In the context of Ukraine’s European integration and ongoing full-scale war, social inclusion has become an important issue for Ukrainian higher education institutions. This study analyses demographic differences in perceptions of the

In the context of Ukraine’s European integration and ongoing full-scale war, social inclusion has become an important issue for Ukrainian higher education institutions. This study analyses demographic differences in perceptions of the implementation of social inclusion. An online survey was conducted from May to July 2025 with 821 respondents: students, academic staff and heads of structural units. The questionnaire included 34 closed questions on inclusive practices, open-ended questions and demographic items. The analysis combined descriptive and inferential statistics with exploratory factor analysis, reliability testing, and thematic analysis. Factor analysis supported the use of the aggregated inclusivity indicator (Pinc) and three subscales, although the formal access subscale had lower reliability. The results showed uneven implementation of inclusive practices: flexible learning formats (88.7%) and diverse opportunities to demonstrate knowledge (82.6%) were among the most developed, while information accessibility (32.2%) and staff training in inclusive education (35.0%) were among the weakest. Gender differences were not statistically significant for the total indicator. Age differences were statistically significant but small and inconsistent across subscales. Role differences were also statistically significant, with heads of structural units assessing inclusion more favourably than students and academic staff. Open-ended responses showed that students and younger respondents more often raised support, safety, information and adapted materials, whereas staff and heads more often referred to funding and resources. The findings indicate the need for clearer student information, better access to adapted materials, inclusive-education training and stronger coordination through inclusion officers.

Generative Artificial Intelligence (GenAI) is increasingly being used within higher education to enhance curriculum design, automate academic tasks, and personalise learning. Despite this, little is known about teaching academics’

Generative Artificial Intelligence (GenAI) is increasingly being used within higher education to enhance curriculum design, automate academic tasks, and personalise learning. Despite this, little is known about teaching academics’ attitudes, intentions and behaviours and in turn, how they use and plan to use GenAI in practice. This qualitative study explored teaching academic staff attitudes, intentions and behaviours regarding their use and future use of GenAI. Data was collected via five open ended questions focusing on current teaching practices. The Theory of Planned Behaviour informed the analytical process. Academic staff were drawn from 20 different disciplines across 24 countries. Six main themes were identified: Efficiency and Automation, Ethics and Authenticity, Quality, Customised Learning, Institutional Policy-Practice and Sociocultural Implications. Overall, there was a dichotomy in responses. Participants noted that while GenAI could streamline teaching and enhance resource quality, it might also increase short-term workload and reduce the role of human judgement, risking unreliable outputs. They also highlighted limited institutional policies, strategies, and training. These attitudes have implications for updating policies, practical strategies, and meaningful training in higher education institutions.

Navigating the landscape of Higher Education can be particularly challenging for Enabling students, with their ability to persevere and maintain feelings of ‘hope’ likely to impact their confidence to complete their Enabling program. This

Navigating the landscape of Higher Education can be particularly challenging for Enabling students, with their ability to persevere and maintain feelings of ‘hope’ likely to impact their confidence to complete their Enabling program. This paper explores the impact of hope on student perseverance and progress within an Enabling program. Using data collected from in-depth interviews with two participants, we investigate how hope shapes students’ motivation, resilience, and ultimately their ability to cope with academic challenges. The findings reveal that hope serves as a critical psychological resource, fostering a sense of agency and goal-directed behaviour that can enable students to flourish in their educational journeys. Through interpreting participants’ experiences using the lens of hope theory (Snyder, 2000) educators in the Enabling space can better appreciate how students navigated obstacles and sustained their commitment to the program. This paper contributes to the understanding of hope as a vital resource in educational contexts, situated within the growing discourse on equity, access, and the emotional dimensions of learning in transitional educational contexts.

This paper evaluates the integration of non-Western epistemologies into Australian higher education, critiquing the dominance of Western-centric frameworks that have historically shaped teaching and learning in Australia. It challenges the

This paper evaluates the integration of non-Western epistemologies into Australian higher education, critiquing the dominance of Western-centric frameworks that have historically shaped teaching and learning in Australia. It challenges the reliance on positivist knowledge systems, which often prioritise control and efficiency at the expense of ethical and culturally diverse knowledges and perspectives. The study advocates for the inclusion of emancipatory knowledge, grounded in critical theory, emphasising emancipatory epistemologies as a means to transform curricula beyond traditional Western paradigms. The research incorporates reflections from an Indian-Australian academic and a Persian-Australian academic, who offer insights from their respective knowledge traditions. The Indian Australian academic discusses how ancient Indian epistemologies and philosophies, such as those in the Vedas and Upanishads, provide a holistic approach that integrates spirituality, ethics, value system and social responsibility and how it is integrated into education. The Persian Australian academic highlights the intellectual heritage of Iran, drawing on Persian philosophy and poetry, which emphasise the interconnectedness of all beings and the pursuit of wisdom through dialogue. It uses the role of Critical Participatory Action Research (CPAR) to foster critical consciousness among academics in Australasia that can understand and compare knowledge constructs to disrupt hegemonic narratives. Ultimately, the study calls for a reimagining of university education that embraces diverse knowledge traditions by evaluating epistemological differences across three systems.

The Indigenous education movements in Hawaiʻi and Aotearoa New Zealand (Aotearoa) have demonstrated decades of advancement and success, yet we are still confronted with a predominantly Western-centric teaching and learning context that

The Indigenous education movements in Hawaiʻi and Aotearoa New Zealand (Aotearoa) have demonstrated decades of advancement and success, yet we are still confronted with a predominantly Western-centric teaching and learning context that resists recognising Indigenous education as an essential foundation for all educators (Hutchings & Lee-Morgan, 2016; Wilson-Hokowhitu & Goodyear-Ka‘ōpua, 2019). This article draws from a larger PhD research study, Decolonizing the colonizer: Indigenous education as the foundation of teacher education in Hawaiʻi and Aotearoa, offering specific guidance to transform mainstream teacher education. The research grounds in Hawaiʻi and Aotearoa as their Indigenous peoples have shared colonial experiences and their Indigenous resurgence movements have evolved together and strengthened one another (Asensio, 2019; Walker, 2004; Wilson & Kamanā, 2001). They hold a strong connection stemming not only from their geographic proximity but also shared histories reflected in their cosmogony, ancestors, language, and cultural practices. These connections ignited an Indigenous education movement that has grown and evolved over the past 50 years, leading to the revitalisation of Hawaiian and Māori languages and cultural practices, and the creation of a robust Indigenous education pipeline. The study applies oral storytelling and semi-structured interview methods to gather moʻolelo/pūrākau (stories, narratives, history), ʻike/mātauranga (knowledge, wisdom), and manaʻo/whakaaro (thoughts, opinions, ideas) from 20 Hawaiian and Māori Indigenous education leaders who have dedicated their personal and professional lives to their respective Cultural Renaissances. The leaders offered guidance for mainstream teacher education on how to ground in Indigenous knowledge systems and practices. Through the study, the metaphor of a three-whiri wahakura (flax bassinet with three foundational braids) emerged, depicting that for transformative and restorative shifts in teacher education to occur, there must be change at the system, programmatic, and individual level. This article will focus on the programmatic level by proposing a framework for decolonising and indigenising teacher education based on eight themes detailing how Indigenous Pacific epistemologies, pedagogies, and philosophies can be employed in university teaching and learning practices.

Peer assisted learning (PAL) is integral to student learning in higher education and provides opportunities for learning that extend beyond academic support. This study explores how students perceive the peer support received from tutors

Peer assisted learning (PAL) is integral to student learning in higher education and provides opportunities for learning that extend beyond academic support. This study explores how students perceive the peer support received from tutors, mentors, retention officers and teaching assistants. Principles of Ubuntu pedagogy, namely support from a position of love and care, building positive relationships, working collectively and nurturing students’ minds underpin this study. Qualitative surveys with closed and open-ended questions were administered for data generation to garner perceptions of academic and social interventions. It allowed participants to articulate their experiences and viewpoints in their own words, providing rich insights and perspectives. Findings revealed that those who provided peer support are epistemic agents facilitating pedagogical encounters, and in this dialogical process both epistemic agents and students develop reciprocally. This study foregrounds a novel approach to peer support where the principles of Ubuntu are central to opening vistas for student learning, empowerment and success. The study contributes to strategies on the role of indigenous knowledge systems in transforming peer-to-peer engagement and recommends that tacit Ubuntu values be made overt in PAL training programmes.

This paper explores the transformative experiences of participants in the redesigned Graduate Certificate in University Learning and Teaching (GCULT). The program was redesigned by a small team of educators with a key focus on Indigenising

This paper explores the transformative experiences of participants in the redesigned Graduate Certificate in University Learning and Teaching (GCULT). The program was redesigned by a small team of educators with a key focus on Indigenising the GCULT curriculum and serving as a model for program participants to do the same. Graduate Certificates have previously been found to be transformative for educators in Higher Education (Patfield et al. 2022). We utilised this platform to encourage transformation of participants to engage in these decolonial practices. The redesign process itself drew upon Indigenous ways of being, doing and knowing, through yarning, challenging western norms within the higher education system, and continual critical self-reflection. Western norms were disrupted through providing alternative forms of engagement in learning and assessment. In addition, Indigenous knowledges and perspectives were intentionally integrated throughout the curriculum to serve as a model for educators across the university. We (two educators involved in the redesign) engaged in decolonial reflexivity throughout the redesign process and in writing this paper. Applying action research, we examined participants’ reflections and feedback on the program to identify key themes related to Indigenous knowledges. The findings indicate that participants were engaging in a process of decolonising themselves and recognising ways to Indigenise the curriculum.

This article explores the challenges and opportunities of teaching in internationalized undergraduate classrooms at a South Korean university. Drawing on autoethnography, reflexive pedagogy, and constructivist learning, it examines how

This article explores the challenges and opportunities of teaching in internationalized undergraduate classrooms at a South Korean university. Drawing on autoethnography, reflexive pedagogy, and constructivist learning, it examines how student-led and reflexive approaches can lead to more inclusive learning environments. Through classroom examples, including discussions on media framing, privilege, and cultural assumptions, the paper illustrates how constructivist and student-centred pedagogies disrupt traditional learning hierarchies. It argues that reflexivity is essential in global education, enabling both students and educators to critically engage with power structures in the classroom. Ultimately, this study calls for a pedagogical shift that places students’ lived experiences at the centre of the learning process, challenging educators to move toward co-constructed and socially engaged education.

In Southeast Asia, English language education has been influenced by the import and integration of various curricula and frameworks originating from the west. In response to this, English language teachers at various educational levels

In Southeast Asia, English language education has been influenced by the import and integration of various curricula and frameworks originating from the west. In response to this, English language teachers at various educational levels have demonstrated how they have had to adapt these imported materials. To critical scholars, this may be viewed as a process of decolonisation. Against this backdrop, this study aimed to examine how university English language teachers responded to the integration of Common European Framework of Reference for Languages (CEFR) through an extent of resistance. To this end, three English language teachers from a Malaysian university and three others from a Thai university were interviewed. Specifically, they reflected on how they reconfigured the framework to be more contextually and locally meaningful. Through the examination of the participants’ reflections, it was found that their resistance was shaped by both their individual perspectives and practices, as well as the context. The former was marked by enacting agency and a reluctance to accept external forces, while the latter was illustrated through structural mismatch and a cultural misalignment. Findings of this study ultimately contribute to our understanding of how western educational frameworks and English language education were decolonised. This study also illustrates how the classroom is a pivotal space for the displacement of dominant forces in education.

Artificial Intelligence (AI), particularly Generative AI (GenAI), is profoundly reshaping assessment practices in computer science education by enabling automation, scalability, and personalized feedback mechanisms. AI-enhanced tools

Artificial Intelligence (AI), particularly Generative AI (GenAI), is profoundly reshaping assessment practices in computer science education by enabling automation, scalability, and personalized feedback mechanisms. AI-enhanced tools facilitate adaptive testing, real-time learner support, and data-driven insights that foster deeper engagement and learning outcomes. However, the integration of AI also raises critical concerns related to academic integrity, algorithmic bias, transparency, and ethical implications of AI-driven evaluation. This theoretical paper critically examines the opportunities and complexities of GenAI-enabled assessment in CS education. Drawing on contemporary literature, pedagogical theory, and emerging use cases, the paper explores how GenAI can enhance student engagement, support equitable learning, and relieve instructional burden—while also highlighting the need for ethical safeguards and pedagogically grounded frameworks. It argues that the successful integration of GenAI depends not solely on technological capability but on deliberate, human-guided design that upholds transparency, fairness, and educational purpose. By advancing a nuanced and critically reflective perspective, this paper contributes to the evolving discourse on AI in education and provides actionable insights for educators, researchers, and policymakers seeking to harness GenAI responsibly in the future of computer science education.

The rapid expansion of Generative Artificial Intelligence (GenAI) in higher education presents a critical pedagogical challenge for research training: how to integrate these tools without undermining methodological integrity. In

The rapid expansion of Generative Artificial Intelligence (GenAI) in higher education presents a critical pedagogical challenge for research training: how to integrate these tools without undermining methodological integrity. In qualitative research, unstructured GenAI use may encourage overreliance, superficiality, and unreflexive judgment among novice researchers. Despite growing debate, limited empirical evidence shows how GenAI can be deliberately designed to strengthen rigor in undergraduate qualitative data analysis. This study proposes and analyze the Sequencial Augmented Analysis a structured instructional model that embeds the use of chatbots within Human-Centered AI in Education and Experiential Learning frameworks. Using an exploratory multiple-case design with final-year pre-service teachers, we examined how GenAI-enhanced investigator triangulation and guided reflexivity support methodological integrity. Findings indicate that introducing chatbots after manual analysis stimulated collective reconsideration of decisions, systematic returns to original data, and clearer justification of methodological choices. It also surfaced personal biases, methodological assumptions, and ethical concerns regarding authorship and disclosure. Rather than replacing human judgment, GenAI functioned as a catalyst for dialogue and critique. The study offers a replicable pedagogical design for integrating GenAI into qualitative research courses while reinforcing academic integrity.

Educators and institutions are grappling with how to navigate the integration of generative artificial intelligence (GenAI) while preserving academic integrity and human-centred education. The rapid emergence of GenAI has created a

Educators and institutions are grappling with how to navigate the integration of generative artificial intelligence (GenAI) while preserving academic integrity and human-centred education. The rapid emergence of GenAI has created a persistent disconnect between institutional policy and practice, leaving students and staff to manage ambiguity in which anxiety often displaces agency. This paper reports on a Design-Based Research (DBR) study that explored how a theoretically informed, co-designed pedagogical strategy can support the development of ethical AI literacy, defined as students’ knowledge, reasoning, and regulatory capacities to use GenAI ethically. Drawing on a Student–Staff Partnership (SSP) methodology grounded in regulatory learning theory and emotion regulation, we iteratively developed and formatively evaluated a multimodal educational module within the Faculty of Science of a research-intensive Australian university. Independent quality review provided formative evidence that the co-design process produced resources perceived as authentic, accessible, and empathetically framed. Pilot implementation, however, revealed a critical challenge: an opt-in delivery model had limited reach among the intended audience. From this work we advance four emergent, testable design principles for ethical pedagogy: partner for authenticity, scaffold ethical self-regulation, attend to holistic competence, and employ empathy as pedagogy. The findings suggest a need for educators to embed AI literacy directly into curriculum, moving beyond centralised, opt-in supports.

Ethics in translation is often treated as a marginal or theoretical concern, rather than a central, integrated component of the curriculum. This mixed-methods study aims to investigate students’ perceptions of ethical principles in

Ethics in translation is often treated as a marginal or theoretical concern, rather than a central, integrated component of the curriculum. This mixed-methods study aims to investigate students’ perceptions of ethical principles in translation teaching in the era of AI-supported education. 416 fourth-year students from a university in Vietnam completed a structured questionnaire. Eleven students were randomly selected for semi-structured interviews to explore deeper insights into their ethical perspectives. While students showed ethical awareness of copyright and confidentiality, they lacked sufficient understanding of or interest in privacy policies. They highly appreciated professional values, acknowledging the role of human translation in refining AI-generated translations. Still, they paid little attention to sustainability and justice, which are implicit aspects of AI use in translation. The findings highlight the need for curriculum integration of translation ethics in the AI-enabled era to train both competent and ethically grounded novices who can evaluate platform terms, form privacy-aware decision-making habits, and engage with sustainability and justice. Clearer AI platform policies are needed to support responsible and ethical use of translation technologies. Future research should explore students’ ethical decision-making in AI-based translation and the impact of AI tools on students’ professional development and translators’ agency.

New generative AI (GenAI) tools are largely a product of the Global North but have rapidly spread worldwide. This scoping review examines the current perceptions of Generative AI in higher education across the Global South by analysing 75

New generative AI (GenAI) tools are largely a product of the Global North but have rapidly spread worldwide. This scoping review examines the current perceptions of Generative AI in higher education across the Global South by analysing 75 papers published between 2022-2025. Following the PRISMA-ScR methodology, the review categorised the findings into five main areas: GenAI acceptance and adoption, implications and challenges, academic integrity considerations, educational practices, and equity concerns. The analysis reveals that GenAI offers transformative possibilities for personalised learning, research support, and administrative efficiency in higher education across the Global South, but its implementation faces significant barriers, including infrastructure limitations, human capital deficiencies, ethical concerns, inadequate policy frameworks, and contextual challenges. Notably, equity considerations have received the least research attention despite their critical importance in inclusive education. This review also identified substantial gaps in the literature, including limited geographic representation, stakeholder imbalance, and insufficient exploration of long-term outcomes. The authors recommend that future research prioritise equity-centred approaches, methodological diversity, contextual specificity, implementation science, and interdisciplinary collaboration to better understand how Generative AI can enhance educational opportunities without reinforcing existing disparities across the diverse contexts of the Global South.

Generative artificial intelligence (GenAI) presents journalism educators with a paradox. It promises efficiencies and new creative possibilities for students, yet threatens academic integrity, authorship, and the core values of the

Generative artificial intelligence (GenAI) presents journalism educators with a paradox. It promises efficiencies and new creative possibilities for students, yet threatens academic integrity, authorship, and the core values of the profession. This paper presents a practice-based curriculum intervention based on an ethical framework that embeds GenAI into undergraduate journalism assessment. The framework integrates Colin Beard’s Experiential Learning Design with Bloom’s revised taxonomy to scaffold students’ movement from human-only reporting tasks to AI-integrated work and critical reflection. Qualitative data from a second-year journalism unit at an Australian global campus in Sarawak, Malaysia, reveal that students already use GenAI strategically but hold deep concerns about accuracy, originality and disclosure. These findings inform the design of authentic, scaffolded activities that aim to convert students’ intuitive concerns into explicit competencies in ethical decision-making, prompt engineering and verification. The paper contributes a model that links Australian and institutional quality expectations to the realities of GenAI in journalism education in Malaysia campus.

As generative AI (GenAI) tools increasingly influence higher education, instructors face urgent decisions about how to address these technologies in their teaching, often without institutional policies or clear guidance. This study

As generative AI (GenAI) tools increasingly influence higher education, instructors face urgent decisions about how to address these technologies in their teaching, often without institutional policies or clear guidance. This study examines how academic development can support educators in making ethical, pedagogically sound decisions about GenAI integration. Grounded in a practitioner inquiry framework, we analyse data from a workshop, Communicating about Ethical AI Use with Learners. Participants engaged in structured reflection, peer discussion, and syllabus policy drafting activities designed to surface values, clarify learning goals, and build confidence in communicating course-level GenAI expectations. Findings from participant-surveys (pre- and posttests) and workshop artifacts reveal that faculty overwhelmingly emphasize academic integrity in discussions of course AI policies, but also express concerns about equity, access, and student learning. Participants reported increased confidence in their ability to create and communicate GenAI policies after engaging in the workshop. We argue that academic development functions as ethical infrastructure, offering not only policy templates but also reflective space to support human-centred and context-sensitive decision-making. This article contributes a practice-informed model of GenAI ethics that can guide faculty developers and instructors in designing responsive learning environments. It offers insights for those seeking to foster ethical awareness, transparency, and pedagogical intentionality in a rapidly evolving technological landscape.

This article explores the integration of artificial intelligence (AI) in an English course for Academic and Professional Communication, situated within the broader context of digital transformation in higher education and the evolving

This article explores the integration of artificial intelligence (AI) in an English course for Academic and Professional Communication, situated within the broader context of digital transformation in higher education and the evolving demands of academic integrity. Rather than restricting AI use, the study adopts a critical digital pedagogy approach to foster students' awareness of ethical and effective engagement with AI tools. The activities were designed to encourage reflective practices, promote critical analysis of AI-generated content, and establish clear guidelines for responsible use. These activities include setting explicit expectations for AI-assisted work, integrating reflective assessments to evaluate AI outputs, and designing tasks that strengthen students’ critical thinking and academic integrity. Additionally, the approach aims to improve students’ retention of the course content by encouraging them to use AI not as a shortcut, but as a means to actively reflect, process, and engage with the material explained in class. By interacting with AI to rephrase, question, edit, or elaborate on key concepts, students become more conscious of the content, reinforcing understanding and promoting deeper learning. The results suggest that the students developed a more nuanced understanding of the capabilities and limitations, enabling them to engage with it as a support tool rather than a substitute for the original work. The study concludes that structured integration of AI can enhance students' digital literacy, content retention, and critical thinking skills in the academic context.

Raising students’ ethical awareness of generative artificial intelligence (GenAI) is critical as higher education responds to rapid technological change. This study investigates how guided reflection embedded within self‑assessment can

Raising students’ ethical awareness of generative artificial intelligence (GenAI) is critical as higher education responds to rapid technological change. This study investigates how guided reflection embedded within self‑assessment can support students to engage responsibly and confidently with GenAI in learning and assessment, while maintaining academic integrity. The self‑assessment, designed to foster readiness and learner agency, prompted students to reflect on their use of GenAI for critical thinking, writing, and understanding disciplinary concepts, positioning them as reflective practitioners capable of navigating ethical dimensions of AI use. Data were collected through pre‑ and post‑semester surveys administered to commencing university students. Likert‑scale items measured confidence in academic and digital literacies, while an open‑text response invited reflection on the ethical implications of GenAI. Qualitative data were thematically analysed to examine ethical engagement and emerging learner agency. Findings indicate that students recognised both the benefits and limitations of GenAI, demonstrating ethical awareness and critical evaluation of its role in academic work. Reflections revealed tensions between efficiency and academic integrity, as well as uncertainty about institutional expectations. Students also reported an increased sense of personal responsibility, describing the reflective process as confidence‑building during their transition to university study. The evolving role of educators involves supporting students to engage critically and responsibly with emerging technologies. Embedding GenAI‑focused reflection within self‑assessment reframes ethical inquiry as a pedagogical strategy. This study contributes to scholarship on ethical GenAI use and offers a scalable, student‑centred approach that can be adapted across disciplines and year levels.

Since generative artificial intelligence (genAI) applications became widely available in November 2022, university students and teachers have confronted choices about using genAI in coursework, research, and other tasks. In this article

Since generative artificial intelligence (genAI) applications became widely available in November 2022, university students and teachers have confronted choices about using genAI in coursework, research, and other tasks. In this article, we investigate Swedish university students’ and teachers’ perspectives on the ethics of genAI (non)use in higher education. Data comes from anonymous responses to voluntary online surveys and five focus group interviews with undergraduate and postgraduate students and teachers in the social science faculty of a Swedish public university. We ask what ethical concerns informed research participants’ perceptions and (non)use of genAI, and draw on the discipline of moral philosophy, particularly the work of environmental ethicist Carolyn Merchant, to consider how higher education institutions might work holistically with this material to support ethical genAI (non)use. Merchant proposes “partnership ethics” as an environmentally-informed, dialogue-based alternative to the ethics that often dominate decision-making. We argue that partnership ethics can guide university teachers and students in making decisions about this rapidly evolving technology and offer practical suggestions for implementing partnership ethics in higher education settings.

60% of higher education institutions worldwide reported that their faculty used generative artificial intelligence tools in teaching. However, fewer than 15% had implemented formal ethical guidelines. This issue underscores the importance

60% of higher education institutions worldwide reported that their faculty used generative artificial intelligence tools in teaching. However, fewer than 15% had implemented formal ethical guidelines. This issue underscores the importance of equipping English for Academic Purposes educators in higher education to utilise artificial intelligence effectively while maintaining academic integrity, transparency, and equity. This study addressed the lack of evidence from Global South contexts, the shortage of field-tested professional development models, and the limited integration of technical and ethical training. Guided by Mezirow's Transformative Learning Theory and established ethical decision-making frameworks in educational technology, the study designed, implemented, and evaluated a GenAI-integrated Professional Development program that embeds ethical reasoning within a multicultural Global South institution. A convergent mixed-methods approach engaged 97 higher education educators in quantitative testing and 15 in qualitative interviews. Original instruments, including a Scenario Rubric, Artefact Rubric, and engagement index, measured pre- and post-program changes. Quantitative results showed significant gains in ethical awareness (d = 0.93) and digital andragogical competence, supported by high inter-rater reliability. Qualitative findings confirmed challenges such as plagiarism and student overreliance on artificial intelligence, and revealed an unexpected barrier: reconciling institutional policy gaps with personal ethical values. Recommendations include embedding artificial intelligence policy literacy into professional development, fostering peer-led communities of practice, and creating shared resources on artificial intelligence. The professional development model can be adapted for use in other contexts, and future research should investigate its scalability.

Generative artificial intelligence has become part of everyday academic work despite many questions centring around its ethical, pedagogical, and institutional aspects. This paper synthesises the results of two questionnaire studies from

Generative artificial intelligence has become part of everyday academic work despite many questions centring around its ethical, pedagogical, and institutional aspects. This paper synthesises the results of two questionnaire studies from the European higher educational context, one administered with students (n = 226) and another with instructors (n = 256). Parallel five-point scales measured AI literacy, motivation, ethics, intention, and support. Independent-samples t-tests revealed significant group differences: students rated their ethical awareness higher than instructors, while instructors reported stronger willingness to experiment with AI tools and reported higher behavioural intention, which might be because students tend to view ethics through their immediate coursework practices, whereas teachers interpret it through the lack of institutional clarity and treat is as a question of integrity. Cluster analysis of instructors identified three user groups that differed in several literacy dimensions, with the scale of ethics providing a clear distinction. Correlation analyses indicated that instructors’ moral awareness and intention grow parallel with institutional and social support, while students’ confidence and readiness correlate mostly with self-efficacy and collaboration rather than with formal instruction.

Generative Artificial Intelligence (GenAI) has rapidly emerged as a dramatic disruptor across multiple sectors, significantly impacting higher education and workplace dynamics (Baidoo-anu & Owusu Ansah, 2023). Understanding how students

Generative Artificial Intelligence (GenAI) has rapidly emerged as a dramatic disruptor across multiple sectors, significantly impacting higher education and workplace dynamics (Baidoo-anu & Owusu Ansah, 2023). Understanding how students and educators engage with the complexities, challenges, and affordances of GenAI is essential to developing robust institutional educational responses. In 2023, we administered a survey to academic staff at our Australian-based University to explore their perspectives, attitudes and experiences regarding GenAI in learning and teaching. Findings revealed substantial concerns regarding academic integrity, ethical considerations, and the potential erosion of essential academic skills such as critical thinking and creativity. Staff highlighted equity concerns related to student access and proficiency in GenAI tools and digital literacy, with uncertainty about staff responsibilities in training students. Conversely, staff recognised substantial opportunities for using GenAI to enhance teaching practices through streamlined administrative processes, improved curriculum and assessment design, and innovative, student-centred learning activities. Given our findings, there is an urgent need for clear governance frameworks, structured professional training programs, interdisciplinary collaboration, and the active inclusion of student perspectives.

This study examines the organisational and technological determinants influencing the adoption of artificial intelligence (AI) technologies specifically data-driven decision support systems (DSS) and smart learning platforms in Saudi

This study examines the organisational and technological determinants influencing the adoption of artificial intelligence (AI) technologies specifically data-driven decision support systems (DSS) and smart learning platforms in Saudi Arabian higher education institutions. Guided by the integrated Technology–Organisation–Environment (TOE) framework and Diffusion of Innovations (DOI) theory, the study employs a quantitative approach using a structured survey administered to 300 academic and administrative staff across multiple institutions. The survey captures key constructs, including social trends, organisational culture, sustainability practices, waste management, technology compatibility, relative advantage, complexity, social drivers, innovation attributes, intention to use data-driven DSS, and government regulatory support. Structural equation modelling (SEM) was applied to test the hypothesised relationships and evaluate the interplay among organisational, technological, and environmental factors. The results reveal that internal organisational conditions, particularly organisational culture, sustainability policies, and waste-management practices- significantly strengthen internal social drivers that promote technological change. Technological characteristics, including Compatibility with existing systems and perceived relative advantage, strongly enhance the perceived innovation attributes of AI technologies. These innovation attributes, in turn, serve as a major catalyst for both the intention to use and actual adoption of AI-enabled systems. Adoption within the higher education context was associated with improvements in teaching practices, enhanced learner engagement, and curriculum innovation. Moreover, government regulations and policy incentives emerged as crucial external enablers that facilitate institutional readiness and adoption. This study contributes to the growing body of knowledge on AI integration in higher education by providing an empirically validated model that highlights the interaction between organisational drivers, innovation characteristics, and environmental enablers. The findings offer practical insights for policymakers, higher education leaders, and system designers seeking to accelerate responsible and effective AI adoption in academic environments.

This paper explored students' use of Generative Artificial Intelligence (GenAI) for Objective Structured Clinical Examinations (OSCE) preparation using a retrospective cohort study conducted over two years (2023–2024) across Australia and

This paper explored students' use of Generative Artificial Intelligence (GenAI) for Objective Structured Clinical Examinations (OSCE) preparation using a retrospective cohort study conducted over two years (2023–2024) across Australia and Malaysia. Results analysed OSCE grades and written self-reflections from students. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was applied as a lens to interpret qualitative data using summative content analysis. Of 997 students, 163 (16.3%) stated they did use GenAI to prepare for OSCEs. Across both campuses, there was no significant difference in mean OSCE grades between GenAI users (79.9%, SD = 15.3) and non-GenAI users (79.6%, SD = 17.4; p = .6); however, non-GenAI users performed significantly better (p < .05) in four of the seven communication rubric criteria. Themes around mistrust or perceived inaccuracy of GenAI data for clinical application deterred use in non-users. From our results, the use of GenAI did not demonstrate additional benefits for overall OSCE preparation, suggesting the potential need for more pedagogically aligned applications of GenAI tools to maximise their utility for clinical assessment preparation.

ChatGPT’s intuitive interface and instant feedback can either support learning or enable superficial task completion, depending on how it is integrated into academic work. While generative AI has rapidly entered higher education, much

ChatGPT’s intuitive interface and instant feedback can either support learning or enable superficial task completion, depending on how it is integrated into academic work. While generative AI has rapidly entered higher education, much existing guidance focuses on policy and academic integrity rather than explaining how AI use interacts with established mechanisms of learning. This conceptual paper contributes to this discussion by developing an explanatory framework for students’ ChatGPT use grounded in foundational learning theories. Drawing on cognitive load theory and goal orientation theory and incorporating self-efficacy and task relevance as mediating constructs, the study undertakes a theory-driven synthesis of four perspectives relevant to how students engage with complex academic tasks. The framework brings these perspectives together to clarify how cognitive demands, motivational orientations, perceived competence, and perceived task value may shape students’ decisions about when and how to rely on generative AI tools during academic work. The resulting framework illustrates how these mechanisms may influence whether generative AI is used as a scaffold supporting thinking and knowledge construction or as a shortcut that bypasses essential cognitive processes. The article concludes by illustrating how the framework may inform instructional design that aligns AI use with meaningful engagement in disciplinary tasks in higher education.

With the rise of GenAI, business schools must prepare students for a future workforce integrated with this technology. This paper details a case study from a UK business school that introduced GenAI into its curriculum for first-year

With the rise of GenAI, business schools must prepare students for a future workforce integrated with this technology. This paper details a case study from a UK business school that introduced GenAI into its curriculum for first-year undergraduates. Through a mixed-methods survey of 149 students, the study gathered feedback on newly implemented AI-focused learning activities. The findings reveal that students are highly engaged and recognise the necessity of developing GenAI skills for their future careers. Key areas of interest include the real-world business applications of AI, ethical considerations, and future technological advancements. A significant concern for students is the desire to use GenAI in their academic work without unintentionally committing academic misconduct. Based on student feedback and existing research, this study presents a new conceptual framework for integrating GenAI education throughout business degree programmes. It offers practical guidance for educators, including a scaffolded approach to learning activities and assessments across all undergraduate levels. This research contributes an innovative model for applied GenAI learning in business education, adding to the growing body of literature on student AI literacy.

This study aims to systematically map the evolving landscape of artificial intelligence (AI) integration into business education, highlighting dominant research themes, emerging gaps, and future research directions. Adopting a bibliometric

This study aims to systematically map the evolving landscape of artificial intelligence (AI) integration into business education, highlighting dominant research themes, emerging gaps, and future research directions. Adopting a bibliometric analysis framework, the study analyzed 213 peer-reviewed journal articles published between 2015 and 2024, extracted from the Dimensions database. Bibliographic coupling and co-word analysis, facilitated through VOSviewer, were employed to uncover intellectual structures, thematic clusters, and conceptual linkages within the field. The results identified four major research clusters: AI-driven business education transformation, innovative digital pedagogies, AI-enhanced personalization of learning, and business education aligned with the digital economy. Co-word analysis further revealed three conceptual trends: technological transformation, integration of generative AI tools, and advancements in educational quality. Persistent gaps emerged concerning curriculum coherence, educator readiness, and assessment validity. This study offers actionable guidance for educators, curriculum developers, and policymakers to design AI-integrated, ethically grounded, and adaptable business education models that meet the demands of an AI-driven global economy. This study provides a comprehensive, empirical foundation for future research agendas and strategic educational reforms

This conceptual paper aims to identify the characteristics of Design-Based Research (DBR) projects that support the sustainable, expansive or adaptive implementation of technological learning innovations in higher education and thus

This conceptual paper aims to identify the characteristics of Design-Based Research (DBR) projects that support the sustainable, expansive or adaptive implementation of technological learning innovations in higher education and thus address this gap in the literature. Four examples of Design-Based Research implemented in different discipline contexts through technology enhanced learning interventions in higher education are retrospectively analysed and compared. The higher education discipline contexts of the projects include health education, music performance, biomedical engineering, electrical and mechanical engineering. The analysis uses a shared framework based upon identifying five characteristics of design research and activity theory. Shared characteristics include addressing an identified pedagogical problem or innovation through iteratively designing and evaluating an intervention that enhances learning while developing theoretical insights. Transdisciplinary collaboration enhances the transferability of design principles derived from these projects into wider contexts. Activity Theory analysis is utilised to identify context-specific contradictions and strengths in each example. These four longitudinal project designs illustrate how Design-Based Research can be combined with Activity Theory and practically implemented as a transferable educational design framework to generate impact on teaching and learning that is either sustained, expansive or adaptive.

This paper critically evaluates the third prototype design iteration of an immersive reality (XR) enhanced simulation project in healthcare higher education. Drawing from design principles developed since the project’s inception in 2016

This paper critically evaluates the third prototype design iteration of an immersive reality (XR) enhanced simulation project in healthcare higher education. Drawing from design principles developed since the project’s inception in 2016, the research addresses a gap in current literature: whilst XR has demonstrated positive impacts on clinical skill development, examples of longitudinal studies and engagement with learning theory to inform the design of these environments remain limited. The MESH360 project applies design-based research (DBR) to explore the impact of XR-enhanced simulation for training novice and professional paramedics, triangulating participant feedback, observation, and biometric data. The resulting XR design principles provide a framework for transferable learning designs in high-risk, practice-based environments.