Why NOT Plagiarize?
A Study of Behavioral Controls in College Students
Joshua Hattem
Professor Lynn Addington (Faculty Supervisor)
Plagiarism is a critical and growing problem in the world of higher education.
Unfortunately, most prior research on this issue has failed to utilize an
encompassing theoretical framework to direct its investigation. The current study
enriches the Grasmick and Bursik (1990) deterrence framework and applies the
new model to undergraduate plagiarism. Three major spheres of control,
internal, social, and institutional, outline a self-report survey for which 830
responses were obtained from the full population of undergraduate students at
American University. Constructs derived from the deterrence framework are
compared to determine the factors most predictive of past plagiarism. The
findings conclude that ethics and a propensity to neutralize deviant behavior are
the best suppressants of academic dishonesty. The results will hopefully inform
more effective, empirically validated policy decisions that curb the instance of
plagiarism in colleges and universities.
American University Honors Capstone
Josh Hattem
Why NOT Plagiarize?
A study of behavioral controls in college students
I. Introduction
… page 2
II. Background
… page 3
III. Methodology
…page 14
IV. Results
… page 14
V. Discussion
… page 25
VI. Conclusion
… page 36
Works Cited
… page 45
Appendixes
A. Demographics Tables
… appendix 1
B. Univariate Tables
… appendix 3
C. Correlation Tables
… appendix 31
D. Regression Tables
… appendix 36
E. Post-Hoc Tables
… appendix 40
F. Survey
… appendix 44
***Special thanks for pivotal assistance to: Lynn Addington; Meg Weekes; and Carl Cook
Thanks also to: the University Honors Program; Karen Froslid-Jones; Seth Cutter and the AU
Student Government; 16 freshmen in the Crime and Media Learning Community***
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I. Introduction
The plagiarism problem exists in much of higher education. Meta-analyses (Whitley,
1998) and general reviews of studies on cheating college students (McCabe, Trevino, &
Butterfield, 2001; McCabe & Trevino, 1993) reveal a surprisingly wide range of rates at which
academic cheating is self-reported. In his meta-analysis of cheating literature, Whitley (1998)
finds studies have reported plagiarism frequencies from 3 to 98 percent of student bodies,
averaging out to 47 percent across all surveyed institutions. McCabe and Trevino (1993) report
that past studies have shown rates of between 13 and 95 percent. Donald McCabe (2005),
reflecting on his fifteen years of empirical studies of student cheating, claims that typical surveys
result in plagiarism rates between 25 and 50 percent.
A study conducted by the Josephson Institute on self-reported cheating rates among U.S.
high school students found cheating to be an alarmingly robust and growing problem (Josephson
Institute, 2009). Well over half of student respondents admitted to cheating on a test in the
preceding year and more than a third had used the internet to plagiarize. Josephson, the
institute’s founder, proffered an explanation for students’ lack of restraint, suggesting that many
may think, “Why shouldn’t we? Everyone else does it” (Crary, 2008).
Plagiarism is in this and many other ways a rational behavior for many students.
Omitting a citation is less time consuming than completing a bibliography; copying another’s
writing takes less effort than formulating and articulating one’s own ideas. The work of an
expert should exceed the merits of the most carefully crafted undergraduate essay. Plagiarizing
students may attain better grades for less time and exertion. Reasons cited for student cheating
have been multitudinous and varied (Park, 2003). Whatever collection of rationales a student has
to plagiarize, the incentives alluded to here cannot be eliminated.
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Discovery of these rationales has consumed much of the prior research in the cheating
and plagiarism field,1 diminishing the usefulness of this literature to policy solutions. Schools
hoping to combat this trend should be helped not by knowing these intractable inducements to
plagiarize but why these are not enough to compel certain students to delinquency. The present
study proposes that abstaining students hold some equilibrant to plagiarism’s incentives that
prevents them from committing the devious act. To fulfill this need, the current study inquires
not into the circumstances or motives behind cheating, but into factors associated with abstinence
from plagiarism. In knowing why some students are prevented from cheating, the derivative
“best practices” can supply a script for controlling the deviant pupils. By delineating the most
influential behavior deterrents, this study will provide a policy guide to education administrators
seeking to effectively reduce the incidence of plagiarism at their institution.
II. Background
A. Introduction
This section seeks to accomplish two goals: summarize the past literature most pertinent
to the current study, and develop a theoretical framework that encompasses the deterrents of
plagiarism. Prior plagiarism and cheating studies are reviewed to identify factors relevant to
plagiarism’s deterrence. This literature is parsed to extract the correlates of academic dishonesty
that have both been previously examined and fit within the parameters of the current study.
Those factors specifically relevant to the deterrence of plagiarism can then be employed in the
methodology section. Ashworth, Freewood, and Macdonald (2003) have noted that many
fallacies of past cheating studies can be attributed to a dearth of theoretical approaches. To avoid
1
Plagiarism is really a subfield of cheating. While expansion to all forms of cheating would be desirable in the
future, the present study looks only at plagiarism.
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such errors, this section also constructs a theoretical framework through which plagiarism can be
explored.
B. Review of Cheating Literature
As exhaustive reviews of the literature on cheating in higher education have been
executed in recent years (Whitley, 1998; McCabe, Trevino, & Butterfield, 2001; McCabe, 2005),
those endeavors will not be replicated here. This section summarizes the research most relevant
to the current study’s development of a broad framework due to their inclusion of a large sample
of diverse predictor variables. All of the examined works utilized self-report surveys to analyze
factors correlated with cheating behavior among a sample of college students. This line of
studies will be dissected for its factors most related to the deterrence of cheating behavior.
1. Personal and Situational Factors
The earliest example uncovered by the present study’s literature review of such a
multifaceted study was one conducted by Bonjean and McGee in 1965. This study compared
“personal background characteristics” and “situational characteristics” to determine cheating’s
most effective predictors. Bonjean and McGee (1965) found only moderate evidence to support
the importance of individual characteristics, which were a combination of status variables (e.g.,
fraternity membership) and demographic variables (e.g., gender). The study found strong
evidence of a relationship with situational factors, which were perceptual variables such as “fear
of sanctions” and peer attitudes.
The above categorization of predictor variables has been salient across cheating literature
(McCabe & Trevino, 1997), though the delineations of personal and situational constructs have
evolved. McCabe and Trevino (1997) define the two categories generally to mean (personal)
variables relating to trait and status differences between individuals, and (situational) variables
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relating to external forces on a person’s behavior, exluding those engaged with due to trait
differences such as membership on a sports team. The personal and situational categories
overlap somewhat, demonstrated by the shift of the variable “fraternity membership” from the
individual category to the situational category between the Bonjean and McGee (1965) and
McCabe and Trevino (1997) studies, but generally this distinction is an effective tool to parse
past literature.
Since the mid-1990s, a few studies have looked at a broad base of factors from both the
situational and personal categories within the same student sample (Diekoff, LaBeff, Clark,
Williams, Francis, & Haines, 1996; McCabe & Trevino, 1997; Stephens, Young, & Calabrese,
2007; Jordan, 2001). These studies focus on particular areas within college cheating, including
the role of motivation in cheating (Jordan, 2001), electronic versus traditional cheating (Stephens
et al. 2007), and neutralization of cheating behavior (Diekhoff et al. 1996).
2. Futher Subdivision of Factors
Upon closer examination, factors in these projects can be grouped by a further level of
division. The personal category can be subdivided into the status and trait clusters, and the
situational category can be subdivided by social and institutional clusters. Status variables are
those used as social labels and categorizations. Variables within the trait cluster represent an
individual’s propensities and characterizations. The social cluster consists of variables
pertaining to people and social structures in an individual’s environement, and institutional
variables are those pertaining to the powers of the school attended. All variables analyzed by
these studies can be logically classified into one of these clusters (Table 1).
Status variables such as age, gender, and year in school are used in Diekhoff et al. (1996),
McCabe and Trevino (1997), and Jordan (2001); marital status (Diekhoff et al., 1996), grade-
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point average (Diekhoff et al., 1996; McCabe & Trevino 1997; Jordan, 2001), and parents
education (McCabe & Trevino, 1997) are also examples from this cluster. Trait variables take
on many forms such as propensity to justify inapropriate behaviors (Diekhoff et al., 1996;
Jordan, 2001; Stephens et al., 2007) and resentment of cheating by other students (Stephens et
al., 2007). Within the situational category, social constructs include perceived peer attitudes
(Diekoff et al., 1996; McCabe & Trevino, 1997; Stephens et al., 2007) and perceived peer
behavior (Diekoff et al., 1996; McCabe & Trevino, 1997; Jordan, 2001; Stephens et al., 2007).
Finally, institutional constructs are the least used in this literature sample, but are represented by
severity of penalties (McCabe & Trevino, 1997) and knowledge of institutional policy (Jordan,
2001).
Table 1 Factors by cluster
Clusters
Personal
Status
Trait
Situational
Social
Institutional
Examples of Factors
gender, age, year in school, race, GPA, marital status, parents education
justify inappropriate behaviors, resentment of cheating by others
perceived peer attitudes, perceived peer behavior, fraternity membership
severity of penalties, knowledge of institutional policy
3. Direct and Indirect Factors
Direct and indirect factors provide an additional layer to the personal-situational
taxonomy that has not been explored in past literature reviews. Factors will be more relevant to
behavior when they measure perception instead of reality. Direct factors either assess a
perception itself or address a characteristic that crucially impacts perception. Within the
personal factors category, this distinction separated trait and status factors. For example, it
seems highly unlikely that being classified as male inherently predisposes one towards academic
dishonesty, though some association may exist with an underlying trait factor such as heightened
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risk-taking. Another disadvantage to using status factors to discriminate between cheaters and
non-cheaters is their inapplicability to a university’s deterrence policy. It would be unrealistic
for a college to favor 22 year-olds in admissions to combat an inverse association between age
and cheating (Whitley, 1998). Trait factors, to the contrary, can be integrated into admissions
standards and student programming, such as building intolerance for cheating in the student
body. Maturity (Diekhoff et al., 1996), for example, is a feasible criterion for admissions and
can be fostered in the student body.
A similar conflation of constructs has existed in prior studies’ use of situational variables.
This is illustrated by the use of perceived peer cheating behavior and perceived peer attitudes in
the same study (McCabe & Trevino, 1997). Cheating has been found to correlate with a
delinquent student’s prediction of the percentage of his peers who cheat (McCabe & Trevino,
1997; Jordan, 2001). However, this variable seems an indirect version of the more directly
relevant construct: the belief that one’s peers endorse the decision to cheat. Indeed, in the
McCabe & Trevino (1997) study, perceived peer attitudes were found to be far more predictive
than perceived peer behavior.
Presence of an honor code is another indirect situational factor that was shown to lack
substantial predictive power. McCabe and Trevino (1993) hypothesized that rates at institutions
without an honor code would exceed those at institutions with an honor code. However,
conflicting results led them to the conclusion that the truly controlling variable was “an
environment where academic dishonesty is socially unacceptable” (p. 534), a more directly
relevant behavioral inhibitor.
Factors that mediate between broad, indirect correlates and delinquency itself are more
potent predictors of cheating behavior. As demonstrated above, this splits personal factors into
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trait factors, which are direct predictors, and status factors, which are not. Within the situational
category, direct and indirect factors exist in both the social and institutional clusters (Table 2).
Direct predictors within these two clusters can be distinguished from their indirect counterparts
as those that signify a student’s interpretation of the meaning and implications of his
surroundings.
Table 2 Examples of direct and indirect factors
Direct Factors
Indirect Factors
Social
Cluster
perception of peer attitudes
perception of peer
behavior
Institutional
Cluster
perception of the severity of
consequences
prescribed consequences for
academic dishonesty
4. Developing a Framework of Control
From the analysis above, we are left with three clusters of factors from the original
organization that fit the parameter of direct predictability: trait variables, direct social variables,
and direct institutional variables. As this study focuses on deterrents to plagiarism, these
correlates of cheating must be further refined to include only those with a hypothetically inverse
relationship to deviant behavior, or those associated with non-cheating. The three clusters of
preventative factors can be abstracted as internal controls (trait factors), social controls, and
institutional controls. These three sources of control are commensurate with those discussed
below and parallel the current study’s theoretical framework.
C. Theoretical Framework
The theoretical framework proffered by the present study builds off of the general
deterrence model proposed by Grasmick and Bursik (1990). These authors developed an
umbrella deterrence theory that integrated three sources of punishment: “(1) state-imposed
physical and material deprivation, (2) self-imposed shame, and (3) socially-imposed
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embarrassment” (p. 841). The Grasmick and Bursik (1990) framework was later applied to
undergraduate cheating in a study by Cochran, Chamlin, Wood, and Sellers (1999). These
researchers utilized Grasmick and Bursik’s (1990) three pronged deterrence theory, replacing the
three original crimes from the Grasmick and Bursik (1990) with five forms of cheating behavior.
The following section will discuss the underpinning theories behind the current study’s
deterrence framework and their applications to plagiarism in higher education and the present
study.
1. Institutional Controls
Institutional control is the prong of the deterrence framework most apparently
engendered by criminology’s “rational choice perspective” (Cornish & Clarke, 1986, as
presented in Grasmick & Bursik, 1990). Rationality underlies Grasmick and Bursik’s (1990)
deterrence framework, as well as that of the present study. Cornish and Clarke (1986) first
popularized this perspective by applying the economic rules of costs and benefits to criminal
deviance. According to rational choice theory, an individual considering commission of a
criminal act, when given the opportunity, will weigh the potential benefits of the act against its
costs to determine a course of action.
As an exploration of behavioral inhibitors, the present study incorporates only the
potential costs inherent in an act of plagiarism within a university context. Within the
institutional sphere, such costs to a student’s behavior are determined by an established system
of material disincentives. These disincentives usually take the form of some negative event
interjected into an offending student’s life, such as a reduced grade or suspension.
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2. Social Controls
An individual’s behavior should be most controlled by those social entities whose
opinion the individual values, termed “significant others” by Grasmick and Bursik (1990, p.
839). The theoretical rational behind the inclusion of social controls in the present study, as well
as the Grasmick and Bursik (1990) study, lies in Travis Hirschi’s (1969, as presented in Sampson
& Laub, 1990) control theory. He postulates that social bonds are created between individuals
and the people and social structures around them. The strength of the bond determines the
likelihood of criminality; those with sturdy bonds are less inclined to act in a way that
undermines these relationships. Bonds also decrease in influence as the subject of attachment is
increasingly distant from the individual’s nuclear world—bonds with loved ones are more vital
than those with, for example, colleagues (Sampson & Laub, 1990). This control theory is
interpreted to suggest that destruction of social bonds should be adverse to the criminal offender.
This extension to rational choice theory is, by Hirschi’s (1986, as presented in Grasmick &
Bursik, 1990) own admission, logical.
Preceding cheating studies have utilized social learning theory (Bandura, 1986) to
evaluate students’ awareness of the normative attitudes on plagiarism held by their peers only
(McCabe & Trevino, 1997; McCabe & Trevino, 1993; Bonjean & McGee, 1965). The current
study, in accordance with Hirschi and Grasmick and Bursik (1990), explores the perceived social
norms held by all social entities relevant to a college education. Any source of aversive social
judgment that may befall a deviating student is considered. This includes faculty, staff, and
those outside the university with an interest in a student’s academic record.
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3. Internal Controls
Ethical Control
Grasmick and Bursik (1990) contend that “shame” is deterrent of criminal behavior as a
“self-imposed, or reflective, punishment” (p. 841). This mechanism is predicated on the
offender having internalized social norms or values that conflict with his proscribed act.
However, Grasmick and Bursik (1990) do not sufficiently develop ethical control’s theoretical
basis and so omit a potentially critical element. The current study’s conception of this sphere of
control is described below along with its corresponding theories.
Ethical control is recognized by among the earliest of contemporary criminological
perspectives: positivism. The Gluecks (1950, as presented in Laub & Sampson, 1988) unveiled
the first major human subjects study of delinquent youth behavior. They conducted a
longitudinal inquiry into developing behavior patterns in boys moving from pre-adolescence to
adolescence. By isolating contextual and demographic variables through a matching process,
they were able to conclude that static, psychobiological traits—personal characteristics—best
discriminate between deviants and non-deviants. The theory proffered by Glueck and Glueck
(1950) was castigated by many academics, particularly sociologists, for lacking a driving theory
for its methodological choices and too uniformly dismissing social influence on juveniles’ ethics,
or “delinquent sub-culture” theory (Glueck, 1960).
Sykes and Matza (1957) sought an alternative to both the Gluecks and competing
sociologists. Sykes and Matza (1957) worked on the assumption that when delinquents
experience guilt and agree with prevailing social norms, their deviance cannot be explained by a
deficient personal value system. Instead, some unacceptable behaviors can be justified by
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circumstance such that “disapproval flowing from internalized norms… is neutralized” (Sykes &
Matza, 1957, p. 666).
Building off of this premise, many ostensibly ethical students may be capable of
neutralizing their principles on plagiarism in certain situations. A student who can deftly shirk
internal culpability by justifying his actions with their context should render his ethical controls
toothless. For plagiarism, neutralization would likely take the form of attributing the behavior to
some element of the academic setting in which the plagiarism is perpetrated.
In addition to neutralization as a theoretical factor in plagiarism, an ethical compass is
integral as its antecedent: without values, there is no need to justify conflicting behavior. While
it cannot be considered identical to the shame factor of the Grasmick and Bursik (1990)
framework, it is comparable to the moral condemnation construct in Cochran and colleagues
(1999). Plagiarism rules are not as widely understood or accepted as natural laws, such as the
sanction of murder. Intellectual property violations, particularly for students, are on the fringe of
criminality, making their commission more ethically ambiguous.
Academic Self-Esteem
Grasmick and Bursik (1990) did not include a self-esteem component in their framework.
This may be partially attributable to the association between self-esteem and criminality
remaining undiscovered until well after their experiment adjourned. While theory to support
self-esteem as deterring to criminality was not developed until much later, Abramson, Seligman,
& Teasdale (1978) generated interest self-esteem when they pioneered the study of helplessness.
The team identified three dimensions of helplessness, inferable from the way in which people
attribute the causes of life’s events, or one’s “explanatory style.” Stable, global, and internal
attribution patterns are found in those prone to helplessness, and vice versa for the non-helpless.
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Maruna (2004) first applied this “explanatory styles” framework to criminality and
discovered non-helplessness’ correlation with desistence. He suggested that neutralization, as
discussed above, is part of only the internal/external attribution process and that a test
incorporating all three helplessness dimensions was necessary to the study of criminal behavior.
His hypothesis—that a cognitive shift from helplessness to optimism would assist in exiting a
criminal career—was supported by the study’s findings. However, Maruna (2004) never offers
an explanation for the helplessness-criminality relationship.
One such explanation is that helplessness motivates criminality. A helpless person who
believes his strengths are insufficient for a desired achievement would be impelled to use
unethical measures to fulfill this need. Conversely, non-helplessness is a deterrent for
criminality. A non-helpless person is optimistic about the potential of his own faculties and
believes his goals attainable without infringing on his ethical code. Non-helplessness is therefore
deterring because its bearer can dodge both the punishment of shame and the disappointment of
an unsatisfied goal. While not intrinsically deterring, non-helplessness provides a conduit for
avoiding both consequences simultaneously. A less fortunate person may still elect not to offend
to avoid the experience of shame, instead submitting to the sting of dissatisfaction when their
goals go unmet. However, a non-helpless person is more completely deterred as he never
encounters a need to make this tradeoff.
In the current study, helplessness and non-helplessness are placed within a classroom
context. Helplessness in schoolwork equates to lacking the optimism that personal capacity can
lead to academic success, with the opposite true for non-helplessness. The complexities of the
full Abramson and colleagues (1978) framework can therefore be substituted, for the purposes of
the present study, with “academic self-esteem.” While meta-analyses and other mass literature
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reviews on university student cheating have revealed some predictive power in academic merit
(Park, 2003; McCabe, Trevino, & Butterfield, 2001; Whitley, 1998), the present study
presupposes that an underlying variable may be more important. A student’s optimism
concerning her academic ability should deter that student from supplementing her work with
illicit material.
III. Research Questions
The present study will attempt to illuminate those sources of control most predictive of
abstinence from plagiarism. Following from this determination, optimally effective university
policy can be surmised. To this end the first question addresses which predictor is most strongly
associated with students reporting no past plagiarism. Six constructs, described below, drawn
from the theoretical framework comprise the pool of possible correlates. These measures should
be unique from one another and encompass the possible factors that prevent students from
plagiarizing. A second research question will ensure that relatively static, demographic
characteristics have negligible predictive value.
IV. Methodology
A. Data Collection
1. Population studied
To study plagiarism, the full population of undergraduate students at American
University was surveyed. American University is a competitive, private school located in a
residential area of the District of Columbia. The student population includes approximately
5,800 undergraduates and 5,000 graduate students distributed across five academic colleges and
a law school. While the quantifiable characteristics of the student body vary by college, the
interquartile range of incoming students’ SAT scores (critical reading and mathematics) in 2007
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was 1180-1350 (American University, 2007), compared to a national average of 1017 the same
year (The College Board, 2007). American University admits slightly fewer than half of its total
number of applicants.
American University does not have an honor code. In the school’s Academic
Integrity Code, the definition of plagiarism is reasonably parallel to the conception of
plagiarism adopted by this study:
Plagiarism is the representation of someone else’s words, ideas, or work as one’s
own without attribution. Plagiarism may involve using someone else’s wording
without using quotation marks—a distinctive name, a phrase, a sentence, or an
entire passage or essay. Misrepresenting sources is another form of plagiarism.
The issue of plagiarism applies to any type of work, including exams, papers, or
other writing, computer programs, art, music, photography, video, and other
media (American University, 2007, fall).
2. Survey development
After the initial development of survey questions, the instrument was tested on a focus
group consisting of sixteen freshmen participating in a select seminar program at American
University. Completed surveys were not collected in order to protect confidentiality.
Participants in this group took approximately five to ten minutes to complete the survey.
Following the survey, the students were solicited for feedback on whether sections of the survey
were dragging, repetitive, or confusing. Several relevant points were made and resulted in minor
alterations to the original draft for clarity and ease of use.
Prior to distribution, the survey was also reviewed by two American University
professors, the Associate Dean of the School of Public Affairs, and the Director of Institutional
Research. Each of these reviewers helped to shape the body of questions and hone phraseology
to the survey’s audience. Two psychology professionals with experience in academia, and two
academically excelling, upper-class students at American University provided feedback on the
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survey as well with similar results. Internal Review Board approval was obtained from
Professor Candice Nelson in the American University School of Public Affairs.
3. The survey
The final version of the survey appears in Appendix F. The survey is divided into eight
instruments, the first of which gathers basic demographic and scholastic information intended to
associate plagiarism rates with particular subpopulations across American University. The
subsequent seven sections are based on the framework described above and provide the
substance of the study. These sections include internal control (academic self-esteem),
institutional control, social control, internal control (ethics), internal control (neutralization),
internal control (why not), and committed plagiarism. The last of these sections, committed
plagiarism, acquires information on past plagiarism behavior, while the six prior each deal with
the student’s perception of himself and his environment.
4. Survey implementation
Survey Monkey, an online survey creation and collection site, was employed to deliver
the survey to students and acquire results. To elicit response, all participants were given the
chance to enter into a raffle for one of four $25 gift certificates to the American University
student bookstore. Student email addresses were solicited for a unique ID and contact method to
randomly select the four winners. Participants were assured that this identification would not be
associated with survey responses, and this was accomplished by creating a separate survey
through which the email addresses were submitted. Students were forewarned that this process
also provided the opportunity to eliminate redundant email addresses, a method of preventing
eligible students from repeating entry to improve their chances.
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Due to the complexity of the Survey Monkey survey’s web address, a webpage with a
simple URL containing a hyperlink to the survey was created. An advertisement containing the
simple URL was disseminated through the daily student newsletter, and emails from academic
advisors and the student government. Circulation of this advertisement began on January 15 and
continued until February 13, 2009, when the final data was downloaded and the survey was
taken offline.
B. Measures
1. Outcome Variable
Committed Plagiarism
The outcome variable is a measure of prior plagiarizing activity. The items for this
construct are adopted from a study by Lovett-Hooper, Komarraju, Weston, & Dollinger (2007),
which looked at cheating and plagiarism as gateway deviance to a career of antisocial behavior.
The Lovett-Hooper and colleagues (2007) survey developed new subscales from a set of items
used earlier by McCabe (1992). One of these subscales focused on plagiarism. These six items
questioning the frequency of past plagiarizing behavior are included in the current study along
with the original response set: “never,” “once,” and “more than once.” One substantial change
was made to the original set. Two questions dealing with the same violation but discriminating
between electronic and hard-copy methods were combined as the current study has no interest in
this distinction. Some alterations were also made to the prompts’ wordings for the sake of
clarification, resulting in asking about the following behaviors:
•
•
•
•
“Filling in parts of citations or bibliographies with made-up information,”
“Turning in a paper obtained in large part from a class paper distributor or website,”
“Paraphrasing or copying a sentence or two from ANY source (e.g. electronic, written)
without footnoting or referencing it in a paper,”
“Copying material, almost word for word, from ANY source (e.g. electronic, written) and
turning it in as your own work,” and
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“Turning in a paper copied, at least in part, from another student’s paper, whether or not
that student is currently taking the same course, or a past paper of your own.”
These five variables measuring committed plagiarism were recoded into five dummy
variables. In deviant behavior study, findings often place a large proportion of samples in the
default answer “never.” To balance the response levels within the plagiarism items’ three
conditions, “once” and “more than once” were combined into a single affirmative category.
Finally, a dummy variable was created to aggregate individuals who responded affirmatively to
any of the five questions.
2. Predictor Variables
The predictor variables deviate significantly from the methodology proposed in Grasmick
and Bursik (1990), which relies on Expected Utility Theory. This theory, taken within Grasmick
and Bursik (1990), suggests that the multiplicity of one’s belief in the severity of a punishment
and the likelihood that the punishment will be inflicted correlates with a reduced likelihood of
committing the punishable behavior. The present study does not explicitly distinguish between
expectation and severity variables. Juxtaposition of the first two institutional control questions—
“student will be caught,” and “student will be caught and face serious consequences”—
approximates this formula, but most of the control questions in the current survey assume either
a fixed expectation or severity.
Questions were instead asked of participants in a contextualized format that hopefully
lends itself to more specific policy solutions. Instead of asking participants to imagine potential
embarrassment from “the people whose opinions you value” (Grasmick & Bursik, 1990, p. 846),
the present study identifies such “people” in its questions to classify more contrete, specific
factors in a student’s decision making calculus. This approach is advantageous from a policy
standpoint as concrete factors can more readily be addressed. If it appears plagiarizing students
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are unique in positing that university officials do not take the offense seriously, the institution
can take measures to ensure more universal acceptance of its position. The methodology
imposed by Grasmick and Bursik (1990) limits the congruent question to “do you think you
would get caught if…” (p. 845). This does not discriminate the school’s influence on a student’s
rationale from a student’s boundless sense of immunity and thereby does not articulate a
definitive policy remedy.
A five-point Likert scale ranging from “Strongly Disagree” to “Strongly Agree” was used
throughout the predictor constructs to standardize results. Responses to each item were placed
on a scale ranging from -2 to +2 with 0, or “neutral,” as its midpoint. The solitary negative
variable in the ethics instrument, “I would NOT feel guilty…,” was inverted for uniformity. All
neutralization items, representing the only disinhibitors of cheating, were also inverted in order
to theoretically correlate negatively with plagiarism. Finally, all six predictive instruments were
recalculated into six new variables representing the cumulative scores of each item grouping.
This created scales of -6 to +6 (ethics), -8 to +8 (institutional control), -10 to +10 (social control,
academic self-esteem, why not), and -16 to +16 (neutralization). Assuming a reasonable level of
inter-item correlation within each instrument, assessed in the results section, these aggregate
scores should be reflective of their related constructs.
Institutional Controls
Items representing the institutional control construct are divided between the participant’s
perception of how willing professors and staff are to enforce heavy consequences and how likely
it is the plagiarism will be detected. Students are not caught every time they plagiarize. The
perceived size of the “dark figure” of plagiarism—the discrepancy between the volumes of
actual and institutionally reported plagiarism—should be as important as the perception of the
Why NOT Plagiarize
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20
consequence’s severity. Questions therefore ask the extent to which the participant agrees that
the following occurs when a student at American University violates the plagiarism policy:
•
•
“that student will be caught,” and
“that student will be caught and face serious consequences.”
Participants are also asked general questions about institutional enforcement of the
plagiarism policy:
•
•
“American University staff and faculty take plagiarism seriously,” and
“Professors and staff are effective at catching those who plagiarize.”
Modifying potential consequences with “serious” attempts to connote a sanction to which
that student would be averse. Students responding in the affirmative to these queries should be
fearful of their University’s capacity to disrupt their livelihood.
Social Controls
Items relevant to social control address each entity an undergraduate would likely
identify as an important evaluator of his behavior. Students are prompted to predict the
‘disappointment’ that would be felt by their parents and American University friends and
professors upon discovery that they plagiarized. Participants are also asked to evaluate the
potential impact on future employers’ willingness to hire them. Finally, students provide the
extent to which they believe plagiarism is a normalized element of American University’s
student culture.
•
•
•
•
•
“Future employers would be less inclined to hire me if they discovered that I plagiarized
in college,”
“My professors would be disappointed if I plagiarized in one of their classes,”
“My friends at American University would be disappointed if I plagiarized,”
“My parents would be disappointed if I plagiarized,” and
“American University students see plagiarism as wrong.”
American University Honors Capstone
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Various elements of a student’s social environment are likely more influential than
others. However, some combination of these constituents should encapsulate an undergraduate’s
perception of the taboos of his social environment.
Internal Controls: Ethics
This construct includes questions on one’s internalized social norms associated with
plagiarism. Three questions were obtained from Beck and Azjen’s (1991) study attempting to
predict deviance of college students with the theory of planned behavior. The survey used
contained a set of items on “moral obligation:” “I would not feel guilty for cheating on a test or
exam,” “Cheating on a test or exam goes against my principles,” “It would be morally wrong for
me to cheat on a test or exam” (Beck & Ajzen, 1991, p. 7). The three items above were adapted
to fit the purposes of this study, essentially by substituting “plagiarize” for “cheat,” and “paper or
presentation” for “test or exam.” These slight alterations resulted in the following questions:
•
•
•
“I would not feel guilty for plagiarizing on a paper or presentation,”
“Plagiarizing on a paper or presentation goes against my principles,” and
“It would be morally wrong for me to plagiarize on a paper or presentation.”
Potentially, semantic discrepancies between “moral” and “ethical” could lead participants
to reach an undesired interpretation when asked about their morals, confusing this study’s
association of the two constructs. While there may be a theoretical distinction between these two
categorizations they both deal with the judgment of virtue. The focus group indicated that they
made little operational distinction between the two words. These questions also differ
substantively from the shame items used in past applications of the presently employed
deterrence theory (Grasmick & Bursik, 1990; Cochran et al., 1999). However, the current items
represent a less emotionally vested approach to a similar if not identical construct. Their use
Why NOT Plagiarize
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may avoid the potentially spurious denomination of “shame” as the controlling form of internal
punishment.
Internal Controls: Neutralization
Diekhoff and his colleagues (1996) used hypotheticals to test the bounds of
neutralization; they placed a generic male student, “Jack,” in circumstances that could mitigate
the immorality of plagiarizing and asked to what extent Jack should be “blamed” (for full
instrument, see p. 492). Of the eleven circumstances delineated by Diekhoff and his colleagues
(1996), three were cut for the purposes of the current study as they were relevant only to cheating
generally. The subject of the hypotheticals was also changed to a non-named, non-gendered
student, and some wording in the situation descriptions was altered for clarity.
Additionally, “blamed” was replaced in the prompt with “more excusable.” “Blamed”
seemed open to interpretation as a question of whether the subject should be held accountable at
all for his offence. Concern over this phrasing originated from review by a psychologist with
specific expertise in psychometric instruments. He noted that, as neutralizers are essentially
excuses for the given behavior, it is prudent to identify them as such. These modifications
resulted in the following, final questions: “When an upper-class student plagiarizes in a typical
class at American University, it would be MORE excusable if…
•
•
•
•
•
•
•
•
“The course material is too hard,”
“The student is in danger of losing his/her scholarship,”
“The student doesn’t have time to do all the work,”
“The instructor doesn’t seem to care,”
“The instructor acts like his/her class is the only class the student is taking,”
“The student plagiarizing isn’t hurting anyone,”
“Everyone else in the class seems to be plagiarizing,” and
“The course is required.”
American University Honors Capstone
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Internal Controls: “Why Not”
When speaking with one administrator at American University in preparation for this
study, she pointed out that while some students know in principle that plagiarism is wrong, most
students are unable to attest to the justification for its interdiction. This assertion has been
confirmed by qualitative studies of student cheating behavior such as that by Ashworth and
Bannister (1997). A student might respond affirmatively to “feeling guilty” over plagiarism
because he knows that he is supposed to. However, it might not be as visceral and controlling a
reaction if he does not understand why he should feel guilty. In response to this possibility, five
questions (referred to as the “why not” instrument) reflecting the reasons why plagiarism is
wrong are included in the survey: “When a student plagiarizes,…
•
•
•
•
•
“He/she learns less than he/she should,”
“Other students are affected,”
“The writer of the stolen work is affected,”
“He/she missed a learning opportunity that would have helped him/her in the future,” and
“Other students are deprived of a fair evaluation by the professor.”
Internal Controls: Academic Self-Esteem
A measure of academic self-esteem is obtained through a composite of five questions
asking the student to reflect upon his academic abilities and expectations. Participants were
asked to respond with the extent to which they agree to the following prompts: “In my typical
class at AU…
•
•
•
•
•
“I am likely to succeed,”
“my classmates see me as a good student,”
“my professors see me as a good student,”
“I see myself as a good student,” and
“I expect to earn a B or above.”
Classmates, the professor, and one’s self comprise the various entities that pass judgment
on one’s performance in the classroom on a routine basis. The first and last questions ask
Why NOT Plagiarize
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24
whether the student believes himself to be a good student (a “successful” one) and provides an
objective reference for the student’s expectations (a “B” or above). Logically, it should follow
that the two would be near perfectly correlated; however, in reality students may have widely
varying conceptions of “success.”
Unfortunately, the original Attributional Style Questionnaire (ASQ) (Peterson, Semmel,
Baeyer, Abramson, Matalsky, & Seligman, 1982), reflecting Abramson et al.’s (1978)
framework, and its expanded form (Peterson & Villanova, 1988) were too lengthy to include in
the survey. Even a shortened form developed by Whitley (1992) proved too extensive an
addition at 12 items. While, the five questions asked do not elicit the degree of detail had from an
ASQ, they should provide a snapshot indicator of the more specific construct in question:
academic self-esteem.
3. Demographic Control Variables
Demographic information gathered includes gender, year entered university, academic
college in which major is housed, and GPA. While race and ethnicity are often included in
comparable sections of student surveys, they were omitted here due to the potential that the
demographic profile’s specificity could lead to a breach of confidentiality. While gender
provides four response categories, two of these were struck for the analysis, eliminating six rows
of data: two respondents identifying as “transgendered,” and four selecting “do not identify.”
These subgroups were far too limited to have offered any reliable inferences.
Year entered university was used in place of class status because class status is based on
accrued credit hours at American University. Many students enter college with substantial hours
completed from Advanced Placement exams taken in high school. The year entered university,
conversely, more closely estimates the extent of opportunity a student has had to plagiarize in
American University Honors Capstone
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25
college. Hypothetically, the longer a student has been enrolled, the more classes they will take in
the university setting. For the purposes of clarity in analysis, year entered university was
renamed “class status.” Its conditions translated from year entered university are freshman
(2008), sophomore (2007), junior (2006), and senior (2005); senior is a composite of responses
“2005” and “before 2005.” Class statuses were recalculated into three dummy variables with
seniors excluded as the reference such that participants and their plagiarism histories could be
compared against this variable.
The question regarding the home of participants’ academic major was left open to
multiple responses. Many of American University’s students double major across academic
colleges. Consequently, the pools of responses within each academic college overlap with pools
from other colleges. Analysis of these populations was therefore done within each college
individually and any comparison between them should consider this inclusivity. Finally, the
participants’ grade point averages, selected from half letter grade (.5) increments beginning with
an A (4.0), were recoded into a single dichotomous variable whose conditions are “3.5-4.0” and
“3.5 or less.” This division within the variable’s conditions was selected because of heavy
loading within the highest category, discussed further below.
V. Results
A. Response Rate
Of the full undergraduate population at American University, 830 (15.3%) submitted a
survey. Most of the studies discussed above that use self-report surveys to obtain student
perspective have instead gathered samples of convenience. Generally, these surveys have been
distributed to a single university class or set of classes, inviting questions on the generalizability
of results to underrepresented demographic groups. While the present study does not suffer
Why NOT Plagiarize
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26
outright from this caveat, it garnered a relatively lower response rate than other traditional
studies in this area that distribute surveys in and provide time for completion during a class
period. This percentage falls just below the normal range determined by Cook, Heath, &
Thompson (2000), but is reasonable when accounting for variations by school in the methods of
distributing the survey.
B. Representativeness of Respondents
To determine its representativeness, the current study’s response pool is compared across
several demographic schisms against the surveyed population. Specifically, the response pool is
broken down by gender, college, and class status. These demographic variables are the least
sensitive information requested by the survey and are thus the most available dimensions on
which to compare the sample and population. Internal data on these measures for the university
were provided by the Director of the Office of Institutional Research & Assessment, replicated
here as appropriate. Full tables and graphs of the sample’s demographics are located in
Appendix A.
1. Representativeness by college and year
Table 3 shows the percentage of the total student population represented across schools
and class standing. The incongruous response rates for the five undergraduate colleges can be
explained by the disparate methods each college used in the dissemination of the present study’s
survey. The School of International Service (22.1%), the School of Public Affairs (19.4%), and
the School of Communication (17.7%) distributed the survey through a direct email solicitation,
yielding reasonably high response rates. The College of Arts and Sciences (10.9%) posted the
participant request to their online portal. The Kogod School of Business declined to contribute
American University Honors Capstone
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27
to the direct email campaign, so only those business students who encountered one of the student
newsletter advertisements had the opportunity to participate.
Table 3 Percentage of population represented in sample
College of Arts
and Sciences
School of
International
Service
Kogod
School of
Business
School of
Public Affairs
School of
Communication
Totals
10.9% (212)
22.1% (369)
4.9% (44)
19.4% (223)
17.7% (135)
Seniors
13.8%
(216)
9.3%
21.5%
5.0%
18.0%
14.4%
Juniors
10.8%
(184)
8.7%
14.9%
3.9%
13.1%
12.1%
Sophomores
16.4%
(247)
12.4%
24.1%
5.0%
17.5%
24.1%
Freshmen
20.5%
(336)
13.6%
28.5%
5.8%
30.3%
21.7%
Representativeness of the current sample also differed slightly by class standing. These
rates, however, fit within the distribution one would normally expect when accounting for the
declining interest in campus life experienced by many students as they grow older. The junior
year trough in the distribution is likely a product of the very high rate at which American
University students study abroad, which occurs primarily during junior year. The response pool
is more robust from the underclass student population, but usable pools were elicited from all
grade levels.
2. Representativeness by gender
Within each college presented in the response pool, the proportion identifying as female was
calculated into Table 4, below. The percentages of females in the populations of each college
were subtracted from the sample figures to produce the table below. This was done in place of
replicating actual gender ratios within the school population to accommodate a request from the
American University administration. The overall gender ratio for the sample is approximately 10
Why NOT Plagiarize
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28
percent more female than would be expected based on the university’s full population. This
skew is within the conceivable effect size of females simply being more willing to fill out
surveys.
Table 4 Differences between the percentages of females in the sample and population
Differences
in female
proportions
College of
Arts and
Sciences
School of
International
Service
Kogod
School of
Business
School of
Public Affairs
School of
Communication
+2.8%
+6.8%
+21.7%
+13.6%
+10.7%
American
University
+9.8%
The stratification of female proportions between colleges falls somewhat along the lines
of the college’s response rates, with the College of Arts and Sciences as an obvious exception.
Excluding Kogod, whose divergent participation rate hampers any reliable assessment of its
characteristics, the skewedness of each female proportion falls within 9 percentage points of each
other. Due to the relatively robust sample size, gender can be used as a control variable in the
regression model, described later in this section, to ensure that the female skewedness is not a
factor in the general results.
3. Representativeness by grade point average
Unfortunately, grade point average (GPA) could not be juxtaposed with population data
as the researcher was never able to obtain this data. However, a frequency table of grade point
averages revealed an intuitive and noteworthy surprise. Participants placed themselves in high
GPA intervals with questionably high frequency: the highest GPA echelon (3.5-4.0) was claimed
by 62.8% of the respondents. This ostensibly specious result may be a product of either social
desirability or a natural self-selection of the sample; respondents may have exaggerated their
GPA to present themselves as more accomplished than they are in truth, or students with
genuinely high GPAs simply responded to the questionnaire at a higher rate than those with
American University Honors Capstone
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29
lower academic standing. If reality verifies the former postulate, there may be similar
embellishment or downplay in other answers that require candor about behavior or beliefs. If the
latter problem exists, items positively correlated with higher GPA may be inaccurately high in
the sample, misrepresenting the student population.
C. Univariate Analysis
Frequency tables were created for every item in the survey. Although these analyses are
fairly basic, they capture an initial view of the student mindset. This information can also be
integral to the detailing of policy solutions to the plagiarism problem. This section will highlight
a few interesting findings from this analysis of the six predictor instruments and committed
plagiarism. Full tables and graphs for the following data can be found in Appendix B.
1. Predictor Variables
Interestingly, the highest and lowest means, respectively, for items within the institutional
control instrument were “American University staff and faculty take plagiarism seriously” (1.47,
with a majority responding “strongly agree”) and “American University staff and faculty are
effective at catching students who plagiarize” (0.38, with a plurality responding “neutral”). This
initial finding suggests a perception held by students that while the school’s administrators care a
great deal about plagiarism they are generally unable to enforce that position.
Responses to social control questions showed that the average American University
student sees his peers as least likely to disapprove of plagiarism. The items with the two lowest
averages, and only two with an average of less than 1.0 or “agree,” were “my friends at
American University would be disappointed if I plagiarized” (0.77) and “American University
students see plagiarism as wrong” (0.86). Peers eclipsed parents, professors, and future
employers as least troubled by fellow students’ plagiarism. Unfortunately, it is beyond the scope
Why NOT Plagiarize
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30
of the present paper to assess whether any of these entities are capable of rendering a genuine
disincentive to plagiarism. As the survey did not distinguish between the perceived likelihood
and severity of social punishment, the current study can only determine that disappointment is
detected, not the relative punitiveness of the disappointment from these social bodies.
Within the “why not” plagiarize instrument, two averages fell more than a half point
lower than their companion items: “Other students are affected” (0.38), and “The writer of the
stolen work is affected” (0.34). Students’ peers appear to be more of a concern when the
question proposes that those other students will be “deprived of a fair evaluation by the
professor” (0.93). It is not surprising in the case of plagiarism that potential harm to the victim
of the property offense would be the least interesting consequence to the student. All responses
in this instrument, however, are comparatively low, with not a single average response
registering a 1.0 or more. This initial finding suggests that arguments against the commission of
plagiarism are either unpalatable to students for one reason or another, or they are not proposed
with sufficient earnest or supporting logic.
2. Plagiarism
Of the five types of plagiarism offenses asked about in the survey, none were committed
by more than approximately one third of the respondents (see Table 5 below). Unsurprisingly,
the most common offense is paraphrasing without citation (32.8%), likely because it is one of the
least nefarious. The least common is turning in an entire paper purchased or copied from a
website (1.3%), likely for the opposite reason. The data for individual forms of plagiarism fall
within reasonable proximity of the average rates determined by McCabe (2005) across myriad
studies and over 60,000 undergraduates. Frequency analysis of the aggregated dummy variable
resulted in a nearly even split between those who had plagiarized (50.3%) and those who had not
American University Honors Capstone
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31
(49.7%). This finding falls on the high end of the estimated range proposed by McCabe (2005),
but may be attributable to the phrasing of the plagiarism items used in the current survey rather
than characteristics of the school or its student body.
Table 5 Plagiarism types and frequencies
Falsify
citation or
bibliography
Freq.
%
Copy paper
from
website
Freq.
%
Paraphrase
without
citation
Freq.
%
Quote
without
citation
Freq.
%
Copy other
student’s
paper
Freq.
%
Plagiarized
ever
Freq.
%
Never
593
76.4
767
98.7
522
67.2
736
95.1
707
91.5
381
49.7
Once
113
14.6
7
0.9
160
20.6
21
2.7
54
7
385
50.3
> Once
70
9
3
0.4
95
12.2
17
2.2
12
1.6
N/A
N/A
Total
776
100
777
100
777
100
774
100
773
100
766
100
D. Hypothesis Testing
1. Multicollinearity
As much of the present study’s survey has not been validated by past research,
multicollinearity tests were necessary. Many of each instrument’s items are similar to others in
the same instrument and could confound the regression analysis. To address this issue, Pearson
correlation tables for each individual set of instrument items revealed little risk of
multicollinearity (see Appendix C). While each item showed a statistically significant (p < .05,
2-tailed) relationship with every other item within the same instrument, very few of these
Pearson correlations exceeded .700. The social control instrument appeared to have the weakest
levels of internal correlation suggesting that the items may not be appropriately grouped within
the same construct and posing a problem with the validity of the construct’s score.
As the internal control construct presented the most complex measurement with three
closely related instruments, ethics, neutralization, and why not, Pearson correlation tables were
created to compare items between these instruments as well. Contrasting ethics and
Why NOT Plagiarize
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32
neutralization instruments and ethics and why not instruments displayed statistically significant
but trivial relationships between items. These instruments are clearly related, but do not
significantly overlap; the constructs are distinct and unique. Each was entered into the
regression equation individually.
2. Logistic regression
As an implementation of the aforementioned model of control, the central hypothesis of
the present study is that each theoretically founded factor will contribute significantly to
discriminating between students who have and have not plagiarized. To this end, binomial
logistic regressions were estimated for four models. As the types of plagiarism measured are
substantively different and are committed at widely varying rates, each was assigned as the
dependent variable for its own model. Submitting a paper copied mostly or entirely from a
website elicited the lowest rate of affirmative response (1.3%, N = 10) and is therefore unable to
support any reliable findings. It was the only form of plagiarism for which a logistic regression
model could not be estimated.
The models used are defined as follows: falsifying citations or bibliographies (model 1),
paraphrasing without citation (model 2), copying material without citation (model 3), copying
from other student’s paper (model 4). Independent variables used in each of the models included
scores from the six instruments. Gender, GPA, and the three class status dummy variables,
junior, sophomore, and freshman, were added as controls. Significance levels and odds ratios for
the five models are summarized in the table below (see Appendix D for full tables).
Of the six predictor instruments composing in the current survey, social control, why not,
and academic self-esteem did not express statistical significance within any of the four models.
The remaining three, ethics, neutralize, and institutional control, were all significantly related to
American University Honors Capstone
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33
at least one form of plagiarism. The odds ratios corresponding with each relationship were also
all under 1.000 meaning that the accumulation of these factors suppresses the probability of
plagiarism behavior. Institutional control was significantly related to falsifying a bibliography or
citation (model 1, p = .007), with an odds ratio of .901. Ethics and neutralization both
demonstrated a broad and significant relationship with plagiarism. Ethics was significant for all
four models, and neutralization was significant for three of the four.
Table 6 Significance and odds ratios for five models
Model 1
Sig.
Exp(B)
Model 2
Sig.
Exp(B)
Model 3
Sig.
Exp(B)
Model 4
Sig.
Exp(B)
Gender
.164
1.348
<.001*
2.462
.167
1.867
.226
1.483
GPA
.083
0.707
.410
0.856
.893
0.948
.617
0.859
Junior
.133
1.530
.265
0.737
.336
1.792
.302
0.662
Sophomore
.550
1.181
.639
1.125
.847
1.132
.149
0.557
Freshman
.885
1.039
.428
0.827
.366
1.652
.042*
0.462
Academic
Self-Esteem
Institutional
Control
Social
Control
.542
1.024
.634
0.983
.754
0.976
.720
0.979
.007*
0.901
.071
0.938
.218
0.912
.277
0.940
.165
1.069
.448
1.035
.589
1.048
.269
1.081
Ethics
.004*
0.863
.004*
0.867
.048*
0.831
<.001*
0.757
Neutralize
.009*
0.958
<.001*
0.934
.010*
0.920
.551
1.014
Why not
.172
0.963
.265
0.971
.916
0.994
.159
0.944
Constant
.136
0.520
.846
0.923
.002*
0.069
.051
0.295
*p < .05
To demonstrate and compare the operation meaning of the Ethics and Neutralization odds
ratios, the difference between those in the lower and upper quartiles of the scores can be
expressed (see Figure 1). Taking the average beta value across models for which they are
significant, we can roughly compare the influence of ethics and neutralization. For ethics,
participants with the 25th percentile score versus the 75th percentile score are approximately 1.76
Why NOT Plagiarize
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34
times as likely to have plagiarized. Whereas participants in the 25th percentile of neutralization
scores are approximately 1.92 times more likely to have plagiarized than their counterparts with
the 75th percentile score. This means that moving a statistical student from the lower quartile to
the upper quartile of either of these constructs, or ameliorating the participant’s agreement with
the related survey items, should cut by nearly half the odds that they will have plagiarized.
Figure 1 Comparison of predictive powers of ethics and neutralization
Ethics
Neutralization
-.188
-.065
75th percentile 25th percentile
633
12 2 10
Exponentiation
1
.
1
.
Lower quartile 1.76 times
more likely
Lower quartile 1.92 times more
likely
Average β
Greater
Likelihood
The current regression equations generally give no indication that the controlling
demographic variables are relevant to the commission of plagiarism. Only two instances of
statistical significance emerged from testing the demographic control variables. Gender was
found to have a statistically significant relationship (p < .001) with paraphrasing without citation
(model 2). We can conclude from the corresponding odds ratio (2.462) that being female makes
a student nearly two and a half times more likely than their male counterparts to plagiarize in this
most common way. As this isolated phenomenon is theoretically inexplicable, it should be
disregarded as an accident of the sample pool despite its statistical significance. Past studies
have found limited, if any, bidirectional association between gender and academic dishonesty
(Miller, Shoptaugh, & Annette, 2008). This study has found the same.
One class status dummy variable, freshman, was found to have a significant relationship
with the forth type of plagiarism, copying the paper of another student. The odds ratio (.042)
American University Honors Capstone
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35
orients the relationship in the theoretically appropriate direction; being a freshman instead of a
senior reduces by more than half the chance that the student will have plagiarized in this way.
This finding shows a positive but somewhat weak support for the hypothesis that length of
collegiate experience related to plagiarism.
3. Post-hoc Analysis
While past studies have failed to find support for the influence of social controls
(Grasmick & Bursik, 1990; Cochran et al., 1999), the very low levels of inter-item corellation
within the present study’s social control instrument prompted a post-hoc analysis of those items.
Hypothetically, social control’s demostrated lack of relevance to the central hypothesis may be
more a symptom of poor instrument contruction than a problem with the construct itself.
Evaluating the questions individually as predictors of plagiarism may highlight one or two
questions whose conjunction more precisely measures the construct and exhibits power to
control deviant behavior.
The social control items were entered into four logistic regression equations with a
different form of plagiarism set as the dependent variable in each (full results in Appendix E),
following the logic used above. While not printed in Table 7, all other dependent variables
entered into the original logistic regression equation were used here as controls. A Bonferroni
adjustment was conducted on the alpha level for significance to balance out the increased
probability of a Type I error through repeated testing. The new alpha level was set at .0025.
Clearly, this additional test did not illuminate any hidden relevance from within the social
control instrument. These results suggest that, even individually, the items used in the present
survey bear no relationship to the probability that a student has plagiarized.
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Table 7 Significance and odds ratios for five models (social control results only)
Model 1
Model 2
Model 3
Model 4
Sig.
Exp(B)
Sig.
Exp(B)
Sig.
Exp(B)
Sig.
Exp(B)
FutureEmployers
.098
0.8
.600
1.1
.333
0.8
.064
1.6
Professors
.126
1.5
.520
1.2
.151
2.4
.920
1.0
Friends
.999
1.0
.831
1.0
.273
0.8
.056
0.7
Parents
.083
1.5
.511
0.9
.327
1.5
.664
1.1
AU students
.549
1.1
.642
1.1
.604
1.2
.181
1.3
.001*
0.0
.033
0.2
Constant
.020*
0.3
.841
0.9
*significant at the .025 level (Bonferroni adjustment)
VI. Discussion
The findings in the present study generally sustain the conclusions of the Grasmick and
Bursik (1990) and Cochran and colleagues (1999) studies using the comparable deterrence
framework. Grasmick and Bursik (1990) discovered that, for the three crimes to which they
applied their deterrence framework, the institutional and internal controls were significantly
related to criminality while social control was not. Cochran and his colleagues (1999) applied
the same framework to five forms of academic misconduct and distributed a self-report survey to
classes at Oklahoma University. Their analysis of predictors led to the even more limited finding
that only internal control, or shame, was significant to a student’s decision calculus. The present
study found some evidence that students respond to material disincentives, but the Cochran and
colleagues (1999) findings are otherwise supported.
The irrelevance of material disincentives in the study by Cochran and his colleagues
(1999) and its ambivalent position in the current study may emerge from these studies’ use of
students instead of a general adult population. Generally speaking, college students are
inherently detached from the material punishments threatened in the adult world. Customarily,
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37
undergraduates are financially dependent on their parents and assume a sense of immunity to
authority while in the cloistered university environment. Particularly with regard to academic
misconduct, student deviance is handled in-house; the most dramatic punishment at the disposal
of faculty and staff is dismissal from the community, or expulsion. A college’s disciplinary
system pales in comparison to the U.S. criminal justice system, and students by their nature may
be less inclined to fear the consequences of broaching these rules. In summary, material
disincentives are justifiably more important to general deterrence study than to deterrence study
of university students.
The present study added a few predictors to the original Grasmick and Bursik (1990)
study: neutralization, why not, and academic self-esteem. These additions were mostly
dismissed by the current study’s findings with the exception of neutralization. Findings of the
present study confirm what a few other student cheating studies have demonstrated in the past:
the potency of excuse-making to influence student decisions. The collinearity test between
ethics and neutralization items presented little correlation between the two sets, signifying the
distinction of these constructs. Analysis of inhibitors to delinquency by the Grasmick and Bursik
(1990) and Cochran and colleagues (1999) studies would have been improved by a neutralization
instrument.
Three instruments were surprisingly void of relationship with plagiarism: social control,
why not, and academic self-esteem. The lack of association between social control and
plagiarism may indicate that the construct is too nuanced for the level of analysis with which it
has been scrutinized in the past. The insignificance of any individual social control item found
by the present study’s post-hoc analysis was particularly surprising. Clearly the lack of
relationship is not attributable to a problem with the correspondence of the instrument’s items. A
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pitfall in the instrument’s construction is that the social control questions may have erroneously
presumed discovery of plagiarism (e.g. “parents would be disappointed…,” etc.). No
disincentive will be presented to a student by an individual who never discovers that the student
behaved in a disappointing fashion. This logic, however, cannot explain social control’s
insignificance in the two prior deterrence studies as they included a question on the student’s
expectation of being discovered. Grasmick and Bursik (1990) and Cochran and his colleagues
(1999) asked participants explicitly whether or not they believed their deviance would become
known to relevant social entities.
This consistent finding of social control’s negligible predictive value is at odds with
findings in other cheating literature. Jordan (2001), for example, conducted a single-campus,
self-report survey of student attitudes on cheating and found that a student’s cheating behavior
increases proportionate to his indication of the prevalence of cheating among his peers. This
measure, as discussed in the background section of the current article, should be an indirect
formulation of a student’s perception of the social norms held by his peers, falling under the
present study’s definition of social controls. Despite being a less direct measure, Jordan’s (2001)
social control instrument is able to predict past cheating where that of the present study was
unable to do so.
Another surprise from the current results is the irrelevance of having a developed sense of
the victimization consequent to an act of plagiarism, the “why not” construct. With ethics and
neutralization leading the suppression of academic dishonesty, the justification for those ethics
should be related as well. The Pearson correlation table revealed no convincing overlap between
these two constructs, so they are not reliably found among the same students either. These
American University Honors Capstone
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39
findings suggest that non-plagiarizing students often believe that they should not plagiarize, but
do not often know why.
The final predictor construct, academic self-esteem, was also surprisingly discovered not
to relate to plagiarism. While discrediting a portion of the theoretical model developed in the
present study, this result should be encouraging to those with an interest in preventing academic
dishonesty. Self-esteem, arguably in particular among students, can be very difficult to mend.
Many good reasons to address such issues exist, but based on the present study’s measure it
appears that low academic self-esteem is one hurdle that need not be jumped to encourage
student integrity in the classroom.
A. Policy Implications
This section is intended not to detail specific policies and programs a university might
adopt, but simply to outline from a policy perspective the more important findings of the present
study (for examples of this and more specific policy recommendations, see McInnis and Devlin,
2002, and McCabe, 2005b). Here, three major policy areas are briefly explored: character
development, plagiarism detection, and plagiarism definition (see Table 8).
Table 8 Policy Implications
Problem
Solution
(1) Character Development
Ethics, Neutralization
Improve ethical compass of
student body
(2) Plagiarism Detection
Institutional Control
Improve mechanisms for
detecting plagiarism
(3) Plagiarism Definition
Neutralization,
Institutional Control
Clarify parameters of
academic integrity code
1. Character Development
One conclusion that can be drawn from the current study’s findings is that students
appear generally unwilling to contravene their ethical fabric. The strengthening of this fabric,
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therefore, should be the most effective source of deterrence to academic dishonesty.2 In
operational terms, this advises steps that can be taken in two areas of university function. The
first area of application could involve a screening mechanism for ethical character in university
admissions. A second possibility is to implement programs that inculcate students with prosocial
values and a gauge for ethically astute judgment.
Screening for ethical turpitude in undergraduate applicants has an intrinsic appeal but
questionable application. In theory, colleges and universities would be well served by including
in their admissions criteria an upstanding nature and the promise of living an honorable
existence. However, two issues emerge in the execution of this function: the difficulty of
constructing an accurate test and the problem of ethical subjectivity. Using a voluntary reporting
format, such as an exam or essay, to isolate potentially devious students is susceptible itself to
cheating. Admissions departments cannot simply ask applicants about their character as these
hopeful students have too great a motivation to answer affirmatively. A potential pitfall may
arise from the scope of such questions as well. Character questions would need to be limited to
factors that hold broad agreement within the university or college community.
To address the former concern, some smaller colleges require interviews for admissions
and ostensibly place substantial weight on the evaluations by the interviewer, usually an alumnus
of the school living in the applicant’s locale. However, this process is very resource consuming
and may be difficult for schools with larger applicant pools or relatively low alumni capital.
Even if this shortcoming is surmountable, interviews are far from foolproof in assessing
character. The information that can be gathered from an hour of interaction with an applicant is
2
Arguably, “deterrence” is a misnomer for ethics’ effect on plagiarism. However, the present study’s theoretical
model holds that ethics is part of a range of behavioral filters. Violation of internalized norms is one of the factors
considered when contemplating a devious act. The disincentive, self-contempt, to breaching this ethic can be seen
as deterring to plagiarism as part of the decision calculus.
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limited and students can be disingenuous in this process as well; interviews may actually weed
out the weaker performers instead of the unscrupulous people.
The second option is to incorporate some form of ethics education into the required
curriculum. Teaching ethics similarly holds an inherent allure and has been adopted by many
programs. Undergraduate research courses, for example, almost always include at least a unit on
ethics. The policy application of the present study, though, asserts that a broader education in
universal ethics would be useful to deterring academic dishonesty. This could take the form of a
full course on ethics in school and adult life or a seminar for the orientation of newly inducted
students.
The notion itself that ethics can be taught, however, is brought to question by the current
study’s findings. The impotence of the “why not” construct, or the logic behind academic ethics,
suggests that the explanation for ethical rules is not related to the adoption of those ethics or the
appropriate application of those ethics. Knowing why plagiarism is wrong does not necessarily
translate into believing that it is wrong. Students, therefore, should not require a developed
rationale in order to accept plagiarism as antisocial. While the ethical lessons could be applied to
case studies and contextualized in classroom academics, justifications for these ethics should
remain abstract and lessons should concentrate on the virtues of good character instead of the
harms academic dishonesty confers upon its victims.
Neutralization tendencies should also be discouraged as part of the ethics syllabus.
Combating excuse making by students is clearly integral, by the present study’s findings, to the
character development solution. Rationalizations, however, cannot always be checked. The
most allowable rationalization for plagiarizing cited by students in the present study was
maintenance of scholarship funding. Such funding is often necessary to continue enrollment in a
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degree program, completion of which is often necessary to be competitive in today’s job market.
Cheating for this purpose is intuitively logical despite the act’s aberration from one’s ethical
code and the ascendant risk it carries of expulsion. This and other more compelling reasons for
ethical deviation will be difficult to discourage.
2. Plagiarism Detection
The present study found some support for the effectiveness of the threat of detection to
deter student plagiarism. With improvements in information technology, new software is
emerging that provides unprecedented efficiency in the detection of plagiarism at a low cost.
American University itself has experimented with programs in this vein, but has not yet assented
to their widespread implementation and utilization. Universities implementing such technology
have met with dissent on ethical grounds. Many feel that concurrently having an honor code and
automatic plagiarism detection is hypocritical. It is argued that when students sign an honor
code of conduct, the school should have a pretense of trust for those students. This hypocrisy
may also manifest concrete ramifications; the apparent distrust inherent in Turnitin programs
may actually marginalize the role of student ethics. If fear is made the overriding motivation to
avoid cheating, students may be more inclined to plagiarize when they believe that they can get
away with it instead of when they feel that it is wrong.
In order to take full advantage of this approach, however, the efficacy of this technology
must be stressed to the student body. As the present study suggests, influencing decisions is a
matter of altering perspectives. Administrators not only need to make more consistent the
detection of academic misconduct, but also students’ belief that their chances of being caught are
too high to venture the risk. The present study’s findings clearly indicate that students believe
faculty and staff take plagiarism seriously, though at the same time illustrated a general
American University Honors Capstone
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43
disagreement that those same authorities are effective at catching those who plagiarize. This
second point undercuts efforts to establish institutional control and ennobles students to
recalcitrance as they believe themselves immune from punishment. People of the typical
undergraduate age are naturally very low in risk aversion, making even more pressing the need to
convince students of a high likelihood of discovery.
3. Plagiarism Definition
The present study’s neutralization instrument omitted an excuse often cited by students
who have been caught plagiarizing: ignorance of the act’s interdiction. This was the unfortunate
but logical consequence of using a self-report format. Students who are unaware that some acts
from their past constituted plagiarism will report never having plagiarized. While it is difficult to
tally such instances of naïve plagiarism, unawareness of policy could be used as a neutralization
scheme or, when veracious, a cause for not fearing institutional controls.
Both of these difficulties may arise from opaqueness in an institution’s plagiarism policy.
Students must understand restrictions in order to abide by them, and an undeniable
comprehension of the policy should reduce the opportunity for rationalizations. This solution
immediately encounters the problem of actually writing a policy that explicitly and conclusively
condemns every possible conception of academic dishonesty. However, even if unwritten
verbatim in the academic integrity code, the typical construal and application of the plagiarism
policy can be explained to students. This could potentially be accomplished through a module
on student plagiarism as a component of academic requirements. New students would obviously
benefit the most from this information as it can be internalized and practiced more consistently if
communicated early on.
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B. Study Limitations
Discussion of the present survey’s results must include a caveat. As the data collected
are based on voluntary self-report, a possibility exists that respondents will be disingenuous,
particularly when they might be ashamed of past deviance or, conversely, ashamed of lacking
past deviance. However, the utility of self-report surveys as an efficient way to gather the
thoughts of participants far outweighs this drawback. Also, because this type of offense is rarely
discovered, volunteered information is the only way to closely approximate its frequency.
Students may also be less inclined to share past deviance if they believe that an authority will
gain access to the information (Payne & Chappell, 2008). This concern was hopefully
diminished in the present study by assurances of unanimity and that, at the time at which the
study was conducted, the principle investigator was a student as well. Both points were
emphasized in the study’s advertisements and the survey’s description.
A third cause of underestimation exists as well in a line of research into “unintentional
plagiarism,” which proposes that some students may not understand the functional definition of
plagiarism or may suffer occasionally from “cryptomnesia” (Park, 2003, p. 476). The latter
problem occurs when a person’s memory creates the illusion that he is the proprietor of an idea,
which he actually absorbed from another source. There is no mens rea present in the
commission of plagiarism under this condition, yet the academic integrity code imposed by this
study’s host university makes no distinction between intent and accident. This policy is justified
by eliminating the easy excuse created for indicted students by a need to prove intent.
Nonetheless, unintentional plagiarism is another source of underestimation produced by
voluntary recollection of past offenses.
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One caveat introduced by both former deterrence studies previously discussed, though
only directly addressed by Grasmick and Bursik (1990), was between prior and projected deviant
behavior. The present study and the study by Cochran and his colleagues (1999) asked
respondents to divulge their history of academic dishonesty. Grasmick and Bursik (1990)
requested participants in their study to project what they believed their behavior would likely be
in the future. The recollection method is susceptible to confusing the direction of causation: a
person’s perceptions and belief system might have been altered by, as opposed to having created,
past deviance. Escaping culpability for an offense, for example, is theorized to change the
offender’s belief that they would be punished should they offend again. Grasmick and Bursik’s
(1990) projected behavior method, though, suffers from the downside that people may not have
perfectly formulated concepts of when and how they might violate a law. An individual’s
perception of his tendencies may not be a better measurement than his recollection of past
behavior.
VII. Conclusion
Plagiarism and academic dishonesty are ongoing, pressing issues in today’s colleges and
universities. The gold standard in higher education is teaching students to create their own
knowledge, a model that implicitly requires students comprehend and respect the need for
intellectual property rights. Ethics policies are also pertinent in a more global context.
Contemporary broaches of codified or socially recognized ethics in the professional world are
frequently the subject of headlines and televised news leads. Most of these guilty professionals,
however, were at one time undergraduates, and a handful of undergraduates every year represent
another generation of ethical drifters. Clearly, ethical controls are salient beyond the classroom;
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ethical controls developed in the classroom may stymie future improprieties in the professional
universe.
Qualitative research is a major segment of the cheating literature that could not be
incorporated substantively into the present study, but deserves future exploration. The relatively
unstructured methodologies exercised in these cheating studies (Ashworth & Bannister, 1997;
Ashworth et al., 2003; Devlin & Gray, 2007) produces unparalleled access to the unabridged
perspective of students on this crucial problem. The findings of this research might provide a
conduit for more rigorous scientific analysis. Future surveys could take a comprehensive list of
students’ justifications for cheating behavior produced by qualitative interviews and conduct a
factor analysis to determine inductively the constructs and instruments that best reflect the
differences between cheaters and non-cheaters.
This qualitative method may be an effective way to avoid measurements flawed by
investigators out of touch with student mentality and thereby vulnerable to misstatements of
perspectives or omission of important constructs. The reviewed literature in the present article
has tested questions on students that were created by investigators without firsthand knowledge
of students’ decision calculus. Instead, this process of obtaining student perspective on the
causes of plagiarism could be inverted by using open-ended student responses to construct an
instrument. Constructs could then be derived from the dataset through a factor analysis of the
variables.
The present research does not fall neatly within a single strain of literature as it draws
from methods and analyses in both education policy and deterrence studies. This line of work
will hopefully be expanded upon by future exploration in the synthesis of these fields. Future
studies may also take a cue from the current work by acting on the opportunity to suggest
American University Honors Capstone
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47
practical policy solutions to the investigated problem that extend naturally from the study’s
findings. Public policy, and university policy as well, is not frequently enough grounded in
empirical discovery, despite the existence of relevant writing. Researchers can be more
proactive in forging this connection between the academic and policy communities. The
interests of all corners of our society are advanced by enacting empirically validated policies that
can more judiciously prevent the ills that befall us. Hopefully, the present study will contribute
to this effort in suppressing undergraduate plagiarism, leading to a more enriching university
education for all students.
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48
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