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From ad hoc to constructive: the ABC levels of GenAI integration in business education

by Qianqian Chai and Xue Zhou

Introduction – the challenge of GenAI integration in business education

Since the release of ChatGPT, Generative Artificial Intelligence (GenAI) has rapidly entered higher education. Business schools, with their strong ties to industry and emphasis on applied skills, provide a particularly important setting for examining GenAI’s role in curriculum design. Yet, while adoption has expanded quickly, the educational outcomes of GenAI integration have not been consistent (Kurtz et al, 2024). Across cases, educators identified both benefits and risks, including engagement, skills development, and overreliance. This unevenness suggests that rather than reflecting a single trajectory of adoption, early practice appears to involve different approaches to integration. The central issue is not whether GenAI is used, but how different approaches shape outcomes.

This blog draws on our recent study of GenAI integration in business modules at a UK Russell Group university (Zhou et al, 2026). Through a qualitative analysis of 17 educator cases across 24 modules, we examined how GenAI was incorporated into curriculum design, and how different approaches were associated with distinct benefits and challenges. Using the lens of constructive alignment (Biggs, 1996), we identified three patterns of integration: ad hoc, blended, and constructive, which together form the ABC levels for understanding how GenAI is integrated into curriculum practice. We use these levels to explore why some approaches appear more educationally effective than others. In particular, this blog will offer research-informed insights into how GenAI can be integrated more effectively and sustainably in business higher education. While the cases are drawn from business education, the patterns identified and principles of constructive integration have wider relevance across disciplines where GenAI is increasingly embedded in curriculum design.

ABC levels of GenAI integration in the business curriculum

Our analysis identified three levels of GenAI integration: ad hoc, blended, and constructive. Table 1 outlines these distinctions across key dimensions.

Table 1 ABC levels of GenAI curriculum integration

Constructive integration represents a qualitatively different approach, grounded in constructive alignment, where intended learning outcomes, teaching activities, and assessment are deliberately designed to develop and evaluate students’ ability to use GenAI critically and effectively. At this level, GenAI is not an optional or supporting tool, but an integral component of disciplinary learning, with a clear pedagogical purpose and coherent role across the curriculum.

By contrast, ad hoc integration is characterised by occasional and isolated use, where GenAI is introduced as an optional or experimental tool without being planned into the broader curriculum design. Blended integration moves beyond this by incorporating GenAI into selected learning activities or tasks, giving it a more purposeful pedagogical role, but its use remains only partially embedded. Both approaches therefore fall short of the coherence and strategic alignment that define constructive integration.

The distinction between these patterns is therefore not simply a matter of more or less GenAI use, but of how GenAI is positioned within the curriculum: as an experiment, as a support, or as a capability to be deliberately developed. Although developed from business education contexts, this typology offers a lens that can be applied more broadly to understand how GenAI is positioned within different disciplinary curricula.

Why constructive integration matters

Across the cases, GenAI integration generated benefits and challenges across students, educators, and institutions. At the student level, reported benefits included stronger engagement, confidence, and employability-related skills, while the main risks centred on overreliance, inequality, ethical concerns, and ineffective outputs. For educators, benefits included efficiency gains, professional learning, and improved teaching performance, but these were accompanied by increased workload and the need to redesign activities and assessments. At the programme level, GenAI enhanced curriculum relevance but raised concerns about academic standards.

Figure 1 shows that these benefits and challenges were not distributed evenly across the three patterns of integration. Constructive integration displayed the strongest and broadest benefits, while ad hoc and blended approaches showed narrower gains alongside more exposed challenges. In other words, the issue is not whether GenAI brings value or risk, but how curriculum design shapes the balance between them.

Figure 1 Trade-offs of GenAI integration: challenges (red) vs benefits (green)

What makes constructive integration different is not the removal of challenge, but the stronger presence of educational value. In the study, constructively integrated cases were linked more clearly to student engagement, capability development, employability, and curriculum relevance because GenAI was embedded through aligned outcomes, activities, and assessment, rather than added on as a tool or support. Importantly, these cases also showed stronger educator development, including pedagogical reflection and confidence, despite workload pressures. This suggests constructive integration enhances both student outcomes and educator learning by embedding AI within coherent curriculum design.

How constructive integration is achieved

Table 2 presents examples from the modules in this study, showing how GenAI was constructively integrated into existing pedagogical strategies without requiring curriculum redesign.

Table 2 Constructive GenAI Integration into Existing Pedagogical Strategies

Taken together, the cases suggest several practical principles for integrating GenAI more coherently within the curriculum. These principles are not specific to business education, but reflect broader curriculum design considerations that can be adapted across disciplines with different pedagogical traditions.

  • Integration builds on existing pedagogical strategies: GenAI should be embedded within approaches already familiar to the discipline, such as project-based or simulation-based learning, without requiring curriculum redesign (Chugh et al, 2023).
  • Sharpen the role of GenAI by disciplinary purpose: In different contexts, GenAI supported strategic analysis, research and synthesis, reflective thinking, or data interpretation. Its value depends on alignment with module aims (Zhou & Milecka-Forrest, 2021).
  • Make AI use purposeful through assessment and evaluative tasks: In stronger cases, GenAI was connected to tasks that required students to interpret, justify, compare, or critique AI-supported outputs, rather than simply using AI to complete tasks (Biggs & Tang, 2010).
  • Support deeper student engagement through scaffolding: Structured guidance, such as prompting strategies, comparison activities, and reflective tasks, enabled more critical and purposeful use (Cukurova & Miao, 2024).

Overall, constructive integration is less about introducing new tools than about redesigning existing curriculum elements so that GenAI is meaningfully aligned with disciplinary learning.

Conclusion

The ABC levels developed in our study show that GenAI integration in business education does not follow a single trajectory but ranges from ad hoc and blended use to constructive integration. The key difference lies in approach: constructive integration embeds GenAI through aligned outcomes, activities, assessment, and scaffolding. The challenges observed across GenAI integration practices suggest an urgent shift from ad hoc GenAI integration toward strategic and constructive integration in business education. In this way, higher education can support students’ employability and capability development, strengthen educators’ professional and pedagogical confidence, and enable institutions to sustain coherent, future-facing curricula.

Dr Qianqian Chai is a Lecturer in Business and Management at Queen Mary University of London and Chair of the AI in Education Innovation Sub-committee in the School of the Arts. Her research focuses on AI in higher education, including curriculum design, academic integrity, and policy. q.chai@qmul.ac.uk

Professor Xue Zhou is a Professor in AI in Business Education and Dean of AI at the University of Leicester. Her research interests include digital literacy, digital technology adoption, cross-cultural adjustment, and online professionalism. xue.zhou@le.ac.uk


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In defence of SoTL: anchoring educational evaluation and educational research

by Liz Austen

By the end of 2025 I had attended three HE related conferences: Euro SoTL, the Wonkhe Festival of HE and the SRHE Annual Conference. I presented on similar topics at all three events; what evidence do we generate to help us understand and act to enhance student experiences and outcomes in higher education? During the Wonkhe panel and my SRHE session, I defined two approaches at the disposal of HE practitioners:

Higher Education Evaluation: an approach which helps to understand and explore what works and doesn’t work in a given context and is of value to stakeholders. The aim of evaluation is to generate actionable evidence-informed learning, which encourages, informs and supports continuous improvement of process and impact (Evaluation Collective 2025)

Higher Education Research: to extend knowledge and understanding in all areas of educational activity and from a wide range of perspectives, including those of learners, educators, policymakers and the public (adapted from BERA, 2024)

At the Wonkhe panel, Clare Loughlin-Chow (CEO of SRHE) helpfully outlined the higher education research topics that were most prevalent in the SRHE journals. Omar Khan (CEO of TASO) then outlined the scope and priories of TASO, an affiliate member of the government’s What Works Network which focuses on higher education evaluation. My conceptual discussion of evidence generation brought the two together.

At EuroSoTL earlier in the year, my colleagues and I outlined our new institutional approach to the Scholarship of Teaching and Learning:

Scholarship of Teaching and Learning (SoTL): to improve student learning through engagement in the existing knowledge of teaching and learning, developing contextual ideas and innovation in practice, reflecting on practice, applying methodological rigour, working in partnership with students, and sharing of scholarship publicly (adapted from Felton (2013))

When I attended SRHE in December 2025, SoTL appeared in only one session I attended and some of this discussion focused on the challenges of bringing SoTL into spaces for educational research. My hand in the air comment – that criticism of SoTL by educational researchers was an example of ‘academic snobbery’ – certainly raised a few eyebrows. This blog post considers the relationship between these three approaches and whether, for the good of our students, it’s time for some reconciliation.

Educational evaluation, SoTL and educational research

Educational research in higher education has developed over the last 60 years. Interestingly, research into teaching and learning is cited as the most theorised by this type of research (Tight, 2012). Higher education evaluation, sometimes considered as applied research, was recently propelled by the Office for Students’ agenda to ‘evaluate, evaluate, evaluate (Office for Students, 2022). SoTL has developed alongside HE research and evaluation, emerging from Boyer’s work in 1990.

The aims of each endeavour are distinct, tied by the notion of ‘enquiry’. Research seeks to build new knowledge, and evaluation seeks to provide judgment on a contextual problem. SoTL has a narrower focus on teaching and learning than the broader scope of research and evaluation but incorporates prior knowledge and contextual problem solving through focused enquiry (Gray, 2025). SoTL builds on the foundation of social sciences methodology and can integrate disciplinary methodology into practitioner’s teaching and learning enquiry (Riddell, 2026). Educational evaluation often asks questions of the effectiveness of interventions, but in some teaching and learning spaces, the evaluative language of ‘intervention’ isn’t appropriate (Austen (2025) in Austen and McCaig (2025)). Exploring what works through SoTL enquiry aligns better. Often the bridging term ‘pedagogic research’ is used as integral to SoTL (close to practice) but distinct from educational research (broader anticipated impact). Our chosen SoTL definition uses neither research nor evaluation terminology, but has component parts – knowledge, innovation, method, dissemination – that are central to all.

The essential agents in educational research, evaluation and SoTL are the same – individual students (as partners, as participants and as voice givers), individual staff (academic and professional services), institutional groups or clusters, collaborating HEIs, and third space organisations. Reasons for enquiry are also similar and include sector expectations and shared learning, the desire for institutional enhancement and impact, personal development and career progression. Or as Ashwin & Trigwell (in Evans et al, 2021) note:  to inform a wider audience; to inform a group within context; to inform oneself. All research, evaluation and SoTL agents must navigate the practical and ethical considerations of ‘insider’ enquiry if they are exploring their own practices or within their institutional contexts (BERA, 2018; Barnett & Camfield, 2016).

Output pathways are also interconnected. The SoTL staircase (Beckingham, 2023) recognised the variety of outputs encouraged by SoTL and includes those traditionally aligned with research and evaluation (reports and journal articles). Research outputs may be guided by REF criteria, and evaluation outputs by readership. The conclusions in research articles frequently state that more research needed, and evaluation reports often sit unread in metaphorical desk draws. In comparison, SoTL practitioners benefit from publications which are close to practice, quicker to publish, and more likely to influence change.

Both educational evaluation and educational research are inherently theoretical, grounded by educational or pedagogic theory or a theory of change. SoTL is more action focused, less theoretical than research yet can be more exploratory than evaluation. In 2011, Kanuka questioned SoTL’s credibility due to the lack of theoretical underpinning or reference to existing scholarship. At times, I suggest that educational research can be positioned too far in the opposite direction. The presentations at SRHE were heavily theoretical and sometimes I was left thinking ‘so how would this work actually improve the learning experiences of students’? In contrast, the breadth of SoTL includes both theory and action, albeit in more pragmatic ways.

There are values and specific skill sets of educational researchers and evaluators (and often epistemological disagreements occur between the two). This commitment to identity can be excluding and may help to understand why SoTL has been challenged. Canning & Masika (2022) caution us on the ‘threat to serious scholarship’ posed by SoTL, which they believe risks devaluing research into higher education learning and teaching. Their criticism of ‘anything goes’ I would frame as an important approach to inclusion. Their criticism of the ‘watered-down version of teaching and learning research’ I frame as SoTL’s recognition of the developmental, particularly in building staff confidence. Where confusion over definitions and scope still occur, I question whether institutional SoTL has been well grounded or well led.

Conclusion

There is clearly a divide between higher education research and SoTL. There are few recent SRHE blog posts which reference SoTL at all and one that does advises against flag-in-the-sand nomenclature (Sheridan, 2019). Having spent a lot of time in these circles, I believe higher education evaluators are more agnostic, but I include them in this discussion as they bring a new dynamic to this debate.

In this blog I have identified the ways in which research, evaluation and SoTL have their own agendas and yet have much in common. I argue that SoTL emerges as a grounding anchor between higher education research and higher education evaluation. SoTL borrows from both. SoTL feeds into both. SoTL is more than both (Potter, 2025). SoTL’s inherent value is the ability to build a community which improves student experiences and outcomes in an enquiry led and timely way.

For more details on the approach to SoTL at Sheffield Hallam University see: https://lta.shu.ac.uk/scholarship

Reference

Riddell, J (2026) ‘Hope circuits in practice: how the scholarship of teaching and learning fuels pedagogical courage and systemic change’ Guest Lecture, Sheffield Hallam University

Liz Austen is Professor of Higher Education Evaluation and Associate Dean Learning, Teaching and Student Success at Sheffield Hallam University. She has worked as an independent Evaluation Consultant on HE sector contracts and is a regular keynote speaker on all things evaluation in HE. Her focus is on evidence informed practice across the student lifecycle. Liz also leads a cross sector HE network called the Evaluation Collective.


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End of the road for higher education student loans?

by Gavin Moodie

Although we’ve come to the end of the road

Still, I can’t let go

As an expat Aussie I have been sad to see the unremitting erosion of public support for what is arguably Australia’s most innovative modern higher education export, income contingent student loans. While Australian student financing may not yet be as ‘unsustainable’ as England’s, the former Labor leader and current vice chancellor of the University of Canberra Bill Shorten argued that Australian universities are in a ‘political cul-de-sac’, with ‘a tired funding model’.

This blog seeks to understand how Australia’s higher education finance reached its Neighbourly cul-de-sac Ramsay Street, why it is perhaps not yet quite unsustainable, and the difficult choices confronting policy makers over the next 5 to 10 years in Australia, England, and elsewhere in the UK.

Introduction and early years: 1989 – 1996

The national Australian Labor Government introduced substantial tuition fees accompanied by income contingent loans in 1989 on the recommendation of the Committee on Higher Education Funding chaired by the astute late Neville Wran, former Labor premier of Australia’s biggest state, New South Wales. A consultant to the committee was Bruce Chapman, an advocate for income contingent loans for higher education and a range of other public policy problems such as farmers’ drought relief and penalties for insider trading and other white collar crimes.

The Wran committee recommended that total student charges should be about 20% of estimated costs in 8 categories of disciplines, which it aggregated into 3 contribution levels. While the Government agreed that student contributions should be about of 20% of system costs, it introduced a single price that avoided the complexities of students paying different rates for different subjects, and the possibility that higher charges may discourage students from enrolling in higher cost courses.

The Wran Committee also recommended an employers’ training levy, which was similar to the UK’s apprenticeship levy except that it could be spent on any form of employee training. Australia’s training guarantee was reasonably successful, but it was vociferously opposed by at least some employers and the Government discontinued it in 1994 after only 4 years of operation. This is consistent with employers’ long term substantial cuts to their induction and development of their own employees in Australia and Canada, as well as the UK.

Government charges by cost and expected income: 1997 – 2004

In 1997 the newly elected conservative Australian Government cut funding to higher education and increased student charges to about 40% of the presumed cost of higher education. The Government established 3 bands of student charges based on a combination of the presumed cost of subjects and graduates’ expected earnings.

In the lowest band were humanities and social sciences that were funded at a lower rate and whose graduates had lower earnings. Also in band 1 were languages and the creative arts. These were higher-cost disciplines, but most graduates’ earnings were lower than average.

In band 3 were disciplines with high costs and high graduates’ earnings: dentistry, medicine, and veterinary science. Also in band 3 was law: it was a low-cost discipline but graduates had high earnings. Band 3 charges were 1.7 times band 1 charges. All other disciplines were in band 2 which were charged 1.4 more than band 1: health, science, and engineering because they were high cost; and business because graduates had high incomes.

University fees by cost, expected income, and Government priorities: 2005 – 2020

From 2005 the Conservative Government changed student contributions from Government charges to institutions’ fees, and established four maximum fee amounts. It introduced a new fee band for the expensive STEM disciplines and for business which is funded at the base rate but has high graduate incomes, though lower than law which was still in the top band.

The Government also published government contribution amounts in 12 bands. The combination of maximum fee amounts and government contribution amounts gave total financing in eight bands. Agriculture, dentistry and medicine were in the highest financing band, which was 2.6 times the lowest band for business and humanities.

The Government also sought to influence students’ behaviour by setting low maximum fee amounts and to influence institutions’ behaviour by setting higher government contribution amounts for the ‘national priority’ disciplines of education and nursing. Institutions’ total revenue for education was 1.2 times the base rate and 1.5 times for nursing.

Job-ready graduates: 2021 –

In 2021 the then Conservative government further cut higher education funding and increased maximum student fees to be a weighted average of about half of total teaching financing, although this differs markedly by discipline, as we shall see. The Government also extended its attempts to influence both students and institutions’ behaviour with financial incentives intended to create ‘job-ready graduates’.

The Government set the lowest student fees for agriculture, education, English, foreign languages, mathematics and statistics, and nursing. It added humanities and most social sciences to business and law in the top fee rate of 3.7 times the base rate. Humanities and social sciences students now pay annual fees 28% higher than dentistry and medicine students, whose maximum fees are 2.9 the base rate.

The Government’s contribution is lowest for business, humanities and social sciences, and law; it is highest for agriculture, dentistry, medicine, and veterinary science, which is 24.6 times the base rate.

The combination of maximum student fees and Government contributions generates total financing for dentistry, medicine, and veterinary science 2.5 times the base rate for business, humanities and social sciences, and law. Total financing for engineering and science is 1.6 times the base rate.

Students pay markedly different proportions of the total financing for their courses. Business, humanities and social sciences, and law students pay 93% of the total financing of their course; engineering, science and medicine pay around 30% of their course’s financing; and education, languages, mathematics, and nursing students pay around 20% of their course’s financing.

These differences are widely considered unfair. It is also doubtful that they have changed students’ and institutions’ behaviour as they were designed to. Humanities and social sciences enrolments have fallen since the introduction of job-ready graduates, but that has continued a long established trend likely influenced by other factors such as prospective students’ interests and perceptions of employment prospects.

Enrolments in English and other languages have fallen even more than the humanities and social sciences, despite the government cutting their fees by 40%. An econometric study concluded ‘Overall, we estimate that the studied policy change led 1.52% of students to demand courses they wouldn’t have demanded under the old fee structure’.

This is entirely consistent with economic theory and Australia’s experience with its previous changes to students’ fees. The whole point of income-contingent loans is to insulate students from the up-front price of education, and that is just what they do, even when humanities’ students fees were increased by 113% and creative arts students’ fees were increased by 64%.

The Australian Labor government was elected in 2022 on a platform that included reversing job-ready graduates, and it was re-elected in 2025 with the same commitment. Yet Labor has kept job-ready graduates for longer than the previous conservative government, to the intense annoyance of many students and staff.

Debts, interest rates, return on investment

The size of Australian Government debt was a concern in the early years of income contingent loans when enrolments and thus accumulated unpaid debt was growing strongly and there were relatively few graduates yet in well-paying jobs repaying their debt. It is not such a big concern now: outstanding student debt is equivalent to 8% of all Australian government debt, which is around 50% of gross domestic product (in contrast to the UK where government debt is 101% of GDP).

The proportion of student debt not expected to be repaid increased from 16% to 25% from 2010 to 2016. However, this is sensitive to repayment conditions, and for 2024 the proportion of new debt not expected to be repaid was 12%.

The size of students’ debts has been concerning. Graduates’ average debt is currently about 30% of average annual earnings and takes just over 10 years to repay. But this varies greatly by individual circumstances. We have seen that the Government has set the maximum fee for arts subjects in the top band, meaning that arts graduates are likely to incur a total debt of half average annual earnings. Arts graduates have lower incomes than other graduates, and many are women who work part time at times during their career. Many are likely to take up to 40 years to repay their debt, if at all.

Graduates’ expected earnings was one of the Australian Government’s criteria for setting maximum student fees, and that remains the only explicitly progressive part of Australia’s student loans. The Australian Government charges interest on student debts, but only to preserve the debts’ real value. Australia does not charge higher income earners higher interest on their student debts, although they may have to repay their debt more quickly than lower paid graduates, as higher paid graduates are required to repay higher amounts each year than lower paid graduates.

Nevertheless, as in England, during a period of high inflation there has been controversy over which of the several measures of inflation to use, and when indexation should be assessed. Also as in England, there have been reports of new graduates’ annual repayments not even covering annual interest charges so their debt continues to increase. Accordingly the Labor Government promised to make repayment conditions more favourable to students, and to cut graduates’ debts once by 20%. Cutting graduates’ debt has been popular, despite being arbitrary and regressive, and arguably contributed to Labor’s re-election in a landslide in 2025.

Despite Australian students’ concerns about fees, debts, and interest rates, graduates have high economic returns, although these vary by gender and discipline.

Substantial differences from England

Further substantial differences between Australian and English higher education have important implications for student fees and loans in each country. The Australian Government retains student number controls. It removed number controls in 2012, some three years before most student number controls were removed for England in 2015/16. Australia introduced its so-called ‘demand driven system’ after a period of pent up demand for higher education, which saw very big increases in enrolments as enrolment caps were removed.

At the time the Australian Government provided about 60% of the financing for each student place, and of course it provided all of the up-front funds for student loans, so the demand driven system substantially increased Government spending on higher education. This was too much for the Australian Government, which ended the demand driven system and reintroduced number controls in 2017. One of the outcomes is that the Australian Government may limit increased expenditure on higher education by limiting its expansion, and not just by worsening students’ loan conditions.

Most Australian higher education students live with their parents. Nearly 80% of Australian higher education students commute from home, even to elite universities. While the proportion of UK 18-year-olds commuting from home is increasing, it is still only 30%. Living in purpose built student housing is a very different experience from commuting from home, and is probably one of the reasons for the UK’s unusually and commendably high student retention and completion rates. Commuting rates also has implications for institutions’ range of programs, which need to be reasonably comprehensive to meet the needs of local students. But a great advantage of commuting is that it greatly reduces students’ living costs, and thus their need for income support.

Universities’ social licence

An important limitation of Australian universities’ financing is their erosion of their social licence. A longstanding concern has been with Australian vice chancellors’ very high pay, amongst the highest in the world for public universities. The average Australian vice chancellor’s pay is almost double the Prime Minister’s. More recently there has been concern at the number of highly paid executives employed by universities: ‘More than 300 Australian university executives make more money than state premiers’. Closely related are complaints at universities’ changed governance, known broadly as the imposition of managerialism.

The very high pay and conditions of Australian universities’ senior executives is in almost feudal contrast to the very high number of academics they engage on precarious employment conditions. Australian universities’ staffing data collection and reporting are very weak on this issue, but the union estimates that about 45% of public Australian university employees are on casual contracts. This is related to widespread underpayment of casual staff.

As in the UK, Canada, and elsewhere, Australian universities have relieved their public funding pressures by recruiting high numbers of international students. Some 35% of Australia’s higher education students are international, 80% of whom live in Australia on a temporary entry permit. There are the familiar concerns that Australian universities lower standards to recruit and graduate large numbers of international students who crowd locals out of accommodation, all to fund senior executives’ lavish pay. Accordingly, the Australian Government is cutting the number of international students. Regardless of the merits of these arguments, there is little public sympathy for increasing universities’ funding from their current three main sources: government grants, domestic student fees, and international student fees.

Difficult choices for policy makers

The late great sociologist of higher education Martin Trow observed that:

“No society, no matter how rich, can afford a system of higher education for 20 or 30 percent of the age grade at the cost levels of the elite higher education that it formerly provided for 5 percent of the population.”

That observation applies equally as we transition to universal participation of more than 50% in post-school education, from mass participation of from 16% to 50% which our countries financed by income contingent loans. That is to say, the current pressures on higher education financing will not be relieved, as some have suggested, just by cutting the number of senior university administrators and their pay, allocating more funds to higher education from increasing taxes on the rich or on companies, or by increasing student fees.

I suggest that there are two main options. The most frequently suggested, especially in England, is to retreat from universal and even mass participation in higher education by cutting greatly the number of higher education students. A second commonly suggested option is to cut radically the cost of providing higher education.

Advocates of each option need to address two consequential issues. To what extent would the much smaller or cheaper system retain stratified elite, mass and universal parts, as Trow envisaged? Secondly, how would access to the elite, mass and universal parts of the system be allocated? I would answer these questions by considering the relative importance I would give to egalitarianism, and to expensive forms of higher education such as research intensity.

Gavin Moodie is Honorary Research Fellow, University of Oxford Department of Education. He worked at 6 Australian universities over 38 years. @GavinMoodie. https://www.researchgate.net/profile/Gavin-Moodie


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Digital accessibility debt in higher education: how institutional decisions create structural exclusion

by Kevin Andrews

Digital accessibility in higher education is often discussed as a compliance requirement. Universities are expected to meet legal duties, publish accessibility statements, and make reasonable adjustments when barriers arise. Over the last decade the policy environment has strengthened considerably. In the UK the Equality Act 2010 established obligations to remove barriers for disabled students and staff, while the Public Sector Bodies (Websites and Mobile Applications) Accessibility Regulations introduced additional scrutiny of institutional digital services. More recently the Jisc Accessible Digital Futures project has highlighted the opportunities created by emerging digital and AI technologies when accessibility is considered early in design and procurement.

These developments signal an important shift. Accessibility is no longer treated solely as a matter of compliance or accommodation. Instead it is increasingly recognised as part of the digital infrastructure that supports teaching, research, and student experience. Yet despite this growing awareness, accessibility failures remain common across higher education systems. Students still encounter inaccessible learning platforms, course materials that cannot be used with assistive technologies, and institutional processes that place the burden of adaptation on disabled individuals.

This persistence of barriers suggests that the problem is not simply one of awareness or policy guidance. Rather, accessibility failures often arise from the way institutions adopt and govern digital technologies. To understand why the problem continues even where intentions are good, it is useful to think in terms of accessibility debt.

Accessibility debt in higher education systems

Accessibility debt accumulates when digital systems are adopted without accessibility being fully considered from the outset. Like technical debt in software development, the consequences may not be immediately visible. Platforms may appear to function adequately until disabled students begin to rely on them at scale. At that point the cost of remediation becomes significant, requiring workarounds, retrofitting, or labour-intensive accommodations.

Universities are particularly susceptible to this problem because their digital environments are complex and layered. Institutional technology ecosystems typically include learning management systems, student portals, library platforms, assessment tools, lecture capture technologies, and a growing number of AI enabled services. Many of these systems are supplied by external vendors and integrated with one another over time.

Even when individual platforms claim compliance with standards such as WCAG 2.2 AA, accessibility problems can emerge through the interaction between systems. A student may navigate successfully through one platform only to encounter barriers when moving to another tool that forms part of the same learning environment. Over time these problems accumulate as institutions add new tools without addressing existing accessibility limitations.

How institutions create accessibility debt

Procurement and governance decisions are central to the accumulation of accessibility debt. In principle, accessibility requirements can be evaluated during vendor selection. In practice this process is often difficult. Suppliers may provide incomplete or ambiguous accessibility documentation, and institutional buyers may lack the expertise needed to interpret those claims.

The Accessible Digital Futures project identified procurement as a major challenge for the UK higher education sector. Universities frequently struggle to obtain reliable information about whether digital and AI powered products meet accessibility standards. Even when accessibility statements are available, they may not reflect how the system performs in real institutional contexts.

Institutional governance structures add another layer of complexity. Universities are typically decentralised organisations where digital decisions are made in multiple places. Academic departments adopt specialised teaching tools. Administrative units introduce new platforms to manage services. Individual instructors experiment with emerging technologies. Each decision may appear limited in scope, but collectively they shape the accessibility of the institutional digital environment.

Under these conditions accessibility responsibility can become fragmented. Policies may exist at the institutional level, yet practical decisions about technology adoption occur across many different teams. Without clear governance and accountability, accessibility considerations are often introduced late in the process rather than guiding decisions from the beginning.

Why retrofitting accessibility rarely works

When accessibility barriers become visible, institutions often respond by attempting to retrofit accessibility into existing systems. This approach is understandable but rarely efficient. By the time problems are identified, platforms may already be embedded in teaching and administrative processes.

The scale of institutional digital infrastructure makes remediation difficult. Learning management systems may contain thousands of courses with legacy materials. Institutional websites can consist of hundreds of thousands of pages. Third party platforms may require vendor cooperation to address technical barriers. Even well-resourced remediation efforts can take years to complete.

In the meantime new technologies continue to be introduced. Emerging tools such as generative AI, immersive learning environments, and advanced analytics systems offer significant potential benefits. The Jisc project highlights how these technologies could support more inclusive forms of digital learning if accessibility is considered early. However the same technologies may create new barriers if institutions repeat existing patterns of procurement and governance.

The result is a cycle in which accessibility problems are repeatedly addressed after the fact rather than prevented through earlier decision making.

What structural change would look like

Reducing accessibility debt requires institutions to treat accessibility as a governance issue rather than a purely technical one. Responsibility cannot sit solely with disability services or specialist accessibility teams. Decisions about procurement, platform adoption, and digital strategy shape the accessibility of the entire institutional environment.

Procurement practices are one important lever. Universities need clearer processes for evaluating vendor accessibility claims and stronger expectations that suppliers provide reliable documentation. The European Accessibility Act having recently gone into force may increase pressure on technology providers to meet accessibility standards, but institutional buyers will still need the expertise and governance structures necessary to interpret those requirements.

Accessibility expertise must also be integrated earlier in institutional decision making. Too often accessibility specialists are consulted only after technology has already been selected. Involving accessibility expertise during planning and procurement can significantly reduce the need for costly remediation later.

Finally, institutions must recognise the cumulative nature of accessibility debt. Addressing individual barriers is necessary but not sufficient. Progress depends on examining the institutional systems that produce those barriers in the first place.

The higher education sector is currently undergoing rapid technological transformation. Digital platforms and AI driven tools are reshaping how universities teach, assess, and support students. Initiatives such as Accessible Digital Futures rightly emphasise the opportunity to ensure these changes produce more inclusive educational environments.

Whether that opportunity is realised will depend less on technological capability than on institutional governance. Accessibility failures rarely arise from a single decision. They emerge gradually as accessibility debt accumulates across procurement choices, platform ecosystems, and fragmented responsibility. Recognising and addressing that structural dynamic may be one of the most important steps universities can take toward genuinely accessible digital futures.

Kevin Andrews is a Certified Web Accessibility Specialist working at the intersection of digital accessibility, technology governance, and higher education systems. His work focuses on how institutional technology decisions shape accessibility outcomes for disabled students and staff. He brings both professional expertise and lived experience of disability to his work on accessible digital infrastructure.  


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The missing middle ground between research-led and practice-led education

by Saeed Talebi and Nick Morton

A peer reviewer recently challenged our pedagogical approach. We had described embedding an industry-led research project on Digital Twin development into our built environment curriculum as ‘research-informed teaching’. The reviewer disagreed: this was ‘practice-led rather than research-informed,’ they argued, because students weren’t producing research outputs themselves.

The comment revealed a conceptual confusion we suspect is widespread in higher education. We often assume that if students aren’t producing original research, then any industry-focused teaching must simply be vocational training with academic window-dressing. This leaves practice-facing disciplines in an awkward position: industry engagement is essential to what we do, but it risks being dismissed as less scholarly. There is, however, a middle ground.

Healey and Jenkins’ (2009) model offers a useful way through this confusion. They identify four modes of engaging undergraduates with research: research-led (learning about current scholarship), research-oriented (learning research methods), research-based (undertaking inquiry), and research-tutored (engaging in research discussions). These are mapped across two dimensions: whether students are positioned as audience or participants, and whether the emphasis falls on research content or processes. The model’s key insight is that students can be meaningfully engaged with research even when they aren’t producing research outputs themselves. The question isn’t simply whether students are ‘doing research’, it’s whether they’re positioned as passive recipients of established knowledge or as active participants in scholarly inquiry.

Practice-led teaching operates on different logic, though that logic has a closer relationship to applied research than is sometimes acknowledged. Its primary aim is developing professional competence through authentic engagement with messy problems and competing stakeholder priorities. The distinction isn’t whether industry is involved – it can be present in both approaches. The distinction lies in how students are positioned in relation to knowledge. In practice-led education, knowledge tends to be treated as relatively settled. In research-informed education, knowledge is contested, evolving, and open to question. An opportunity arises when these approaches coincide without conscious design, and a risk emerges when they collapse into one another. Research-informed teaching can become performative, referencing staff publications without changing how students learn. Practice-led teaching can slip into employability theatre, where live briefs are added without interrogating what knowledge students are actually developing.

As Professor Hanifa Shah OBE recently argued in Times Higher Education, STEAM education at its best equips students to “move fluidly between analytical and imaginative modes of thinking“, asking critical questions, considering ethical implications, and bringing meaning to innovation. This is precisely the disposition that research-informed teaching seeks to develop. In STEAM disciplines, including architecture, built environment, computing and engineering, emerging technologies create spaces where research and practice intersect meaningfully. Digital Twins and real-time monitoring tools, for example, allow students to work with live systems while engaging critically with the assumptions and ethics embedded within them. Students aren’t merely applying research after the fact, nor mimicking professional routines. They’re learning to question how data is generated, how models simplify reality, and how decisions are shaped by both evidence and judgement. Practice becomes a site of inquiry.

There’s an institutional dimension here too. Across the sector, promotion frameworks, workload models, and teaching quality metrics often reward research visibility and industry engagement without asking how either is translated pedagogically. Academics are encouraged to ‘bring research into teaching’ and ‘embed employability’, yet rarely supported in doing the difficult design work that meaningful integration requires. Recent discussions within the sector have highlighted how delivery models shape the possibilities for integrating academic and workplace learning. These are sector-wide conversations, and they reflect shared challenges around diverse learner cohorts, blended delivery, and the risk of compliance overtaking genuine learning. As a result, many innovative practices remain dependent on individual effort rather than structural support.

None of this means practice-led and research-informed approaches are mutually exclusive. The most effective curricula often blend elements of both. But blending deliberately is quite different from conflating accidentally.

When designing industry-engaged teaching, it’s worth asking honest questions. Are students positioned as inquirers or executors? Are they engaging with contested knowledge or settled practice? Does assessment reward critical reflection or merely competent performance? Is the industry project a vehicle for scholarly inquiry, or is scholarly framing a veneer over vocational training?

The answers won’t always be clear-cut, and that’s fine. But asking the questions helps us design with intention rather than stumbling into confusion – and helps us articulate what we’re doing when a peer reviewer, a sceptical colleague, or a university committee asks us to justify our approach.

Dr Saeed Talebi is an Associate Professor in the Department of Architecture and Built Environment at Birmingham City University and a Senior Fellow of the Higher Education Academy (SFHEA). He has held a number of T&L leadership roles, including Departmental Lead, Course Leader, and Academic Lead for Teaching Excellence and Student Experience. He has a keen interest in pedagogy in higher education, with particular interest in research-informed teaching and the integration of emerging technologies and practice-led projects into built environment curricula to enhance student outcomes and experience. He has also led the delivery of large STEAM research projects.

Professor Nick Morton is the Academic Director of Partnerships and STEAM at Birmingham City University. A Principal Fellow of the Higher Education Academy (PFHEA), he was awarded a National Teaching Fellowship in recognition of his track record in curriculum development. He has held a number of senior leadership roles at BCU, including Associate Dean for Teaching Education and Student Experience, overseeing Computing, Engineering and the Built Environment. He was elected Vice-Chair of the Council of Heads of the Built Environment (CHOBE) in 2012 and is a Fellow of the Royal Institution of Chartered Surveyors (FRICS).


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Reconceptualising transnational education through decolonial approaches

by Nilakshi Das

Transnational Education (TNE) represents a rapidly expanding form of cross-border provision, underpinned by an economic imaginary that positions the UK as a ‘key player’ in the global higher education market. While earlier internationalisation strategies focused primarily on bringing overseas students to Britain, TNE reflects a shift towards delivering British higher education to students globally through offshore provisions. The rapid expansion of TNE has elicited growing academic debate about its potential to reproduce the political, economic and epistemic hegemony of the Global North, reinscribing earlier colonial hierarchies and patterns of dependency.

Before the emergence of TNE, the internationalisation of UK higher education was primarily organised through the academic mobility of overseas students, shaped by Britain’s imperial and post-imperial educational networks. During the 1960s, technical assistance programmes and scholarship schemes, such as the Commonwealth Scholarship programme, facilitated student mobility to British universities. In the 1970s, as overseas student numbers gradually increased, differential student fees were introduced alongside tightening immigration regulations, a shift that continued throughout the Thatcher government in the 1980s into the present day. By the late 1990s, the University of Nottingham had established one of the earliest overseas branches, with the general idea that the curriculum in the host country would largely mirror the home institution. From the 2000s onwards, TNE expanded in scope and provision through franchised programmes, joint and dual degrees, distance and online courses in new markets, particularly across the Middle East and Asia. These arrangements allowed UK universities to expand their global presence and competitiveness beyond traditional overseas student recruitment.

Political economy of TNE and latest policy ambitions

The latest articulation of TNE goals includes the Labour government’s new strategy for national renewal by ‘turbocharging education’ as an engine for economic growth, with a target of £40 billion in education exports by 2030. This decision reflects increasing political pressure to cut net migration by reducing overseas student recruitment. Recent policy recommendations have radically argued that universities should be ‘selling education, not immigration’, with growing concerns that student visas are being used as a backdoor route into the UK labour market. Against broader anxieties around immigration in which international students are repositioned as migration liabilities, TNE offers a politically viable solution by exporting education in favour of substituting inward student mobility. As universities’ budgets shrink due to ongoing visa restrictions for international students, TNE engagements are expected to further increase (Hartmann and Lee, 2026).

According to the latest data, the number of students studying entirely overseas through UK TNE increased by 8% in 2024/25, and has risen by 37% since 2020/21. TNE student numbers are now close to the number of international students studying in the UK, with approximately one in six students in UK HE being educated across overseas campuses. Yet, despite this rapid growth, there is a lack of public data on student experiences at TNE. While aggregate data records the number of students enrolled in TNE programmes and level of education, there is limited publicly available information on student progression, degree outcome and labour market prospects. The experiences of students and educators involved in these programmes often tend to remain marginal within UK policy debates.

As higher education increasingly operates through a ‘big business’ model, institutional priorities have rapidly shifted towards generating revenue and maintaining competitiveness. In doing so,commitments to uphold student welfare, equality, and meaningful international collaboration are often sidelined in favour of positional advantage. Therefore, the expansion of TNE under growing market competition raises further pressing questions about equity and power within global HE systems.

Towards a decolonial approach to TNE

Most of the latest policy and institutional analyses of TNE tend to adopt an instrumentalist perspective focusing on business indicators, such as risk assessment, return on investment, international branding and reputation, quality assurance and transnational management strategies. As a result, TNE is mainly understood through frameworks of foreign investment and transnational service delivery further entrenching the logic of the market that frames education as a tradable commodity rather than a global public good (Lauren Clarke, 2021). While these considerations are important for universities operating in a competitive global environment, they risk overshadowing broader questions about equity, inclusion and the social purposes of higher education.

Adopting a decolonial approach to TNE can help address questions around embedding Western systems and structures of education in the Global South. Debates around the coloniality of TNE are not entirely new. Some scholars have drawn parallels between contemporary TNE arrangements and colonial models of education between the 16th and the 19th centuries. Colonial education systems were often characterised by limited access for the local population, a lack of relevance to local realities, the marginalisation of indigenous knowledge systems, the exclusive use of English as the primary medium of instruction, institutional authority with control originating from colonial centres and limited curricula featuring vocational degrees (Teferra and Altbach, 2004). TNE arrangements have been articulated as operating through a similar binary model in which a ‘core’ of sending institutions from the West sets the agenda for a marginalised ‘periphery’ of receiving partners, perpetuating historical legacies of colonialism (Caruana and Montgomery, 2015).

Against this background, there are growing calls for more introspective approaches to TNE that challenge post-colonial structures of dependence and compliance, while remaining attentive to the risk that transnational partnerships may reproduce these hierarchies through networks of alliance with local elites in host countries. Ravindra Sidhu advocates an ‘engaged pedagogy’ and an ‘ethics of care’ in the design and governance of TNE partnerships, emphasising the need to recognise the histories, aspirations and agency of local communities involved in these programmes.

Drawing insights from postcolonial and decolonial scholarship that emphasise justice, inclusion and agency will enable TNE strategies to better examine their implications on student success, outcomes and experiences as well as their wider impact on local communities and higher education systems in host countries. At the same time, greater attention to the national and cultural contexts in which TNE operates, particularly where differing political and institutional norms raise ethical challenges around academic freedom, governance and accountability, can support more informed institutional decision-making and partnerships. These perspectives will ensure that the expansion of TNE is not guided by short-term commercial imperatives but by broader commitments to equity and responsible global engagement, avoiding polarised strategic approaches (Sanderson, 2023).

Nilakshi Das has recently completed her PhD in History of Science. Her PhD was funded by the ESRC and jointly undertaken at the University of Leicester and the University of Warwick. Nilakshi holds an MSc in Education from the University of Oxford and an MA in Sociology from the University of Manchester, funded by a Commonwealth Scholarship. She is a Fellow of the Institute for Historical Research.


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Inclusion without structural change: what neurodiverse academics tell us about inequality in higher education

by Eleni Meletiadou

The blog is based on the recent outputs from our COST ACTION CA20137 VOICES project entitled: ‘Lived Experiences of Neurodiverse Academics and Early Career Researchers in Higher Education: Identifying Structural Barriers and Pathways to Inclusion.’

Introduction

Higher education institutions across Europe increasingly emphasise equality, diversity, and inclusion, yet neurodiversity remains unevenly addressed within academic career structures. While universities have developed policies to support disabled and neurodiverse students, far less attention has been given to the experiences of neurodiverse academics, particularly early-career researchers and women. As a result, inclusion is often framed as an issue of individual adjustment rather than institutional design.

This blog presents findings from a qualitative survey conducted as part of the work of the VOICES COST Action, which examines inequalities affecting Young Researchers and Innovators (YRIs) from a gender perspective and promotes dialogue between researchers, institutions, and policy-makers across the European research ecosystem. The project explored the lived experiences of neurodiverse academics in higher education to identify structural barriers and inform policy and practice.

The findings suggest that, despite the growing visibility of neurodiversity, academic systems continue to be shaped by narrow assumptions about productivity, communication, and career progression. These assumptions can disadvantage those whose cognitive styles or working patterns do not align with dominant norms, particularly in contexts characterised by high workload, precarity, and informal career expectations.

Academic norms and the persistence of the ‘ideal worker’ model

Participants in the survey frequently described academic work as governed by implicit norms rather than transparent criteria. Expectations related to teaching, research, administration, and collegiality were often perceived as unclear, variable, and dependent on departmental culture.

Previous research has shown that academic environments tend to reward constant productivity, long working hours, and high levels of self-management, reflecting what has been described as the ‘ideal worker’ model. These expectations can create difficulties for academics whose cognitive styles involve fluctuating concentration, sensory sensitivity, or the need for predictable routines.

Respondents highlighted challenges associated with unpredictable workloads, competing deadlines, and the pressure to remain constantly available. Conferences, meetings, and networking events were also described as demanding environments, particularly when participation required rapid communication, multitasking, or tolerance of sensory overload.

Such findings indicate that the difficulties experienced by neurodiverse academics are not simply individual challenges but are closely linked to the way academic work is organised. Consistent with the objectives of the VOICES COST Action, inequalities affecting early career researchers often arise from structural features of the research environment rather than from personal limitations.

Intersectional inequalities: neurodiversity, gender, and career stage

The survey also revealed that neurodiversity intersects with gender and career stage in ways that intensify disadvantage. Early career researchers on temporary or part-time contracts reported reluctance to disclose neurodivergence or request adjustments due to concerns about job security and professional reputation.

These findings align with existing research showing that precarious employment conditions are common in early academic careers and can discourage individuals from seeking support. When career progression depends on short-term contracts, publication output, and informal recommendations, academics may feel pressure to conform to existing expectations even when these expectations are difficult to meet.

Female participants described additional pressures related to expectations of organisation, emotional labour, and collegial behaviour, which have been widely documented in studies of gender inequality in academia. These expectations were perceived as particularly demanding in environments where workloads are high and institutional support is limited.

From the perspective of the VOICES COST Action, such findings highlight the importance of examining inequalities through an intersectional lens. Neurodiversity does not operate in isolation but interacts with gender, career stage, and employment conditions to shape academic experiences.

Inclusion policies and the gap between commitment and practice

Most respondents reported that their institutions had formal equality, diversity, and inclusion strategies. However, the implementation of these policies was often described as inconsistent. Support frequently depended on individual supervisors, line managers, or departmental cultures rather than on clear institutional procedures.

Participants noted that adjustments were typically provided only after formal disclosure, placing responsibility on individuals to identify their needs and request support. This approach can be particularly challenging for neurodiverse academics, for whom disclosure may involve perceived professional risks.

Research on disability and inclusion in higher education has shown that institutional responses often focus on individual accommodations rather than structural change. While accommodations are important, they do not address the underlying assumptions about productivity, communication, and career progression that shape academic work. The findings of this study suggest that inclusion policies may have a limited impact if they are not accompanied by changes to workload models, evaluation criteria, and organisational culture.

Implications for policy and institutional practice

The qualitative data point to several areas where institutional policy could better support neurodiverse academics and early career researchers.

Greater transparency in workload and progression criteria

Clear expectations regarding teaching, research, and administrative responsibilities can reduce uncertainty and support fairer evaluation. When criteria are implicit, those who struggle with informal norms may be disadvantaged.

Flexible and predictable working practices

Flexible deadlines, structured communication, and predictable scheduling can support a wider range of working styles without lowering academic standards. Such measures may benefit many staff, not only those who identify as neurodivergent.

Training for academic leaders

Supervisors, heads of department, and line managers play a key role in implementing inclusion policies. Training that increases understanding of neurodiversity can help ensure that support is applied consistently and fairly.

Mentoring and peer support networks

Structured mentoring programmes can reduce isolation, particularly for early-career researchers and women. Informal support networks were frequently described by participants as essential for coping with the demands of academic work.

Dialogue beyond the institutional level

In line with the aims of the VOICES COST Action, improving inclusion requires discussion not only within universities but also at national and European policy levels. Research evaluation frameworks, funding structures, and career pathways all shape the conditions in which academics work and therefore influence who is able to succeed.

Towards more inclusive research environments

The findings presented here indicate that neurodiversity in higher education continues to be addressed primarily through individual adjustments rather than structural reform. Academic career systems remain shaped by implicit norms that privilege particular working styles and disadvantage those who do not conform to them.

If universities are to meet their commitments to equality, diversity, and inclusion, neurodiversity must be considered within broader discussions of precarity, gender inequality, and the sustainability of academic careers. Creating more inclusive environments requires not only support for individuals but also critical reflection on the assumptions that underpin academic work.

As initiatives such as the VOICES COST Action emphasise, meaningful change depends on sustained dialogue between researchers, institutions, and policy-makers. Without such dialogue, there is a risk that inclusion will remain a policy aspiration rather than an everyday reality.

Higher education has the opportunity to move beyond reactive accommodations towards more inclusive structures. Doing so is not only a matter of fairness but also essential for retaining talented researchers whose contributions may otherwise be lost to systems that remain insufficiently flexible to support diverse ways of thinking and working.

Dr Eleni Meletiadou is Associate Professor (Teaching) at London Metropolitan University and a Principal Fellow of the Higher Education Academy. Her research focuses on equity, diversity, and inclusion in higher education, with particular emphasis on neurodiversity, gender equality, digital pedagogy, and education for sustainable development. She leads the Research Group on Inclusive Learning, Transnational Education and Academic Sustainability (RILEAS) and the Gender Equity, Diversity, and Inclusion (GEDI) Research Group. Her work has been recognised with the British Academy of Management Education Practice Award (2023) and includes several European and international projects on inclusive assessment, AI in higher education, and widening participation. She is an active member of COST Actions examining inequalities in the research ecosystem and the impact of digital transformation on higher education. Her research interests include organisational change in universities, inclusive curriculum design, early career researcher development, and socially just approaches to teaching and learning.

LinkedIn: https://www.linkedin.com/in/dr-eleni-meletiadou/


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Judgement under pressure: generative AI and the emotional labour of learning

by Joanne Irving-Walton

What AI absorbs and why that matters

Most debates about generative AI in higher education fixate on what it produces: essays, summaries, answers, paraphrases. I find myself increasingly interested in something else – what it absorbs. Over the past year, as conversations about AI have threaded through seminars and tutorials, a pattern has gradually become visible. In those discussions, students rarely begin with content production; instead, they talk about how it helps them get started and steadies them enough to keep going. They use it when the blank page paralyses, when feedback stings and when uncertainty feels exposing. One student described asking AI to “make it feel possible”. Another spoke of feeding tutor comments into the system so they could be “explained more kindly”. A third reflected, almost apologetically, “I don’t want it to do my work… I just need something to push against before I say it out loud and risk looking stupid”.

In each case, AI is not replacing thinking. It is absorbing part of the emotional labour involved in it, and as that labour is redistributed, the texture of judgement shifts. Academic judgement does not tend to emerge from comfort. It develops in the stretch between knowing and not knowing, when confidence dips, stakes feel heightened, and your sense of competence is quietly tested (Barnett, 2007). Staying in that stretch long enough for thinking to clarify demands more than intellectual effort; it requires emotional steadiness, time, space and the capacity to tolerate uncertainty without rushing to resolution (Biesta, 2013). Traditionally, that steadying work has been shared across learning relationships: tutors reframing feedback, peers normalising confusion, supervisors encouraging persistence through doubt. Generative AI now occupies part of that terrain.

I do not think this is inherently a problem. For some students, it is transformative. It marks a shift in where the labour of learning takes place and that change deserves examination rather than alarm.

Four modes of engagement and emotional labour

When students talk about how they use AI, their practices tend to cluster into four overlapping orientations. These are not moral categories so much as shifts in where emotional and cognitive labour is undertaken.

Instrumental engagement appears when students use AI to summarise readings, refine phrasing or impose structure. Here the friction lies in form-making and shaping thought into something communicable. The judgement at stake is procedural: what is proportionate or efficient in this context?

Dialogic engagement emerges when students test interpretations or rehearse arguments. AI becomes a low-stakes sounding board, absorbing some of the vulnerability of articulating something half-formed. The question beneath it is interpretive: what does this mean, and how far do I trust my reading and myself?

Metacognitive engagement is evident when students ask AI to critique their reasoning or compare approaches. What is absorbed here is evaluative tension and the discomfort of examining one’s own argument. The judgement in play is comparative and strategic: which option is stronger, and why? And then there is affective-regulatory engagement. Here, AI absorbs the anxiety that precedes judgement itself. It breaks tasks into steps, softens feedback, lowers the threshold for beginning, offers reassurance before submission and quietens the internal ruminations and rehearsals of everything that might go wrong. This is not peripheral to learning. It is increasingly central.

Figure: Where the labour of learning now lives

Accessibility, safety and the risk of smoothing too much

For many students, particularly those navigating anxiety, executive dysfunction, neurodivergence or heavy external commitments, this emotional buffering is not indulgence but access (Rose & Meyer, 2002). Breaking tasks into steps or privately rehearsing ideas before speaking can widen participation rather than diminish it.

We should not romanticise struggle. Nor should we imagine that institutional structures have ever been able to hold every student perfectly. For some learners, AI offers another place to rehearse thinking, one that sits alongside, rather than replaces, human dialogue.

But there is a tension here. If AI consistently absorbs the strain of uncertainty before ideas encounter resistance, if feedback is softened before it unsettles, if structure replaces the slow work of wrestling thought into form, then something quieter begins to shift. Much of this work happens privately, in browser tabs and late-night prompts, in spaces students do not always feel comfortable admitting to. That makes it harder for us to see what is being strengthened and what may be thinning. The danger is not comfort, but the quiet disappearance of formative strain.

By formative strain, I do not mean suffering for its own sake, nor simply the “desirable difficulties” described in cognitive load theory (Bjork & Bjork, 2011) or the stretching associated with a Vygotskian zone of proximal development (Vygotsky, 1978). I am referring to the lived experience of remaining with ambiguity, critique and partial understanding long enough for judgement to consolidate; the emotional as well as cognitive work of staying with a problem. If that work is always pre-processed, it may narrow the rehearsal space where judgement forms.

Scaffold or substitute

Much depends on whether AI remains a scaffold or begins to function as a substitute. Used as scaffold, it lowers the emotional threshold just enough for deeper engagement, absorbing anxiety without displacing judgement. Used as substitute, it reduces not only strain but evaluation itself; the work of deciding and committing shifts elsewhere. The distinction lies less in the tool than in how it is woven into the learning environment.

Individual awareness and institutional responsibility

It would be easy, and unfair, to frame this as a matter of individual discernment. Students already carry a great deal. But nor is this simply a matter of institutional correction. We are all navigating new terrain in real time, without a settled script.

If we are serious about judgement formation, then responsibility is shared — and it is evolving. This is less about detection or prohibition than about openness. AI engagement is happening whether we discuss it or not. The question is whether we bring it into the light. That might mean inviting students to reflect on how they used AI in a task, not as confession, but as analysis. It might mean modelling, in our own teaching, what it looks like to question or refine an AI response rather than accept it wholesale. It certainly means acknowledging the emotional labour of learning openly (Newton, 2014), recognising that starting can be harder than finishing and that this, too, is part of learning.

At a structural level, we also need some candour. Systems built on speed, metrics and visible output inevitably amplify the appeal of friction-reducing tools. If polish is rewarded more consistently than process, we should not be surprised when students bypass the stretch between uncertainty and articulation. Cultivating discernment, then, is not a matter of allocating blame. It is a collective project of making the shifting terrain of AI use visible, discussable and educative.

Where the emotional work now lives

Generative AI has not diminished the importance of human judgement. If anything, it has made visible how emotionally mediated that judgement has always been (Immordino-Yang & Damasio, 2007). The interior work of learning – the hesitation, the rehearsal, the private negotiation of uncertainty – has never been fully observable. It has always unfolded, at least in part, elsewhere.

What AI changes is not the existence of that interior space, but its texture. Some of that labour now takes place in dialogue with a system that can stabilise, extend or subtly redirect thinking. That creates an opportunity: we are at a juncture where the emotional dimensions of learning can be surfaced and examined more deliberately than before.

It also carries risk. Students can disappear down an AI rabbit hole just as easily as they once disappeared into rumination. The question is not whether the interior work exists, but how it is shaped and whether it ultimately strengthens judgement or thins it.

References

Barnett, R (2007) A will to learn: Being a student in an age of uncertainty Open University Press

Biesta, GJJ (2013) The beautiful risk of education Paradigm Publishers

Bjork, EL & Bjork, RA (2011) ‘Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning’ in MA Gernsbacher, RW Pew, LM Hough & JR Pomerantz (eds), Psychology and the real world: Essays illustrating fundamental contributions to society (pp. 56–64) Worth Publishers

Newton, DP (2014) Thinking with feeling: Fostering productive thought in the classroom Routledge

Vygotsky, LS (1978) Mind in society: the development of higher psychological processes Harvard University Press Rose, DH & Meyer, A (2002) Teaching every student in the digital age: universal design for learning ASCD

Joanne Irving-Walton is a Principal Lecturer at Teesside University, working across learning and teaching and international partnerships. She is particularly interested in how academic judgement and professional identity develop through the emotional realities of higher education.


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Preparing the Future Leaders of Society with a Systems Thinking Mindset Through Effective Learning and Teaching

by Amrik Singh and Joy Garfield

In a world defined by rapid change, complexity, and interdependence, traditional linear ways of thinking are struggling to keep up. Whether we look at global supply chains, climate challenges, digital transformation, or organizational culture, a recurring truth emerges, everything is connected. This is why systems thinking,a mindset for understanding wholes rather than isolated parts, is becoming increasingly relevant across all sectors (Comstock, 2024). Systems thinking allows us to understand the perspective of multiple stakeholders in the situation and guards against jumping to the right solution, which human nature sometimes make us do. When we understand the notion that problems are multi-faceted and need the buy-in of multiple stakeholders to address the solutions, only then we can really unearth the understanding of complexity and ambiguity of the situation. Higher education students as future leaders of society, need to grasp the concept of systems thinking to explore the complexity and ambiguity of modern-day problems.

Understanding the Complexity of Modern Problems

For much of the 20th century, we operated on the assumption that problems could be broken down and solved independently. Problems and solutions were easily connected. But today’s challenges are mostly complex, dynamic, and interconnected, making reductionist approaches insufficient (Eftekhari Shahroudi et al., 2025).

A decision made in one area can unintentionally trigger effects in others. Without a systemic lens, those secondary impacts are missed until they become major problems. Dynamic conditions change faster than linear plans can keep up. Because challenges evolve through shifting interactions like climate events affecting energy markets, or geopolitical shifts affecting food systems a static, linear approach fails. A systemic perspective helps leaders adapt in real time. Climate change, digital transformation, public health, and security issues span sectors, borders, and disciplines. No single stakeholder can solve them alone; systems thinking helps identify leverage points for multi‑stakeholder actions.

Modern organisations function as complex adaptive systems shaped by culture, relationships, and information flows. Linear change models often fail because they ignore these interdependencies; systems thinking helps leaders identify leverage points, anticipate consequences, and design resilient structures (Ellis, 2024). Systems thinking literature alike argues that traditional problem‑solving methods lose effectiveness as societal and technological complexity grows, strengthening the case for dynamic, holistic approaches in organisational decision‑making (Eftekhari Shahroudi et al., 2025).

A Harvard Business Review article states that innovations often create unintended ripple effects because interactions across systems are overlooked reinforcing the need for a systemic perspective (Bansal and Birkinshaw, 2025). Problems have multiple interacting causes, not a single root. Reductionist thinking focuses on one cause at a time, but modern challenges involve overlapping drivers, environmental, economic, technological, political, and social. Addressing only one strand often creates new issues elsewhere. The demand for systems thinking based pedagogical higher education is thus very real and requires educators to embrace these methods of teaching and learning.

How Can Education and Learning Shift Toward Systems Thinking Literacy

As future leaders in an increasingly complex and demanding world, higher education students need a solid understanding of social, political, economic, and environmental issues, along with the confidence to propose well‑reasoned solutions. Systems thinking is increasingly recognised as a vital pedagogical approach in higher education, enabling learners to understand complexity, interdependence, and uncertainty within contemporary societal and organisational challenges.

As educators prepare students for an uncertain future, systems thinking literacy is emerging as a core skill. The future of jobs report (World Economic Forum, 2025) indicates that systems thinking, and empathy are very essential core skills needed by organisations. Case studies from engineering and technology education further illustrate the value of systems thinking pedagogy. Dhukaram et al. (2016) show how systems-oriented curricula enhance student capability in diagnosing multifaceted problems, fostering collaborative solution-building, and developing resilience in decision-making processes. These studies collectively highlight that systems thinking not only enhances subject-specific learning but also strengthens transferable skills such as critical reasoning, communication, and adaptive expertise, all very relevant to organisations as cited in the future of jobs report 2025.

Systems thinking pedagogy also allows students to dive into the complexity and ambiguity of modern-day challenges and allows them to understand the multiple stakeholder perspectives and worldviews. Only then can a rich picture of the problem can be ascertained. Studying relationships, patterns, and structures fosters deeper understanding than memorising isolated facts or writing notes of the situation alone. Frameworks such as Soft Systems Methodology (Checkland and Poulter, 2006) enhance critical thinking and decision‑making from multiple perspectives. Sustainability education literature also stresses that complex global issues require integrative thinking, interdisciplinary collaboration, and shared sense‑making, the central tenets of systems thinking (Ezeaku, 2024).

Soft Systems Methodology, although not new, has proven effective across a wide range of settings for tackling complex modern-day problems. Its seven-stage process offers a structured approach to exploring “wicked” issues by first examining what is happening in the real world from the viewpoints of various stakeholders. The methodology then moves to imagining an ideal world, one free from constraints, from multiple stakeholder perspectives, helping to surface differing expectations, needs, and aspirations for a future idealised system. Students should be encouraged to use empathetic dialogue to appreciate the diverse viewpoints present in the situation. By comparing real-world conditions with these idealised models, Soft Systems Methodology enables the development of feasible, mutually acceptable paths forward.

Recent scholarship highlights that real-world, experiential learning environments help students develop the ability to interpret dynamic systems and identify leverage points for meaningful change (Alford et al., 2025). Such approaches support a shift from linear, fragmented learning toward holistic understanding, enabling students to explore the multiple interacting forces shaping modern problems. Soft Systems Methodology can help develop this understanding.

The importance of systems thinking in higher education is also evident in efforts to prepare students for professional environments characterised by complexity and rapid change. As Elsawah, Ho, and Ryan (2022) note, teaching systems thinking requires intentional integration of modelling, reflection, and interdisciplinary engagement to help students internalise systemic concepts. Their work demonstrates that learners benefit from iterative exploration of system behaviours, reinforcing deeper conceptual understanding and long-term retention.

A Mindset for the 21st Century

Across disciplines, systems thinking offers a transformative framework for higher education, supporting educators and students in jointly navigating complex realities while fostering the next generation of holistic, strategic, and future-oriented thinkers.

At its core, systems thinking is more than a method, it is a mindset that promotes deeper insight, anticipatory understanding, and long‑term thinking. Scholars and practitioners argue it is essential for addressing intertwined challenges like climate disruption, social inequality, and technological acceleration (DigitalVital HUB, 2025). By helping individuals and organisations recognise interconnected structures, systems thinking supports more informed, sustainable, and strategic action, shifting us from short‑term fixes to long‑term solutions rooted in an understanding of whole systems (Ellis, 2024).

The combination of Soft Systems Methodology and empathy enhances systems thinking by placing equal emphasis on the human elements and the technical components. It focuses on designing solutions that function not only in theory but also in the complex, unpredictable realities of human‑centred environments. Engaging in empathetic dialogue helps reveal stakeholders’ perspectives and experiences. When problems are rooted in human complexity and ambiguity, the solutions must be human centric also.

We live in an era defined by complexity and constant change. Linear thinking on its own is no longer enough. Systems thinking offers powerful tools for higher education students to see the bigger picture, understanding interconnections, and designing solutions that work not just today, but for generations ahead. As future leaders of society this is a vital commodity that cannot be overlooked. Across sustainability, technology, education, and organisational practice, the evidence converges: systems thinking is shifting from a possibility to a must‑have capability for future leaders (Bansal and Birkinshaw, 2025; Schoormann et al., 2025).

References.

Alford, K.R., Stedman, N.L.P., Bunch, J., Baker, S. and Roberts, T.G. (2025) ‘Real-world experiences in higher education: contributing to developing a systems thinking paradigm’, Journal of Experiential Education, 48(1), pp. 169–188.

Bansal, T. and Birkinshaw, J. (2025) ‘Why you need systems thinking now’, Harvard Business Review, September–October.

Checkland, P. and Poulter, J. (2006) Learning for action: A short definitive account of Soft Systems Methodology and its use for practitioners, teachers and students. Hoboken: Wiley.

Comstock, N.W. (2024) ‘Systems thinking’, EBSCO Research Starters.

Dhukaram, A., Sgouropoulou, C., Feldman, G. and Amini, A. (2016) ‘Higher education provision using systems thinking approach – case studies’, European Journal of Engineering Education, 43, pp. 1–23.

DigitalVital HUB (2025) ‘Systems thinking in innovation design and sustainability: Critical framework for seeing the whole’, 21 March.

Eftekhari Shahroudi, K., Conrad, S., Speece, J., Reinholtz, K., Span, M.T., Chappell, S., Saulter, Q. and Bokhtier, G.M. (2025) ‘Why systems thinking?’, in Practical Systems Thinking. Cham: Springer.

Ellis, J. (2024) ‘Unlocking complex problems: the power of systems thinking’, TheSystemsThinking.com, 30 September.

Elsawah, S., Ho, A. and Ryan, M. (2022) ‘Teaching systems thinking in higher education’, INFORMS Transactions on Education, 22, pp. 66–102.

Ezeaku, E.C. (2024) ‘Systems thinking as a paradigm shift for transformational sustainability’, Global Scientific Journal, 12(1).

Schoormann, T., Möller, F., Hoppe, C. and vom Brocke, J. (2025) ‘Digital sustainability: understanding and managing tensions’, Business & Information Systems Engineering, 67, pp. 429–438.

World Economic Forum (2025) The Future of Jobs Report 2025.

Dr Amrik Singh is a Senior Teaching Fellow at Aston University, UK. He has over 15 years of academic experience in Higher Education. He is also a Senior Fellow of the Advance HE, SFHEA. His teaching areas includes operations management, effective management consultancy, and business operations excellence. 

Joy Garfield holds a PhD in Informatics from the University of Manchester, UK.  She is a Senior Teaching Fellow and Deputy Head of Department for Business Analytics and Information Systems at Aston Business School, Aston University, UK.  With over 20 years of experience in academia, Joy is a Senior Fellow of the Higher Education Academy.  Joy is currently an external examiner for the University of Westminster Tashkent, Uzbekistan and a member of the Governing Council of the Society for Research into Higher Education.


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Can folk pedagogies help us understand the limited impact of research on higher education?

by Alex Buckley

The SRHE conference is a great place to see our field in all its glory. From the sessions I attended in December 2025, one thing that was abundantly clear was the desire of so many HE researchers to change the world. A distinctive feature of contemporary HE research – reflecting the social sciences more broadly – is the focus on political and ethical issues, with avowedly political and ethical intentions. The improvement of society is often the explicit end, rather than the more humble improvement of our own part of the education system.

Despite this desire to make a difference, higher education research has for many years been held up as an area where the impact of those working in the field is not what it could be. As George Keller said in 1985, “hardly anyone in higher education pays attention to the research and scholarship about higher education”,

Asking the right questions?

There hasn’t been a lot of work on the gap between research and practice in HE – though there is a fair amount in the schools sector from which we can extrapolate, to a greater or lesser extent – but one issue that has received some attention is the fundamental one: are researchers actually asking the right questions?

Vivianne Robinson is a researcher who has laid a substantial amount of blame at the feet of researchers, who “have little to offer by way of alternative solutions, when the problems they have been studying are not those of the practitioner” (Robinson 1993). I have recently used Robinson’s model of Problem-Based Methodology to explore whether research about exams in higher education does engage sufficiently with the challenges that teachers take themselves to face. The results were not encouraging.

One of the more straightforward of Robinson’s criteria for impactful research is that researchers should be addressing teachers’ beliefs, and correcting them where they are erroneous. That’s important, but what if those beliefs are hard to shift? We all have stubborn hunches about how higher education works: good ways of motivating students, how to write feedback that will make students pay attention, how to clearly communicate complex ideas. What if there are teacher beliefs that are deeply embedded, so deeply that we don’t always know we have them, but that aren’t helping us and need to change?

One idea that has been explored in the school sector, but has largely passed us by, is the concept of ‘folk pedagogies’. This idea was developed in the 1990s as an extension of the more famous concept of ‘folk psychologies’: the tacit theories that we all have that allow us to make sense of people’s behaviour. For Jerome Bruner, a natural next step from folk psychologies was the idea that we have intuitive theories about how people learn.

“Watch any mother, any teacher, even any babysitter with a child and you’ll be struck by how much of what they do is steered by notions of ‘what children’s mind are like and how to help them learn,’ even though they may not be able to verbalise their pedagogical principles.” Bruner (1996)

There has been some research in the school sector about the implications of this idea, particularly in terms of how much difference research makes to educational practice. Folk pedagogies have two features that will make them a factor in the impact of education research: they interfere with the uptake of new research-based ideas and approaches, and they are stubborn. On the first point, the idea is that new ideas about higher education will have to replace the old if they are to influence teachers; and on the second, evidence suggests that even where trainee teachers have ostensibly internalised more scientific theories of learning, the folk pedagogies come creeping back.

In the case of higher education, what might these commonsense, intuitive theories look like? They might just be very general ideas about how people learn, applied to the particular context of higher education. Bruner identifies a range of broad folk pedagogical views, such as one which sees ‘children as knowers’, with a focus on the gathering and organising of facts. Perhaps one kind of folk psychology of higher education would be the application of that idea specifically to students in universities rather than other sectors: a focus on the selection, organisation and retention of propositional knowledge within degree programmes. Perhaps there are also specific intuitive theories about higher education that influence teachers’ practices. Perhaps there is a folk intuition that university students should not be spoon-fed – that they must take responsibility for their own learning and seek to develop their own views. Perhaps there is a folk intuition that students should encounter challenging views that encourage them to question their own certainties. In the absence of research, we can only speculate (and introspect).

Respecting the ‘folk’

The idea that teachers have deep intuitions about how students learn, that those intuitions can prevent them from acting on more evidence-based beliefs, and that those intuitions are hard to shake; none of those ideas are particularly earth-shattering. They are probably common sense among those researching and enhancing higher education. The value of the idea of ‘folk pedagogies’ lies instead in the way that it encourages us to take those intuitions seriously, both as an object of study and a powerful barrier to change.

Rather than dismissing intuitions about higher education – as ignorant beliefs and hide-bound traditions – we can study them. What are they? Where do they come from? How do they change? The idea of folk pedagogies is not pejorative. There’s no shame in having intuitions about how learning works. As with folk psychological theories, they are necessary parts of how we navigate the world, and something we can’t do without. There is also deep wisdom to be found in those intuitions, even if they are sometimes misleading. Research goes wrong by departing from common sense, at least as much as the other way around.

Acknowledging the existence of folk theories of higher education can help improve the impact of our research in all sorts of ways. We can research them, to understand why teachers and students (and others) do what they do, and the conditions in which deep intuitions can change. It can help us understand where – and why – research has departed so far from common sense as to be of little practical relevance.

It can also help us understand the scale of the challenge. In much of what we do, we’re seeking to modify what university teachers do, which very often means changing how they think. The reality is that we aren’t usually changing superficial, specific beliefs, at least not where the improvements we’re seeking are substantive. We’re changing deep beliefs picked up over a lifetime. Our model of improvement may then need to fit the old adage: if you’re not making progress at a snail’s pace, you’re not making progress. That’s a bit different from annual quality enhancement cycles or short-term strategic initiatives. We can change the world, but it will take time.

References

Bruner, J. (1996). The culture of education. Harvard

Robinson, V. M. J. (1993). Problem-Based Methodology: Research for the Improvement of Practice. Pergamon Press

Dr Alex Buckley is an Associate Professor in the Learning & Teaching Academy at Heriot-Watt University, Scotland. His research is focused on conceptual aspects of research and practice in assessment and feedback.