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Contract Cheating: The Outsourcing of Assessed Student Work
Abstract
This chapter reviews the issues associated with contract cheating, loosely defined as the outsourcing of student work to third parties. The chapter is intended to serve as an overview of current research while also providing practical instruction and guidance to academics and educators.
The discussion begins by introducing contract cheating and comparing this specific form of academic misconduct with student plagiarism. The suggestion is made that current anti-plagiarism methods are not suitable for contract cheating, defined as where a student is requesting an original bespoke piece of work to be created for them. Six types of services that students can use to have work produced for them are listed; these are (1) essay writing services; (2) friends, family, and other students; (3) private tutors; (4) copyediting services; (5) agency websites; and (6) reverse classifieds. Specific challenges associated with each service are provided.
Findings related to the wider contract cheating area are given. This includes particular discussion of the research into agency sites, where a student makes the offer of work available to a large number of people who then bid to complete it. The student selects one of the bidders to complete the work based on a form of cost-benefit analysis. Issues considered include the extent of contract cheating, the cost and quality of outsourced work, and the range of subjects in which students are cheating.
The chapter concludes with a discussion of the main methods that can be used to prevent contract cheating. Research into technical solutions, such as stylometrics, put in place to find automated technical solutions to detect contract cheating, is also presented.
... Some authors believe that contract cheating necessarily engages a financial transaction (Walker & Townley, 2012) between a customer (student) and a service provider (company), whereas others consider it as a learner outsourcing their work with no money involved for the service they receive (Hill et al., 2021;Eaton & Turner, 2020). In line with Harper et al. (2019) and Lancaster and Clarke (2016), students can use essay writing services or get support from peers, family members or private mentors, and many other outsiders. According to Erguvan's (2021) observations on many occasions of reported contract cheating, colleagues have exchanged their work with each other just as a favour or as a help. ...
... Among them, technology-based remedies and detection programmes are at the forefront of all. Nevertheless, word-matching detection applications such as Turnitin, PlagScan, AntiPlag, TeSLA, and Urkund could use to recognize subcontracted academic work (Lancaster & Clarke, 2016;Wang & Xu, 2021), they are recognised as unsuccessful in detecting contract cheating (Ahsan, 2019) as work done by those services are normally skillfully written and sufficiently referenced (Lines, 2016). Software tools, such as Cadmus (Lines, 2016) and digital forensic methods -stylometrics and linguistics (Dawson et al., 2019;Ison, 2020) -may help address contract cheating. ...
... Grounded on the outcomes of the study, recommendations related to contract cheating and academic integrity in higher education are discussed within this section. In that regard, several suggestions to address the issue have been made by the respective authorities, including scholars and educational quality assurance organisations (Lancaster & Clarke, 2016;QAA, 2020). At the very basic level, increasing the attentiveness toward contract cheating among the academic staff and newcomers is of considerable importance since both parties equally experience its unfavourable consequences. ...
Contract cheating has become increasingly an issue as universities adapt to online and hybrid teaching, learning, and assessments. Due to the COVID-19 pandemic, higher education institutions began to administer examinations more frequently online, and it led to the emergence of websites and commercial service providers who offer contract cheating services globally. In this paper, we examine the key elements that lead students to turn to contract cheating as well as the elements that deter the students from engaging in such unethical behaviour. We also investigate how assessment design can encourage authentic learning, although assessment design alone cannot eliminate contract cheating. The effects of contract cheating on academic standards and quality assurance are also examined. Mainly the study results show that the act of contract cheating is a result of interrelated internal and external factors in an individual. Although a number of measures, including authentic evaluations and digital tools, have been implemented to discourage students from cheating, no strategy is strong enough to control the issue permanently. Hence, academic integrity is still not assured, highlighting the necessity of a global movement to solve the problem.
... For example, Bretag et al. (2018) surveyed students in Australia and found the belief that there were opportunities to cheat as an influencing factor. Recommendations about how to think about contract cheating and redevelop assessments exist (Lancaster & Clarke, 2016). National quality assurance bodies have begun to provide advice, (e.g., Quality Assurance Agency (QAA) in the UK, 2017; Tertiary Education Quality and Standards Agency (TEQSA) in Australia, 2017). ...
... The second most common reason, stated by 20.9% of students, was academic aptitude, where students found the material too difficult and said they needed help. Both of these reasons point towards agreement with an earlier recommendation from Lancaster and Clarke (2016), that academic institutions need to reconsider the design of their curriculum to ensure that students are equipped for success. Alongside this recommendation, universities need to consider the types of assessment that they use to ensure that they are fit for purpose and offer some resistance to contract cheating. ...
The contract cheating industry, those services and individuals who are supplying students with original work for assessment, is evolving. Contract cheating companies are using enhanced marketing techniques, including social media marketing, to encourage potential customers to avail themselves of services that breach academic integrity. Social media is proving to be integral to the success of the contract cheating industry as a whole. It allows contract cheating companies to recruit academic ghost writers and other staff. In addition, social media is fuelling a black market trade in contract cheating service accounts. Potential ghost writers who would not otherwise qualify are using this hidden market to get accounts to work for contract cheating services.This paper examines the state of the contract cheating industry, paying particular attention to the role that social media has played in the industry’s development and apparent growth. The discussion of the industry is supported by example and case studies. These cover the end-to-end contract cheating process from when an essay mill is first set up, through to supplying services to students and to engaging contract cheating service workers. Examples of contract cheating and social media use of specific interest to Canadian academics and scholars are included. The paper concludes with a discussion of future challenges as well as the opportunities for academic integrity discussions. These are intended to enable academics to work with students as academic integrity partners and to enable discussions that make use of what is known about the operation of the contract cheating industry.
... As technology continues to evolve, the academic community faces the ongoing challenge of adapting its strategies to ensure that academic honesty is maintained in this new digital landscape (Lancaster & Clarke, 2016). ...
... There is a growing concern that an over-reliance on surveillance and detection tools may inadvertently foster a culture of suspicion, potentially undermining the very ethos of academic integrity they aim to protect (Jones, 2011). Additionally, the impact of these tools on student anxiety, motivation, and the development of critical thinking skills remains underexplored (Lancaster & Clarke, 2016). ...
Introduction: This study delves into the realm of digital tools and their impact on academic honesty, with a specific focus on the EduIntegrity Suite. In an era where digital resources are increasingly integral to educational practices, understanding their influence on academic integrity is crucial. Objectives: The primary objectives are to assess the effectiveness of these digital tools in detecting and deterring academic dishonesty, evaluate their ethical implications, and understand their broader impact on academic culture. Methods: Adopting a qualitative, exploratory approach, the study employs document analysis and narrative analysis. This involves a thorough evaluation of academic papers, policy documents, and personal narratives obtained from online sources, offering a comprehensive view of the current academic landscape. Results: The findings reveal that tools such as PlagScan, Grammarly, and Turnitin effectively identify instances of plagiarism. However, they also raise significant ethical concerns, particularly regarding privacy and the risk of creating a surveillance culture. These tools are found to have a multifaceted impact on academic culture, affecting trust dynamics and the promotion of intrinsic academic honesty. Conclusions: While these digital tools are instrumental in upholding academic integrity, their usage comes with complex ethical and cultural implications. The study acknowledges its limitations and suggests the need for continuous evaluation and research in this field. This research sheds light on the critical role and challenges of technology in fostering academic integrity in the digital age.
... A recent phenomenon, which has become known as contract cheating or essay mills, involves students receiving a range of services from a third party to help them to complete assessments, often for payment, as a step up from ghost-writing by friends and family (Lancaster & Clarke 2016;Clarke & Lancaster 2006;. The intentional nature of such conduct elevates this from misconduct to corruption. ...
... from the same courses Lancaster & Clarke 2016;Mills (pseudonym) 2017, Healey 2018). ...
This report sets out the results from a study conducted
during 2017-18 for the Council for Higher Education
Accreditation / CHEA International Quality Group
(CHEA/CIQG).
The study was designed to capture
information about actions and responses of accreditation
and quality assurance bodies (AQABs) for addressing
different forms of corruption in higher education. The
results, recommendations and conclusions in this report
are based on the findings of the study.
https://www.chea.org/sites/default/files/2019-03/CHEA_Corruption-Report-Final-underlines.pdf
... Even though ghostwriters, especially commercial ones, claim their essays are original and therefore cannot be detected using text-matching software, thirdparty assignments may still contain recycled text (Aitken et al., 2017;Newton & Lang, 2015). Textmatching detection software could use these breaches to identify outsourced academic work (Lancaster & Clarke, 2016;Wang & Xu, 2021). This study compared about four thousand term papers written in the languages Hebrew, Arabic and English that were submitted using the Moodle system a year before the outbreak of the COVID-19 epidemic, with about four thousand term papers submitted at the time of the closure of the first wave of COVID-19 outbreaks. ...
... Thus, it seems that ghostwriters do deliver their promise of writing custom academic work. The results demonstrate that even when using state-of-theart automated detection methods, contract cheating remains difficult to detect (Johnson & Davies, 2020;Lancaster & Clarke, 2016;Sivasubramaniam et al., 2016). This provides alarming evidence for higher education institutions and constitute a serious threat to academic integrity. ...
... Contract cheating, where students outsource their academic work to third parties, presents a growing challenge to maintaining academic integrity (Lancaster & Clarke, 2016;Stoesz et al., 2019). Traditional forms of discovery can prove to be ineffective as there are continuous and innovative developments in this area making it difficult to detect (Lancaster & Clark, 2016;Stoesz et al., 2019). ...
It is with great pride and gratitude that we present this Book of Abstracts, marking the successful completion of the FAITH Conference 2024. This remarkable initiative, focused on promoting academic integrity by integrating ethics, technology, and education, has achieved its goals and left a lasting impact. The FAITH Project has brought together educators, researchers, and practitioners to tackle the challenges of academic misconduct and foster ethical practices in a changing educational world.
We extend our sincere thanks to everyone who contributed to the success of the FAITH Conference. The event united a vibrant community, including 3 inspiring keynote speakers, 33 submissions from 12 countries, and the invaluable efforts of 24 dedicated reviewers. With participation from 75 authors, the conference covered 5 key topics and attracted 186 registered audience members. Alongside the academic sessions, we hosted 3 engaging panel discussions and 4 significant FAITH Project meetings. These impressive numbers reflect the strong commitment of the academic community to addressing issues of integrity and ethics.
This conference has been an important step forward for the academic integrity community. It provided a platform to share new ideas, practical solutions, and research findings, helping to build a stronger global network of integrity-focused professionals. The insights shared during the sessions have opened new opportunities for fostering ethical practices in education, promoting responsible use of technology, and creating a culture of trust and fairness in academia. These discussions and collaborations will undoubtedly shape future approaches and policies.
As we conclude this conference, we want to express our deepest gratitude to everyone who made it possible—organizers, keynote speakers, contributors, reviewers, panelists, committees, sponsors, and participants. Your dedication and enthusiasm have been the foundation of this event’s success. Let us move forward together, continuing to uphold the principles of academic integrity and ensuring these values remain central to all our work.
... Contract cheating or "the outsourcing of student work to third parties" (Lancaster & Clarke, 2016, p. 639) is a type of academic misconduct that is growing and changing due to advancements in technology and the emergence of a lucrative, multi-million dollar per year industry that targets students relentlessly (Lancaster & Clarke, 2016). In an effort to protect students from engaging in contract cheating, three postsecondary institutions in Manitoba (i.e., Assiniboine Community College, Red River College, and the University of Manitoba) launched initiatives to block access to websites that offer contract cheating services from their networks. ...
Contract cheating or “the outsourcing of student work to third parties” (Lancaster & Clarke, 2016, p. 639) is a type of academic misconduct that is growing and changing due to advancements in technology and the emergence of a lucrative, multi-million dollar per year industry that targets students relentlessly (Lancaster & Clarke, 2016). In an effort to protect students from engaging in contract cheating, three postsecondary institutions in Manitoba (i.e., Assiniboine Community College, Red River College, and the University of Manitoba) launched initiatives to block access to websites that offer contract cheating services from their networks. This initiative facilitated a preliminary examination of student activity on institutional networks. In any given month, a relatively large number of students (i.e., up to 3,519 unique users) were attempting to access websites identified as providing contract cheating services. We recognize that a single initiative will not eliminate academic misconduct, however, by combining various educational, protective, and preventative strategies, the likelihood that students will make ethical decisions regarding their academic work can be increased.
... Academic dishonesty has previously been defined as "any fraudulent actions or attempts by a student to use unauthorised or unacceptable means in any academic work" (Chala, 2021). It encompasses a broader spectrum of unethical behaviour, including plagiarism, collusion and contract cheating (Lancaster and Clarke, 2016). Academic cheating, a type of academic dishonesty, includes behaviours like exchanging information with others during an exam/ test; cheating by using prohibited materials or information; and actions taken to evade the assessment process (Cizek, 2012). ...
Purpose
Academic integrity is vital to the success and sustainability of the academic project and particularly critical in the training of ethical and informed health professionals. Yet studies have found that cheating in online exams was commonplace during the COVID-19 pandemic. With the increased use of online and blended learning post-COVID-19, an understanding of student cheating dynamics is essential for developing effective strategies to combat academic dishonesty in the rapidly changing educational landscape.
Design/methodology/approach
This study explored academic integrity and reasons for dishonesty from the perspective of health sciences students at a South African University of Technology (UOT) via the Fraud Diamond. To gain an in-depth understanding of the topic, a qualitative method was employed, and data were collected via focus group discussions with nine student class representatives. These data were analysed thematically using the Clarke and Braun approach.
Findings
Cheating during online assessment was common and innovative, with students manipulating others and exploiting friendships to facilitate dishonest practices. Student motivations for dishonesty included a lack of consequences and pressure due to a lack of time management, engagement and preparation.
Practical implications
This study underscores the need for institutions to adopt an adaptable, multi-faceted approach that addresses student cheating opportunity, motivation and normalisation of dishonest practices whilst strengthening academic integrity policies and enforcement thereof.
Originality/value
The findings contribute valuable insights into the ongoing academic integrity crisis in higher education in the South African context.
... A major part of the phenomenon described above is known as contract cheating (Lancaster and Clarke, 2016). Contract cheating occurs when "a student is requesting an original bespoke piece of work to be created for them" (Lancaster and Clarke, 2016, p. 639). ...
Contract cheating, the act of students enlisting others to complete academic assignments on their behalf, poses a significant challenge in academic settings, undermining the integrity of education and assessment. It involves submitting work that is falsely represented as the student’s own, thus violating academic standards and ethics. The advent of artificial intelligence-based language models, such as ChatGPT, has raised concerns about the potential impact of contract cheating. As these language models can generate human-like text with ease, there are concerns about their role in facilitating and increasing contract cheating incidents. Innovative approaches are thus needed to detect contract cheating and address its implications for academic integrity. This study introduces a machine learning (ML) model focused on identifying deviations from a learner’s unique writing style (or their linguistic fingerprint) to detect contract cheating, complementing traditional plagiarism detection methods. The study involved 150 learners majoring in engineering and business who were studying English as a foreign language at a college in Saudi Arabia. The participants were asked to produce descriptive essays in English within a consistent genre over one semester. The proposed approach involved data preprocessing, followed by transformation using Term Frequency-Inverse Document Frequency (TF-IDF). To address data imbalance, random oversampling was applied, and logistic regression (LR) was trained with optimal hyperparameters obtained through grid search. Performance evaluation was conducted using various metrics. The results showed that the ML model was effective in identifying non-consistent essays with improved accuracy after implementing random oversampling. The LR model achieved an accuracy of 98.03%, precision of 98.52%, recall of 98.03%, and F1-score of 98.24%. The proposed ML model shows promise as an indicator of contract cheating incidents, providing an additional tool for educators and institutions to uphold academic integrity. However, it is essential to interpret the model results cautiously, as they do not constitute unequivocal evidence of cheating but rather serve as grounds for further investigation. We also emphasize the ethical implications of such approaches and suggest avenues for future research to explore the model’s applicability among first-language writers and to conduct longitudinal studies on second-language learners’ language development over longer periods.
... Academics strive to uphold integrity in their teaching, learning, and assessing to ensure students are developing knowledge and skills needed in the workplace. Historically, student cheating in exams (Bowers, 1964;McCabe, 1999McCabe, , 2005Christensen Hughes & McCabe, 2006), plagiarism in submitted essays or reports (Wilhoit, 1994;Ashworth et al., 1997;Park, 2003;Peters et al., 2022), students using essay mills or contract cheating (Clarke & Lancaster, 2006;Lancaster & Clarke, 2016;Rigby et al., 2015;Wallace & Newton, 2014;Eaton et al., 2022), degree frauds (Eaton & Carmichael, 2023), and others have been researched, discussed, debated, and possible ways to curb such behavior proposed and implemented. ...
... Contract cheating is a breach at which one pays another to complete an assessment (Lancaster & Clarke, 2016). The payee could be their colleague, their senior, or even a professional. ...
Artificial Intelligence (AI) can foster education but can also be misused to breach academic integrity. Large language models like ChatGPT are able to generate solutions for individual assessments that are expected to be completed independently. There are a number of automated detectors for AI assisted work. However, most of them are not dedicated to programming and/or they rely on existing student submissions (i.e., the learning approach). This paper presents a straightforward detector for AI assisted code, relying on code anomaly. No existing student submissions are needed. The detector employs 34 features covering constants, data structures, branches, loops, functions, and others. According to our evaluation on three data sets, the detector and its normalized variation are effective with 89% top-K precision. However, allowing discussion among colleagues and access to the internet might reduce the effectiveness by 25%. The effectiveness is further reduced by about the same amount when AI assistance is only used on some tasks, not the whole submissions. Although our detectors should be used with caution due to the limitations, it sufficiently shows that code anomaly can be distinctive for identifying AI assisted work. Instructors can start looking for the code anomaly among the submissions for such identification.
... The same study reported that 1.4% of recent PhDs admitted to scientific dishonesty themselves, whereas 3% said that they had experienced undue pressure to commit serious forms of dishonesty in their research. Among students, outsourcing academic work to a third party using contract cheating (Clarke & Lancaster, 2006;Lancaster & Clarke, 2016) is yet another type of misconduct: a systematic review of 65 studies of self-reported contract cheating noted a historical average of 3.52% of students committing such cheating, with a sharp increase to 15.7% in 2014 (Newton, 2018). In addition, such outsourcing tends to repeat itself: of those who have engaged in contract cheating, 62.5% were repeat offenders (Curtis & Clare, 2017). ...
Given the prevalence of misconduct in research and among students in higher education, there is a need to create solutions for how best to prevent such behaviour in academia. This paper proceeds on the assumption that one way forward is to prepare students in higher education at an early stage and to encourage a smoother transition from academic integrity to research integrity by incorporating academic integrity training as an ongoing part of the curriculum. To this end, this paper presents three checklists developed as part of the Erasmus+ Strategic Partnership project Bridging Integrity in Higher Education, Business and Society (BRIDGE, 2020-1-SE01-KA203-077973). The aim of the checklists is to help students and their supervisors to bridge academic integrity and research integrity in research training. The checklists target master students, doctoral students, and their supervisors. This paper presents the theoretical background of the checklists, how they were developed, their content, and how they may be used in supervising thesis/dissertation work to promote a transition from academic integrity to research integrity.
... Contract cheating is defined as compensating any third party for the production of assessed work and then submitting it as one's own (Clarke & Lancaster 2006). This might involve written assignments, presentation decks, and even sitting of actual examinations Lancaster & Clarke, 2016). Contract cheating services have become increasingly accessible and economically rational to students via several technological developments. ...
This paper presents the first systematic investigation into the search engine optimization practices of major contract cheating websites in the United States. From a business perspective, visibility in organic search engine results is considered one of the top client recruitment tools. The current understanding of student recruitment strategies by these companies remains largely unexplored in both academic literature and popular press. Replicating the business research practices used in the search engine optimization industry, comprehensive search engine ranking and traffic data was obtained for the 38 largest contract cheating websites in the US. The overall objective was to illuminate the strategies that these companies take to get their services at the top of the search results of as many students as possible – not just the relatively small proportion of students actively cheating. The results show that these companies dominate the search results for not just students searching to cheat, but also for naïve search efforts, when students are simply doing genuine research or classwork. These nefarious companies use highly sophisticated search engine manipulation strategies to bait naïve student searchers onto their sites, thus enabling the potential to switch them to cheaters. Higher education institutions, armed with the specific details provided in this study, can use the strategies outlined in the discussion to directly and negatively impact on the success of these contract cheating services.
... 7.3 Personal Gain: Financial incentives, bonuses, or rewards associated with academic performance may motivate lecturers to engage in dishonest practices during examination marking [1]. 7.4 Workload and Time Constraints: Lecturers with heavy workloads or time constraints may be tempted to take shortcuts or compromise academic integrity during examination marking to cope with the demands of their job [21]. 7.5 Personal Ethical Beliefs: While it is less common, some lecturers may engage in academic dishonesty due to their personal ethical beliefs or moral justifications [3]. ...
Academic dishonesty is a critical concern within the education system, often associated with students attempting to gain unfair advantages. However, there is a growing need to acknowledge the potential for academic dishonesty among lecturers during the examination marking process. This research paper aims to shed light on the hidden side of academic dishonesty by exploring the factors that contribute to the potential misconduct of lecturers during examination marking. The study reviews the motives, methods, and consequences of such dishonest practices and discusses the implications for maintaining the integrity of the academic assessment process.
... As well as being an area that universities and higher education providers must attend to, contract cheating is also an active area of academic research. Several summaries of current research and practice as it relates to the contract cheating field exist (Ahsan et al, 2022;Curtis et al, 2022;Lancaster and Clarke, 2016). ...
Commercial contract cheating, the act of requesting a third party to complete an assignment for payment, is a growing industry and poses a problem that academic institutions are trying to tackle internationally. The reach of the industry in nine fields of education and across four locations – Australia, the United Kingdom, Canada, and the United States – are analysed through an automated data-gathering process on a total of 4032 Google searches and with the help of a machine learning model trained to identify which results are essay mills. 49% of all results are found to be essay mills, 3247 of which results are found to be paid advertisements despite this being against Google’s advertising policies. The fields of Arts and Humanities and Education are found to be at the highest risk of further exploitation by the industry. The paper concludes by recommending that the educational community continues to monitor the reach of the contract cheating industry and that it considers solutions to further promote academic integrity.
... Academics strive to uphold integrity in their teaching, learning, and assessing to ensure students are developing knowledge and skills needed in the workplace. Historically, student cheating in exams (Bowers, 1964;McCabe, 1999McCabe, , 2005Christensen Hughes & McCabe, 2006), plagiarism in submitted essays or reports (Wilhoit, 1994;Ashworth et al., 1997;Park, 2003;Peters et al., 2022), students using essay mills or contract cheating (Clarke & Lancaster, 2006;Lancaster & Clarke, 2016;Rigby et al., 2015;Wallace & Newton, 2014;Eaton et al., 2022), degree frauds (Eaton & Carmichael, 2023), and others have been researched, discussed, debated, and possible ways to curb such behavior proposed and implemented. ...
... With the increase in online education during the COVID-19 pandemic, there has been a significant increase in the number of students taking online courses. This may create a competitive environment in which students feel pressure to perform well, even if it means engaging in contract cheating (Clarke & Lancaster, 2013;Lancaster & Clarke, 2016). ...
Aim/Purpose: The purpose of this study is to explore the correlation between contract cheating and online education in China, which has become a major concern due to the extensive promotion of online education worldwide amid the COVID-19 pandemic. Background: Contract cheating, also known as academic ghostwriting, refers to the act of students outsourcing academic assignments to third parties, who complete the work on their behalf. With the development of online education, the incidence of contract cheating is rising progressively. Whilst numerous scholars have conducted extensive research on the causes, prevention, and handling of contract cheating, the issue persists and needs further localized understanding. Methodology: This study employs a mixed-methods approach. First, textual data on Sina Weibo, a popular Chinese social media platform, is collected and analyzed using VOSviewer and NVivo12 software. Field observation methods are also utilized for theme analysis and sentiment analysis. Second, the theoretical framework of organizational theory is applied to explain the impact of different modes of online education implementation on contract cheating. Finally, based on the findings, possible solutions to mitigate contract cheating are proposed. Contribution: This study contributes to the literature by providing a theoretical framework to explain the relationship between online education and contract cheating in China. The study’s findings highlight the importance of the mode of online education implementation when addressing contract cheating. Findings: This study finds that online education does exacerbate contract cheating in China, and the extent of this phenomenon varies depending on the mode of online education implementation. This study also identifies the lack of academic integrity education and supervision as a major factor contributing to contract cheating. Recommendations for Practitioners: Reducing the costs of educational organizations in combating cheating through institutional arrangements, such as establishing effective channels of communication between teachers and schools and controlling teachers’ workload outside of their primary responsibilities, can help curb contract cheating. Recommendation for Researchers: Both history and reality have demonstrated that possible solutions cannot rely solely on new technologies or single institutional arrangements. Contract cheating is essentially an unethical means of competing for scarce resources, and as long as resources remain scarce, this phenomenon will persist. Impact on Society: As a social phenomenon, contract cheating cannot be completely eradicated through top-down policy enforcement. Future Research: The stringent enforcement against contract cheating also involves the education regulatory and judicial departments, and their relationship is worthy of future research.
... Academics strive to uphold integrity in their teaching, learning, and assessing to ensure students are developing knowledge and skills needed in the workplace. Historically, student cheating in exams (Bowers, 1964;McCabe, 1999McCabe, , 2005Christensen Hughes & McCabe, 2006), plagiarism in submitted essays or reports (Wilhoit, 1994;Ashworth et al., 1997;Park, 2003;Peters et al., 2022), students using essay mills or contract cheating (Clarke & Lancaster, 2006;Lancaster & Clarke, 2016;Rigby et al., 2015;Wallace & Newton, 2014;Eaton et al., 2022), degree frauds (Eaton & Carmichael, 2023), and others have been researched, discussed, debated, and possible ways to curb such behavior proposed and implemented. ...
... Assignment outsourcing involves students getting others to complete their assignments using '…essay mills, bespoke assignment services, essay bidding services, peerto-peer file sharing sites (peer-sharing sites), and obtaining work from other students, colleagues, friends and family members' (Awdry et al. 2020:1). While much has been written on this type of cheating (often referred to as contract cheating), in higher education (HE) in the last two decades (Bretag et al. 2019;Dawson & Sutherland-Smith 2018;Ellis et al. 2018;Lancaster & Clarke 2016), relatively little has come from the discipline of criminology, though this base of knowledge is growing. Detailed theoretical analyses and some empirical studies have emerged, employing methods and/or epistemologies drawn from criminal justice or criminology perspectives looking at university cheating, contract cheating or assignment outsourcing more broadly (Awdry et al. 2022;Clare Page 2 of 23 Awdry and Groves International Journal for Educational Integrity (2023) Rundle et al. 2019). ...
Assignment outsourcing is an intractable challenge for higher education. While various academic and legislative approaches have sought to explain/respond to this problem, recent media, community, and government concerns suggest students are increasingly outsourcing assessments. This paper reports on the qualitative findings of an international survey (n = 7000 +) of students’ perceptions and experiences of outsourcing, to test the utility of a multi-theoretical criminological explanation for this behaviour. The results reveal a complex learning environment where students’ knowledge is shaped by an assemblage of social, cultural, and institutional influences; a learning environment where engagement in, or avoidance of, cheating are dynamic. Interdependent behaviours are learnt, shared or observed, and reinforced through peer networks. Interrogation of students’ qualitative comments emphasises that intervention is possible, albeit equally complex.
... By ensuring that the answers they acquire are original, students are unlikely to be detected as having plagiarised when their work is run through text matching software. Contract cheating has been explored in multiple languages and suggested interventions are available, particularly taking the form of normative and educational interventions (Lancaster and Clarke, 2016;Comas et al., 2020). Although the problem is not new, evidence from student surveys suggests that the extent of contract cheating has increased in recent years (Newton, 2018). ...
Text matching tools employed to detect plagiarism are widely used in universities, but their availability may have pushed students to find ways to evade detection. One such method is the use of automatic paraphrasing software, where assignments can be rewritten with little effort required by students. This paper uses the search engine analytics methodology with data from SEMrush and Google Trends to estimate the level of interest in online automatic paraphrasing tools, focusing on the period 2016 to 2020 and the four countries: the USA, UK, Canada and Australia. The results show a concerning trend, with the number of searches for such tools growing during the period, especially during COVID-19, and notable increases observed during the months where assessment periods take place in universities. The method employed in this study opens up a new avenue of analysis to enrich and supplement the existing knowledge in the field of academic integrity research. The data obtained demonstrates that faculty should be alert for student use of automatic paraphrasing tools and that academic integrity interventions need to be in place across the sector to address this problem.
... To date, no studies report comprehensive connections between online test design choices and cheating threats. This research addresses scholars' calls for educators to adopt a holistic approach to addressing issues of academic integrity in educational institutions (Bretag 2013), by carefully structuring online tests to reduce the utility of students engaging in cheating (Lancaster et al. 2016). Although no assessment can be designed to perfectly deter all cheating (Bretag & Harper 2017), this research argues that a more comprehensive understanding of design choices and their relationship to cheating behaviours can enhance online test design practice. ...
Online testing is a popular practice for tertiary educators, largely owing to efficiency in automation, scalability, and capability to add depth and breadth to subject offerings. As with all assessments, designs need to consider whether student cheating may be inadvertently made easier and more difficult to detect. Cheating can jeopardise the validity of inference drawn from the measurements produced by online tests, leading to inaccurate signals and misperceptions about what students know and can do. This paper extends theoretical understanding about cheating behaviours to link online test design choices and their influence on a student’s capability and willingness to cheat. This research reviews the literature on cheating theories and a typology construction methodology to relate common online test design choices to their cheating threat consequence. In doing so, the typology offers educators designing online tests general normative guidance aimed at reducing threats to assessment inference validity, and academic integrity in general, brought about by student cheating. While we admit that cheating cannot be completely eliminated in online testing, the guidance provided by the typology can assist educators to structure online tests to minimise cheating.
... But tools for detecting plagiarism are constantly lagging behind the inventions they are designed to deter. If students submit AI-generated text, such cases represent "contract cheating" (Curtis & Clare, 2017;Lancaster & Clarke, 2015), but as we have shown, they are not plagiarism-copying and stealing other people's ideas. Rather, they are the opposite, the ideas of outis, nobody. ...
AI-based natural language production systems are currently able to produce unique text with minimal human intervention. Because such systems are improving at a very fast pace, teachers who expect students to produce their own writing—engaging in the complex processes of generating and organizing ideas, researching topics, drafting coherent prose, and using feedback to make principled revisions that both improve the quality of the text and help them to develop as writers—will confront the prospect that students can use the systems to produce human-looking text without engaging in these processes. In this article, we first describe the nature and capabilities of AI-based natural language production systems such as GPT-3, then offer some suggestions for how instructors might meet the challenges of the increasing improvement of the systems and their availability to students.
Students are increasingly relying on contract cheating (CC), a phenomenon in which a third party completes the assignment, quiz, or homework for students in exchange for a fee. Using an exploratory qualitative method and underpinned by critical theory and social responsibility theory, this study explored the perceptions of faculty members regarding CC in the United Arab Emirates’ (UAE’s) higher education institutions. In particular, this study addressed how faculty members perceive and deal with CC in contexts where policies towards the practice are absent from higher institution honour codes. Using thematic analysis, the results showed that CC arouses the indignation of faculty and staff to the violation of individual and religious rights. Also, they believe they have a sense of responsibility towards students and the community. The results also showed that faculty members’ hesitation in reporting CC incidents was due to their perceived lack of support from higher administration institutions and the lack of clear procedures in ethical manuals. This paper concludes with practical recommendations for faculty and staff, managers, department heads and decision makers to mitigate this phenomenon proactively.
Artificial intelligence offers the opportunity to revolutionise work and it is now ubiquitous globally. In higher education the use of generative artificial intelligence has raised concerns about the integrity of assessment and research. The current study analyses the academic integrity policy and practice at leading universities globally to assess the early response to the use of artificial intelligence. A sample of twenty universities (N=20) from four different countries—USA, UK, Australia, and Canada—were selected. Data was collected and analysed in May-June 2023. Fostering of academic integrity at the higher education institutions was assessed using the core elements of exemplary policy and framework for enacting exemplary academic integrity policy. A minority (45%) of the universities mentioned the use of artificial intelligence in their academic integrity policy. Higher education institutions globally need to update academic and research integrity policy and practice to facilitate the ethical use of artificial intelligence.
Este artigo apresenta conceitos básicos de integridade, integridade científica e integridade acadêmica bem como algumas propostas para a promoção da cultura de integridade nas Instituições de Ensino Superior, agências de fomento e fundações de pesquisa. Argumenta-se que: a) a ética e a integridade são conceitos distintos, mas inter-relacionados e que é produtivo associá-los em documentos, políticas institucionais e pesquisas; b) os conceitos de integridade científica e integridade acadêmica são essenciais para garantir a credibilidade e a confiabilidade da pesquisa; e c) a promoção de uma cultura de integridade requer a criação de políticas institucionais de ética e integridade.
Este verbete tem por objetivo apresentar conceitos básicos de
integridade, integridade na pesquisa, integridade científica,
integridade acadêmica e de política institucional de ética e
integridade, bem como destacar a importância e a necessidade da criação de políticas institucionais de ética e integridade nas agências de fomento, nas universidades e nas instituições de pesquisa.
For Computer Science instructors, upholding academic integrity requires approaching teaching and assessment in a way that encourages students to follow progressive principles such as honesty, trust, fairness, respect and responsibility, At the same time, instructors also have to take steps to minimise the risk of academic misconduct by students, whether intentional or accident. This means that instructors need to be aware of behaviours such as plagiarism, collusion, contract cheating, the use of machine generated answers, examination cheating and research fraud. Instructors also need to put measures into place to design out opportunities for students to engage in unacceptable behaviours. This chapter explores academic integrity from the perspective of the knowledge needed by a Computer Science instructor. This is a changeable feast, as new methods to subvert academic integrity are always emerging, particularly in Computer Science where students are already technically sophisticated and understand how to use artificial intelligence-based solutions that can solve many standard assessment tasks. As such, the chapter recommends that although detecting breaches of academic integrity may be necessary, instructors should lead by example, work in partnership with students and develop a curriculum with a pro-active focus on academic integrity.KeywordsAcademic integrityAcademic misconductPlagiarismContract cheatingArtificial intelligence
Background
Institutions of higher learning are persistently struggling with issues of academic dishonesty such as plagiarism, despite the availability of university policies and guidelines for upholding academic integrity.
Methodology
This was a descriptive qualitative study conducted on 37 students of a Healthcare Ethics course at an Australian tertiary institution from February 2016 to October 2018. The purpose of the study was to explore the reasons for plagiarism detected the TurnitinR plagiarism checking software and extensive review of manuscripts. The interviews were conducted in private rooms and in strict confidence. Thematic analysis was manually done.
Results
Four major themes namely, lack of interest; pressure of time with competing priorities; lack of understanding of the policy on academic honesty, and “the determined students” were identified. Sub themes under lack of interest were lack of preparation and effort, low self-efficacy, poor studying techniques, and convenience of internet sources. Under pressure of time, the subthemes were, misplaced priorities, procrastination, high workloads, poor planning, competing interests, and the perception of availability of time at the start of the semester. Regarding lack of understanding of the policy on academic honesty, the subthemes identified were, lake of awareness of plagiarism, lack of awareness of acceptable similarity, conflicting messages from tutors and confusion with high school learning. The determined students were those that either made all effort to reduce plagiarism but still remained high, used the another language at home other than English, had poor paraphrasing techniques or lacked resources for English language editing.
Conclusion
There are varied and diverse reasons for plagiarism. There is a need to systematically reinforce and educate students on issues pertaining to academic dishonesty and their associated implications.
Contract cheating requests are typically not visible to researchers looking to explore the problem, but when these are made through publicly accessible outsourcing platforms, a greater understanding of contract cheating and possible solutions for this problem can be developed. This chapter presents an analysis of 3843 outsourcing requests observed on a freelancing website between 7th August 2017 and 9 September 2019. The focus is on requests tagged as academic writing or essay writing. This fresh analysis builds on previous research conducted on freelancing sites. An overview of previous findings is provided at the start of the chapter.The contract cheating requests seen on the Freelancer.com website are highly varied in nature, with some showing sophisticated workflows. The most frequent buyers say they are in India and the most frequently hired contractors in Kenya, but buyers and contractors are seen to operate from all around the world. Outsourced writing support and assignment production services can be purchased for many academic disciplines. On average, buyers pay $67.67 United States Dollars (USD) per project outsourced, but with price premiums exist for certain types of work. Of particular concern for the sector are a notable number of requests for work in the medical field, attempts at admissions fraud and the market for ghost-written academic research papers. The chapter concludes by advocating further analysis at discipline level, ideally supported by student academic integrity partners and champions.KeywordsContract cheatingFreelancer.comGhost writingAcademic writingArtificial intelligence
Essay mills providing contract cheating services over the Internet are a thriving twenty-first century industry. In the UK, this has resulted in legislation prohibiting commercial academic writing services and a shift in priorities from prevention to detection of contract cheating. This in turn has placed university assignment markers on the frontline of contract cheating detection efforts. Linguistic analysis of texts written for university assignments using stylometric authorship analysis (Crockett and Best, 2020; Juola, 2017; Turnitin Authorship Investigate, 2019) has proved a useful tool for investigations of suspected cheating, linguistic tools to support contract cheating detection during routine assignment marking are limited. Fortunately, the commercial practices of essay mills have led to the wide availability of known commercial and student-written essays on the Internet. This research exploits this resource by applying investigative corpus linguistic methods utilised in fake news and fake online review detection to the problem of ‘fake essays’.756 commercial and student Law, Business and Nursing essays, a subset of a sample of over 12,000 essays downloaded from a leading UK-based essay mill website, were analysed using cognitive, affective and functional linguistic features drawn from a range of academic writing frameworks. Deploying natural language processing tools and a data pipeline consisting of four separate principal components analyses followed by logistic regression text classification, this research demonstrates that commercial essay writing is distinguishable from authentic student essay writing with ten distinct linguistic components. Commercial academic writing was found to display a superficial quality with writers maximising the appearance of quality through lexical sophistication and adherence to classic academic writing conventions whilst minimising cognitive effort through repetitiveness, redundancy, verbosity and text inflation strategies. A predictive text classification model with fivefold cross validation achieved 82% accuracy (12% above the majority class baseline). A contract cheating detection matrix is presented that can be used to guide markers in marking assignments on dimensions of cognitive effort as well as quality.KeywordsContract cheatingGhost-writingEssay millsAcademic writingAssessmentInvestigative corpus linguisticsForensic linguisticsDeception detectionText classification
The Reddit platform offers users access to more than two million discussion forums as of 2021, each known as subreddits. The subreddits include discussions aimed at university staff and at students. The role of question-and-answer subreddits in an academic integrity setting has not been explored within the research literature, but their availability potentially provides students with the ability to commit academic misconduct.This chapter considers how Reddit is being used by students to access contract cheating providers who are offering students unauthorised help with homework questions. The wide range of questions being asked are considered. Many homework style questions on Reddit are seen to have a mathematical base to them. An analysis of 141,136 homework help requests shows peak requests to match typical student deadlines with a spike in requests matching the start of the Covid-19 pandemic.The chapter concludes by noting that other question-and-answer sites exist and are being misused by students. The chapter recommends further exploration and the use of machine learning techniques to aid in large scale data processing in the academic integrity field. A warning is also provided to be passed on to students about the risks associated with contract cheating using question-and-answer sites, including the scams in operation and the chance of being detected.KeywordsContract cheatingRedditCommunitiesHomework helpFile sharing
This paper reports on progress and findings to date on an ongoing action research
project designed to address the problem of academic malpractice, notably collusion,
amongst postgraduate students on an international MBA programme. Its roots lie in
2008 when it was found that case study assignments had largely designed-out plagiarism but that collusion had taken its place with the result that 132 cases were taken to
the University‟s Unfair Practices Committee. Understanding the problem was approached in several ways, including reference to existing literature, which highlighted
the importance of students‟ previous cultural and educational experiences, and qualitative research drawing on students‟ views and feelings. As a result, a two-pronged
strategy was adopted, one element being a zero-tolerance policy with all MBA assignments submitted to the Turnitin text matching software and wide broadcasting of the
dangers and penalties resulting from malpractice. These were coupled with strengthening the induction and Study Skills elements of the programme in order to develop
students‟ independent study skills and understanding and ability to comply with UK
academic conventions. We conclude that the dual strategy of prevention and cure
was effective, resulting in the overall rate of academic malpractice falling from a high
of 34.8%, and of collusion of 26.6%, to single figures with both being maintained with
subsequent cohorts. The ongoing question of how best to adapt teaching practices to
suit the background and expectations of international students remains unresolved.
Therefore, further research is being conducted with selected preliminary findings being presented in this paper.
We conduct the first empirical economic investigation of the decision to cheat by university students. We investigate student demand for essays, using hypothetical discrete choice experiments in conjunction with consequential Holt–Laury gambles to derive subjects’ risk preferences. Students’ stated willingness to participate in the essay market, and their valuation of purchased essays, vary with the characteristics of student and institutional environment. Risk preferring students, those working in a non-native language, and those believing they will attain a lower grade are willing to pay more. Purchase likelihoods and essay valuations decline as the probability of detection and associated penalty increase.
Contract cheating is the process whereby students auction off the opportunity for others to complete assignments for them. It is an apparently widespread yet under-researched problem. One suggested strategy to prevent contract cheating is to shorten the turnaround time between the release of assignment details and the submission date, thus making it difficult for students to make arrangements with contractors. Here, we outline some characteristics of the current market for contract cheating and demonstrate that short turnaround times are unlikely to prevent contract cheating because requested turnaround times for university-level assignments completed via contract cheating are already short (average 5 days). In addition, for every contractor awarded a job, there are an average of 10 others offering to complete it within the specified time suggesting that there is abundant excess capacity in the market.
The free-rider problem, also known as social loafing, occurs when one or more members of a group do not do their fair share of the work on a group project. In this article, the authors present a group evaluation instrument characterized by early implementation, multiple evaluation points, and the use of specific evaluative criteria. They tested their assessment method on a sample of 330 undergraduate students enrolled in an introductory, crossdisciplinary business course. The results suggest that the use of this instrument can mitigate free-rider problems and improve students' perceptions about groups and group projects.
Academic institutions can sometimes make it easy for students to gain qualifications using dishonest means. This paper is a guide for students that motivates and suggests modern techniques that can be used to cheat. The methods are inspired by the authors’ own experiences, especially from researching contract cheating and student plagiarism. They have been selected to be suited to students with a technological background, such as Computing students. The five tips covered include: (i) choosing modules to cheat on; (ii) creating a ‘stone soup’ assignment from other peoples’ cumulative contributions; (iii) outsourcing the work using an auction site; (iv) using online communities to create private cheating networks; and (v) using TurnItIn.com [1] to improve off-the-shelf assignments. No attempt is made to glamorise cheating. It is hoped instead that the paper will provoke open discussion amongst tutors and students alike.
The paper argues that the word pairs metric, which calculates the proportion of consecutive words in common between two documents, is the most suitable metric for automatically comparing documents to find possible plagiarism. The metric is shown to meet three criteria for similarity detection, namely that the process should be effective, efficient for tutors and computationally efficient. Tests show that the metric closely correlates with the list of ordered similar pairs of documents that could have been found by exhaustive, visually aided, manual checking of real corpora.
The paper studies the use the RentACoder Web site to contract cheat by Computing students. RentACoder is an outsourcing service for computer work which operates under auction principles. Contract cheating is where students have assessed work completed for them on their behalf. The work is original, so not will be detected by the regular anti-plagiarism mechanisms that look for shared commonality. The paper describes the background to contract cheating and discusses a catalogue of 910 bid requests collected by the authors over two and a half years. The UK is seen to supply them with over 25% of contract cheating bid requests. This is largely composed of students outsourcing Java programming assignments; substantial projects are highlighted as a concern. Trends are seen to exist for other countries but are not the same as those identified for UK students.
Academic institutions are finding they have to operate under a pro-active anti-plagiarism policy, where plagiarism is actively sought out as a serious breach of acceptable academic behaviour. This paper considers the reasons that institutions need such a policy and the issues they should be aware of when implementing one.
Student plagiarism, the process where a student uses the words or ideas of another without acknowledgement and for academic credit, is believed to be increasing. This is of concern since it devalues the awards that academic institutions make and has recently been receiving increased media attention. This thesis presents a process through which similarity within a corpus of documents can be found and verified by a tutor to see if it represents plagiarism. Two key requirements for the process are identified. The first is that it should be effective in that it correctly identifies those documents that are the most similar. The second is that it should be efficient; this means both computationally and in terms of tutor workload.
A number of new ideas are introduced. The literature study reveals that there is no consistency in the terms used to talk about plagiarism and a taxonomy is proposed. It also finds inconsistencies in classifications of detection engines for source code plagiarism. Alternative classifications that do not preclude free text engines are presented. The main shortcoming of existing systems is that although the engines might be effective the systems they support impact too greatly on a tutor's time.Hence they are not efficient.
A four-stage detection process consisting of collection, analysis, verification and investigation is proposed. The greatest need for tool support would be on the labour intensive verification and investigation stages. Here a tutor has to examine two documents that have been flagged during the analysis stage. A visual approach to demonstrate the similarity is recommended. A new graphic known as a similarity visualisation is used that presents pixels whose intensity is generated by the commonality of overlapping word fragments. The visualisations are deployed by an interactive tool named VAST that allows quick verification and investigation of suspect areas of the two submissions.
The similarity visualisation is argued to provide the best representation of similarity between two submissions and an ordering of pairs based on its properties is argued to be effective. Generating visualisations for all possible pairs of a large corpus is considered to not be currently computationally feasible. Instead, this ordering is approximated using less computationally intensive metrics. Using real and synthetic submissions it is argued that the word pairs metric, based upon the proportion of two consecutive words that two submissions have in common, is demonstrated to be the most efficient and effective metric.
The paper identifies a growing problem, referred to as contract cheating, considered to be the successor to pure plagiarism. Contract cheating is defined as the submission of work by students for academic credit which the students have paid contractors to write for them. The usage of one particular site, RentACoder, known to be used for contract cheating is manually monitored. RentACoder is a site where computer solutions are written to contract for legitimate uses but can also be used for students to cheat. An exhaustive study shows that 12.3% of bid requests placed on RentACoder are identified as contract cheating. The primary study reported in the paper quantifies and discusses these contract cheaters. Out of 236 identified contract cheaters only 8.1% of these have made only a single bid request. Over half of the 236 cheaters have previously requested between two and seven pieces of work. The paper argues that this shows that this form of cheating is becoming habitual. The primary study identifies that as well as the usual types of individual students using the services of RentACoder non-originality agencies also appear to be working as subcontractors offering to complete student assignments. This adds an extra layer of complexity to methods of tracking cheating students. The paper concludes by advising that more automated detection techniques are needed and advises that assessments and academic policies need to be redesigned to remove the potential for contract cheating to be committed.
Twenty years ago, plagiarism was seen as an isolated misdemeanor, restricted to a small group of students. Today it is widely recognized as a ubiquitous, systemic issue, compounded by the accessibility of content in the virtual environment. Student Plagiarism in an Online World: Problems & Solutions describes the legal and ethical issues surrounding plagiarism, the tools and techniques available to combat the spreading of this problem, and real-life situational examples to further the understanding of the scholars, practitioners, educators, and instructional designers who will find this book an invaluable resource.
This chapter outlines various strategies employed to reduce plagiarism both at a departmental and an institutional level. A detailed description and evaluation is given of two workshops that were designed specifically to educate students about the nature of plagiarism. The workshops also aim to provide students with alternatives to plagiarism by improving their writing skills. Most importantly, we believe that students should learn about plagiarism in the context of professional ethics and an ethical attitude should be promoted throughout their study. By using both an ethical and educational approach to dealing with plagiarism, we hope that students will learn that they have nothing to gain from plagiarising and be confident in their own skills.
Written for Higher Education educators, managers and policy-makers, Plagiarism, the Internet and Student Learning combines theoretical understandings with a practical model of plagiarism and aims to explain why and how plagiarism developed. It offers a new way to conceptualize plagiarism and provides a framework for professionals dealing with plagiarism in higher education. Sutherland-Smith presents a model of plagiarism, called the plagiarism continuum, which usefully informs discussion and direction of plagiarism management in most educational settings. The model was developed from a cross-disciplinary examination of plagiarism with a particular focus on understanding how educators and students perceive and respond to issues of plagiarism. The evolution of plagiarism, from its birth in Law, to a global issue, poses challenges to international educators in diverse cultural settings. The case studies included are the voices of educators and students discussing the complexity of plagiarism in policy and practice, as well as the tensions between institutional and individual responses. A review of international studies plus qualitative empirical research on plagiarism, conducted in Australia between 2004-2006, explain why it has emerged as a major issue. The book examines current teaching approaches in light of issues surrounding plagiarism, particularly Internet plagiarism. The model affords insight into ways in which teaching and learning approaches can be enhanced to cope with the ever-changing face of plagiarism. This book challenges Higher Education educators, managers and policy-makers to examine their own beliefs and practices in managing the phenomenon of plagiarism in academic writing.
Although online courses can provide access to higher education through e-learning systems which would not otherwise be available for students, they also pose challenges for academic integrity. Paramount to this is contract cheating, where students have been observed paying other people to complete work for them to complete their online courses. This paper analyses attempts by students at contract cheating using Transtutors.com, which is a billed as a site for homework support. A sample of 174 online assignments found on Transtutors.com are analysed and traced back to 17 online universities. Assignments from online institutions are demonstrated to be a particular problem for contract cheating detectives, since notifying staff at those institutions of attempts by their students to cheat has proved to be difficult or impossible. The paper concludes by looking at the wider issues posed by online contract cheating and the opportunities for automated detection within this field.
Analysis of student survey data from 6,096 respondents in thirty-one institutions found that academic dishonesty was associated with the existence of an honor code, student perceptions of the certainty of being reported, the severity of penalties, and cheating among peers.
Plagiarism is a problem. Most of the existing literature on source code plagiarism focuses on detecting plagiarism within a body of work when two submissions are found to be suspiciously similar. There are a number of tools that do this, and some of these work very well. Obviously, these tools will not detect anything untoward if the offending work comes from outside the collection of work that is being assessed. It is now easy to obtain small bespoke programs using one of several web sites. This study sets out to examine how these sites work, and to determine how easy it is to present this work for assessment while escaping detection.
The advantages of using contextual information in order to detect contract cheating attempts by students have not yet been fully explored in the academic literature. Contract cheating occurs when a student uses a third party to produce assessed work for them. This paper focuses on contract cheating using agency websites, where an auction type process is used by students to select a contractor to have the assessed work produced for them, often at a financially advantageous price. Currently, the process of finding contract cheating on agency sites is manually intensive, with a detective required to investigate and attribute each cheating attempt. This paper aims to formally identify the context internally and externally available for contract cheating posts on an agency website. The paper is offered as a starting point for academics interested in producing an automated intelligent contextually-aware tool to detect contract cheating.
Although methods for automatically detecting contract cheating, that is finding students who have outsourced the production of their assessed work to a third party, have been proposed, successful implementations of these detection methods have not yet been reported. This paper instead reports on an investigation to make use of a database of known work for this purpose. The work is accessed through the non-originality engine Turnitin, against which attempts at contract cheating found on agency websites are matched.
369 assignment specifications found on online agency contract cheating sites, such as Freelancer.com, were collected between January and November 2013. These were all assignment specifications for which attempts to attribute these with any level of certainty to an academic institution had proved impossible to a contract cheating detective. The assignment specifications all represented cases that looked likely to belong a UK educational institution. The assignment specifications were run through the Turnitin database in use within the UK and the results analysed as part of a process attempting to notify tutors that one of their students may be attempting to cheat.
The initial indications were that the use of Turnitin was of value to the contract cheating detection process, with 105 out of 369 (28.5%) initially identified. 2 out of 369 (0.5%) were subsequently found by a tutor at the institution concerned as a result of being in the database. However, several challenges were identified that will require the Science, Technology, Engineering and Mathematics (STEM) communities to come together and work to improve the use of Turnitin within the contract cheating detection process. This paper explores the results of this study and the wider issues surrounding the use of Turnitin for the detection of contract cheating.
Many forms of student plagiarism are detectable, providing that staff are given time, training and access to the most suitable Text Matching Tools. This chapter provides a background to how Text Matching Tools can be used to support the entire educational process, from helping students to write better assignments, to finding students who are attempting to cheat their way to an academic qualification by using external sources, such as the web, without acknowledgement.
The chapter begins with a brief review of how Text Matching Tools operate by finding common word patterns. Where these patterns exist across multiple pieces of student work, this generally indicates collusion. Alternatively the pattern may share form with other sources, indicating copying. The chapter continues by discussing how these Text Matching Tools can be integrated into the assessment process, providing some level of consistent indication when work submitted is not that of the expected student.
Text Matching Tools can never be a “one-stop” solution to plagiarism. They do have limitations as to what sources they can find. The drawbacks of becoming reliant on Text Matching Tools are explored in the chapter.
One underused feature of these tools is the role that they play in educating students and presenting plagiarism. Methods through which this can be accomplished are discussed.
The chapter concludes by discussing emerging issues in tool supported plagiarism detection, such as the original work provided through contract cheating services. This is intended to inform academics about the challenges that lie ahead.
The process of contract cheating, the form of academic dishonesty where students outsource the creation of work on their behalf, has been recognised as a serious threat to the quality of academic awards. Unlike student plagiarism, this cheating behaviour is not currently detectable using automated tools.
This paper analyses the monetary value of contract cheating to the different parties who play a role in the contract cheating process. The main analysis is based on a corpus consisting of 14,438 identified attempts to cheat. The corpus was collected between March 2005 and July 2012. The corpus was formed as part of a manual contract cheating detection process identifying students using online agencies. These online agencies are web sites which enable students to contract cheat. The agencies usually benefit from this by receiving a percentage cut of the money raised from the contract cheating that they facilitate. This corpus is used as the basis of an attempt to quantify the monetary value of contract cheating to online agencies.
Other parties exist who benefit from the contract cheating process. The paper identifies several such parties and gives examples of the monetary value of contract cheating to each of them. Most notably this includes the contractors who bid for the opportunity to produce work on behalf of the students. Further, the paper identifies the role of intermediary contractors. These are people who post assignment requests on agency sites but who are not themselves students. These intermediary contractors appear to benefit by first receiving requests to complete work for students and then re-outsourcing this work at a much lower cost than they were paid. The group of frequent workers, that is people who regularly work on student assignments and hence benefit financially, is also identified.
The paper concludes by presenting the changing trends in contract cheating that the authors have observed since they started working against this form of academic misconduct in 2005. Finally, recommendations for academics towards dealing with the issues posed by contract cheating are provided.
Student cheating and plagiarism present a combined threat to the value of academic awards. The technological age has increased the ease with which students can cheat. Although some computerised solutions exist to detect plagiarism and cheating in its other forms, many of these are easily fooled. For other types of cheating, technical solutions are not yet widely available. This suggests that students are receiving awards that they do not deserve. This paper presents three different examples of student cheating, all of which provide academics with a problem. These issues include: (1) plagiarism of documents through automated essay spinning, (2) social media facilitated student cheating groups, and (3) contract cheating using agency and auction web sites. Each of these problems is shown to benefit from the provision of intelligent context-aware systems. The context behind each problem is explored and suggestions for technical implementations of intelligent context-aware systems for each are provided.
This paper describes an illuminative small-scale study that piloted an initial survey instrument intended to investigate correspondences between 47 undergraduate Education final year students' use of information and communications technology (ICT), including the Internet, and – within the context of their adoption of tactics intended to impress lecturers or to exploit the hidden curriculum – students' engagement in cheating behaviours such as plagiarism. The study disclosed that 0.23 of the sample had reported single instances of cheating behaviours and that 0.21 of the sample had reported multiple instances of cheating behaviours. Analysis of data discerned correspondences between these cheating behaviours and personal factors. However, indicators of ICT capability and the Internet did not correlate significantly with cheating behaviours. Those students who had reported multiple instances of cheating behaviours were found to rate their ICT capabilities higher than their peers but had a tendency to report less frequent use of the Internet for coursework. Inferences are tentatively drawn for further research and for academic practices. © 2012 Wiley Periodicals, Inc.
‘Contract cheating’ has recently emerged as a form of academic dishonesty. It involves students contracting out their coursework to writers in order to submit the purchased assignments as their own work, usually via the internet. This form of cheating involves epistemic and ethical problems that are continuous with older forms of cheating, but which it also casts in a new form. It is a concern to educators because it is very difficult to detect, because it is arguably more fraudulent than some other forms of plagiarism, and because it appears to be connected to a range of systemic problems within modern higher education. This paper provides an overview of the information and literature thus far available on the topic, including its definition, the problems it involves, its causal factors, and the ways in which educators might respond. We argue that while contract cheating is a concern, some of the suggested responses are themselves problematic, and that best practice responses to the issue should avoid moral panic and remain focussed on supporting honest students and good academic practice.
Many Computing Schools use plagiarism detection techniques on student source code submissions, but these can greatly add to tutor workload. Visual support for the detection process is now becoming available. This paper classifies and compares the different visual techniques that can be used to detect source code plagiarism including applicable techniques from the free text detection literature. It suggests how the visual tools can be used to support an existing source code detection process.
The problem of maintaining academic integrity when setting and marking assignments is of continued concern. Assignment specifications need to be structured so as to minimise the opportunities available for students to cheat. This includes students colluding with their peers and through contract cheating. One solution is to individualise the assessment taken by each student, so that each student within a cohort works
on a different problem. This offers an additional benefit of adding elements that allow an assignment specification found placed on a contract cheating auction site to be traced back to the culprit.
This paper presents a number of methods through which assessment can be individualised. The focus is on individualisation that is led by staff. Four case studies of computing assignment specifications that the authors have individualised are presented. The intention of this paper is to assist tutors who are considering implementing their own individualisation strategies.
The issue of attribution, identifying the institutions which students who attempt to outsource work are from, poses a major difficulty for detectives monitoring online sites used for contract cheating. This form of academic misconduct occurs when students get other people to complete assessed work for them. Previous studies on contract cheating have focused on student use of Internet-based outsourcing services. The studies have demonstrated that those sites primarily provide students with work for subjects falling within the computing spectrum.
This paper focuses on a study of 627 sample postings made on EssayBay, a commercial site aimed at providing assignment writing solutions for students. The study identifies that students across a range of academic subjects and levels of study, far beyond the computing field, are using EssayBay for purposes of contract cheating. Only 23.7% of the postings investigated are found to be attributable, that is, they can be traced back to the academic institution to which the assignment specification belongs. This suggests that there are issues across the sector with the way that assignments are set and made available for detectives.
Based on the study, two factors for measuring the attributability of a posting on a contract cheating are proposed, namely searchability and individuality. Searchability measures how easily a posting can be found using a search engine. Individuality measures how unique an assignment specification is. Generally, both searchability and individuality are necessary to allow assignment specifications to be attributed. The paper concludes by making recommendations detailing how academic departments can combat contract cheating by improving the attributability of the assignment specifications that they release.
This paper proposes a systematic six-stage process that tutors can use to detect students who are contract cheating. Contract cheating is where students have original work completed for them and submit it, without acknowledgement, for academic credit. A background to the problem is presented along with the current problems of preventing and detecting contract cheating. Examples of how pervasive computing techniques have made it easier for students to cheat are given. A description of how contract cheating is currently detected is presented, with shortcomings of these methods detailed. The paper formalises new six-stage contract cheating detection process developed to parallel approaches taken in the plagiarism literature.
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List of sites associated with contract cheating. http:// cboard. cprogramming. com/ attachments/ brief-history-cprogramming-com/ 8927d1242763399-contract-cheating-680_ workshop_ list. pdf
- R Clarke
Contract cheating – The hidden trend in computer science education
- G Koumantaris
The contract cheating saga of crazylarry23 the-contract-cheating-saga-of-crazylarry23
- T Lancaster
The current landscape of contract cheating [Presentation slides]. Higher education academy contract cheating workshop. http:// www. slideshare. net/ ThomasLancaster/ contract-cheatingcomputin gdiscipline-currentlandscape
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Essay mills: University course work to order [News story]. Times Higher Education
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Pace university researchers work on new way to stop online cheating [News story]
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Moving beyond plagiarism detection towards a culture of academic integrity
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Cheating goes global as essay mills multiply
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How do you stop online students cheating?
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Inverse authorship attribution [Presentation slides], Higher education academy contract cheating workshop
- F Culwin
Inside the black market for college homework [News story]. http:// dailydot. com/ lifestyle/ college-professors-black-market-paper
- M Fenn
Prevention, detection and policies in contract cheating [Presentation slides]. Higher education academy workshop. http:// www. slideshare. net/ ThomasLancaster/ prevention-detection-and-policies-in-contract-cheating-higher-education-academy-workshop-at-birmingham-city-university
- T Lancaster
http:// www. transtutors. com
- Transtutors