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This study aims to address a systematic literature review (SLR) using bibliometrics on the relationship between academic integrity and artificial intelligence (AI), to bridge the scattering of literature on this topic, given the challenge and opportunity for the educational and academic community.

This review highlights the enormous social influence of COVID-19 by mapping the extensive yet distinct and fragmented literature in AI and academic integrity fields. Based on 163 publications from the Web of Science, this paper offers a framework summarising the balance between AI and academic integrity.

With the rapid advancement of technology, AI tools have exponentially developed that threaten to destroy students' academic integrity in higher education. Despite this significant interest, there is a dearth of academic literature on how AI can help in academic integrity. Therefore, this paper distinguishes two significant thematical patterns: academic integrity and negative predictors of academic integrity.

This study also presents several contributions by showing that tools associated with AI can act as detectors of students who plagiarise. That is, they can be useful in identifying students with fraudulent behaviour. Therefore, it will require a combined effort of public, private academic and educational institutions and the society with affordable policies.

This study proposes a new, innovative framework summarising the balance between AI and academic integrity.

Academic integrity in tertiary education is a global concern. This chapter describes academic integrity in Australian universities and proposes an “it takes a village” framework to guide universities toward a re-evaluation of academic integrity education. It takes a village to raise a child – a child needs role models and positive influences from multiple people for healthy growth and development. With regard to academic integrity, the parallel is that the entire university community needs to be involved to foster development of students of integrity. The institution and its community need to provide structures, multiple positive and effective learning experiences, and clear guidelines to support both staff and students. In this chapter, we argue that academic integrity needs to be seen as a complex system, one in which everyone involved has responsibility to develop and maintain a culture of integrity and one which supports a student throughout their academic journey.

For researchers and sector agencies around the world, poor academic integrity is seen as a significant risk to universities (Bretag & Harper, 2017; QAA, 2020; TEQSA, 2019). Given the existential threat that acts of academic misconduct are deemed to pose to higher education, interest in ways of developing academic integrity is correspondingly high and often invokes the concept of values (Macfarlane et al., 2014; Morris, 2018). However, to ascribe to academic integrity, the status of a self-evident, perhaps universal, value of contemporary higher education is contentious on many levels. This chapter takes in turn three of the most common ways in which students and scholars infringe on the principles of academic integrity – plagiarism, collusion, and contract cheating – and explores what the prohibiting of each of these acts reveals about the values of contemporary higher education. It argues that, far from neutral or universal, the values of academic integrity appear both normative and culturally specific, promoting a particular conception of higher education which risks excluding large sections of the global population. To counter this, the notion of threshold values – borrowing from Meyer and Land's (2005) notion of the “threshold concept” – is proposed, identifying the development of shared values as crucial to ensuring that contemporary, globalized universities are inclusive and accessible spaces.

The purpose of this paper is to demonstrate the advancements in artificial intelligence (AI) and conversational agents, emphasizing their potential benefits while also highlighting the need for vigilant monitoring to prevent unethical applications.

As AI becomes more prevalent in academia and research, it is crucial to explore ways to ensure ethical usage of the technology and to identify potentially unethical usage. This manuscript uses a popular AI chatbot to write the introduction and parts of the body of a manuscript discussing conversational agents, the ethical usage of chatbots and ethical concerns for academic researchers.

The authors reveal which sections were written entirely by the AI using a conversational agent. This serves as a cautionary tale highlighting the importance of ethical considerations for researchers and students when using AI and how educators must be prepared for the increasing prevalence of AI in the academy and industry. Measures to mitigate potential unethical use of this evolving technology are also discussed in the manuscript.

As conversational agents and chatbots increase in society, it is crucial to understand how they will impact the community and how we can live with technology instead of fighting against it.

Human perceptions, attitudes, and relationships are shaped by worldviews and values. The rich mosaic of worldviews in today's fast-changing global village, where cultures interact and information flows freely, challenge educators and students. Worldviews influence problem modeling and solutions. Worldviews give us psychological confidence that the world is as we see it, safe, secure, and belonging. Each worldview is consistent with the assumptions, ideals, and analytical processes. Values define behavior, attitudes and decision-making. The global higher education system's long history and recent developments in globalization, technological innovations, and internationalization make it even more complex. Globally, higher education is evolving rapidly. Global political, economic, social, technological, and environmental factors promote rapid change. Higher education institutions have struggled to adapt to these developments due to limited resources and capacity. Growing demand has created new business models and institutions. Access, equity, inclusion, and quality are new issues that emerged. To be relevant in a rapidly changing environment, higher education institutions must adapt to the knowledge society and growing need for access. This anthology contains 14 thought-provoking studies on worldviews and values in teaching-learning, curricula, assessment, and outcomes.

The purpose of this paper is to reflect on the creation of safe academic (education and research) environments that offer proper protections to adult academics and staff, so that academia and society at large may benefit from the fruits of safe workplaces. Not all academic environments are entirely safe, and there are recorded cases of victims of harassment and sexual abuse.

Given that co-workers in a laboratory, or research subjects in a research project, may be victims of harassment or sexual abuse, and that the same individuals may then become co-authors or anonymized research subjects, respectively, in academic papers, there is a need to appreciate what structural protection exists for such victims at the post-publication level. What should academia do with the literature of legally recognized sex offenders who have published in peer-reviewed and indexed academic journals?

Currently, there is no specific guidance by ethics organizations (e.g., Committee on Publication Ethics and International Committee of Medical Journal Editors) to deal with this issue, so protective mechanisms for adult victims, as well as punitive measures against perpetrators at the post-publication stage, are needed.

There may be career-altering repercussions – personal, professional and reputational – for co-authors of legally recognized sex offenders in papers published in peer-reviewed and indexed journals. There may also be life-altering outcomes to victims of sexual abuse who are the study subjects of such papers. Thus, a robust form of post-publication protection (and justice) based on unbiased and independent ethical and legal investigations, coordinated by editors, publishers and research institutes, needs to be established.

This paper aims to examine the opportunities and challenges of using ChatGPT in higher education. Furthermore, it is also discuss the potential risks and plunders of these tools.

The paper discuss the use of artificial intelligence (AI) in academia and explores the opportunities and challenges of using ChatGPT in higher education. It also highlights the difficulties of detecting and preventing academic dishonesty and suggests strategies that universities can adopt to ensure ethical and useful use of these tools.

The paper concludes that while the use of AI tools, ChatGPT in higher education presents both opportunities and challenges. The universities can effectively address these concerns by taking a proactive and ethical approach to the use of these tools. This paper further suggests that universities should develop policies and procedures, provide training and support, to detect and prevent cheating intentions.

The paper provides insights into the opportunities and challenges of using ChatGPT in higher education, as well as strategies for addressing concerns related to academic dishonesty. The paper further adds importance to the discussion on the ethical and responsible use of AI tools in higher education.

The use of generative artificial intelligence (genAi) language models such as ChatGPT to write assignment text is well established. This paper aims to assess to what extent genAi can be used to obtain guidance on how to avoid detection when commissioning and submitting contract-written assignments and how workable the offered solutions are.

Although ChatGPT is programmed not to provide answers that are unethical or that may cause harm to people, ChatGPT’s can be prompted to answer with inverted moral valence, thereby supplying unethical answers. The authors tasked ChatGPT to generate 30 essays that discussed the benefits of submitting contract-written undergraduate assignments and outline the best ways of avoiding detection. The authors scored the likelihood that ChatGPT’s suggestions would be successful in avoiding detection by markers when submitting contract-written work.

While the majority of suggested strategies had a low chance of escaping detection, recommendations related to obscuring plagiarism and content blending as well as techniques related to distraction have a higher probability of remaining undetected. The authors conclude that ChatGPT can be used with success as a brainstorming tool to provide cheating advice, but that its success depends on the vigilance of the assignment markers and the cheating student’s ability to distinguish between genuinely viable options and those that appear to be workable but are not.

This paper is a novel application of making ChatGPT answer with inverted moral valence, simulating queries by students who may be intent on escaping detection when committing academic misconduct.

This paper undertakes a structured literature review to analyse the literature on performance management and measurement (PMM) in universities over the last four decades. Over that time, PMM has emerged as an influential force in universities that impacts their operations and redefines their identity.

A structured literature review approach was used to analyse a sample of articles on PMM research from a broad range of disciplines over four decades. This was undertaken to understand the impacts of PMM practices on universities, highlight changes over time and point to avenues for future research.

The analysis highlights the fact that research on PMM in universities has grown significantly over the 40 years studied. We provide an overview of published articles over four decades regarding content, themes, theories, methods and impacts. We provide an empirical basis for discussing past, present and future university PMM research. The future research avenues offer multiple provocations for scholars and policymakers, for instance, PMM implementation strategies and relationships with various government programs and external evaluation and the role of different actors, particularly academics, in shaping PMM systems.

Unlike a traditional literature review, the structured literature review method can develop insights into how the field has changed over time and highlight possible future research. The sample for this literature review differs from previous reviews in covering a broad range of disciplines, including accounting.