Perkins et al. International Journal for Educational Integrity
https://doi.org/10.1007/s40979-020-00052-8
(2020) 16:3
International Journal for
Educational Integrity
ORIGINAL ARTICLE
Open Access
Reducing plagiarism through academic
misconduct education
Mike Perkins1* , Ulas Basar Gezgin2 and Jasper Roe1
* Correspondence: mgperkins@
gmail.com
1
British University Vietnam, BUV
Ecopark Campus, Ecopark Township,
Hung Yen, Vietnam
Full list of author information is
available at the end of the article
Abstract
Although there is much discussion exploring the potential causes of plagiarism, there
is limited research available which provides evidence as to the academic
interventions which may help reduce this. This paper discusses a bespoke English for
Academic Purposes (EAP) programme introduced at the university level, aimed at
improving the academic writing standards of students, reducing plagiarism, and
detecting cases of contract cheating. Results from 12 semesters of academic
misconduct data (n = 12,937) demonstrate a 37.01% reduction in instances of
detected plagiarism following the intervention, but due to limited data, cannot
demonstrate a direct impact on reducing detected rates of contract cheating. The
results also show a lower than expected proportion of plagiarised assignments
(3.46%) among submissions.
Keywords: Academic misconduct, Plagiarism, Contract cheating, Turnitin, Academic
dishonesty, Ghost-writing, EAP intervention, fingerprinting
Introduction
Academic dishonesty is not a new problem for higher education service providers.
However, the rising availability of information sources which can easily be accessed by
student writers, as well as essay-writing services heavily marketed towards university
students, has led to an increase in discussions on this topic in both the media and academic journals. One way in which universities have attempted to monitor and control
academic integrity is through the use of text matching software such as Turnitin. However, Turnitin and other software packages used to detect similarities between text
submissions have been widely acknowledged as far from a perfect solution to ‘solve’
plagiarism (Heckler et al. 2012; McKeever 2006; Scheg 2012) as they do not inherently
detect whether plagiarism has occurred.
Aside from cases of plagiarism that can be detected using text matching software,
other, more subtle and difficult to detect forms of plagiarism such as contract cheating
also need to be addressed. Throughout this paper, we use the term ‘contract cheating’
to refer to any form of plagiarism where a student has contracted another individual or
organisation to carry out assessed work on their behalf.
© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to
the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The
images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise
in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright
holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain
Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless
otherwise stated in a credit line to the data.
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
Although student use of contract cheating services are not new (Lancaster and Culwin 2007) and prevalence of this behaviour is low (Rundle et al. 2019), they are becoming more visible, to the point where it is not uncommon to see these services
advertised on social media. These services show evidence of being mature, wellestablished commercial operations, suggesting that there is a substantial demand feeding this supply (Ellis et al. 2018).
In this study, we present and discuss an intervention designed to improve the academic writing skills of students, reduce levels of plagiarism, and provide a tool to assist
in the detection of contract cheating, by capturing a ‘fingerprint’ of a writing sample in
an offshore international higher education service provider: British University Vietnam
(BUV). BUV has operated in Vietnam’s capital city, Hanoi, since 2009. Although the
faculty are entirely expatriate employees, almost all the students are Vietnamese, and
therefore use English as their second or even third language. BUV faces the same problems as any other university with regards to plagiarism threats. However, due to the
suggested negative relationship in the literature between English language ability and
the propensity to commit plagiarism (Abasi and Graves 2008; Bretag 2007; Chen and
Ku 2007; Goh 2015; Jones 2011; Li 2015; Marshall & Garry 2006; Perkins et al. 2018;
Pennycook 1996; and Walker and White 2014), BUV must be more aware of the potential threats of plagiarism in its student body. In this paper we focus specifically on how
the use of a bespoke English for Academic Purposes (EAP) programme (referred to internally as the Academic English Masterclass) may improve the academic writing skills
of students, assist in reducing overall plagiarism levels within BUV, and specifically, assist in the identification of cases of contract cheating. As proposed by Kakkonen and
Mozgovoy et al. (2010), we demonstrate how a final exam for this programme may be
used to help identify potential cases of contract cheating by providing ‘fingerprints’ of a
writing style which may be checked for consistency against a piece of work submitted
later.
Literature review
Although there are multiple definitions and characterisations of plagiarism (see: Park
2004; Bennett et al. 2011; Mozgovoy et al. 2010), for the purpose of this paper, we refer
to plagiarism as an act of submitting a document that belongs partially or completely
to somebody else without due reference, and therefore misrepresents the effort that has
been carried out by the submitting author. It is important to recognise that plagiarism
can also occur unintentionally. We believe that the primary benefit of the initiative we
present is that it has the potential to reduce instances of unintentional plagiarism by
developing the academic skills of students, whilst also serving as a disincentive to the
minority of students who seek to benefit by engaging in one or more deliberate forms
of plagiarism discussed above. However, as the analysis presented in this paper uses institutional data on detected cases of plagiarism, we cannot differentiate between deliberate and accidental cases of plagiarism.
The reasons students engage in plagiarism has been well explored in numerous other
papers, but as most students at BUV are Non-Native English Speakers (NNES), we wish
to highlight the effect that low levels of English may have on incidences of plagiarism.
This finding is supported by Bretag et al. (2018) who found that a factor influencing
Page 2 of 15
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
contract cheating prevalence was the use of a language other than English in students’
homes. Studies which have found a generally negative relationship between English language ability and plagiarism include Abasi and Graves (2008), Bretag (2007), Bretag
et al. (2018), Chen and Ku (2007), Goh (2015), Jones (2011), Li (2015), Marshall and
Garry (2006), Pennycook (1996), Perkins et al. (2018), and Walker and White (2014).
However, many studies exploring this relationship are based on self-reported data from
both students (Goh 2015; Jones 2011) and faculty (Abasi and Graves 2008; Bretag 2007;
Li 2015; Walker and White 2014) which raise methodological concerns about the
potential validity of this relationship.
In terms of interventions which may assist in combatting plagiarism, several options
have been suggested in the relevant literature. These include an online academic integrity module (Belter and du Pré 2009; Curtis et al. 2013), a web-based module with a
blended method on plagiarism (Stetter 2013), an online quiz through Blackboard
(O'Donnell 2011), a plagiarism assignment (Davis 2011), an ethics-related module (Guo
2011), computer simulations and games as a preventative measure (Bradley 2015),
marker training and the use of novel detection software, (Dawson et al. 2019; Dawson
et al. 2019) and student plagiarism workshops (Chen and Van Ullen 2011; Hoanca
2019). Soto et al. (2004), and Levine and Pazdernik (2018) provide clear evidence of a
reduction in plagiarism following a combination of initiatives, including structured educational modules, implementation of policies, increasing the difficulty of plagiarism by
requiring students to submit drafts, and ensuring there are consequences of plagiarism.
The fear of consequences arising from being caught committing plagiarism was also
shown to be a strong deterrent to plagiarism by Bennett (2005). Amigud and Lancaster
(2019) also identify that in some cases, familial involvement occurs in the process of
purchasing contract cheating services, although it is not specified how this takes place.
The authors suggest that ultimately, reducing contract cheating should focus on detection rather than attempting to stop it happening in the first place.
Proposals which have been suggested to specifically reduce contract cheating include:
collecting writing samples from students (McLafferty and Foust 2004; Jones & Sheridan, 2014); setting assignments that specifically refer to lecture contents rather than
generic essays (McLafferty and Foust 2004); improving the teaching and learning environment, including the relationship between staff and students and reducing the turnaround time of assessments (Wallace and Newton 2014); ‘designing out’ plagiarism
(Fazel and Kowkabi 2014) by providing alternative forms of assessment such as exams,
oral presentation (Lines 2016), internship experience and field trip-based reports, as
part of a holistic assessment methodology (Goh 2015); and incorporating assessments
that involve critical thinking and personal involvement with the course content (Carroll
2007; Heckler et al. 2012; McLafferty and Foust 2004; Probett 2011).
There is limited research in the field providing evidence of how contract cheating
may be detected in the first place. Clarke and Lancaster (2007) present a ‘Six-Stage
Contract Cheating Detection Process’ for identifying incidences of contract cheating in
computer science assignments. However, this method relies on the availability of public
information; in this case, ‘bids’ to an auction site. This ignores a common pathway of
students obtaining papers from ‘essay mills’ or from advertisements on private social
media groups. Morris (2018) on the other hand, suggests a more holistic model of five
considerations for addressing contract cheating, including determining strategy,
Page 3 of 15
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
reviewing institutional policy, developing an understanding of students, edited and revisiting practices for assessment and including areas for staff professional development.
Koppel and Winter (2014) demonstrate how computational linguistic methods can be
used to determine whether the author of two documents is the same. Although the results of their study indicate that this method has a good degree of accuracy in determining whether two documents were written by one author, it relies on having access
to digital copies of all text being examined. This method is therefore unable to determine whether contract cheating has taken place, as it is not possible to analyse work
from authors who are not in the existing database.
Clare et al. (2017) present a method of determining whether contract cheating may
have occurred by examining whether unusual patterns exist between the grades received by students for unsupervised work compared to those for supervised work. This
approach may be helpful to identify where further investigation could take place, but
given the wide range of factors which could also influence differences in grades between different types of assessment (student preferences, differences in grading practices between markers, quantitative vs qualitative assessments, etc.), it cannot be relied
upon by itself as a tool to identify contract cheating.
Dawson and Sutherland-Smith (2018) show that experienced markers were able to
detect contract cheating 62% of the time in one experiment. However, these papers
were all obtained from dedicated contract cheating websites which may be of varying
quality, and the study only examined twenty papers from one course.
Harper et al. (2020) demonstrate that staff are generally skilled at detecting contract
cheating rates for text-rich assessments, but this reported detection rate was lower for
exam-based assessments as opposed to take-home assignments.
Although it is very easy for software solutions to identify text that is already present in
its database, the ability of current software is not yet advanced enough to detect the complexities of contract cheating (Kakkonen and Mozgovoy 2010; Mozgovoy et al. 2010). As
advances in technologies such as deep learning, neural networks, and quantum computing
develop and become available for use in higher education, these difficulties may be eased.
It is worth noting that new products from Turnitin such as Authorship Investigate have
shown potential in identifying contract cheating cases (Dawson et al. 2019) although are
not yet widely available. As software cannot adequately assist with detecting incidences of
contract cheating, this is therefore left to faculty. However, studies such as Lines (2016)
and Malesky et al. (2016) have shown how these contract cheating services can both be
undetected by faculty (despite knowledge of their use) whilst also providing acceptable
grades for the students engaging in these practices.
As there have been few reports of studies which have been specifically designed to
both reduce plagiarism and identify potential cases of contract cheating, we contribute
to the literature by detailing the methods which BUV have taken in order to resolve
this problem, whilst at the same time increasing the academic writing capabilities of
our students.
Language, plagiarism and context in British University Vietnam (BUV)
BUV is a private educational institution which began operations in 2009. BUV holds a
unique position in Vietnam’s higher education system, as the only university to offer
Page 4 of 15
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
entirely British undergraduate programmes which are accredited by and offered in partnership with two UK universities. As of February 2020, BUV has approximately 700
students primarily studying degrees in Business and Management subjects.
The majority of BUV students are NNES and study a programme comprising two semesters of study per academic year. All students who begin a course of study must have
achieved an English language proficiency score: either an official IELTS Band score of
6.0 with no sub-skill below 5.5, or an alternative English language qualification equivalent to this level.
BUV is in the process of undertaking rapid expansion and has recently relocated to a
suburban campus with a capacity for over 7000 students. This dramatic increase in
scale has the potential to give rise to new and increased risks for academic quality and
reputation, and so it is imperative that appropriate measures are employed to safeguard
the quality and rigour of the programmes offered during this period of growth and in
the future. Consequently, the faculty of BUV has been working towards the development of an intervention to detect, reduce, and deter students from voluntarily or involuntarily participating in behaviours which would constitute plagiarism, whilst at the
same time improving the key language and study skills required by students studying in
an international educational setting.
Prior to the introduction of the BUV intervention in April 2016, faculty had identified
that many students in their classes may benefit from additional support in developing
their academic study skills. BUV had, by chance, also discovered some challenging cases
of contract cheating and were also anecdotally aware that this was more common in
the student body than previously thought. Due to the historical reliance in the institution on Turnitin as the key tool to identify instances of plagiarism, a new approach to
managing the academic integrity of the university needed to be taken which could further improve the English language ability of students.
As any potential threats to the academic integrity of the BUV programmes need to
be taken extremely seriously, and the potential benefits to the English language ability
of students were clear, the introduction of an initiative to tackle both issues was required. The highly competitive market of private, international higher education in
Vietnam also means that any additional benefits provided to students may act as market differentiators. By developing an initiative which could tackle both issues at BUV,
and therefore increase the likelihood of students attaining good degrees, this would
likely act as a potential selling point to the fee payers and decision makers (most often
the parents of students). In this market, as in many others, a strong reputation is a key
decision-making factor in the choice of universities. If there was a suggestion that the
academic integrity of BUV was anything other than impeccable, this could cause significant problems with student recruitment, as well as damage our relationships with local
and international stakeholders.
This intervention had to address several key concerns. Firstly, students had to be provided with additional academic English classes in order to attempt to reduce feelings of
low confidence and improve their overall ability to write in English. Secondly, students
also had to receive additional support in terms of time management and fostering motivation. An intervention had to provide a tangible, stringent method of detecting instances of contract cheating. Finally, the intervention had to specify the rules and codes
of conduct relating to academic integrity expected in an international university
Page 5 of 15
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
environment, while being careful not to fall into the trap of assuming that Western academic values are a universal constant.
The intervention: Academic English Masterclass
Based upon the analysis presented above, BUV approved the creation of a standalone
compulsory module for all undergraduate students, entitled Academic English Masterclass (AEM) which ran for the first time in April 2016.
The module consists of 2 hrs of class-based tuition per week for 12 weeks for all
undergraduate students and culminates in a novel final exam, which functions as both
a control and benchmark for students’ English writing ability as well as enabling fingerprinting of submitted work to be carried out.
The process of syllabus development was based on a needs analysis, as suggested
by Nunan (1988), of a convenience sample of 30 students, targeting their ‘necessities, lacks, and wants’ (Nation and Macalister 2010, p.25) and adapted for the
East Asian context based on the research of Cai (2013). This was combined with
informal one-to-one interviews with all 30 members of the sample group, and an
initial diagnostic test in the form of a written essay. The needs analysis revealed
that in terms of composition skills, students required the most assistance with
essay planning, paraphrasing, referencing, and finding relevant sources of information. Many final year students admitted to plagiarising when they were unable to
put ideas into their own words or were unable to identify the boundaries of utilising others’ material versus academic misconduct. This suggests that although first
year students may require more focussed training on academic misconduct policy
and basic EAP training, the requirements for final year students may be different.
This insight was incorporated into the design of the course.
A final consideration in the design of the programme was the international context of BUV. Academic integrity is far from a universal concept and ignores the
Eastern academic tradition of duplicating material as homage (Stowers and Hummel 2011). This is an important consideration in terms of understanding students’
interpretation of plagiarism, and it is possible that the view of reusing material in
‘homage’ is not seen by all students in this cultural context as a breach of academic integrity. However, research on this area is conflicted, and some authors
suggest that plagiarism is more frequently linked to individual preference rather
than cultural acceptability (Martin 2011). Regardless of this potential cultural paradigm clash, it remains important in this context that the AEM programme explicitly teaches and explains the underlying philosophical foundations of the British
academic system, and the conventions that must be followed to avoid committing
plagiarism.
The needs analysis led to the development of a multidimensional syllabus with the
course goal of raising the awareness of acceptable practices surrounding plagiarism and
academic misconduct, whilst at the same time, developing students’ researching and
writing skills. This is tested by a final written assessment under exam conditions. Students are provided with a set of multiple-choice questions to assess knowledge about
acceptable academic practices, and are also set a writing task. In this task they are given
extended extracts from a variety of sources, including academic and non-academic
Page 6 of 15
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
sources of information with differing degrees of bias, and must tackle an essay
question in which they utilise these sources. This procedure ensures that the essay
written by the student (and subsequently used as a fingerprint) is entirely their
own work,1 and also provides them with the opportunity to demonstrate their ability in every facet of academic writing, including not only grammatical and lexical
accuracy, but also the skills of paragraphing, paraphrasing, referencing, and critical
thinking (as text extracts must be analysed for their impartiality). Alongside the
original exam script is a companion piece, written by the marker, that contains
several key points related to the writer’s ability, along with a band score of 1–9,
which is developed based on a rubric and band score system of English proficiency.
The rubric and band system scores students on grammatical accuracy, coherence,
academic skills (referencing, paragraphing, and synthesis of material), and vocabulary. The marked sample is available for checking by faculty by the time students
submit their summative assignments for their academic modules.
Markers must carry out a check using the writing sample on all high scoring assessments (papers scoring 70% and above), as well as a random selection of 10% of papers
from each set of assessments, with a minimum sample size of six papers. Although all
grading is carried out anonymously, once a paper has been graded, markers are permitted to use the student number to match up with the student name to aid in initial
authorship investigation. All markers are trained how to perform these checks, and this
process is discussed later in the paper.
Following the introduction of this intervention, all students were reminded of the
dangers of plagiarism and new warnings were introduced to all assignment guidelines highlighting the severity of consequences if students were caught plagiarising.
All students were made aware that their writing samples obtained during the AEM
exam would be made available online for faculty and misconduct panels to check
if there were any suspicions regarding their writing. New writing samples are obtained every semester from students, approximately 3 weeks before the assignment
submission period begins in order to reduce the likelihood of significant changes
being seen in the writing styles of students over time.
Methods and analysis of results
Data collection and screening
If any student submission is flagged by a marker as a potential plagiarism or contract
cheating case, a process is initiated by the faculty members which ends in the student
being notified by the administration that that they are required to attend an informal
meeting to discuss their work. Most cases of plagiarism are resolved at this stage and
any penalties recorded. If, after this stage, there are concerns regarding potential contract cheating students are requested to attend an academic misconduct panel and participate in a viva voce of their submission in the presence of both a subject matter
1
Bretag et al. (2018) demonstrate the widespread nature of cheating in university exams and Harper, Bretag
and Rundle (2020) demonstrate the lack of ability of markers to detect this, which raises a question regarding
this statement. However, given the relatively low stakes of this particular assessment, and that it is the
writing style of the student that we are most interested in as opposed to the content, we believe this to not be
of major concern.
Page 7 of 15
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
expert and a misconduct expert. Following the viva, if this panel has remaining suspicions of contract cheating, then the case is escalated to the most serious university
panel for a meeting with the student. This panel will make the final decision as to
whether contract cheating has occurred and will use a wide variety of sources of evidence in making its final decision. These include the writing samples obtained during
the AEM exam, statements from relevant faculty, the previous marks obtained by the
student, results from the initial viva and additional questions which the panel may put
to the student. As the typical penalty for a student found to have utilised any contract
cheating services is a failure of their award, it is the responsibility of the university to
establish proof beyond reasonable doubt in these cases, and no decision is made solely
on the basis of the comparison of the fingerprint with the submitted piece of work. The
procedures used by BUV are set by the awarding body, and there is an appeal process
available to the student.
In February 2020, we conducted an analysis of the plagiarism and contract cheating
cases recorded during this process from the semesters of April 2014 through October
2019 to answer three questions:
1. What is the overall prevalence of plagiarism committed by students at BUV?
2. Has the AEM initiative been successful in reducing plagiarism cases?
3. Has the AEM initiative been successful in reducing detected incidences of contract
cheating?
Before carrying out the analysis, the data was screened in the following way: Firstly, all recorded cases where a misconduct panel determined that no form of plagiarism had occurred in the flagged submission, and therefore gave a verdict of ‘no case to answer’, were
removed. Any incidences where a verdict of ‘poor academic practice’ was given by the panel
solely due to poor referencing practices were also excluded from the results. If one student
had been punished for several plagiarism violations, each incident was counted separately.
The results of this analysis are shown in Table 1.
Overall prevalence of plagiarism and contract cheating
From a total of 12,937 student submissions, analysis of the data revealed 448 plagiarism
offences over the twelve-semesters between April 2014 and October 2019. The percentage of submissions found to have contained some element of plagiarism (excluding
contract cheating cases) ranged between 2.35% and 7.08% each semester, with a mean
percentage of 3.46% across the period of study. As the dataset covers multiple years,
some incidences of plagiarism were from individual students who had committed plagiarism offences over multiple semesters.
With the caveat that it is possible that the study may underestimate plagiarism in the
student body (as it would be unwise to believe that any higher education institution detects 100% of plagiarism cases), the first point to note is that the prevalence of detected
plagiarised submissions is much lower than described in previous studies examining
plagiarism data (as opposed to self-report studies). These studies have revealed mean
rates of plagiarism of 26% (n = 182) (Barret & Malcolm 2006), 26.2% (n = 290) (Walker
2010), and 10.8% (n = 74) (Warn 2007) respectively. Within a specifically Vietnamese
Page 8 of 15
Perkins et al. International Journal for Educational Integrity
Page 9 of 15
(2020) 16:3
Table 1 Descriptive Plagiarism Results at BUV
Semester Number of Number
start date assignment of
submissions detected
cases of
plagiarism
Plagiarism
cases as
percentage
of
assignment
submission
Number
of
detected
Contract
Cheating
cases
Contract
Cheating
cases as
percentage
of plagiarism
cases
Contract
Cheating cases
as percentage
of assignment
submissions
April
2014
642
33
5.14%
1
3.03%
0.16%
October
2014
715
21
2.94%
1
4.76%
0.14%
April
2015
933
37
3.97%
1
2.70%
0.11%
October
2015
847
60
7.08%
8
13.33%
0.94%
April
2016
872
31
3.56%
3
9.69%
0.34%
October
2016
799
55
6.88%
0
0.00%
0.00%
April
2017
994
39
3.92%
1
2.56%
0.10%
October
2017
1064
43
4.04%
0
0.00%
0.00%
April
2018
940
31
3.30%
1
3.23%
0.10%
October
2018
1492
9
0.60%
1
11.11%
0.07%
April
2019
1577
37
2.35%
2
5.41%
0.13%
October
2019
2062
52
2.52%
0
0.00%
0.00%
Total/Average before
AEM:
3137
151
4.81%
11
7.28%
0.35%
Total/Average after
AEM
9800
297
3.03%
8
2.69%
0.08%
Total/Average overall:
12,937
448
3.46%
19
4.24%
0.15%
Results prior
to the
introduction
of the AEM
intervention
Results
following the
introduction
of the AEM
intervention
context, Ba et al. (2016) found that 73% (n = 681) of the submissions tested in their
study had Turnitin similarity indexes of over 20%, and Tran et al. (2017) found that in
their studies of two Vietnamese universities, there were plagiarism levels (defined by
similarity indexes over 24%) of 91.7% and 61.7%.2 Our study differs from those cited
above due to the longitudinal aspects of the data collection period, meaning that a
much larger sample has been obtained for analysis.
The results may indicate that BUV students demonstrate a lower predilection towards plagiarism than the norm, however, they are more likely explained by the large
sample utilised in the study. Even though faculty (Andrews et al. 2007) and students
(Scanlon and Neumann 2002) alike may consider plagiarism to be a significant problem
2
The authors of these papers suggest that this equates to a high probability of plagiarism having occurred,
however text matching software such as Turnitin does not identify plagiarism, it simply identifies similarities
in documents which may indicate that plagiarism has occurred in some form. Just because there is a high
degree of similarity identified, does not necessarily mean that an author has engaged in plagiarism. This may
occur in cases where students have submitted improved versions of papers as part of a continuous
assessment initiative.
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
in their institutions, our results demonstrate that a quantitative analysis of a larger data
sample could reveal a lesser problem than initially imagined. Despite the professed increased propensity of non-native English speaking ‘International’ students to commit
plagiarism (Walker 2010), the low levels of plagiarism indicated in the set of submissions (even though almost all submitting students are NNES) indicates that this suggestion is not universally accurate, a viewpoint echoed by Soto et al. (2004).
Identified levels of contract cheating were overall very low, with a total number of 19
cases over the period, ranging from 0% to 0.94% of submissions per semester, with a
mean percentage of 0.15% of the total number of submissions in the time period. This
prevalence rate is significantly lower than the figures reported by Curtis and Clare et al.
(2017), of 3.5% of students (not submissions) having committed these offences, and by
Harper et al. (2020) of 2.6%. However, as contract cheating cases are more difficult to
detect than more ‘traditional’ plagiarism offences (whether intentional or unintentional), we recognise that the detected cases are unlikely to be fully representative of
the actual levels of contract cheating in the student body.
Effectiveness of the AEM in reducing plagiarism
Prior to the introduction of the AEM intervention in the April 2016 semester, the mean
percentage of submissions found to contain plagiarism was 4.81% (n = 3137) Following
the introduction of the intervention, the mean percentage of submissions found to contain plagiarism dropped to 3.03% (n = 9800); a 37.01% decrease from the results prior
to the intervention. Although the rates of plagiarism were already low prior to the
introduction of the AEM, the further reduction in plagiarism demonstrates that the
intervention has achieved one of its stated aims of educating students about appropriate academic standards and reducing levels of plagiarism. These findings are in line
with those of Soto et al. (2004), and Levine and Pazdernik (2018), demonstrating that
training programmes such as the AEM may help reduce plagiarism.
Effectiveness of the AEM in reducing contract cheating
With regards to the prevalence of contract cheating before and after the AEM intervention, the results do show a reduction in the percentage of contract cheating cases detected, from 0.35% of submissions, to 0.08% of submissions, a 77.14% decrease. With
the assumption that the decrease in identified cases is not due to any decrease in the
ability of markers to detect these (given the additional training that occurred), this apparent reduction in contract cheating may be due to several factors or a combination
of these factors. Firstly, an improvement in student knowledge of appropriate academic
standards may have increased the awareness of what is expected of them in a university
setting. Secondly, knowing that there will be increased scrutiny of their submissions regarding contract cheating, and the knowledge that samples of their work are available
for checking may have increased the perceived risk of contract cheating. Thirdly, any
reduction may be due to real improvements in the EAP abilities of the students. As the
English language ability of students has been shown to be linked to plagiarism, the increased EAP skills of the students may have reduced the perceived need to obtain contract cheating services.
Page 10 of 15
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
However, the relative rarity of contract cheating as a percentage of submissions, and
the very small total number of cases over the entire period of investigation do not allow
us to make any firm conclusions as to the effectiveness of this intervention on the reduction of detected cases of contract cheating. The relatively large number of cases
identified in the October 2015 semester compared to other semesters, and the limited
periods of data collection prior to the introduction of the intervention have likely made
a comparison of contract cheating data before and after the intervention untenable.
Despite this, we believe that continuing with this initiative is important. By continuing to educate students in academic writing skills and expected academic practice, as
well as establishing a protocol of collecting and checking student writing samples, we
can reduce plagiarism, provide a disincentive for students who may seek to engage in
contract cheating, and obtain a valuable data source for the further investigation of any
such detected cases.
Discussion
Although the preliminary results of this intervention are promising, any benefits of an
intervention such as the AEM must be considered alongside an understanding of the
numerous challenges of any intervention involving the collection and comparison of
student writing samples.
Firstly, faculty carrying out marking of assessments must know which submissions
are suspicious, and therefore warrant checking against the student fingerprints. In order
to do this on an ad-hoc basis, some prior expectations as to the quality of the submitted work must be held. Although some faculty may be aware of the general quality of
work they are expecting from a set of assignment submissions, the use of anonymous
marking means that as long as the quality of work is generally in line with the entire
cohort, markers may not necessarily detect a clear difference between contracted and
legitimate assignments. As the size of student cohorts increases, this leads to a wider
spread of both marks and writing styles being expected, and the likelihood of faculty
having initial suspicions is further reduced, therefore compounding this problem. For
institutions which have a high concentration of NNES, an additional challenge which
may be encountered is that of fellow NNES students being hired for contract cheating,
as opposed to ‘professional’ native English speaking contract cheating services. This
sub-type of contract cheating may be more appealing to some students, as fellow NNES
students may have similar writing styles and have completed the same, or similar classes. This means that the differences between these submissions and fingerprinted work
may not be as apparent when compared to the results obtained from professional contract cheating websites.
Secondly, faculty may not always accurately detect cases of contract cheatings, even if
a submission is checked for consistency against the fingerprinted sample. Markers will
likely have differing skill levels in their ability to accurately detect differences in writing
styles between a submission and a fingerprint and some cases may be missed. Therefore, any institution considering the introduction of fingerprinting must be aware of
the potential increase in false negatives occurring due to some submissions not being
investigated appropriately and implement training programmes to address this. This
method also does not address cases where a writing sample would not be helpful in determining authorship of an assessment, such as computer coding or artwork.
Page 11 of 15
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
Conversely, the potential risk of false positives must also be considered. If faculty members flag a submission as a possible case of contract cheating due to a change in writing
styles between a fingerprint and a submitted assignment, there must be a fair and consistent
approach to investigating these cases fully. Markers must also be aware that improvements
in English language abilities and writing styles are likely to be seen when comparing what
can be produced under timed, exam conditions, compared to a take-home assignment, as
students will have had time to proofread, plan, edit, and check their final submission.
Research by Dawson et al. (2019) has indicated that the training of markers can improve
their ability to identify contract cheating, therefore to minimise the problems stated above,
all faculty members receive training on how to assess work for potential cases of contract
cheating, and assessments are only graded by faculty who have completed this training.
When checking for potential evidence of contract cheating, markers are asked to investigate several things. The initial step is an overall comparison of the student’s writing in the
unsupervised, external assessment with the sample produced under exam conditions. If a
student produced a flawless submission in adherence to all academic standards, but during the AEM written exam had received a low score in this area, or the overall standards
of English were very different, this might indicate a second or alternate author.
Other techniques based on forensic linguistics are also used. These include comparing the submission with the sample to see if there are mismatches between the writer’s
unique choice of words and individual style of writing (idiolect), and their tendency to
use certain constructions (coselection and lexical choice) (Coulthard, 2010).
Markers are also trained to identify other potential indicators of contract cheating, either of the whole document, or of partial sections. These indicators include changes in
formatting or styles of writing in different sections of the text, as well as examining the
document properties for any suspicious elements such as very short editing times (indicative of content being copied into a brand new document before submission), or whether
there are inconsistences in the named author of the document. Even the choice of sources
used or not used in a submission could raise suspicions: for example, not citing key
sources indicated during class sessions. By training all markers how to check for contract
cheating, making comparisons between the sample and submissions part of the marking
procedure, and carrying this procedure out on a regular basis, it is our hope that we can
improve the capacity of markers to identify instances of contract cheating.
Although individually none of the above indicators would ever be considered conclusive evidence of contract cheating, and the fingerprinting method has significant limitations as discussed, all the above can be employed by a panel investigating whether
academic misconduct may have occurred.
Reducing and detecting plagiarism and contract cheating requires a holistic approach
to be taken (McCabe 2005; Morris 2018). We believe that initiatives such as the AEM
programme which aim to improve the English capabilities of students, educate them on
expected academic conduct practices, and discourage contract cheating fit this definition, and our results demonstrate how doing so may assist with this goal.
Conclusion
This paper has discussed the introduction of an intervention designed to improve the academic writing skills of students, reduce levels of plagiarism, and provide a tool to assist in the
detection of contract cheating by capturing a ‘fingerprint’ of a writing sample.
Page 12 of 15
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
The data collected over the course of 12 semesters show a 37.01% decrease in the
rate of detected plagiarism following the introduction of the AEM intervention, and
suggest that the introduction of a programme like this could help institutions with reducing plagiarism.
The levels of detected contract cheating cases did decrease following the introduction
of the intervention, however, the very small numbers of detected contract cheating
cases both pre and post intervention mean that we cannot make a conclusion regarding
the use of collecting writing samples as an effective tool to help detect these cases. We
have recognised the limitations of this fingerprinting exercise and suggested potential
mitigations to these through faculty training.
Despite using a large database of student submissions (n = 12,937), the data shows
surprisingly low levels (3.36%) of detected plagiarism overall, which do not match the
high prevalence of plagiarism that has previously been recorded in the literature, however, by analysing detected cases of plagiarism data as opposed to student self-reported
data, it is possible that this study may have underestimated plagiarism in the student
body. Previous studies have used much smaller samples of student submissions in their
analysis, which suggests that different results may be obtained when examining larger
sets of data. We therefore recommend that further research should try to use longitudinal university or department wide databases for analysis purposes, as opposed to individual class submissions, as this may give a more accurate representation of the
prevalence of plagiarism in an institution.
The issue of academic misconduct is becoming increasingly more visible to the general public. In the United Kingdom, 40 university leaders have written to the Minister
of State for Universities, Science, Research and Innovation demanding a ban on companies offering contract cheating services (BBC News 2020), and the Advertising Standards Authority has already banned misleading advertisements from one of these
companies (Advertising Standards Agency, 2019). We recognise that the costs required
for an intervention strategy such as the AEM may pose a barrier to entry for many institutions, but given the increasing focus on academic integrity, this is not an issue that
universities can afford to ignore. We therefore recommend the use of similar initiatives
in other institutions as a potential method to educate students about expected academic practice, reduce plagiarism, and believe the potential benefits justify the challenges of introducing such an initiative.
Abbreviations
AEM: Academic English Masterclass; BUV: British University Vietnam; EAP: English for Academic Purposes; NNES: NonNative English speaker
Acknowledgements
The authors would like to thank Louise Cotrel-Gibbons for her kind support in offering suggestions for improvement
and proof reading of this article.
Availability of data and data materials
Data not available due to confidentiality of student information.
Authors’contributions
All authors contributed to this work. The percentage of contributions is indicated by the order of authorship provided.
The author(s) read and approved the final manuscript.
Funding
The authors received no funding for this work.
Page 13 of 15
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
Competing interests
All authors were employed by the university in question during the time of authorship of the paper.
Author details
1
British University Vietnam, BUV Ecopark Campus, Ecopark Township, Hung Yen, Vietnam. 2Duy Tan University, 3 Quang
Trung, Danang City, Vietnam.
Received: 23 September 2019 Accepted: 24 March 2020
References
Abasi A, Graves B (2008) Academic literacy and plagiarism: conversations with international graduate students and
disciplinary professors. J Engl Acad Purp 7:221–233. https://doi.org/10.1016/j.jeap.2008.10.010
Advertising Standards Authority (2019) ASA ruling on the Oxbridge research group ltd t/a Oxbridge essays. In: Asa.org.uk.
https://www.asa.org.uk/rulings/the-oxbridge-research-group-ltd-a18-458914.html. Accessed 17 Mar 2020
Amigud A, Lancaster T (2019) I will pay someone to do my assignment: an analysis of market demand for contract cheating
services on twitter. Assess Eval High Educ. https://doi.org/10.1080/02602938.2019.1670780
Andrews G, Smith A, Henzi D, Demps E (2007) Faculty and student perceptions of academic integrity at US and Canadian
dental schools. J Dent Educ 71:1027–1039
Barrett R, Malcolm J (2006) Embedding plagiarism education in the assessment process. Int J Educ Integr 2:38–45
BBC News (2018) Unis demand ban on essay-writing firms. In: bbc.com/news. https://www.bbc.com/news/education-4564
0236. Accessed 21 Mar 2020
Belter R, du Pré A (2009) A strategy to reduce plagiarism in an undergraduate course. Teach Psychol 36:257–261. https://doi.
org/10.1080/00986280903173165
Bennett K, Behrendt L, Boothby J (2011) Instructor perceptions of plagiarism. Teach Psychol 38:29–35. https://doi.org/10.1177/
0098628310390851
Bennett R (2005) Factors associated with student plagiarism in a post-1992 university. Assessment Evaluation Higher Educ 30:
137–162. https://doi.org/10.1080/0260293042000264244
Bradley E (2015) Using computer simulations and games to prevent student plagiarism. J Educ Technol Syst 44:240–252.
https://doi.org/10.1177/0047239515617653
Bretag T (2007) The emperor's new clothes: yes, there is a link between English language competence and academic
standards. People Place 15:13–21
Bretag T, Harper R, Burton M, Ellis C, Newton P, Rozenberg P, Saddiqui S, van Haeringen K (2019) Contract cheating: a survey of
Australian university students. Stud High Educ 44:1837–1856. https://doi.org/10.1080/03075079.2018.1462788
Cai L (2013) Students’ perceptions of academic writing: a needs analysis of EAP in China. Language Education in Asia 4:5–22.
https://doi.org/10.5746/leia/13/v4/i1/a2/cai
Carroll J (2007) A handbook for deterring plagiarism in higher education. Oxford Centre for Staff Learning and Development, Oxford
Chen T, Ku TNK (2007) EFL students: factors contributing to online plagiarism. Student Plagiarism in an Online World:
Problems and Solutions: Problems and Solutions
Chen Y, Van Ullen M (2011) Helping international students succeed academically through research process and plagiarism
workshops. Coll Res Libr 72:209–235. https://doi.org/10.5860/crl-117rl
Clare J, Walker S, Hobson J (2017) Can we detect contract cheating using existing assessment data? Applying crime
prevention theory to an academic integrity issue. Int J Educ Integrity. https://doi.org/10.1007/s40979-017-0015-4
Clarke R, Lancaster T (2007) Establishing a systematic six-stage process for detecting contract cheating. The Second
International Conference on Pervasive Computing and Applications
Coulthard M (2010) Forensic Linguistics: the application of language description in legal contexts. Langage et société 132 (2):15.
Curtis G, Clare J (2017) How prevalent is contract cheating and to what extent are students repeat offenders? J Acad Ethics
15:115–124. https://doi.org/10.1007/s10805-017-9278-x
Curtis G, Gouldthorp B, Thomas E, O'Brien G, Correia H (2013) Online academic-integrity mastery training may improve
Students' awareness of, and attitudes toward, plagiarism. Psychology Learning Teaching 12:282–289. https://doi.org/10.
2304/plat.2013.12.3.282
Davis L (2011) Arresting student plagiarism: are we investigators or educators? Bus Commun Q 74:160–163. https://doi.org/
10.1177/1080569911404053
Dawson, P. Sutherland-Smith, W Ricksen, M. (2019). Can software improve marker accuracy at detecting contract cheating? A
pilot study of the Turnitin authorship investigate alpha. Assessment & Evaluation in Higher Education. Advance online
publication DOI: https://doi.org/10.1080/02602938.2019.1662884d
Dawson P, Sutherland-Smith W (2018) Can training improve marker accuracy at detecting contract cheating? A
multi-disciplinary pre-post study. Assess Eval High Educ 44:715–725. https://doi.org/10.1080/02602938.2018.1531109
Ba DK, Ba DK, Lam QD, Le DTBA, Nguyen P, Nguyen PL, Nguyen PQ, Pham QL (2016) Student plagiarism in higher education in
Vietnam: an empirical study. Higher Educ Res Dev 36:934–946. https://doi.org/10.1080/07294360.2016.1263829
Ellis C, Zucker I, Randall D (2018) The infernal business of contract cheating: understanding the business processes and
models of academic custom writing sites. Int J Educ Integr. https://doi.org/10.1007/s40979-017-0024-3
Fazel I, Kowkabi N (2014) Students’ source misuse in language classrooms: sharing experiences. TESL Can J 31:86. https://doi.
org/10.18806/tesl.v31i1.1168
Goh E (2015) Exploring underlying motivations behind extreme cases of plagiarism in tourism and hospitality education. J
Hospitality Tourism Educ 27:80–84. https://doi.org/10.1080/10963758.2015.1033101
Guo X (2011) Understanding student plagiarism: an empirical study in accounting education. Accounting Education 20:17–
37. https://doi.org/10.1080/09639284.2010.534577
Harper R, Bretag T, Rundle K (2020) Detecting contract cheating: examining the role of assessment type. Higher Education
Research & Development 1-16. https://doi.org/10.1080/07294360.2020.1724899
Page 14 of 15
Perkins et al. International Journal for Educational Integrity
(2020) 16:3
Heckler N, Forde D, Bryan C (2012) Using writing assignment designs to mitigate plagiarism. Teach Sociol 41:94–105. https://
doi.org/10.1177/0092055x12461471
Hoanca B (2019) Combating plagiarism: a three-pronged approach to reducing prevalence in higher education. In: Scholarly
ethics and publishing: breakthroughs in research and practice 532–548. IGI Global, Hershey
Jones D (2011) Academic dishonesty: are more students cheating? Bus Commun Q 74:141–150. https://doi.org/10.1177/
1080569911404059
Jones M, Sheridan L (2014) Back translation: an emerging sophisticated cyber strategy to subvert advances in ‘digital age’
plagiarism detection and prevention. Assess Eval High Educ 40:712–724. https://doi.org/10.1080/02602938.2014.950553
Kakkonen T, Mozgovoy M (2010) Hermetic and web plagiarism detection Systems for Student Essays—an Evaluation of the
state-of-the-art. J Educ Comput Res 42:135–159. https://doi.org/10.2190/ec.42.2.a
Koppel M, Winter Y (2014) Determining if two documents are written by the same author. J Assoc Inf Sci Tech 65:178–187.
Lancaster T, Culwin F (2007) Preserving academic integrity? Fighting against nonoriginality agencies. Br J Educ Technol 38:
153–157. https://doi.org/10.1111/j.1467-8535.2006.00491.x
Levine J, Pazdernik V (2018) Evaluation of a four-prong anti-plagiarism program and the incidence of plagiarism: a five-year
retrospective study. Assess Eval High Educ 43:1094–1105. https://doi.org/10.1080/02602938.2018.1434127
Li Y (2015) Academic staff's perspectives upon student plagiarism: a case study at a university in Hong Kong. Asia Pacific J
Educ 35:14–26. https://doi.org/10.1080/02188791.2013.835710
Lines L (2016) Ghostwriters guaranteeing grades? The quality of online ghostwriting services available to tertiary students in
Australia. Teach High Educ 21:889–914. https://doi.org/10.1080/13562517.2016.1198759
Malesky L, Baley J, Crow R (2016) Academic dishonesty: assessing the threat of cheating companies to online education. Coll
Teach 64:178–183. https://doi.org/10.1080/87567555.2015.1133558
Marshall S, Garry M (2006). NESB and ESB students' attitudes and perceptions of plagiarism. International Journal For
Educational Integrity, 2:26–37.
Martin D (2011) Culture and unethical conduct: understanding the impact of individualism and collectivism on actual
plagiarism. Manag Learn 43:261–273. https://doi.org/10.1177/1350507611428119
McCabe D (2005) Cheating among college and university students: a north American perspective. Int J Educ Integr 1:1–11
McKeever L (2006) Online plagiarism detection services—saviour or scourge? Assess Eval High Educ 31:155–165. https://doi.
org/10.1080/02602930500262460
McLafferty C, Foust K (2004) Electronic plagiarism as a college Instructor's nightmare—prevention and detection. J Educ Bus
79:186–190. https://doi.org/10.3200/joeb.79.3.186-190
Morris E (2018) Academic integrity matters: five considerations for addressing contract cheating. International journal for
educational integrity 14. https://doi.org/10.1007/s40979-018-0038-5
Mozgovoy M, Kakkonen T, Cosma G (2010) Automatic student plagiarism detection: future perspectives. J Educ Comput Res
43:511–531. https://doi.org/10.2190/ec.43.4.e
Nation P, Macalister J (2010) Language curriculum design. Routledge, London
Nunan D (1988) Syllabus Design. Oxford University Press, Oxford
O'Donnell K (2011) Linking multimodal communication and feedback loops to reinforce plagiarism awareness. Bus Commun
Q 74:216–220. https://doi.org/10.1177/1080569911404404
Park C (2004) Rebels without a clause: towards an institutional framework for dealing with plagiarism by students. J Furth
High Educ 28:291–306. https://doi.org/10.1080/0309877042000241760
Pennycook A (1996) Borrowing Others' words: text, ownership, memory, and plagiarism. TESOL Q 30:201. https://doi.org/10.2307/
3588141
Perkins M, Gezgin U, Roe J (2018) Understanding the relationship between language ability and plagiarism in nonnative English speaking business students. J Acad Ethics 16:317–328. https://doi.org/10.1007/s10805-018-9311-8
Probett C (2011) Plagiarism prevention. Bus Commun Q 74:170–172. https://doi.org/10.1177/1080569911404054
Rundle K, Curtis G, Clare J (2019) Why students do not engage in contract cheating. Front Psychol. https://doi.org/10.3389/
fpsyg.2019.02229
Scanlon P, Neumann D (2002) Internet plagiarism among college students. J Coll Stud Dev 43:374–385
Scheg A (2012) The impact of Turnitin to the student-teacher relationship. J Interdisciplinary Stud Educ 2:29–38
Soto J, Anand S, McGee E (2004) Plagiarism avoidance. J Coll Sci Teach 33:42
Stetter ME (2013) Teaching students about plagiarism using a web-based module. J Furth High Educ 37:675–693
Stowers R, Hummel J (2011) The use of technology to combat plagiarism in business communication classes. Bus Commun
Q 74:164–169. https://doi.org/10.1177/1080569911404406
Tran U, Huynh T, Nguyen H (2017) Academic integrity in higher education: the case of plagiarism of graduation reports by
undergraduate seniors in Vietnam. JAcad Ethics 16:61–69. https://doi.org/10.1007/s10805-017-9279-9
Walker C, White M (2014) Police, design, plan and manage: developing a framework for integrating staff roles and institutional policies
into a plagiarism prevention strategy. J High Educ Policy Manag 36:674–687. https://doi.org/10.1080/1360080x.2014.957895
Walker J (2010) Measuring plagiarism: researching what students do, not what they say they do. Stud High Educ 35:41–59.
https://doi.org/10.1080/03075070902912994
Wallace M, Newton P (2014) Turnaround time and market capacity in contract cheating. Educ Stud 40:233–236. https://doi.
org/10.1080/03055698.2014.889597
Warn J (2007) Plagiarism software: no magic bullet!. Higher Education Research & Development 25 (2):195–208. https://doi.
org/10.1080/07294360600610438
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Page 15 of 15