of personal worth, so that self-serving attributions can be made to confirm the individual’s
self-esteem.
In an attempt to reconcile the two different viewpoints,
some researchers have suggested that cognitive and motivational aspects may be operating concurrently. Pyszcynski,
Greenberg, and LaPrelle (1985), for example, argued that
an extensive information search that occurs after a failure
experience may be a reaction to self-threat, and motivates
the individual to find information consistent with a selfserving attribution. The individual would only engage in
the extensive information search, however, if he or she
expected to confirm a self-serving conclusion. In this situation, elements of both motivational and information-processing theory are used to account for self-serving bias.
A field experiment conducted by Taylor and Reiss
(1989) concluded that self-serving bias may not occur in
natural settings, and the authors suggested that previous
studies (particularly laboratory experiments) may not generalize to field settings as expected. In contrast, however,
most reviews on self-serving bias have concluded that selfserving bias does exist albeit with certain caveats.
Problem Statement(s)
Given the significance of overconfidence and SAB among
students, in the present study we attempted an empirical
examination of the presence of the same among management students by conducting a comparative analysis on
gender. The objectives of the study were (a) to find out the
presence of overconfidence among management students
across gender; and (b) to explore the existence of SAB
among management students across gender.
Hypotheses
Study hypotheses follow:
ILLUSION VERSUS REALITY
Hypothesis 1 (H1): To test the differences in actual and
expected frequencies on the variable ability to understand MBA courses (for overall sample; and based on
gender):
Downloaded by [Universitas Maritim Raja Ali Haji] at 19:17 11 January 2016
H0 (Overall Sample): Actual frequency (ability to understand)
would be equal to expected frequency (ability to
understand)
H0 (Gender D Male): Actual frequency (ability to understand)
would be equal to expected frequency (ability to
understand)
H0 (Gender D Female): Actual frequency (ability to understand) would be equal to expected frequency (ability to
understand)
H2: To test the presence of differences on ability to understand, grade perception, and actual grade across
gender:
H0: Male perception (ability to understand) would be
equal to female perception (ability to understand)
H0: Male perception (grade perception) would be equal to
female perception (grade perception)
H0: Male perception (actual grade) would be equal to
female perception (actual grade)
Significance of the Study
It would be worthwhile to know if a gender difference in
overconfidence exists within the management students.
Such a gender difference could have far-reaching consequences; among other things, it could explain why students
fail to understand the fact that their performance was actually dismal while their belief about their ability to perform
well was actually high. Overconfidence may lead to discouragement among such students; hence, it becomes
imperative for the institutions to have periodic counseling
sessions for the students in order to make them understand
the differences in their performances and how to recover
from the same. This would help them prevent from entering
into SAB and make them understand the difference
between illusion and reality.
RESEARCH PHILOSOPHY
This research problem required an intense research process
that used both interpretivist (qualitative) and positivist
(quantitative) approaches to research. Both quantitative and
qualitative methods were needed to provide the information
required for sound and effective analysis. Each approach
can inform the other with a study of an issue following a
circular course through a qualitative-quantitative or quantitative-qualitative sequence. In this sense the research
201
process was both inductive (bottom-up) and deductive (topdown) in nature.
In the first phase of the study, inductive approach was
used to describe and explain the research problem. To do
this, observations were collected and patterns were identified to formulate the hypothesis. Once this was done, the
second phase of the study used the deductive approach,
wherein the hypotheses were tested using the collected
observations. The empirical results obtained in the second
phase were unexpected and hard to explain. Therefore, we
had to resort to inductive approach to substantiate the findings from other researches (Burns & Burns, 2008).
Questionnaire Design
Primary data were collected from postgraduate management
students with the help of a structured questionnaire, which
contained three questions, wherein question 1 was designed
to capture overconfidence and question 2 for capturing SAB.
Question 3 was incorporated to validate their claims.
The first question was regarding how they rate themselves
on their ability to understand management courses. The
responses were taken using a 5-point Likert-type scale ranging from 1 (highly able) to 5 (highly unable). The second
question was about their grade perception (good or bad).
This particular question was divided into two parts: if the
student thinks that the grades that he or she has scored are
good then, they would fill part (a) or else part (b). The third
question was about their actual grade earned (or cumulative
grade point average [CGPA]).
Data Collection Procedure and Processing
The questionnaire was administered to the students separately; that is, the students were asked to give the response
to the first question and the responses were collected. Then
the second question was provided and the responses were
collected. Finally, the third question was given to get the
responses. This was intentionally done to avoid biased
responses mainly because response to one question could
have influenced the response to the next question, and we
did not want the students to know what the next question
was. All the questions were coded with the same number
and it was ensured that the same questionnaire goes to the
same student.
Before giving the response to the first question, the
respondent was asked to check the box against male or
female. In order to make CGPA comparable on Likert-type
scale, the CGPA was categorized from 1 (highest existing
grade [i.e., 8.1–10]) to 4 (lowest existing grade [i.e., < 4]).
The data were collected over a period of two years (2012
and 2013; i.e., for two different master of business administration batches). Thus, the sample size was 320 management students. Of the total number of students surveyed
202
V. SHARMA AND M. SHAKEEL
TABLE 1
Difference in Ability Perception
h2
df
p
289.531
137.852
153.351
4
4
4
.000
.000
.000
Ability to understand
Ability to understand (overall)
Ability to understand (male)
Ability to understand (female)
TABLE 3
Ability to Understand
TABLE 2
Gender Differences Across Questions
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Item
Ability to understand
Grade perception
Actual grade
Mann-Whitney U
Wilcoxon W
Z
p
12358.000
11590.000
9558.000
21538.000
20770.000
18738.000
¡0.173
¡1.269
¡3.588
.862
.205
.000
over the period of two years, 58% (n D 185) were female
respondents and 42% (n D 135) were male respondents.
Ability
Valid highly able
Moderately able
Neither able nor unable
Moderately unable
Highly unable
Total
n
%
Valid %
Cumulative %
115
156
37
4
8
320
35.9
48.8
11.6
1.2
2.5
100.0
35.9
48.8
11.6
1.2
2.5
100.0
35.9
84.7
96.2
97.5
100.0
observation by conducting cross-frequency tables to substantiate the findings.
The data used for the study are multidimensional
(nominal), therefore it was apt to use chi-square statistic
to test whether the variables are independent of each
other. Further, the Mann-Whitney test was applied to
conduct the independent samples test to confirm whether
the significant difference exist on a particular variable
based on gender.
Statistical Techniques
Our research was inductive, as it starts with analysis followed by specific observations and descriptions that produced explanation of the results generated. Therefore, this
research was qualitative in nature as it developed a picture
of what is occurring, generating tentative conjectures and
determining the feasibility and sense of direction for more
rigorous follow-up. Given this background, we have used
nonparametric tests (quantitative approach) such as chisquare and Mann-Whitney and then dived deep for specific
FINDINGS
To illustrate the existence of difference in overconfidence among the management students in general, and
across gender, we conducted a chi-square analysis. We
used it here to determine whether there was equal number of students within the five categories of ability perception by testing the differences between the observed
and expected frequencies. Previous research has
TABLE 4
Gender £ Ability to Understand Cross-Tabulation
Ability to understand
Gender
Count
Expected count
% within gender
% within ability to understand
% of total
Male
Count
Expected count
% within gender
% within ability to understand
% of total
Total
Count
Expected count
% within gender
% within ability to understand
% of total
Highly able
Moderately able
Neither able nor unable
Moderately unable
Highly unable
Total
68
66.5
36.8%
59.1%
21.2%
86
90.2
46.5%
55.1%
26.9%
21
21.4
11.4%
56.8%
6.6%
3
2.3
1.6%
75.0%
0.9%
7
4.6
3.8%
87.5%
2.2%
185
185.0
100.0%
57.8%
57.8%
47
48.5
34.8%
40.9%
14.7%
70
65.8
51.9%
44.9%
21.9%
16
15.6
11.9%
43.2%
5.0%
1
1.7
0.7%
25.0%
0.3%
1
3.4
0.7%
12.5%
0.3%
135
135.0
100.0%
42.2%
42.2%
115
115.0
35.9%
100.0%
35.9%
156
156.0
48.8%
100.0%
48.8%
37
37.0
11.6%
100.0%
11.6%
4
4.0
1.2%
100.0%
1.2%
8
8.0
2.5%
100.0%
2.5%
320
320.0
100.0%
100.0%
100.0%
203
ILLUSION VERSUS REALITY
TABLE 5
Grade Range £ Ability to Understand £ Grade Perception Cross-Tabulation
Ability to understand
Grade perception
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Bad grade range
8.1–10
6.1–8
4.1–6
Total
Good grade range
6.1–8
4.1–6
Total
Highly able
Moderately able
Neither able nor unable
Moderately unable
Highly unable
Total
2
10
38
50
4
30
45
79
0
2
17
19
0
1
2
3
0
0
4
4
6
43
106
155
7
58
65
14
63
77
1
17
18
0
1
1
0
4
4
22
143
165
suggested that there exists a difference in overconfidence among male and female students and they often
exhibit overconfident grade expectations that tend to
overestimate the actual course grade at the completion
of the course (Nowell & Alston, 2007). Our chi-square
result suggests an expected frequency of 64 in each of
the categories in the ability question; however, given
the actual frequencies the test suggest that there is a significant difference between them (x2 p D .000). The
same test was then applied on ability perception based
on gender to know further whether these differences
also present in male and female students separately. The
result shows that there is also a significant difference
(x2 p D .000) for male and female students, respectively
(see Table 1).
As mentioned in research methodology, Mann-Whitney test was then applied to substantiate the above
results. The test depicts that there is no significant difference (p D .862) on their perception about their ability
to understand the management courses (see Table 2).
This reflects that both the genders are equally overconfident when it comes to their ability. These results are in
line with previous studies (Clayson, 2005; Kennedy,
Lawton, & Plummee, 2002).
At the microlevel, we also investigated the first objective
of the study, that is, overconfidence among management
students. Simple frequency tables were used for the first
variable on the ability to understand management courses.
Of the total students, a majority of the students considered
themselves to be moderately to highly able. If we consider
only those students who opted for highly able, then they are
around 36% (see Table 3); of this, 59% (68 of 115) were
women and 41% (47 of 115) were men (see Table 3). This
depicts that higher number of female students displayed
overconfidence than male students.
When we link this perception of the students about themselves on ability to understand management courses with
their perception about grades and their actual grades, then
we can decipher whether they have a tendency to overestimate their ability or not. As shown in Table 5, exactly half
of the students have actually scored bad grades but they still
consider their grades good, which displays their
TABLE 6
Ability to Understand £ Grade Range Cross-Tabulation
Grade range
Item
Ability to understand
Highly able
Count
% within ability to understand
% within grade range
% of total
Moderately able
Count
% within ability to understand
% within grade range
% of total
Neither able nor unable
Count
% within ability to understand
% within grade range
% of total
;Moderately unable
Count
% within ability to understand
% within grade range
% of total
Highly unable
Count
% within ability to understand
% within grade range
% of total
Total
Count
% within ability to understand
% within grade range
% of total
8.1–10
6.1–8
4.1–6
Total
2
1.7%
33.3%
0.6%
17
14.8%
26.2%
5.3%
96
83.5%
38.6%
30.0%
115
100.0%
35.9%
35.9%
4
2.6%
66.7%
1.2%
44
28.2%
67.7%
13.8%
108
69.2%
43.4%
33.8%
156
100.0%
48.8%
48.8%
0
0%
0%
0%
3
8.1%
4.6%
0.9%
34
91.9%
13.7%
10.6%
37
100.0%
11.6%
11.6%
0
0%
0%
0%
1
25.0%
1.5%
0.3%
3
75.0%
1.2%
0.9%
4
100.0%
1.2%
1.2%
0
0%
0%
0%
0
0%
0%
0%
8
100.0%
3.2%
2.5%
8
100.0%
2.5%
2.5%
6
1.9%
100.0%
1.9%
65
20.3%
100.0%
20.3%
249
77.8%
100.0%
77.8%
320
100.0%
100.0%
100.0%
204
V. SHARMA AND M. SHAKEEL
TABLE 7
Gender £ Ability to Understand £ Grade Range Cross-Tabulation
Ability to understand
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Grade range
4.1–6
Gender
Female
Count
Expected count
% within gender
% within ability to understand
% of total
Male
Count
Expected count
% within gender
% within ability to understand
% of total
Total
Count
Expected count
% within gender
% within ability to understand
% of total
6.1–8
Gender
Female
Count
Expected count
% within gender
% within ability to understand
% of total
Male
Count
Expected count
% within gender
% within ability to understand
% of total
Total
Count
Expected count
% within gender
% within ability to understand
% of total
8.1–10
Gender
Female
Count
Expected count
% within gender
% within ability to understand
% of total
Male
Count
Expected count
% within gender
% within ability to understand
% of total
Total
Count
Expected count
% within gender
% within ability to understand
% of total
Highly able
Moderately able
Neither able nor unable
Moderately unable
Highly unable
Total
58
60.1
37.2%
60.4%
23.3%
70
67.7
44.9%
64.8%
28.1%
18
21.3
11.5%
52.9%
7.2%
3
1.9
1.9%
100.0%
1.2%
7
5.0
4.5%
87.5%
2.8%
156
156.0
100.0%
62.7%
62.7%
38
35.9
40.9%
39.6%
15.3%
38
40.3
40.9%
35.2%
15.3%
16
12.7
17.2%
47.1%
6.4%
0
1.1
0%
0%
0%
1
3.0
1.1%
12.5%
0.4%
93
93.0
100.0%
37.3%
37.3%
96
96.0
38.6%
100.0%
38.6%
108
108.0
43.4%
100.0%
43.4%
34
34.0
13.7%
100.0%
13.7%
3
3.0
1.2%
100.0%
1.2%
8
8.0
3.2%
100.0%
3.2%
249
249.0
100.0%
100.0%
100.0%
9
7.1
33.3%
52.9%
13.8%
15
18.3
55.6%
34.1%
23.1%
3
1.2
11.1%
100.0%
4.6%
0
.4
0%
0%
0%
27
27.0
100.0%
41.5%
41.5%
8
9.9
21.1%
47.1%
12.3%
29
25.7
76.3%
65.9%
44.6%
0
1.8
0%
0%
0%
1
.6
2.6%
100.0%
1.5%
38
38.0
100.0%
58.5%
58.5%
17
17.0
26.2%
100.0%
26.2%
44
44.0
67.7%
100.0%
67.7%
3
3.0
4.6%
100.0%
4.6%
1
1.0
1.5%
100.0%
1.5%
65
65.0
100.0%
100.0%
100.0%
1
.7
50.0%
50.0%
16.7%
1
1.3
50.0%
25.0%
16.7%
2
2.0
100.0%
33.3%
33.3%
1
1.3
25.0%
50.0%
16.7%
3
2.7
75.0%
75.0%
50.0%
4
4.0
100.0%
66.7%
66.7%
2
2.0
33.3%
100.0%
33.3%
4
4.0
66.7%
100.0%
66.7%
6
6.0
100.0%
100.0%
100.0%
205
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ILLUSION VERSUS REALITY
overconfidence. Splitting this result based on gender depicts
that, of 58 students 41% of the male students had a tendency to overestimate their ability, which is less than that
of female students, 59% (see Table 4). One reason for this
could be that young men often grow up expecting to work
and take over the responsibility of their family while
females are still less likely to grow up believing they must
support their family (Duffy & Atwater, 2011). Therefore,
the conjecture that could be made is that even though the
marks of more female students were bad they considered
them good and was otherwise for male students. On the
other hand, there were 33% of the students who had actually earned bad grades and considered their grades bad.
However, they perceived themselves to be highly able. This
displays their psychological thought process that it was not
the lack of ability due to which they got bad grades; rather
there were other factors that might have been the reasons
for their grades such as those mentioned in question 2 of
the questionnaire (Appendix; see Table 5).
Another analysis was conducted on ability to understand and actual grade scored by the students. It was
found that majority of the total population, irrespective
of gender, considered themselves to be moderately to
highly able on understanding management courses.
However, when the actual grades were seen, 78% of the
students have scored the lowest grade (see Table 6).
When the same analysis was conducted gender wise,
84% (156 of 185) of the female students were found to
be lying in the lowest grade category. Interestingly, of
these 156 female students, 82% rated themselves to be
highly to moderately able. Similarly, 68% (93 of 135)
of the male students were found to be lying in the lowest grade category. Of these 93 male students, 81%
rated themselves to be highly to moderately able (see
Table 7).
These results were substantiated by the Mann-Whitney
test. It was found that there was no significant difference in
grade perception, and ability perception; however, ironically there was a significant difference in the actual grades
scored by male and female students. Thus, it can be inferred
that female students are more over-confident compared to
the male students.
To investigate the second objective of the study that is,
SAB among management students, cross-tabulation was
first conducted on actual bad grade scored. It was found
that in 50% of the total students, SAB was missing. Comparing male students with the female students, 35% of the
male students depicted SAB, while 63% of the females
showed SAB (see Table 8).
Surprisingly when the same analysis was conducted on
actual good grade scored, again among 50% of the total students, SAB was found. Comparing male students with
female students almost equal percentages of the male and
female students displayed SAB (see Table 9).
CONCLUSION AND RECOMMENDATIONS
The results imply that majority of the students considered
themselves to be highly able. Almost equal numbers of
male and female students thought the same. However, more
of the male students seemed to be modest relative to the
female students. A negligible number of students underrated themselves. This can further be supported by comparing their ability with their grade perception or by
comparing their ability perception with their actual grades.
The analysis depicts that almost half of the sample size
considered their grades to be bad. Wherein from this it can
be deduced that there are two observations; first, that these
students have actually scored good grades but this may not
TABLE 8
Gender £ Bad Grade Cross-Tabulation
Bad grade
Gender
Male
Count
% within gender
% within bad grade
% of total
Female
Count
% within gender
% within bad grade
% of total
Total
Count
% within gender
% within bad grade
% of total
Teacher taught badly
Difficult course
I did not work hard
Not attentive
Tough paper
Strict checking
Total
6
8.5%
28.6%
3.9%
12
16.9%
38.7%
7.8%
33
46.5%
56.9%
21.4%
13
18.3%
68.4%
8.4%
6
8.5%
37.5%
3.9%
1
1.4%
11.1%
0.6%
71
100.0%
46.1%
46.1%
15
18.1%
71.4%
9.7%
19
22.9%
61.3%
12.3%
25
30.1%
43.1%
16.2%
6
7.2%
31.6%
3.9%
10
12.0%
62.5%
6.5%
8
9.6%
88.9%
5.2%
83
100.0%
53.9%
53.9%
21
13.6%
100.0%
13.6%
31
20.1%
100.0%
20.1%
58
37.7%
100.0%
37.7%
19
12.3%
100.0%
12.3%
16
10.4%
100.0%
10.4%
9
5.8%
100.0%
5.8%
154
100.0%
100.0%
100.0%
206
V. SHARMA AND M. SHAKEEL
TABLE 9
Gender £ Good Grade Cross-Tabulation
Good grade
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Gender
Male
Count
% within gender
% within good grade
% of total
Female
Count
% within gender
% within good grade
% of total
Total
Count
% within gender
% within good grade
% of total
Teacher taught well
Easy course
I work hard
Not attentive
Easy paper
Lenient checking
Total
16
25.0%
39.0%
9.7%
11
17.2%
35.5%
6.7%
22
34.4%
41.5%
13.3%
11
17.2%
37.9%
6.7%
4
6.2%
44.4%
2.4%
0
0%
0%
0%
64
100.0%
38.8%
38.8%
25
24.8%
61.0%
15.2%
20
19.8%
64.5%
12.1%
31
30.7%
58.5%
18.8%
18
17.8%
62.1%
10.9%
5
5.0%
55.6%
3.0%
2
2.0%
100.0%
1.2%
101
100.0%
61.2%
61.2%
41
24.8%
100.0%
24.8%
31
18.8%
100.0%
18.8%
53
32.1%
100.0%
32.1%
29
17.6%
100.0%
17.6%
9
5.5%
100.0%
5.5%
2
1.2%
100.0%
1.2%
165
100.0%
100.0%
100.0%
correspond to their actual ability to understand management
courses. Second, that these students have actually scored
bad grades, which depicts that they are overestimating the
accuracy of their knowledge (i.e., overconfidence). It is
also observed that more of the female students have a tendency of being overconfident.
While comparing ability to understand management
courses with the actual grades of the students, it was again
substantiated that management students are overconfident.
As a majority of the students who rated their ability to
understand was high, a major chunk of the students actually
scored the lowest grades, ranging between 4.1 and 6.
It was also observed that there exists a SAB among management students. However, gender-wise breakup of the
students those who displayed SAB depicted that more
female (almost double) students portrayed SAB specifically
when bad grades were scored. On the other hand, when
good grades were scored by female students, this percentage declined to the percentage of male students, which
increased in this case. Therefore, it can be said that in case
of female students when something bad happens to them
SAB becomes more prominent.
This study was an attempt to find out the presence of
overconfidence and SABs among management students.
The results indicate the presence of both. Although, it
gets different when gender-wise comparisons were
made.
The results of this study could have significant implications, given an insight into the fact that most of the management students are still lacking in certain skills, which they
do not realize and hence are not employable. Therefore,
there is a need for students and institutions to understand
the existence of overconfidence and SAB and to take measures such as to come up with the counseling sessions and/or
foundation courses before the students actually begin their
classes formally. Students indeed can be trained to perform
better.
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APPENDIX: QUESTIONNAIRE
Gender: Male: __________
Female: __________
Q1: How would you rate yourself on the ability to understand Management courses? (Please tick your response)
Highly able: __________
Moderately able: __________
Neither able nor unable: _____ Moderately unable: ______
Highly unable: __________
Q2(a): If you got bad grades/marks then the reason that you
attribute to this is: - (Please tick only one option from the
followings):
1. Teacher/s taught badly.
2. The course/s was difficult.
3. I did not work hard.
4. I was not attentive in the class.
5. The paper was tough.
6. Paper checking was strict.
(OR)
Q2(b): If you got good grades/marks then the reason that
you attribute to this is (Please tick only one option from the
followings):
1. Teacher/s taught very well.
2. The course/s was easy.
3. I worked hard.
4. I was attentive in the class.
5. The paper was easy.
6. Paper checking was lenient.
Please write down your commutative grades (CGPA) up to
the last semester you passed.
Grades: __________