essay on plagiarism and students in higher education

• Original article
• Open access
• Published: 01 May 2020

Reducing plagiarism through academic misconduct education

• Mike Perkins   ORCID: orcid.org/0000-0002-4479-4565 1 ,
• Ulas Basar Gezgin 2 &
• Jasper Roe 1  

International Journal for Educational Integrity volume  16 , Article number:  3 ( 2020 ) Cite this article

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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.

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.

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, well-established 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 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, 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 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 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 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, Footnote 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 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:

What is the overall prevalence of plagiarism committed by students at BUV?

Has the AEM initiative been successful in reducing plagiarism cases?

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 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%. Footnote 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 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.

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.

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.

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.

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.

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.

Bretag et al. ( 2018 ) demonstrate the widespread nature of cheating in university exams and Harper et al. (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.

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.

Abbreviations

Academic English Masterclass

British University Vietnam

English for Academic Purposes

Non-Native English speaker

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Student Plagiarism in Higher Education

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Student Plagiarism in Higher Education is a crucial read for any university teacher concerned about plagiarism. It provides the tools and information needed to assess this often complex international phenomenon constructively and effectively from a variety of angles, and provides a framework for further discussion and research.

Each chapter poses a question about an essential aspect of plagiarism and examines the central theoretical, ethical and technical questions which surround it. Providing a unique perspective on the topic of academic plagiarism, this book:

• addresses questions which are vexing in teaching practice, but for which ready answers are not available in professional skills development materials;
• relates plagiarism to wider issues of learning and intellectual development;
• collates the thinking of international leading experts on the topic of plagiarism from different areas of the academy.

Student Plagiarism in Higher Education provides an excellent insight which thoroughly interrogates all aspects of the plagiarism argument. Theoretically based and carefully considered contributions from international experts ensure that this volume is an invaluable asset to anyone wishing to read more, learn more and think more about plagiarism.

TABLE OF CONTENTS

Chapter chapter 1 | 11  pages, why so many questions about plagiarism, chapter chapter 2 | 16  pages, can plagiarism be defined, chapter chapter 3 | 19  pages, how much can you copy, chapter chapter 4 | 15  pages, is student plagiarism still a serious problem in universities today, chapter chapter 5 | 12  pages, why does plagiarism detection software not find all plagiarism, chapter chapter 6 | 15  pages, can we use plagiarism detection services responsibly, chapter chapter 7 | 16  pages, how does intertextuality inform plagiarism, chapter chapter 8 | 18  pages, shouldn't our expectations of students' and academics' intertextuality practices differ, chapter chapter 9 | 17  pages, are we making our students plagiarize, chapter chapter 10 | 17  pages, what really is the relationship between plagiarism and culture, chapter chapter 11 | 11  pages, so what should we do.

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Plagiarism in higher education across nations: a case of language students

• Majid Farahian , Farnaz Avarzamani , M. Rezaee
• Published 15 February 2021
• Education, Linguistics
• Journal of Applied Research in Higher Education

3 Citations

Plagiarism awareness efforts, students’ ethical judgment and behaviors: a longitudinal experiment study on ethical nuances of plagiarism in higher education, perception, prevalence and prevention of academic dishonesty: evidence from a middle east country, how do researchers perceive research misbehaviors a case study of indian researchers, 51 references, plagiarism in theses: a nationwide concern from the perspective of university instructors, on iranian efl undergraduate students’ perceptions of plagiarism, taiwanese college students’ perceptions of plagiarism: cultural and educational considerations, an investigation of iranian efl masters students' perceptions of plagiarism, plagiarism among local and asian students in australia, cultural values, plagiarism, and fairness: when plagiarism gets in the way of learning, the problem of plagiarism in academic culture, reducing unintentional plagiarism amongst international students in the biological sciences: an embedded academic writing development programme, cultural constructions of plagiarism in student writing: teachers’ perceptions and responses, plagiarism: academic dishonesty or 'blind spot' of multicultural education, related papers.

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‘It’s not fair’: policy discourses and students’ understandings of plagiarism in a New Zealand university

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Plagiarism is a concept that is difficult to define. Although most higher education institutions have policies aimed at minimising and addressing student plagiarism, little research has examined the ways in which plagiarism is discursively constructed in university policy documents, or the connections and disconnections between institutional and student understandings of plagiarism in higher education. This article reports on a study that explored students’ understandings of plagiarism in relation to institutional plagiarism discourses at a New Zealand university. The qualitative study involved interviews with 21 undergraduate students, and analysis of University plagiarism policy documents. The University policy documents revealed moral and regulatory discourses. In the interviews, students predominantly drew on ethico-legal discourses, which reflected the discourses in the policy documents. However, the students also drew on (un)fairness discourses, confusion discourses, and, to a lesser extent, learning discourses. Notably, learning discourses were absent in the University policy. Our findings revealed tensions between the ways plagiarism was framed in institutional policy documents, and students’ understandings of plagiarism and academic writing. We suggest that, in order to support students’ acquisition of academic writing skills, plagiarism should be framed in relation to ‘learning to write’, rather than as a moral issue.

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Factors influencing plagiarism in higher education: A comparison of German and Slovene students

1 Department of Personnel and Education, Faculty of Organizational Sciences, University of Maribor, Kranj, Slovenia

Matjaž Perc

2 Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia; School of Electronic and Information Engineering, Beihang University, Beijing, China

Barbara Lämmlein

3 Department of Economics and Law, Frankfurt University of Applied Sciences, Frankfurt, Germany

Janja Jerebic

4 Department of Methodology, Faculty of Organizational Sciences, University of Maribor, Kranj, Slovenia

Iztok Podbregar

Polona Šprajc, associated data.

All relevant data are within the paper and its Supporting Information files.

Over the past decades, plagiarism has been classified as a multi-layer phenomenon of dishonesty that occurs in higher education. A number of research papers have identified a host of factors such as gender, socialisation, efficiency gain, motivation for study, methodological uncertainties or easy access to electronic information via the Internet and new technologies, as reasons driving plagiarism. The paper at hand examines whether such factors are still effective and if there are any differences between German and Slovene students’ factors influencing plagiarism. A quantitative paper-and-pencil survey was carried out in Germany and Slovenia in 2017/2018 academic year, with a sample of 485 students from higher education institutions. The major findings of this research reveal that easy access to information-communication technologies and the Web is the main reason driving plagiarism. In that regard, there are no significant differences between German and Slovene students in terms of personal factors such as gender, motivation for study, and socialisation. In this sense, digitalisation and the Web outrank national borders.

Introduction

Many of those who teach in higher education have encountered the phenomenon of plagiarism as a form of dishonesty in the classroom. According to the Oxford English Dictionary online 2017, the term plagiarism is defined as ‘the practice of taking someone else's work or ideas and passing them off as one's own’. Perrin, Larkham and Culwin define plagiarism as the use of an author's words, ideas, reflections and thoughts without proper acknowledgment of the author [ 1 – 3 ]. Koul et al. define plagiarism as a form of cheating and theft since in cases of plagiarism one person takes credit for another person’s intellectual work [ 4 ]. According to Fishman, ‘Plagiarism occurs when someone: 1) uses words, ideas, or work products; 2) attributable to another identifiable person or source; 3) without attributing the work to the source from which it was obtained; 4) in a situation in which there is a legitimate expectation of original authorship; 5) in order to obtain some benefit, credit, or gain which need not be monetary’ [ 5 ]. But why do students use someone else's words or ideas and pass them on as their own? Which factors influence this behaviour? That is the main focus of our research, to discover the factors influencing plagiarism and see if there are any differences between German and Slovene students.

Koul et al. pointed out that particular circumstances or events should be considered in the definition of plagiarism since plagiarism may vary across cultures and societies [ 4 ]. Hall has described Eastern cultures (the Middle East, Asia, Africa, South America) and Western cultures (North America and much of Europe) using the idea of ‘context’, which refers to the framework, background, and surrounding circumstances in which an event takes place [ 6 ]. Western societies are generally ‘low context’ societies. In other words, people in Western societies play by external rules (e.g., honour codes against plagiarism), and decisions are based on logic, facts, and directness. Eastern societies are generally ‘high context’ societies, meaning that people in Eastern societies put strong emphasis on relational concerns, and decisions are based on personal relationships. Nisbett et al. have suggested that differences between Westerners and Easterners may arise from people being socialised into different worldviews, cognitive processes and habits of mind [ 7 ]. In Germany, there has been ongoing reflection on academic plagiarism and other dishonest research practices since the late 19th century [ 8 ]. However, according to Ruiperez and Garcia-Cabrero, in Germany, 2011 became a landmark year with the appearance of an extensive public debate about plagiarism—brought back into the limelight because of an investigation into the incumbent German Defence Minister’s doctoral thesis [ 9 ]. Aside from the numerous cases of plagiarism detected in academic work since 2011, several initiatives have enriched the debate on academic plagiarism. For example, the development of a consolidated cooperative textual research methodology using a specific Wiki called ‘VroniPlag’ has made Germany one of the most advanced European countries in terms of combating these practices. Similar to Germany, Slovenia has also paid increased attention to plagiarism in recent years. The debate about plagiarism became public after it was discovered that certain Slovene politicians had resorted to academic plagiarism. Today, universities in Slovenia use a variety of tools (Turnitin, plagiarism plug-ins for Moodle, plagiarisma.net, etc.) in order to detect plagiarism. The focus of this research is to investigate the factors influencing plagiarism and if there are any differences between Slovene and German students’ factors influencing plagiarising. The research questions (RQ) of the study were divided into three groups:

• RQ group 1: Which factors influence plagiarism in higher education?
• RQ group 2: Are there any differences between male and female students regarding factors influencing plagiarism? Are the factors influencing plagiarism connected with specific areas of study (technical sciences, social sciences, natural sciences)?
• RQ group 3: Does the students’ motivation affect their factors influencing plagiarism? Are there any differences between male and female students regarding this?

In addition, for all three research question groups, we also wanted to know if there were any differences between the German and Slovene students.

Theoretical background

Plagiarism is a highly complex phenomenon and, as such, it is likely that there is no single explanation for why individuals engage in plagiarist behaviours [ 10 ]. The situation is often complex and multi-dimensional, with no simple cause-and-effect link [ 11 ].

McCabe et al. noted that individual factors (e.g. gender, average grade, work ethic, self-esteem), institutional factors (e.g., faculty response to cheating, sanction threats, honour codes) and contextual factors (e.g., peer cheating behaviours, peer disapproval of cheating behaviours, perceived severity of penalties for cheating) influence cheating behaviour [ 12 ]. Giluk and Postlethwaite also related individual characteristics and situational factors to cheating—individual characteristics such as gender, age, ability, personality, and extracurricular involvement; and situational factors such as honour codes, penalties, and risk of detection [ 13 ]. The study of Jereb et al. also revealed that specific individual characteristics pertaining to men and women influence plagiarism [ 14 ]. Newstead et al. suggested that gender differences (plagiarism is more frequent among boys), age differences (plagiarism is more frequent among younger students), and academic performance differences (plagiarism is more frequent among lower performers) are specific factors for plagiarism [ 15 ]. Gerdeman stated that the following five student characteristic variables are frequently related to the incidence of dishonest behaviour: academic achievement, age, social activities, study major, and gender [ 16 ].

One of the factors influencing plagiarism could be that students do not have a clear understanding of what constitutes plagiarism and how it can be avoided [ 17 , 18 ]. According to Hansen, students don’t fully understand what constitutes plagiarism [ 19 ]. Park states genuine lack of understanding as one of the reasons for plagiarism. Some students plagiarise unintentionally, when they are not familiar with proper ways of quoting, paraphrasing, citing and referencing and/or when they are unclear about the meaning of ‘common knowledge’ and the expression ‘in their own words’ [ 11 ].

Furthermore, it is important to remember that, in our current day and age, information is easily accessed through new technologies. In addition, as Koul et al. have stated, the belief that we as people have greater ownership of information than we have paid for may influence attitudes towards plagiarism [ 4 ]. Many other authors have also stated that the Internet has increased the potential for plagiarism, since information is easily accessed through new technologies [ 14 , 20 , 21 , 22 ]. Indeed, the Internet grants easy access to an enormous amount of knowledge and learning materials. This provides an opportunity for students to easily cut, paste, download and plagiarise information [ 21 , 23 ]. Online resources are available 24/7 and enable a flood of information, which is also constantly updated. Given students' ease of access to both digital information and sophisticated digital technologies, several researchers have noted that students may be more likely to ignore academic ethics and to engage in plagiarism than would otherwise be the case [ 24 ].

In a study of the level of plagiarism in higher education, Tayraukham found that students with performance goals were more likely to indulge in plagiarism behaviours than students who wanted to achieve mastery of a particular subject [ 25 ]. Most of the students plagiarised in order to provide the right responses to study questions, with the ultimate goal of getting higher grades—rather than gaining expertise in their subjects of study. Anderman and Midgley observed that a relatively higher performance-oriented classroom climate increases cheating behaviour; while a higher mastery-oriented classroom climate decreases cheating behaviour [ 26 ]. Park also claimed that one of the reasons that students plagiarise is efficiency gain, that is, that students plagiarise in order to get a better grade and save time [ 11 ]. Songsriwittaya et al. stated that what motivates students to plagiarise is the goal of getting good grades and comparing their success with that of their peers [ 27 ]. The study of Ramzan et al. also revealed that the societal and family pressures of getting higher grades influence plagiarism [ 21 ]. Such pressures sometimes push students to indulge in unfair means such as plagiarism as a shortcut to performing better in exams or producing a certain number of publications. Engler et al. and Hard et al. tended to agree with this idea, stating that plagiarism arises out of social norms and peer relationships [ 28 , 29 ]. Park also stated that there are many calls on students’ time, including peer pressure for maintaining an active social life, commitment to college sports and performance activities, family responsibilities, and pressure to complete multiple work assignments in short amounts of time [ 11 ]. Šprajc et al. agreed that students are under an enormous amount of pressure from family, peers, and instructors, to compete for scholarships, admissions, and, of course, places in the job market [ 30 ]. This affects students’ time management and can lead to plagiarism. In addition to time pressures, Franklin-Stokes and Newstead found another six major reasons given by students to explain cheating behaviours: the desire to help a friend, a fear of failure, laziness, extenuating circumstances, the possibility of reaping a monetary reward, and because ‘everybody does it’ [ 31 ].

Another common reason for plagiarism is the poor preparation of lecture notes, which can lead to the inadequate referencing of texts [ 32 ]. Šprajc et al. found out that too many assignments given within a short time frame pushes students to plagiarise [ 30 ]. Poor explanations, bad teaching, and dissatisfaction with course content can also drive students to plagiarise. Park exposed students’ attitudes towards teachers and classes [ 11 ]. Some students cheat because they have negative attitudes towards assignments and tasks that teachers believe to have meaning but that they don’t [ 33 ]. Cheating tends to be more common in classes where the subject matter seems unimportant or uninteresting to students, or where the teacher seemed disinterested or permissive [ 16 ].

Park mentioned students’ academic skills (researching and writing skills, knowing how to cite, etc.) as another reason for plagiarism [ 11 ]. New students and international students whose first language is not English need to transition to the research culture by understanding the necessity of doing research, and the practice and skills required to do so, in order to avoid unintentional plagiarism [ 21 ]. According to Park to some students, plagiarism is a tangible way of showing dissent and expressing a lack of respect for authority [ 11 ]. Some students deny to themselves that they are cheating or find ways of legitimising their behaviour by passing the blame on to others. Other factors influencing plagiarising are temptation and opportunity. It is both easier and more tempting for students to plagiarise since information has become readily accessible with the Internet and Web search tools, making it faster and easier to find information and copy it. In addition, some people believe that since the Internet is free for all and a public domain, copying from the Internet requires no citation or acknowledgement of the source [ 34 ]. To some students, the benefits of plagiarising outweigh the risks, particularly if they think there is little or no chance of getting caught and there is little or no punishment if they are indeed caught [ 35 ].

One of the factors influencing plagiarism could be also higher institutions’ attitudes towards plagiarism, that is, whether they have clear policies regarding plagiarism and its consequences or not. The effective communication of policies, increased student awareness of penalties, and enforcement of these penalties tend to reduce dishonest behaviour [ 36 ]. Ramzan et al. [ 21 ] mentioned the research of Razera et al., who found that Swedish students and teachers need training to understand and avoid plagiarism [ 37 ]. In order to deal with plagiarism, teachers want and need a clear set of policies regarding detection tools, and extensive training in the use of detection software and systems. According to Ramzan et al., Dawson and Overfield determined that students are aware that plagiarism is bad but that they are not clear on what constitutes plagiarism and how to avoid it [ 21 , 38 ]. In Dawson and Overfield’s study, students required teachers to also observe the rules set up to avoid plagiarism and be consistently kept aware of plagiarism—in order to enforce the university’s resolve to control this academic misconduct.

According to this literature review and our experiences in higher education teaching, we determined that the following factors influence plagiarism: students’ individual factors, information-communication technologies (ICT) and the Web, regulation, students’ academic skills, teaching factors, different forms of pressure, student pride, and other reasons. The statements used in the instrument we developed, and the results of our research are presented in the following chapters.

Participants

The paper-and-pencil survey was carried out in the 2017/18 academic year at the University of Maribor in Slovenia and at the Frankfurt University of Applied Sciences in Germany. Students were verbally informed of the nature of the research and invited to freely participate. They were assured of anonymity. The study was approved by the Ethical Committee for Research in Organizational Sciences at Faculty of Organizational Sciences University of Maribor.

A sample of 191 students from Slovenia (SLO) (99 males (51.8%) and 92 (48.2%) females) and 294 students from Germany (GER) (115 males (39.1%) and 171 (58.2%) females) participated in this study. Slovene students’ ages ranged from 19 to 36 years, with a mean of 21 years and 1 months ( M = 21 . 12 and SD = 1 . 770 ) and German students’ ages ranged from 18 to 40 years, with a mean of 22 years and 10 months ( M = 22 . 84 and SD = 3 . 406 ). About half (49.2%) of the Slovene participants were social sciences students, 34.9% were technical sciences students, and 15.9% were natural sciences students. More than half (58.5%) of the German participants were social sciences students, 32% were technical sciences students and 2% were natural sciences students. More than half of the Slovene students (53.4%) attended blended learning, and 46.6% attended classic learning. The majority of German students (87.8%) attended classic learning, and 6.8% attended blended learning. More than half of the Slovene students (61.6%) were working at the time of the study, and 39.8% of all participants had scholarships. In addition, in Germany, more than half the students (65.0%) were working at the time of the study, but only 10.2% of all the German participants had scholarships. More than two thirds (68.9%) of the Slovene students were highly motivated for study and 31.1% less so; 32.6% of the students spend 2 or fewer hours per day on the Internet, 41.6% spend between 2 and 5 hours on the Internet, and 25.8% spend 5 or more hours on the Internet per day. Also, more than two thirds (73.1%) of the German students were highly motivated for study and 23.8% less so; 33.3% of the students spend 2 or fewer hours per day on the Internet, 32.3% spend between 2 and 5 hours on the Internet, and 27.9% spend 5 or more hours on the Internet per day. The general data can be seen in S1 Table .

The questionnaire contained closed questions referring to: (i) general/individual data (gender, age, area of study, method of study, working status, scholarship, motivation for study, average time spent on the internet), and factors influencing plagiarism (ii) ICT and Web, (iii) regulation, (iv) academic skills, (v) teaching factors, (vi) pressure, (vii) pride, (viii) other reasons. The items in the groups (ii) to (viii) used a 5-point Likert scale from strongly disagree (1) to strongly agree (5), with larger values indicating stronger orientation.

The statements used in the survey were as follows:

• 1.1 It is easy for me to copy/paste due to contemporary technology
• 1.2 I do not know how to cite electronic information
• 1.3 It is hard for me to keep track of information sources on the web
• 1.4 I can easily access research material using the Internet
• 1.5 Easy access to new technologies
• 1.6 I can easily translate information from other languages
• 1.7 I can easily combine information from multiple sources
• 1.8 It is easy to share documents, information, data
• 2.1 There is no teacher control on plagiarism
• 2.2 There is no faculty regulation against plagiarism
• 2.3 There is no university regulation against plagiarism
• 2.4 There are no penalties
• 2.5 There are no honour codes relating to plagiarism
• 2.6 There are no electronic systems of control
• 2.7 There is no systematic tracking of violators
• 2.8 I will not get caught
• 2.9 I am not aware of penalties
• 2.10 I do not understand the consequences
• 2.11 The penalties are minor
• 2.12 The gains are higher than the losses
• 3.1 I run out of time
• 3.2 I am unable to cope with the workload
• 3.3 I do not know how to cite
• 3.4 I do not know how to find research materials
• 3.5 I do not know how to research
• 3.6 My reading comprehension skills are weak
• 3.7 My writing skills are weak
• 3.8 I sometimes have difficulty expressing my own ideas
• 4.1 The tasks are too difficult
• 4.2 Poor explanation—bad teaching
• 4.3 Too many assignments in a short amount of time
• 4.4 Plagiarism is not explained
• 4.5 I am not satisfied with course content
• 4.6 Teachers do not care
• 4.7 Teachers do not read students' assignments
• 5.1 Family pressure
• 5.2 Peer pressure
• 5.3 Under stress
• 5.4 Faculty pressure
• 5.5 Money pressure
• 5.6 Afraid to fail
• 5.7 Job pressure
• 6.1 I do not want to look stupid in front of peers
• 6.2 I do not want to look stupid in front of my professor
• 6.3 I do not want to embarrass my family
• 6.4 I do not want to embarrass myself
• 6.5 I focus on how my competences will be judged relative to others
• 6.6 I am focused on learning according to self-set standards
• 6.7 I fear asking for help
• 6.8 My fear of performing poorly motivates me to plagiarise
• 6.9 Assigned academic work will not help me personally/professionally
• 7.1 I do not want to work hard
• 7.2 I do not want to learn anything, just pass
• 7.3 My work is not good enough
• 7.4 It is easier to plagiarise than to work
• 7.5 To get a better/higher mark (score)

All statistical tests were performed with SPSS at the significance level of 0.05. Parametric tests (Independent–Samples t-Test and One-Way ANOVA) were selected for normal and near-normal distributions of the responses. Nonparametric tests (Mann-Whitney Test, Kruskal-Wallis Test, Friedman’s ANOVA) were used for significantly non-normal distributions. Chi-Square Test was used to investigate the independence between variables.

The average values for the groups (and standard deviations) of the responses referring to the factors influencing plagiarism can be seen in Table 1 (descriptive statistics for all statements can be seen in S2 Table ), shown separately for Slovene and German students. An Independent Samples t-test was conducted to obtain the average values of the responses, and thus evaluate for which statements these differed significantly between the Slovene and German students.

*p < .05.

**p < .01

According to the Friedman’s ANOVA (see Table 2 ), the Slovene students’ factors influencing plagiarism can be formed into four homogeneous subsets, where in each subset, the distributions of the average values for the responses are not significantly different. At the top of the list is the existence of ICT and the Web (group 1). The second subset consists of teaching factors (group 4). The third subset is composed of academic skills, other reasons, and pride, in order from highest to lowest (groups 3, 7 and 6). The fourth subset is composed of other reasons, pride, pressure, and regulation, respectively (groups 7, 6, 5 and 2).

For the Slovene students, ICT and the Web were detected as the dominant factors influencing plagiarism and, as such, we investigated them in greater detail. A Friedman Test ( Chi-Square = 7.180, p = .066) confirmed that the distributions of the responses to the statements 1.1, 1.4, 1.5 and 1.8—those with the highest sample means—are not significantly different. Consequently, the average values (means) of the responses to the statements 1.1, 1.4, 1.5 and 1.8 are not significantly different. The average values of the responses for all the other statements (1.7, 1.6, 1.2, and 1.3 listed in the descending order of sample means) are significantly lower. A Mann-Whitney Test showed that there is no statistically significant difference between the distributions of the responses in the group of ICT and Web reasons considering gender (male, female) and motivation for study (lower, higher). For statement 1.2, a Kruskal-Wallis Test ( Chi-Square = 7.466, p = .024) confirmed that there are different distributions for the responses when the area of study is considered (technical sciences, social sciences, natural sciences).

According to the Friedman’s ANOVA (see Table 3 ), the German students’ factors influencing plagiarism can be formed into five homogeneous subsets, where in each subset, the distributions of the average values for the responses are not significantly different. At the top of the list is the existence of ICT and the Web (group 1). The second subset is composed of pressure and pride, in order from highest to lowest (groups 5 and 6). The third subset consists of pride, teaching factors and other reasons, respectively (groups 6, 4 and 7). The fourth subset is composed of teaching factors, other reasons and academic skills, in order from highest to lowest (groups 4, 7 and 3). Finally, the last subset consists of regulation (group 2).

Just like the Slovene students, for the German students ICT and the Web were detected as the dominant factors influencing plagiarism. That the distributions of the responses to the statements 1.4, 1.5 and 1.8—those with the highest sample means—are not significantly different was confirmed by Friedman Test ( Chi-Square = 5.815, p = .055). Consequently, the average values (means) of the responses to the statements 1.4, 1.5 and 1.8 are not significantly different. The average values of the responses for all the other statements (1.1, 1.7, 1.6, 1.2, and 1.3 listed in the descending order of sample means) are significantly lower. A Wilcoxon Signed Ranks Tests also confirmed that the distributions of the responses to the statements 1.6 and 1.7 are not statistically significantly different ( Z = -0.430, p = .667). The same holds for statements 1.2 and 1.3 ( Z = -0.407, p = .684). A Mann-Whitney Test showed that there is no statistically significant difference between the distributions of the responses in the group of ICT and Web reasons considering gender (male, female), area of study (technical and social sciences (students of natural sciences were omitted due to the small sample size)) and motivation for study.

ICT and Web reasons were detected as the dominant factors influencing plagiarism for Slovene and German students. As can be seen in Table 1 , there are significant differences ( t = 4.177, p = .000 ) between the Slovene and German students regarding this factor. It seems that the Slovene students ( M = 3.69, SD = 0.56) attribute greater importance to the ICT and Web reasons than the German students ( M = 3.47, SD = 0.55). There are also significant differences ( t = 5.137, p = .000 ) between the Slovene and German students regarding regulation. It seems that the Slovene students ( M = 2.35, SD = 0.63) attribute greater importance to regulation reasons than the German students ( M = 2.05, SD = 0.61). Both, however, consider this factor to have the lowest impact on plagiarism overall. There are no significant differences ( t = 1.939, p = .053 ) between the Slovene students ( M = 2.56, SD = 0.67) and the German students ( M = 2.44, SD = 0.68) regarding academic skills. The Slovene students ( M = 2.87, SD = 0.68) attribute greater importance to teaching factors than the German students ( M = 2.56, SD = 0.72). The differences are significant ( t = 4.827, p = .000 ) . There are significant differences ( t = -3.522, p = .000 ) between the Slovene and German students regarding pressure, whereas the German students ( M = 2.71, SD = 0.91) attribute greater importance to this reason than the Slovene students ( M = 2.42, SD = 0.86). The same goes for pride. The German students ( M = 2.67, SD = 0.80) attribute greater importance to pride reasons than the Slovene students ( M = 2.43, SD = 0.84). The differences are significant ( t = -3.032, p = .003 ) . There are no significant differences ( t = - 0.836, p = .404 ) between the Slovene students ( M = 2.47, SD = 0.82) and the German students ( M = 2.54, SD = 0.94) regarding other factors influencing plagiarism.

We conducted an Independent Samples t-test to compare the average time (in hours) spent per day on the Internet by the Slovene students with that of the German students. The test was significant, t = -2.064, p = .004. The Slovene students on average spent less time on the Internet ( M = 3.52, SD = 2.23) than the German students ( M = 4.09, SD = 3.72).

The average values of the responses for individual statements according to gender (male, female) and the significances for the t-test of equality of means are shown in S3 Table for the Slovene students and in S4 Table for the German students. The average values of the responses for these statements are significantly different. They are higher for males than for females (except in the case of statement 3.8 for the Slovene students and 4.1 for the German students). Slovene and German male students think that they will not get caught and that the gains are higher than the losses. Both also think that teachers do not read students’ assignments.

The average values of the responses for individual statements according to area of study (technical sciences, social sciences, natural sciences) and the results for ANOVA for the Slovene students are shown in S5 Table . Gabriel's post hoc test was used to confirm the differences between groups. The significant difference between the students of technical sciences and the students of social sciences was confirmed for all statements listed in S5 Table . There were higher average values of responses for the students of technical sciences. The only significant difference between the students of technical sciences and the students of natural sciences was confirmed for statement 5.6 (there were higher average values of responses for the students of technical sciences). No other pairs of group means were significantly different.

The average values of the responses for individual statements according to area of study (technical sciences, social sciences) and the significances for the t-test of equality of means for German students are shown in S6 Table . For German students, only technical and social sciences were considered because of the low number of natural sciences students. The average values of responses for these statements are significantly different. They were higher for the students of technical sciences than for the students of social sciences.

The average values of the responses for individual statements according to the motivation of the students (lower, higher) and the significances for t-Test of equality of means are shown in S7 Table for the Slovene students and in S8 Table for the German students. The average values of the responses for these statements are significantly different. They were higher for students with lower motivation for both groups of students, except in the case of statements 2.1 and 6.6 for Slovene students.

We conducted an Independent Samples t-test to compare the average time (in hours) spent per day on the Internet by groups of low motivated students with groups of highly motivated students. For Slovene students, the test was not significant, t = -1.423, p = .156. For German students, the test was significant, t = 2.298, p = .024. Students with lower motivation for study ( M = 5.24, SD = 4.84) on average spent more time on the Internet than those with higher motivation for study ( M = 3.76, SD = 3.27).

The Chi-Square Test of Independence was used to determine whether there is an association between gender (male, female) and motivation for study (lower, higher). There was a significant association between gender and motivation for the Slovene students ( Chi-Square = 4.499, p = .034). Indeed, it was more likely for females to have a high motivation for study (76.9%) than for males to have a high motivation for study (61.6%). For the German students, the test was not significant ( Chi-Square = 0.731, p = .393).

In this study, we aimed to explore factors that influence students’ factors influencing plagiarism. An international comparison between German and Slovene students was made. Our research draws on students from two universities from the two considered countries that cover all traditional subjects of study. In this regard the conclusions are representative and statistically relevant, although we of course cannot exclude the possibility of small deviations if other or more institutions would be considered. Taken as a whole, there are no major differences between German and Slovene students when it comes to motivation for study and working habits. In both cases, more than two thirds of the students were highly motivated for study and more than 60% were working during their time of study. About 33% of the surveyed students spend on average two or less hours a day on the Internet, and about one quarter spend on average more than five hours a day on the Internet.

When it comes to explaining plagiarism in higher education, the German and Slovene students equally indicated the ease-of-use of information-communication technologies and the Web as the top one cause for their behaviour. Which does not lag behind other notions of current contributions to the topic of plagiarism in the world. Indeed, our findings reinforce the notion that new technologies and the Web have a strong influence on students and are the main driver behind plagiarism [ 20 , 21 , 22 ]. An academic moral panic has been caused by the arrival in higher education of a new generation of younger students [ 39 ], deemed to be ‘digital natives’ [ 40 ] and allegedly endowed with an inherent ability for using information-communication technologies (ICT). This younger generation is dubbed ‘Generation Me’ [ 41 ], and it is believed that their expectations, interactions and learning processes have been affected by ICT. Introna, et al., Ma et al., and Yeo, agree that the understanding of the concept of plagiarism through the use of ICT is the main contributor to it being a problem [ 42 , 43 , 44 ]. The effortless use of ICT such as the Internet has made it easy for students to retrieve information with a simple click of the mouse [ 45 , 46 ].

The Slovene students in our study nominated the teaching factor as the second most important reason for plagiarism. This result is also found in other studies, namely those of Šprajc et al. [ 30 ] and Barnas [ 47 ]. Young people in Slovenia are, like in other Western societies, given a prolonged period of identity exploration and self-focus, i.e., freedom from institutional demands and obligations, competence, and freedom to decide for themselves [ 48 , 49 ]. The results of the German students however, contradict this finding that teaching factors are one of the most important factors influencing plagiarism. Indeed, the top two factors influencing plagiarism for the German students are actually pressure and pride—and not teaching factors. Overall though, the findings for both the German students and the Slovene students are in line with e.g. Koul et al., who suggest that factors influencing plagiarism may vary across cultures [ 4 ]. Among German students, the pressure and pride in the second and third places in terms of importance are mostly reflected, which does not lag behind the mention of the author Rothenberg stated that in Germany today ‘pride could be expressed for individual accomplishments’ [ 50 ]. As far as the Slovene students are concerned, the authors Kondrič et al. presumed that there is a specific set of values in Slovenia, which perhaps intensify the distinction between the collectivist culture of former socialist countries and the individualism of Western countries [ 51 ]. This might shed light on why the Slovene students consider teaching factors as being one of the most important factors influencing plagiarism.

Furthermore, several studies have implied that individual characteristics, especially gender, play an important role when it comes to plagiarism [ 12 , 13 , 15 , 16 ]. A number of studies from around the world have shown that men more frequently plagiarise than women do. For example, Reviews of North American’s research into conventional plagiarism has indicated that male students cheat more often than female students [ 12 ]. The results we found are basically in line with these findings. Since the average values of responses are significantly different for male and female students, gender seems to play an important role in terms of plagiarism.

Park pointed out that one reason for plagiarism is efficiency gain [ 11 ]. About 15 years after this statement, the study at hand is empirical evidence that efficiency gain due to different forms of pressure is still a factor that influences students’ behaviour in terms of plagiarism. Lack of knowledge and uncertainties about methodologies are additional factors that are frequently recognized as reasons for plagiarism [ 11 , 17 , 18 ]. The results at hand support these studies since the responses about e.g. academic skills demonstrate students’ lack of knowledge.

Another interesting finding of our study shows that students with a lower motivation for study spend more time on the Internet, which complements our finding that the Internet is one of the simplest solutions for studying. The German students showed a somewhat higher level of motivation to study than the Slovene students, but the difference is not statistically significant.

We would nevertheless like to draw attention to the perceived difference, which refers to the perception of the factors influencing the plagiarism of the teacher factors and academic skills (Slovene students) and pride and pressure (German students). The perceived difference between students is one of the social dimensions that represents a tool to promote true motivation for study and proper orientation without ethically disputable solutions (such as plagiarism). In all this, it makes sense to direct students and educate them from the beginning of education together with information technology, while also builds responsible individuals who will not take technology and the Internet as a negative tool for studying and succeeding, but to help them to solve and make decisions in the right way. The main aim of this research into Slovene and German students was to increase understanding of students’ attitudes towards plagiarism and, above all, to identify the reasons that lead students to plagiarise. On this basis, we want to expose the way of non-plagiarism promotion to be developed in a way that will be more acceptable and more understandable in each country and adequately controlled on a personal and institutional level.

Conclusions

In contrast to a number of preliminary studies, the major findings of this research paper indicate that new technologies and the Web have a strong and significant influence on plagiarism, whereas in this specific context gender and socialisation factors do not play a significant role. Since the majority of the students in our study believe that new technologies and the Web have a strong influence on plagiarism, we can assume that technological progress and globalisation has started breaking down national frontiers and crossing cultural boundaries. These findings have also created the impression that at universities the gender gap is not predominant in all areas as it might be in society.

Nevertheless, some minor results in our study indicate that there are still some differences between Slovene and German students. For example, it seems like in Slovenia, teaching factors have a greater influence on plagiarism than in Germany. Indeed, in Germany, the focus should rest on the implementation and publication of a code of ethics, and on training students to deal with pressure.

This research focuses on only two countries, Slovenia and Germany. Thus, the findings at hand are not necessarily generalizable, though they do manifest a certain trend in terms of the reasons why students resort to plagiarism. Furthermore, the results could be a starting point for additional comparative studies between different European regions. In particular, further research into the influence of digitalization and the Web on plagiarism, and the role of socialisation and gender factors on plagiarism, could contribute to the discourse on plagiarism in higher education institutions.

Understanding the reasons behind plagiarism and fostering awareness of the issue among students might help prevent future academic misconduct through increased support and guidance during students’ time studying at the university. In this sense, further reflection on preventive measures is required. Indeed, rather than focusing on the detection of plagiarism, focusing on preventive measures could have a positive effect on good scientific practice in the near future.

Supporting information

Funding statement.

MP was supported by the Slovenian Research Agency (Grant Nos. J1-7009 and P5-0027), http://www.arrs.gov.si/ . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Challenges in Addressing Plagiarism in Education

* E-mail: [email protected]

Affiliation Business School, University of South Australia, Adelaide, South Australia, Australia

• Tracey Bretag

Published: December 31, 2013

• https://doi.org/10.1371/journal.pmed.1001574
• Reader Comments

Citation: Bretag T (2013) Challenges in Addressing Plagiarism in Education. PLoS Med 10(12): e1001574. https://doi.org/10.1371/journal.pmed.1001574

Copyright: © 2013 Tracey Bretag. This is an open-access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: No specific funding was received to write this article.

Competing interests: The author has declared that no competing interests exist.

Provenance: Commissioned; externally peer reviewed.

Summary points

• Plagiarism undermines the integrity of education and occurs at all levels of scholarship.
• Research indicates that both undergraduate and postgraduate students require training to avoid plagiarism.
• Established researchers are not immune to allegations of plagiarism.
• Educational institutions need to move beyond deterrence, detection, and punishment, and take a holistic and multi-stakeholder approach to address plagiarism.

Research Integrity Series This is one article in an occasional PLOS Medicine series on research integrity that examines issues affecting the ethics of health research worldwide.

Academic Integrity and Plagiarism

Academic integrity encompasses a number of values including honesty, trust, respect, fairness, and responsibility [1] and ideals that should be upheld by all educational stakeholders. “Academic integrity involves ensuring that in research, and in teaching and learning, both staff and students act in an honest way. They need to acknowledge the intellectual contributions of others, be open and accountable for their actions, and exhibit fairness and transparency in all aspects of scholarly endeavour” [2] . Academic integrity ensures public trust in the credibility of scholarship at all levels of education including the research process and its outcomes [3] .

Academic integrity breaches include a diverse range of unfair practices including plagiarism, cheating in exams or assignments, inappropriate collusion, theft of other students' work, paying a third party for assignments, downloading whole or part of assignments from the Internet, falsification of data, misrepresentation of records, or other actions that undermine the integrity of scholarship [4] . Plagiarism is one of the most vehemently derided breaches of academic integrity because it undermines the premise that scholarly work will make an original and honest contribution to an existing body of knowledge. Despite the fact that plagiarism occurs at all levels of scholarship, the main focus in the recent explosion of research in this area is on student plagiarism [5] – [9] . For the purpose of this paper, plagiarism is defined as the use of others' words, ideas, or creative work without appropriate acknowledgement, and does not necessarily imply intentional deceit.

Plagiarism by Students

The extent of plagiarism (in its various forms) in students' work depends in part on the methodology used to explore this issue, with most studies using self-report methodologies. The rate of plagiarism for undergraduate students varies wildly from 19% [10] , to 26% [11] , 66% [12] , and 81% [13] . Research has further highlighted issues of plagiarism by students for whom English is an Additional Language (EAL) at both undergraduate and postgraduate levels. Marshall and Garry [14] concluded that EAL students are significantly more likely to have engaged in serious forms of plagiarism (83%) than non-EAL students (65%); Vieyra et al. [15] determined that 47% of EAL graduate students had plagiarised in their research proposals, versus 16% of non-EAL students. Pecorari [16] found that 76% of non-native English speaking graduate students had at least one passage in a writing sample (half of which were completed PhD theses) where over 70% of the text was taken from source material. A recent survey of 15,304 Australian students, from a range of disciplines both undergraduate and postgraduate, reported that international students were more than twice as likely as domestic students to convey a lack of confidence in how to avoid an academic integrity breach [5] .

It is generally assumed that graduate students, having spent at least 15 years in the education system, are conversant with academic integrity requirements and know how to avoid plagiarism [17] ; however, it is becoming increasingly apparent that many graduate students are ill-prepared for the challenges of postgraduate study [18] , [19] and that breaches of academic integrity policy do occur among this student group [13] , [17] . Gilmore et al. [17] found that 42.6% of research proposals by science, technology, engineering, and mathematics graduate students contained plagiarism; McCullogh and Holmburg [20] reported 27% plagiarism in master's theses; and Segal et al. [21] found that 5% of medical residency applications had at least one instance of plagiarism. Results from the Academic Integrity Standards Project [4] indicated that one in five postgraduate research students had never heard of academic integrity and two in five postgraduate students said they did not know whether their university had an academic integrity policy.

Plagiarism by Established Researchers

Given the rates of plagiarism for all groups of students, coupled with research indicating that many students do not receive adequate information or training either at the undergraduate or postgraduate levels [18] , [22] – [24] , it cannot be surprising that breaches of integrity by established researchers are rife. A survey of 3,600 mid-career and 4,160 early-career scientists in the United States found that 33% of the respondents had engaged in questionable research practices relating to data, methods, policy, use of funds, outside influence, peer review, giving credit, and “cutting corners” [25] .

Media scandals regularly threaten individuals' and institutions' reputations. The widely publicised plagiarism in the dissertation of the German Minister of Defence, Karl-Theodor zu Guttenberg (63% of the lines on 94% of the pages) resulted in the minister's forced resignation. VroniPlag Wiki has since documented over 30 cases of plagiarism by other prominent German academics with the result that some universities have rescinded individual doctorates [26] . But the issue goes well beyond Germany and Europe, with reports of serious plagiarism by academics in numerous countries across the globe [27] – [30] .

The Complexities of Plagiarism

Writers in the field have noted the complexities of defining plagiarism [31] , [32] and identifying it, particularly for novice scholars. In two separate studies, Roig [33] , [34] asked students to identify plagiarised text and found that 40%–50% of the students did not complete the exercise correctly. Work by Marshall and Garry [14] , Yeo [35] , and Pecorari [16] , among others, concur that many students cannot identify instances of plagiarism and do not adequately understand how to paraphrase text with appropriate citation to avoid plagiarism. International EAL students are not the only group who may struggle to understand and fulfil the requirements of academic practice. The student body is increasingly diverse, and may include those from socially and academically disadvantaged backgrounds, non-traditional aged students, and those with intellectual, mental, or physical disabilities.

Given the centrality of acknowledgement to definitions of plagiarism, both students and teachers often want to know precisely when “sloppy referencing” becomes “serious plagiarism.” James et al. [36] present three aspects of what needs to be considered by academics in determining whether apparent plagiarism is “serious” and therefore requires a punitive response or whether it is a minor concern best responded to with education. The first is the student's “intent to cheat,” with “deliberately presenting the work of others as one's own” placed at the extreme, punitive end of a continuum. The second aspect is “the extent of plagiarism” with “downloaded essay handed in as own paraphrasing” again representing the extreme end of a continuum. The third aspect is the “possible response to plagiarism” that involves consideration of the first two aspects, and takes either an educative or punitive approach. Recent work by the Exemplary Academic Integrity Project [37] suggests that even apparently harsh outcomes such as suspension or expulsion are, in fact, appropriate educational outcomes for certain types of academic integrity breaches.

The issue of “self-plagiarism,” either by students or researchers, also revolves around appropriate acknowledgement. In seeking a definition of self-plagiarism for previous research on self-plagiarism in academic research, we relied on the concept of “fair use” in Australian Copyright law and determined that articles contained self-plagiarism “if they contained 10% or more of any one of the author's previous publications without appropriate attribution” [38] . Our findings indicated that 60% of the authors in the sample had self-plagiarised in at least one of their published papers. Self-plagiarism by students involves recycling previously submitted work without attribution to the original work and/or without the permission of teaching staff.

Addressing Plagiarism

Much of the research on plagiarism and other breaches of academic integrity has focused on the role of teaching and learning, particularly at the undergraduate level, with targeted induction, support, and training advocated for all students, and in particular for those from non-traditional backgrounds. Strategies to deter plagiarism include advice regarding assessment development, curriculum design, and academic skills education [7] , [39] . These deterrence strategies are advised in conjunction with detection and appropriate penalties. Often erroneously touted as a “plagiarism detection” tool, text-matching software such as Turnitin or SafeAssign provides instructors with the means to check students' work against other material on the Internet, previously submitted student papers, and journal articles. As increasing numbers of schools, colleges, and universities use text-matching software, as both an educational tool and as a deterrence, students may be less inclined to submit assignments based on “cut and paste” plagiarism.

However, plagiarism is not only an issue of student assessment. It is a symptom of a deeply entrenched academic culture that arguably places tangible rewards (grades, diplomas, publications, promotions, grants) above the intrinsic value of learning and knowledge creation. To address the ongoing issue of plagiarism and other breaches of academic integrity, educational institutions must work towards fostering a culture of integrity that goes beyond deterrence, detection, and punishment of students. Bertram Gallant and Kalichman maintain that “individual misconduct is actually a systemic issue, shaped by individual, organisational, educational/academy, and societal factors” [40] . On this basis, to nurture a community with shared academic values of integrity would require a holistic and multi-stakeholder approach encompassing educational policy makers, senior managers, teaching academics and advisors, students at all levels, researchers, funding bodies, editors, and reviewers [41] . A genuinely holistic approach would involve promoting integrity in every aspect of the academic enterprise: including university mission statements and marketing, through admissions processes [40] , to nuanced and carefully articulated policy [4] , [5] , [7] . It must include assessment practices and curriculum design [22] , [24] , information provided during orientation, and frequent and visual reminders on campus [40] . There must be embedded and targeted support in courses and at every level for students [5] , professional development for staff [7] , [42] , and research training [18] . Finally, the use of new technologies to both assist students to avoid academic integrity breaches, and as a tool to detect breaches when they occur, must be adopted [42] , [43] . While such a nuanced and all-inclusive approach to academic integrity is aspirational rather than one that exists in a single institution, two decades of research has provided evidence of the impact of individual interventions (e.g., policy, assessment design, training, detection, penalties) in addressing plagiarism. Both researchers and practitioners are now calling for stakeholders at all levels of education to recognise that the complexity of plagiarism requires an equally sophisticated and multi-pronged approach, which is both targeted and context-specific [37] .

Plagiarism is a serious breach of academic integrity in that it detracts from the value of original and honest scholarly work. While there has been an explosion of interest and research on this topic, by and large the focus has been on undergraduate students plagiarising in assessment. Recent research has demonstrated that plagiarism is a complex issue, with many stakeholder groups requiring much more induction, information, training, and support to ensure that they have the necessary understanding and skills to fulfil their academic responsibilities. Educational institutions therefore need to recognise that addressing plagiarism requires a holistic and multi-stakeholder approach which aims to foster a scholarly community based on shared understandings and practices of academic integrity.

Acknowledgments

My sincere thanks to my colleague Saadia Mahmud for her helpful advice on the structuring of this essay.

Author Contributions

Wrote the first draft of the manuscript: TB. Contributed to the writing of the manuscript: TB. ICMJE criteria for authorship read and met: TB. Agree with manuscript results and conclusions: TB.

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ChatGPT Is Making Universities Rethink Plagiarism

In late December of his sophomore year, Rutgers University student Kai Cobbs came to a conclusion he never thought possible:  Artificial intelligence might just be dumber than humans. 

After listening to his peers rave about the generative AI tool  ChatGPT , Cobbs decided to toy around with the chatbot while writing an essay on the history of capitalism. Best known for its ability to generate long-form written content in response to user input prompts, Cobbs expected the tool to produce a nuanced and thoughtful response to his specific research directions. Instead, his screen produced a generic, poorly written paper he’d never dare to claim as his own. 

“The quality of writing was appalling. The phrasing was awkward and it lacked complexity,” Cobbs says. “I just logically can’t imagine a student using writing that was generated through ChatGPT for a paper or anything when the content is just plain bad.” 

Not everyone shares Cobbs’ disdain. Ever since OpenAI launched the chatbot in November,  educators have been struggling with how to handle a new wave of student work produced with the help of artificial intelligence. While some public school systems, like New York City’s, have banned the use of ChatGPT on school devices and networks to curb cheating, universities have been reluctant to follow suit. In higher education, the introduction of generative AI has raised thorny questions about the definition of plagiarism and academic integrity on campuses where new digital research tools come into play all the time. 

Make no mistake, the birth of ChatGPT does not mark the emergence of concerns relating to the improper use of the internet in academia. When  Wikipedia launched in 2001 , universities nationwide were  scrambling to decipher their own research philosophies and understandings of honest academic work, expanding policy boundaries to match pace with technological innovation. Now, the stakes are a little more complex, as schools figure out how to treat bot-produced work rather than weird attributional logistics. The world of higher education is playing a familiar game of catch-up, adjusting their rules, expectations, and perceptions as other professions adjust, too. The only difference now is that the internet can think for itself. 

According to ChatGPT, the definition of plagiarism is the act of using someone else’s work or ideas without giving proper credit to the original author. But when the work is generated by some thing rather than some one , this definition is tricky to apply. As Emily Hipchen, a board member of Brown University’s Academic Code Committee, puts it, the use of generative AI by students leads to a critical point of contention. “If [plagiarism] is stealing from a person,” she says, “then I don’t know that we have a person who is being stolen from.”

Hipchen is not alone in her speculation. Alice Dailey, chair of the Academic Integrity Program at Villanova University, is also grappling with the idea of classifying an algorithm as a person, specifically if the algorithm involves text generation.

Dailey believes that eventually professors and students are going to need to understand that digital tools that generate text, rather than just collect facts, are going to need to fall under the umbrella of things that can be plagiarized from. 

Although Dailey acknowledges that this technological growth incites new concerns in the world of academia, she doesn’t find it to be a realm entirely unexplored. “I think we’ve been in a version of this territory for a while already,” Dailey says. “Students who commit plagiarism often borrow material from a ‘somewhere’—a website, for example, that doesn’t have clear authorial attribution. I suspect the definition of plagiarism will expand to include things that produce.” 

Eventually, Dailey believes, a student who uses text from ChatGPT will be seen as no different than one that copies and pastes chunks of text from Wikipedia without attribution. 

Students’ views on ChatGPT are another issue entirely. There are those, like Cobbs, who can’t imagine putting their name on anything bot-generated, but there are others who see it as just another tool, like spellcheck or even a calculator. For Brown University sophomore Jacob Gelman, ChatGPT exists merely as a convenient research assistant and nothing more.

“Calling the use of ChatGPT to pull reliable sources from the internet ‘cheating’ is absurd. It’s like saying using the internet to conduct research is unethical,” Gelman says. “To me, ChatGPT is the research equivalent of [typing assistant] Grammarly. I use it out of practicality and that’s really all.” Cobbs expressed similar sentiment, comparing the AI bot to “an online encyclopedia.”

But while students like Gelman use the bot to speed up research, others take advantage of the high-capacity prompt input feature to generate completed works for submission. It might seem obvious what qualifies as cheating here, but different schools across the country offer contrasting takes.

According to Carlee Warfield, chair of Bryn Mawr College’s Student Honor Board, the school considers any use of these AI platforms as plagiarism. The tool’s popularization just calls for greater focus in evaluating the intent behind students’ violations. Warfield explains that students who turn in essays entirely produced by AI are categorically different from those who borrow from online tools without knowledge of standard citations. Because the ChatGPT phenomenon is still new, students’ confusion surrounding the ethics is understandable. And it's unclear what policies will remain in place once the dust settles—at any school.

In the midst of fundamental change in both the academic and technological spheres, universities are forced to reconsider their definitions of academic integrity to reasonably reflect the circumstances of society. The only problem is, society shows no stagnance. 

“Villanova’s current academic integrity code will be updated to include language that prohibits the use of these tools to generate text that then students represent as text they generated independently,” Dailey explained. “But I think it’s an evolving thing. And what it can do and what we will then need in order to keep an eye on will also be kind of a moving target.”

In addition to increasingly complex questions about whether ChatGPT is a research tool or a plagiarism engine, there’s also the possibility that it can be  used for learning. In other educational settings, teachers see it as a way to show students the shortcomings of AI. Some instructors are already  modifying how they teach by giving students assignments bots couldn’t complete, like those that require personal details or anecdotes. There’s also the matter of detecting AI use in students’ work, which is a  burgeoning cottage industry all its own. 

Ultimately, Dailey says, schools may need rules that reflect a range of variables.

“My guess is that there will be the development of some broad blanket policies that essentially say, unless you have permission from a professor to use AI tools, using them will be considered a violation of the academic integrity code,” Dailey says. “That then gives faculty broad latitude to use it in their teaching or in their assignments, as long as they are stipulating explicitly that they are allowing it.”

As for ChatGTP, the program agrees. “Advances in fields such as artificial intelligence are expected to drive significant innovation in the coming years,” it says, when asked how schools can combat academic dishonesty. “Schools should constantly review and update their academic honor codes as technology evolves to ensure they are addressing the current ways in which technology is being used in academic settings.”

But, a bot would say that. 

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