Junhong Xiao

As GenAI technologies become more pervasive in higher education (HE), scholars call for guidance on AI governance. To meet this need, a Delphi technique and collective writing was used in gathering expert perspectives from across 22 countries/locations and six continents. This resulted in the development of a HE GenAI policy/guidelines framework with eight core areas: (1) academic integrity, (2) ethical use and responsible use, (3) privacy and protection, (4) equitable access, (5) GenAI literacy, (6) integration strategy, (7) human oversight and accountability, and (8) institutional support and infrastructure. In addition, a six-part framework was developed to ensure that policies remain current and relevant: (1) creating a dedicated GenAI Committee, (2) conducting regularly scheduled policy reviews, (3) providing ongoing professional development and support, (4) communicating with all stakeholders, (5) evaluating the effectiveness and impact of GenAI, and 6) monitoring external developments. By providing a robust, eight-part framework for policy and guidelines, alongside a six-part mechanism for continued review, this study offers faculty, students, administrators, educational leaders, policymakers, and funders a responsible, adaptable, and consensus-driven blueprint for navigating the integration of GenAI in HE, ensuring that technological innovation serves pedagogical excellence.

Artificial intelligence (AI) is being deployed in higher education at an unprecedented scale and pace as a silver bullet for the “sick” higher education system. This opinion paper examines whether and to what extent AI is the solution to the problems that make higher education purportedly outmoded and/or dysfunctional in the first place. It begins by identifying two persistent challenges confronting the sector: uneven quality and enduring inequities in access. The discussion then turns to the deeper structural causes of these challenges, before examining four potential roles that AI is commonly assumed to play in addressing them. In doing so, the paper critically explores whether AI can meaningfully remedy higher education’s underlying problems, and concludes by proposing a technology-agnostic, future-proof approach to transforming higher education in more sustainable and principled ways. The position of this paper is that the future of higher education should not hinge on any particular technology, no matter how cutting-edge it may appear. Accordingly, a fundamental principle for the selection and use of technology in higher education is proposed, whereby a technology should be adopted only when it enables educators to do what they otherwise cannot, or when it demonstrably performs better than educators at an affordable cost, or when it performs as well as educators while reducing costs. Higher education should remain open to technological advancement, but it must not allow itself to be defined by it.

Open and distance education (ODE) has played a key role in contributing to the growth of Chinese higher education (HE) ever since the mid-1950s. This study sets out to examine the key events of ODE in China, focusing on two main strands of ODE development – the Chinese radio and television/open university system and campus-based universities. Innovative practices from the Chinese ODE community are critiqued, in particular those from the ODE ecosystem and the impacts of ODE on Chinese HE are examined in terms of massification of HE, mainstreaming openness in HE, and the synergetic interaction between ODE and campus-based education. Lessons from the 70-year history of Chinese open and distance higher education are discussed and directions for future development are suggested, ranging from the balance of government support and university autonomy, continuing commitment to access and equity, focus on sustainable development, emphasis on skilling and re-skilling to underscoring lifelong learning for the third age and fit-for-purpose use of technology. Notwithstanding its highly contextualized nature, this study arguably has implications for the international HE community, especially ODE institutions.

The hype surrounding AI for education continues with no sign of dying down in the near term. Given the influence of UNESCO and OECD on national educational policies worldwide, this study examined how they frame artificial intelligence (AI) and how their discourse may affect the wider educational landscape. Drawing upon the theory of Critical Discourse Analysis, this study adopted a two-stage analysis method: framework analysis followed by directed qualitative content analysis. Four themes were identified, including the necessity of AI-driven educational transformation, imagined educational futures enabled by AI, challenges brought about by AI for education, and solutions and walkthroughs. They were critiqued using the schema of practical argument proposed for political discourse analysis which is composed of a Value premise, a Goal premise, a Circumstantial premise, a Means–Goal premise and a Claim (or conclusion). Findings show that while admitting the existence of enormous uncertainties and challenges, UNESCO and OECD take for granted AI’s disruptiveness, inevitability, and potential to change education, its effect on the whole society for the better and its encouragement of the acceleration of AI for education. Possible ramifications of this framing on the ecology of education and beyond were then discussed. The article concludes by calling for a vigilant and critical approach to the AI narratives promoted by influential global agencies, arguing that the future of education depends on our ability to question, adapt and thoughtfully integrate technology without succumbing to unexamined inevitabilities or unwarranted optimism.

Open Praxis is a peer-reviewed open access scholarly journal focusing on research and innovation in open, distance, and flexible education. It is published by International Council for Open and Distance Education - ICDE Web of Science (ESCI) Impact Factor for 2023 is 0,9; ranked 457 out of 759 in Education and Educational Sciences in Q3. Scopus Cite Score is 3.5; ranked 453 out of 1543 in Education category in Q2 and 72 out of 2801 in Library and Information Sciences category in Q2. Facts and Figures: 2024 article acceptance rate is 33%, rejection rate is 67% (13% desk rejections - 54% rejections after review). While the number of days for acceptance is 44, the number of days for rejection is 16.