Generative artificial intelligence in higher education learning: A review based on academic databases

To systematically map existing research on nurse academics incorporation of generative artificial intelligence when developing teaching and learning resources in higher education and to identify knowledge gaps and future research. Generative artificial intelligence technology is rapidly evolving in healthcare and it's use in nursing higher education is developing. However, concerns regarding its adoption in higher education relate to academic integrity and ethical considerations, including privacy, confidentiality, bias and critical thinking development. Generative artificial intelligence tools present new pedagogy possibilities in nursing higher education; however, the scope and impact of its adoption is unclear. The Joanna Briggs Institute (JBI) methodology for scoping reviews were used to guide this scoping review. Electronic databases were searched from inception until February 2025. The search yielded seven quantitative and two qualitative studies. The findings highlight that nurse academics use generative artificial intelligence to assist with student learning and time management. Findings revealed that generative artificial intelligence use may improve student satisfaction and critical thinking skills. Nurse academics were identified as critical role models in academic integrity and the ethical adoption of generative artificial intelligence. Knowledge gaps and opportunities for future research are highlighted. The findings highlight the opportunities of generative artificial intelligence use in nursing higher education. Role modelling ethical use of generative artificial intelligence by nurse academics can instil academic integrity principles. However, gaps in evidence on the impact on student education outcomes and industry readiness highlight the need for further research using randomised control trials and longitudinal studies.

Introduction Author Arthur C. Clarke famously argued that in science fiction literature “any sufficiently advanced technology is indistinguishable from magic” (Clarke). On 30 November 2022, technology company OpenAI publicly released their Large Language Model (LLM)-based chatbot ChatGPT (Chat Generative Pre-Trained Transformer), and instantly it was hailed as world-changing. Initial media stories about ChatGPT highlighted the speed with which it generated new material as evidence that this tool might be both genuinely creative and actually intelligent, in both exciting and disturbing ways. Indeed, ChatGPT is part of a larger pool of Generative Artificial Intelligence (AI) tools that can very quickly generate seemingly novel outputs in a variety of media formats based on text prompts written by users. Yet, claims that AI has become sentient, or has even reached a recognisable level of general intelligence, remain in the realm of science fiction, for now at least (Leaver). That has not stopped technology companies, scientists, and others from suggesting that super-smart AI is just around the corner. Exemplifying this, the same people creating generative AI are also vocal signatories of public letters that ostensibly call for a temporary halt in AI development, but these letters are simultaneously feeding the myth that these tools are so powerful that they are the early form of imminent super-intelligent machines. For many people, the combination of AI technologies and media hype means generative AIs are basically magical insomuch as their workings seem impenetrable, and their existence could ostensibly change the world. This article explores how the hype around ChatGPT and generative AI was deployed across the first six months of 2023, and how these technologies were positioned as either utopian or dystopian, always seemingly magical, but never banal. We look at some initial responses to generative AI, ranging from schools in Australia to picket lines in Hollywood. We offer a critique of the utopian/dystopian binary positioning of generative AI, aligning with critics who rightly argue that focussing on these extremes displaces the more grounded and immediate challenges generative AI bring that need urgent answers. Finally, we loop back to the role of schools and educators in repositioning generative AI as something to be tested, examined, scrutinised, and played with both to ground understandings of generative AI, while also preparing today’s students for a future where these tools will be part of their work and cultural landscapes. Hype, Schools, and Hollywood In December 2022, one month after OpenAI launched ChatGPT, Elon Musk tweeted: “ChatGPT is scary good. We are not far from dangerously strong AI”. Musk’s post was retweeted 9400 times, liked 73 thousand times, and presumably seen by most of his 150 million Twitter followers. This type of engagement typified the early hype and language that surrounded the launch of ChatGPT, with reports that “crypto” had been replaced by generative AI as the “hot tech topic” and hopes that it would be “‘transformative’ for business” (Browne). By March 2023, global economic analysts at Goldman Sachs had released a report on the potentially transformative effects of generative AI, saying that it marked the “brink of a rapid acceleration in task automation that will drive labor cost savings and raise productivity” (Hatzius et al.). Further, they concluded that “its ability to generate content that is indistinguishable from human-created output and to break down communication barriers between humans and machines reflects a major advancement with potentially large macroeconomic effects” (Hatzius et al.). Speculation about the potentially transformative power and reach of generative AI technology was reinforced by warnings that it could also lead to “significant disruption” of the labour market, and the potential automation of up to 300 million jobs, with associated job losses for humans (Hatzius et al.). In addition, there was widespread buzz that ChatGPT’s “rationalization process may evidence human-like cognition” (Browne), claims that were supported by the emergent language of ChatGPT. The technology was explained as being “trained” on a “corpus” of datasets, using a “neural network” capable of producing “natural language“” (Dsouza), positioning the technology as human-like, and more than ‘artificial’ intelligence. Incorrect responses or errors produced by the tech were termed “hallucinations”, akin to magical thinking, which OpenAI founder Sam Altman insisted wasn’t a word that he associated with sentience (Intelligencer staff). Indeed, Altman asserts that he rejects moves to “anthropomorphize” (Intelligencer staff) the technology; however, arguably the language, hype, and Altman’s well-publicised misgivings about ChatGPT have had the combined effect of shaping our understanding of this generative AI as alive, vast, fast-moving, and potentially lethal to humanity. Unsurprisingly, the hype around the transformative effects of ChatGPT and its ability to generate ‘human-like’ answers and sophisticated essay-style responses was matched by a concomitant panic throughout educational institutions. The beginning of the 2023 Australian school year was marked by schools and state education ministers meeting to discuss the emerging problem of ChatGPT in the education system (Hiatt). Every state in Australia, bar South Australia, banned the use of the technology in public schools, with a “national expert task force” formed to “guide” schools on how to navigate ChatGPT in the classroom (Hiatt). Globally, schools banned the technology amid fears that students could use it to generate convincing essay responses whose plagiarism would be undetectable with current software (Clarence-Smith). Some schools banned the technology citing concerns that it would have a “negative impact on student learning”, while others cited its “lack of reliable safeguards preventing these tools exposing students to potentially explicit and harmful content” (Cassidy). ChatGPT investor Musk famously tweeted, “It’s a new world. Goodbye homework!”, further fuelling the growing alarm about the freely available technology that could “churn out convincing essays which can't be detected by their existing anti-plagiarism software” (Clarence-Smith). Universities were reported to be moving towards more “in-person supervision and increased paper assessments” (SBS), rather than essay-style assessments, in a bid to out-manoeuvre ChatGPT’s plagiarism potential. Seven months on, concerns about the technology seem to have been dialled back, with educators more curious about the ways the technology can be integrated into the classroom to good effect (Liu et al.); however, the full implications and impacts of the generative AI are still emerging. In May 2023, the Writer’s Guild of America (WGA), the union representing screenwriters across the US creative industries, went on strike, and one of their core issues were “regulations on the use of artificial intelligence in writing” (Porter). Early in the negotiations, Chris Keyser, co-chair of the WGA’s negotiating committee, lamented that “no one knows exactly what AI’s going to be, but the fact that the companies won’t talk about it is the best indication we’ve had that we have a reason to fear it” (Grobar). At the same time, the Screen Actors’ Guild (SAG) warned that members were being asked to agree to contracts that stipulated that an actor’s voice could be re-used in future scenarios without that actor’s additional consent, potentially reducing actors to a dataset to be animated by generative AI technologies (Scheiber and Koblin). In a statement issued by SAG, they made their position clear that the creation or (re)animation of any digital likeness of any part of an actor must be recognised as labour and properly paid, also warning that any attempt to legislate around these rights should be strongly resisted (Screen Actors Guild). Unlike the more sensationalised hype, the WGA and SAG responses to generative AI are grounded in labour relations. These unions quite rightly fear the immediate future where human labour could be augmented, reclassified, and exploited by, and in the name of, algorithmic systems. Screenwriters, for example, might be hired at much lower pay rates to edit scripts first generated by ChatGPT, even if those editors would really be doing most of the creative work to turn something clichéd and predictable into something more appealing. Rather than a dystopian world where machines do all the work, the WGA and SAG protests railed against a world where workers would be paid less because executives could pretend generative AI was doing most of the work (Bender). The Open Letter and Promotion of AI Panic In an open letter that received enormous press and media uptake, many of the leading figures in AI called for a pause in AI development since “advanced AI could represent a profound change in the history of life on Earth”; they warned early 2023 had already seen “an out-of-control race to develop and deploy ever more powerful digital minds that no one – not even their creators – can understand, predict, or reliably control” (Future of Life Institute). Further, the open letter signatories called on “all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4”, arguing that “labs and independent experts should use this pause to jointly develop and implement a set of shared safety protocols for advanced AI design and development that are rigorously audited and overseen by independent outside experts” (Future of Life Institute). Notably, many of the signatories work for the very companies involved in the “out-of-control race”. Indeed, while this letter could be read as a moment of ethical clarity for the AI industry, a more cynical reading might just be that in warning that their AIs could effectively destroy the w

Purpose As generative artificial intelligence (AI) technologies continue to advance and become more prevalent in higher education, addressing the ethical concerns associated with their use is essential. This study emphasizes the need for robust AI governance as more young consumers increasingly use generative AI for various applications. This paper aims to examine the ethical challenges posed by generative AI and review the AI policies in higher education to regulate young consumers use of generative AI, focusing on the ethical use of AI from foundational principles to sustainable governance. Design/methodology/approach Through a content analysis of literature on generative AI policies in higher education published between 2020 and 2024, this research aims to explore a more holistic approach to integrating generative AI into the educational process. The analysis examines academic policies and governance framework from 28 journal papers regarding generative AI tools in higher education. Data were collected from publicly accessible sources, such as Scopus, Emerald Insights, ProQuest, Web of Science and ScienceDirect. Findings This study analyses ten elements of the governance framework to identify potential AI governance and policy setting, benefiting stakeholders aiming at enhancing the regulatory framework of generative AI use in higher education. The discussions indicate a generally balanced yet cautious approach to integrating generative AI technology, especially considering ethical issues, inherent limitations and data privacy concerns. Originality/value The findings contribute to ongoing discussions to strengthen universities’ responses to new academic challenges posed by the use of generative AI and promote high AI ethical standards across educational sectors.

How Can <i>IJDS</i> Authors, Reviewers, and Editors Use (and Misuse) Generative AI?

PurposeThis article investigates the application of generative artificial intelligence (GenAI) in experiential learning for authentic assessment in higher education. Recognized for its human-like content generation, GenAI has garnered widespread interest, raising concerns regarding its reliability, ethical considerations and overall impact. The purpose of this study is to explore the transformative capabilities and limitations of GenAI for experiential learning.Design/methodology/approachThe study uses “thing ethnography” and “incremental prompting” to delve into the perspectives of ChatGPT 3.5, a prominent GenAI model. Through semi-structured interviews, the research prompts ChatGPT 3.5 on critical aspects such as conceptual clarity, integration of GenAI in educational settings and practical applications within the context of authentic assessment. The design examines GenAI’s potential contributions to reflective thinking, hands-on learning and genuine assessments, emphasizing the importance of responsible use.FindingsThe findings underscore GenAI’s potential to enhance experiential learning in higher education. Specifically, the research highlights GenAI’s capacity to contribute to reflective thinking, hands-on learning experiences and the facilitation of genuine assessments. Notably, the study emphasizes the significance of responsible use in harnessing the capabilities of GenAI for educational purposes.Originality/valueThis research showcases the application of GenAI in operations management education, specifically within lean health care. The study offers insights into its capabilities by exploring the practical implications of GenAI in a specific educational domain through thing ethnography and incremental prompting. Additionally, the article proposes future research directions, contributing to the originality of the work and opening avenues for further exploration in the integration of GenAI in education.

PurposeA gripping keyword emerged in the dynamic world of 2022: GPT or the advent of Generative Artificial Intelligence (GAI), at its forefront, embodied by the mysterious ChatGPT. This technological marvel had been silently lurking in the background for just over five years. However, all of a sudden, it emerged onto the scene, capturing the public’s attention and quickly becoming one of the most widely adopted inventions in history. Therefore, this narrative review is conducted in order to explore the impact of generative AI and ChatGPT on lifelong learning and upskilling of students in higher education and address opportunities and challenges proposed by Artificial Intelligence from a global perspective.Design/methodology/approachThis review has been conducted using a narrative literature review approach. For in-depth identification of research gaps, 105 relevant articles were included from scholarly databases such as Scopus, Web of Science, ERIC and Google Scholar. Seven major themes emerged from the literature to answer the targeted research questions that describe the use of AI, the impact of generative AI and ChatGPT on students, the challenges and opportunities of using AI in education and mitigating strategies to cope with the challenges associated with the integration of ChatGPT and generative AI in education.FindingsThe review of the literature presents that generative AI and ChatGPT have gained a lot of recognition among students and have revolutionized educational settings. The findings suggest that there are some contexts in which adult education research and teaching can benefit from the use of chatbots and generative AI technologies like ChatGPT. The literature does, however, also highlight the necessity of carefully considering the benefits and drawbacks of these technologies in order to prevent restricting or distorting the educational process or endangering academic integrity. In addition, the literature raises ethical questions about data security, privacy and cheating by students or researchers. To these, we add our own ethical concerns about intellectual property, such as the fact that, once we enter ideas or research results into a generative chatbot, we no longer have control over how it is used.Practical implicationsThis review is helpful for educators and policymakers to design the curriculum and policies that encourage students to use generative AI ethically while taking academic integrity into account. Also, this review article identifies the major gaps that are associated with the impact of AI and ChatGPT on the lifelong learning skills of students.Originality/valueThis review of the literature is unique because it explains the challenges and opportunities of using generative AI and ChatGPT, also defining its impact on lifelong learning and upskilling of students.

This chapter delves into the ethical considerations surrounding the utilization of generative artificial intelligence (AI) for global knowledge sharing in higher education. As AI technologies continue to advance, their potential for transforming the educational landscape is becoming increasingly evident. However, the ethical implications of employing generative AI in this context warrant careful examination. The study explores the ethical dimensions related to the use of generative AI in higher education, focusing on issues such as data privacy, algorithmic bias, intellectual property rights, and the impact on human creativity and critical thinking. The findings of this study contribute to the ongoing discourse on the ethical implications of utilizing generative AI in higher education. By addressing these considerations, educators and policymakers can make informed decisions regarding the implementation of generative AI technologies, fostering a responsible and inclusive approach to global knowledge sharing in the higher education sector.

There is a growing interest in using generative artificial intelligence (AI) for educational purposes within the higher education environments, while AI applications (such as ChatGPT) can transform traditional teaching and learning methods. ChatGPT is an advanced AI tool that generates new content and human-like responses. The purpose of this paper is to use ChatGPT as a research assistant in order to explore ways AI can be harnessed to enhance pedagogical practices in higher education. This is a qualitative study, in which the output-responses generated by ChatGPT provided a starting point for the investigation. AI can be harnessed to enhance pedagogical practices in higher education in various ways including personalized learning, automated assessment and feedback generation, virtual assistants and chatbots, content creation, resource recommendation, time management, language translation and support, research assistance, simulations and virtual labs. Other educational affordances that can strengthen the teaching and learning experience regard collaboration and communication, accessibility and inclusivity, as well as AI literacy. When implementing AI tools such as ChatGPT in higher education, ethical considerations (e.g., data privacy, transparency, accessibility, cultural sensitivity), potential misuses and concerns need to also be addressed. Although ChatGPT can aid the generation of content-ideas for further exploration, it is a complementary-supportive tool, and its output necessitates human evaluation and review. The integration of ChatGPT and other AI tools in the higher educational process/practices has implications for educators, students, design of curricula, and university policy makers. Received: 17 January 2024 | Revised: 27 February 2024 | Accepted: 19 March 2024 Conflicts of Interest The author declares that she has no conflicts of interest to this work. Data Availability Statement Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Introduction: The integration of artificial intelligence (AI) into higher education is swiftly revolutionizing pedagogical methodologies, in conjunction with learning processes and research paradigms. The interdisciplinary potential of AI within academic settings was examined in this study, employing a case study conducted at the University of Tirana. Through the utilization of bibliometric analysis and survey-based research, this study comprehensively investigates the swiftly emerging trends in AI applications, students' significant familiarity with AI technologies, as well as the substantial challenges impeding broader adoption. The bibliometric analysis highlights significant exponential growth in AI research, particularly within pivotal domains such as finance and accounting, thereby emphasizing the swiftly increasing relevance of blockchain and automation. The survey indicates a robust enthusiasm among students for AI in educational settings. More than 90 percent of students actively incorporate AI tools in their project work. Nonetheless, resource limitations and ethical considerations, including privacy, data security, and algorithmic bias, pose considerable challenges to the widespread adoption of AI, despite the prevailing enthusiasm. Objective: The aim of this research is to examine the incorporation of Artificial Intelligence (AI) within the realm of higher education. This analysis concentrates on the applications, advantages, and challenges associated with AI, with the intent of advancing interdisciplinary research and educational methodologies at the University of Tirana. Theoretical Framework: This research expands upon the principles of AI adoption within the educational sector, alongside an examination of ethical considerations and multidisciplinary collaboration. Theories pertaining to technological integration and adaptive learning systems serve as the foundational framework for comprehending the implications of AI in the realm of education. Method: The methodology employs bibliometric analysis to examine AI-related research trends utilizing data from SCOPUS and conducts a survey to assess students' familiarity with and perceptions of AI. Data collection was facilitated through bibliometric instruments and an online survey incorporating Likert-scale and open-ended questions. Results and Discussion: The results underscore an increased focus on artificial intelligence (AI) and blockchain within scholarly research, wherein students exhibit considerable engagement and interest in AI applications. Nevertheless, limitations in resources and ethical issues, including privacy and bias, persist as primary challenges. The discourse underscores the imperative for investment in infrastructure and the incorporation of ethical education. Research Implications: This research highlights the imperative for higher education institutions to integrate artificial intelligence tools, cultivate adaptive curricula, and address ethical considerations in order to adequately prepare students for a future shaped by AI. The implications of these findings also pertain to educational policy and the formulation of interdisciplinary research strategies. Originality/Value: The study contributes by delivering a comprehensive bibliometric analysis and gives insights into student engagement with artificial intelligence. Its significance resides in presenting actionable recommendations to enhance the integration of artificial intelligence in higher education.

Over 2023, many universities and policy organisations in the higher education (HE) sector are working to create guiding principles and guidelines for the use of generative artificial intelligence (AI) in HE Teaching and Learning (T&amp;L). Despite these guidelines, students remain unsure if and how they should use AI. This article discusses the AI information sessions held over the Autumn 2023 term in the Department of Classics at the University of Reading, which aimed to provide students with the knowledge and tools to make informed judgements about using AI in their studies. These sessions discussed the benefits and drawbacks of generative AI, highlighting training data, content policy, environmental impact, and examples of potential uses. Staff and student participants were surveyed before and after these information sessions to gather their opinions surrounding AI use. Although at least 60% of participants had previously used generative AI, 80% of participants were apprehensive of or against using generative AI tools for learning purposes following the AI information sessions. By providing staff and students with the ethical considerations surrounding generative AI, they can make an informed judgement about using AI in their work without misplaced faith or excessive fear.

Will generative AI replace teachers in higher education? A study of teacher and student perceptions

Artificial intelligence (AI) has become an increasingly influential force in higher education, particularly in accounting, taxation and business education, where digital competence and analytical skills are essential. Although research in this area has expanded rapidly, the existing literature remains fragmented across disciplines and lacks a systematic overview of its intellectual structure and developmental trends. This study addresses this gap by conducting a bibliometric analysis of research on artificial intelligence in accounting, taxation and business education. Publications were retrieved from the Web of Science Core Collection, resulting in a dataset of 131 peer-reviewed journal articles. Bibliometric and visualisation analyses were conducted using VOSviewer and Scimago Graphica to examine publication trends, disciplinary categories, contributing affiliations, geographic distribution and keyword co-occurrence patterns through network, overlay and keyword cloud visualisations. The results reveal a sharp increase in research output since 2021, coinciding with recent advances in generative AI technologies. The literature demonstrates a strong interdisciplinary orientation, spanning education, business, finance and information systems, and exhibits a globally dispersed pattern of research contributions. Keyword-based analyses indicate that research themes cluster around technological foundations, curriculum and institutional transformation, pedagogical innovation, and behavioural and ethical considerations. More recent studies increasingly focus on generative AI applications, such as ChatGPT, alongside issues related to assessment, academic integrity and AI ethics. Overall, this study provides a systematic mapping of the evolving research landscape and offers insights to inform future research agendas and educational practice.

Generative artificial intelligence (AI) represents a crucial subset of AI models characterized by their ability to generate new content based on user input, showing vast potential to transform learning and teaching. However, educators have raised ethical concerns, particularly regarding the adverse effect on students' learning if students simply parrot generative AI-generated content without engaging in critical analysis or original thought. Moreover, there exists the potential of generative AI to perpetuate existing biases in training data. This editorial discusses three major concerns in generative AI use in education and proposes questions (on task-AI fit and people-AI fit) and approaches to address the ethical considerations by adopting five principles of AI ethics. The editorial also discusses developing a classroom AI use policy as one governance mechanism for promoting ethical use of AI. As generative AI technology continues to evolve, so must our educational practices. The editorial ends with a call for readers (educators) to collaboratively define the terms of engagement with generative AI in educational settings and to begin this discourse by sharing insights and experiences with promoting ethical use of generative AI.

The advancement of Generative Artificial Intelligence (AI) chatbots, such as ChatGPT, presents significant and transformative challenges in higher education teaching and learning, such as assessment and evaluation practices. While this is acknowledged, there has been very little research into what this might look like in daily practice in higher education. This study explored these challenges in one area of higher education practice: developing students’ transferable skills, including writing, critical thinking, and information literacy among undergraduate engineering students at RMIT University, Melbourne, Australia. Using a cohort comparison design, this study evaluated the impact of ChatGPT on students' attainment of transferable skills. The effectiveness of AI tools in enhancing educational outcomes was assessed with a standardised assessment framework used by independent assessors to grade students’ reports. The results, analysed using the Mann-Whitney U test and the intraclass correlation coefficient, revealed significant improvements in critical thinking and information literacy among those students who used ChatGPT. The study also explored the ethical implications of using AI in educational settings and highlighted the need for rigorous academic standards and the implementation of measures to ensure the responsible use of AI technologies. While the preliminary findings suggest that AI tools, particularly ChatGPT in this study, can positively impact certain students’ skills, more detailed and controlled studies are necessary to validate these results and explore further the mechanisms through which AI tools influence learning and skill development.

In the ever-evolving era of technological advancements, generative artificial intelligence (GAI) emerges as a transformative force, revolutionizing education. This review paper, guided by the PRISMA framework, presents a comprehensive analysis of GAI in education, synthesizing key insights from a selection of 207 research papers to identify research gaps and future directions in the field. This study begins with a content analysis that explores GAI’s transformative impact in specific educational domains, including medical education and engineering education. The versatile applications of GAI encompass assessment, personalized learning support, and intelligent tutoring systems. Ethical considerations, interdisciplinary collaboration, and responsible technology use are highlighted, emphasizing the need for transparent GAI models and addressing biases. Subsequently, a bibliometric analysis of GAI in education is conducted, examining prominent AI tools, research focus, geographic distribution, and interdisciplinary collaboration. ChatGPT emerges as a dominant GAI tool, and the analysis reveals significant and exponential growth in GAI research in 2023. Moreover, this paper identifies promising future research directions, such as GAI-enhanced curriculum design and longitudinal studies tracking its long-term impact on learning outcomes. These findings provide a comprehensive understanding of GAI’s potential in reshaping education and offer valuable insights to researchers, educators, and policymakers interested in the intersection of GAI and education.