Academic misconduct in all its various forms is a challenge for degree-granting institutions. Whilst text-based plagiarism can be detected using tools such as Turnitin™, Plagscan™ and Urkund™, contract cheating and collusion can be more difficult to detect, and even harder to prove, often falling to no more than a ‘balance of probabilities’ rather than fact. To further complicate the matter, some students will make deliberate attempts to obfuscate cheating behaviours by submitting work in Portable Document Format, in image form, or (...) by inserting hidden glyphs or using alternative character sets which text matching software does not always accurately detect.Educators do not tend to think of academic misconduct in terms of criminality per se, but the tools and techniques used by digital forensics experts in law enforcement can teach us much about how to investigate allegations of academic misconduct. The National Institute of Standards and Technology’s Glossary describes digital forensics as ‘the application of computer science and investigative procedures involving the examination of digital evidence - following proper search authority, chain of custody, validation with mathematics, use of validated tools, repeatability, reporting, and possibly expert testimony.’. These techniques are used in criminal investigations as a means to identify the perpetrator of, or accomplices to, a crime and their associated actions. They are sometimes used in cases relating to intellectual property to establish the legitimate ownership of a variety of objects, both written and graphical, as well as in fraud and forgery. Whilst there have been some research articles and case studies that demonstrate the use of digital forensics techniques to detect academic misconduct as proof of concept, there is no evidence of their actual deployment in an academic setting.This paper will examine some of the tools and techniques that are used in law enforcement and the digital forensics field with a view to determining whether they could be repurposed for use in an academic setting. These include methods widely used to determine if a file has been tampered with that could be repurposed to identify if an image is plagiarised; file extraction techniques for examining meta data, used in criminal cases to determine authorship of documents, and tools such as FTK™ and Autopsy™ which are used to forensically examine single files as well as entire hard drives. The paper will also present a prototype of a bespoke software tool that attempts to repurpose some of these techniques into an automated process for detecting plagiarism and / or contract cheating in Word documents.Finally, this article will discuss whether these tools have a place in an academic setting and whether their use in determining if a student’s work is truly their own is ethical. (shrink)

Is academic integrity research presented from a positive integrity standpoint? This paper uses Natural Language Processing techniques to explore a data set of 8,507 academic integrity papers published between 1904 and 2019.Two main techniques are used to linguistically examine paper titles: bigram analysis and sentiment analysis. The analysis sees the three main bigrams used in paper titles as being “academic integrity”, “academic dishonesty” and “plagiarism detection”. When only highly cited papers are considered, negative integrity bigrams dominate positive integrity bigrams. For (...) example, the 100 most cited academic integrity papers of all time are three times more likely to have “academic dishonesty” included in their titles than “academic integrity”. Similarly, sentiment analysis sees negative sentiment outperforming positive sentiment in the most cited papers.The history of academic integrity research is seen to place the field at a disadvantage due to negative portrayals of integrity. Despite this, analysis shows that change towards positive integrity is possible. The titles of papers by the ten most prolific academic integrity researchers are found to use positive terminology in more cases that not. This suggests an approach for emerging academic integrity researchers to model themselves after. (shrink)

The study employs a sequential explanatory mixed-method design and aims to understand contract cheating behavior by conducting a survey of 1,081 undergraduate students in Indonesia and following up with five respondents to explore those results in more depth. In the first quantitative phase, we collected a variety of information from questionnaires about students’ practice with contract cheating. However, the interviews provided considerable depth of the students’ experiences, motivations, and attitudes toward contract cheating. Of the 1,081 participants, 73 students (6.75%) reported (...) engaging in contract cheating. The survey responses revealed preliminary insight into students’ experiences with contract cheating and the prevalence of this phenomenon in Indonesia. In the semi-structured interviews with a subsample of survey participants (n = 5), we applied the theory of planned behavior (TPB) to elicit attitudes, subjective norms, and perceived behavioral controls toward contract cheating. Our study revealed that students will have a higher chance of pursuing contract cheating when: (a) they believe that contract cheating provides various benefits (positive attitude toward contract cheating), (b) many of their friends are doing the same thing and expect them to do the same (subjective norms), and (c) they can control their contract cheating behavior to avoid being caught (perceived behavioral control). (shrink)

Academic staff owe a duty of fidelity to uphold institutional standards of integrity. They also have their own values and conceptions of integrity as well as personal responsibilities and commitments. The question of how academic practitioners address or reconcile conflicting values and responsibilities has been underexplored in the literature. Before we can examine effectiveness of academic integrity strategies and develop best practices, we need to examine the breadth of integrity decisions. To this end we posited the academic integrity problem as (...) a set of seven dilemmas and presented them to post-secondary education staff located in Europe, North America, Oceania, and Asia. We asked the participants to recommend a solution to each dilemma. This yielded a modest sample of 498 themes across 30 categories. We expected the responses to fall on a binary scale where decisions either support the integrity or ignore it. However, the data suggests that academic integrity decisions are better suited to continuum where participants aim to reconcile personal and institutional obligations. We further argue that academic integrity decisions are predicated on personal experience and therefore pose a challenge for policy standardization and enforcement. We conclude with a discussion of the implications of the findings for practice. (shrink)

Contract cheating – outsourcing student assignments for a fee – presents a growing threat to the integrity of higher education. As contract cheating is based on students purchasing assignments that are original, traditional plagiarism detection tools remain insufficient to detect contract cheating. Part of the problem is that proving contract cheating is difficult. As a result, instructors may find it hard to prosecute students. To help address the problem, this conceptual paper builds upon extant scholarship on contract cheating and argues (...) that a novel evidence-based approach is needed. Such an approach should allow instructors to detect and prosecute cases of contract cheating effectively and efficiently. The paper then presents an outline of such an approach and calls it the “Doping Test” approach as it mimics some aspects of doping testing in professional sport. (shrink)