Cheating is a growing academic and ethical concern in higher education. This article examines the rise of artificial intelligence (AI) generative chatbots for use in education and provides a review of research literature and relevant scholarship concerning the cheating-related issues involved and their implications for pedagogy. The technological “arms race” that involves cheating-detection system developers versus technology savvy students is attracting increased attention to cheating. AI has added new dimensions to academic cheating challenges as students (as well as faculty and (...) staff) can easily access powerful systems for generating content that can be presented in assignments, exams, or published papers as their own. AI methodology is also providing some emerging anti-cheating approaches, including facial recognition and water- marking. This article provides an overview of human/AI collaboration approaches and frames some educational misuses of such AI generative systems as ChatGPT and Bard as forms of “misattributed co-authorship.” As with other kinds of collaborations, the work that students produce with AI assistance can be presented in transparent and straightforward modes or (unfortunately) in opaquer and ethically-problematic ways. However, rather than just for catching or entrapping students, the emerging varieties of technological cheating-detection strategies can be used to assist students in learning how to document and attribute properly their AI-empowered as well as human-human collaborations. Construing misuses of AI generative systems as misattributed co-authorship can recognize the growing capabilities of these tools and how stressing responsible and mindful usage by students can help prepare them for a highly collaborative, AI-saturated future. (shrink)

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. (shrink)

Although the authorship order on published research plays a significant role for scientific merit in many research contexts, and therefore should be handled with great care not least for the sake o...

While much of the scholarly work on ethics relating to academic authorship examines the fair distribution of authorship credit, none has yet examined situations where a researcher contributes significantly to the project, but whose contributions do not make it into the final manuscript. Such a scenario is commonplace in collaborative research settings in many disciplines and may occur for a number of reasons, such as excluding research in order to provide the paper with a clearer focus, tell a particular story, (...) or exclude negative results that do not fit the hypothesis. Our concern in this paper is less about the reasons for including or excluding data from a paper and more about distributing credit in this type of scenario. In particular, we argue that the notion ‘substantial contribution’, which is part of the International Committee of Medical Journal Editors (ICMJE) authorship criteria, is ambiguous and that we should ask whether it concerns what ends up in the paper or what is a substantial contribution to the research process leading up to the paper. We then argue, based on the principles of fairness, due credit, and ensuring transparency and accountability in research, that the latter interpretation is more plausible from a research ethics point of view. We conclude that the ICMJE and other organizations interested in authorship and publication ethics should consider including guidance on authorship attribution in situations where researchers contribute significantly to the research process leading up to a specific paper, but where their contribution is finally omitted. (shrink)