Introduction
Within higher education, the language of ethics and integrity has become increasingly complex, particularly for students. Terms such as plagiarism, academic misconduct (AM) and academic dishonesty are often used interchangeably in academic practice and discourse. Yet, such terms differ in scope and ethical orientation, and their emphasis and adoption vary by space and time. While I do not seek to conduct a semantic evaluation of the terminologies in this commentary, it is clear that academic integrity remains the backbone of scholarly institutions across the world, as it builds trust, equity and responsibility in academic work. Yet, for many non-native English-speaking students (NNES), maintaining these standards within institutions where English is the medium of instruction presents complex cultural, linguistic and systematic challenges. Although these issues have always been present, the exponential growth of transnational higher education has magnified the complexity of what academic integrity really means in practice and how to address it. Of course, any academic trying to make sense of academic integrity cannot ignore the pace and prevalence of artificial intelligence and technological development over the past few years. In this commentary, I reflect on the scope and evolution of AM, the gravity of the issue in the context of artificial intelligence and implications for adjustments relating to NNES.
Scope of academic misconduct pre-AI
Most higher education institutions have always had strict policies on AM prior to the emergence of artificial intelligence. Misconduct was often labelled as low to severe depending on the level of integrity breach, with low often resulting in a warning or an advisory on academic expectations and severe leading to expulsion or a failed grade. The issue is not limited to contemporary institutions; in the medieval era, at Bologna University (c.1088), Paris University (c.1150) and Oxford University (c.1167), academic integrity, broadly speaking, was the remit of the Catholic Church's intellectual framework, which meant that AM was mostly a moral issue and less an administrative issue. Misconduct, therefore, was not simply a procedural breach but was considered a serious sin – that is, a failure of both intellectual fit and virtue. Although plagiarism was not codified as it is today, any form of dishonesty, disobedience or falsification was deemed serious, inviting judgement by the Church courts. Such offences would have been regarded as sufficiently serious to have wider implications for the individuals and their future careers.
As universities became more secular and industries became more reliant on the outputs of universities (including graduates and research discoveries), academic integrity and, by extension, AM became more mainstream aspects of teaching and learning. This prominence led several universities to formalise systems and train personnel to address academic cheating. Catching cheaters or unintentional plagiarists became more entrenched, leading to the development of software to catch the perpetrators. Although systems such as SafeAssign and Turnitin have been proven to be useful in most cases, they were not without obvious problems. For example, as they rely heavily on stable Internet and network availability, universities in the Global South, where access to electricity and the Internet infrastructure may be uneven, cannot fully utilise such tools.
Current state of integrity breach and academic misconduct
The issue with misconduct is not that it has not been researched or regulated. Across the length and breadth of HE, studies have been focusing on different aspects of AM. For example, in Australia, attempts have been made to re-educate sessional teachers on how to deal with academic integrity (Chugh et al., 2021). Similarly in Canada, studies have highlighted the reluctance to address contract cheating (Eaton and Christensen Hughes, 2022).
As we ponder the scale of AM, especially plagiarism, it is worth reflecting on whether we have always fully understood plagiarism in the NNES context. This view may invite strong opinions from both sides; however, I am not alone in this position. Colleagues in the sector (including Perkins et al., 2024; Bower et al., 2024; Miserandino, 2025) have previously examined possible changes to teaching and assessment practice. In some cases, NNES may just not fully understand what constitutes plagiarism, particularly if they have previously studied in institutions where instances such as collusion, copying, ghostwriting and unacknowledged use of others' work were not treated as problematic. Such cultural norms may suggest that the intention to cheat is not always the reason plagiarism occurs. Anglophone universities have systems in place to educate NNES prior to their coursework submission (Pecorari, 2013; Benuyenah, 2023), yet misconduct continues to occur and may even be worse now with artificial intelligence, except that with the growing robustness of AI, the nature of cheating has rapidly evolved, making it extremely challenging to detect in some cases.
As the academic landscape continues to adapt to developments in the IT sector, academic assessment needs to take into account the following:
Clearer discussions and policy distinctions between intentional deceit and developmental misunderstanding;
A redefinition of plagiarism literacy as a critical academic skill;
The redesigning of detection systems and authentic assessments;
Recognition of misunderstanding as a distinct category of integrity breach and
More proportionate and accurate consequences for blatant violations.
