adaptability

Sustaining Direction Dynamically: Designing governance tempo, portfolio and insight management for future and change capability in higher education

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This is the sixth article in a series on future and change capability in higher education, and the second of two posts on strategy, governance and risk. This post is a long one, because it’s where I get into how institutions can become more agile by making good decisions based on getting the right people with the right authority to move at the right speed with the right information.

The premise of the future and change capable series is that we are in an environment of sustained uncertainty – AI disruption, funding volatility, shifting student demand, policy instability and declining popularity – and universities need more than capable leaders and good intentions to navigate it all effectively. Along with external factors like enabling policy environments, the institutions themselves need future and change capability. This is the designed capability to decide deliberately in the face of change, act coherently and learn from what they do.

The previous post added a third element to the framework developed in this series: decision architecture, which is the structural layer through which strategic commitments are formed and risk is treated as a strategic judgement rather than a compliance activity. That argument built on two foundations developed earlier in this series. Identity is the anchor that tells an institution what matters; permeability is the deliberate design of channels through which insight enters and circulates.

If you need a recap, all of the posts are here in order:

post 1: why future and change capability in higher education?

post 2: identity before adaptability

post 3: university permeability and adaptive ecosystems

post 4: midway point reflection and why is Ruth exploring all this?

post 5: decision architecture

And post 6 is this one – governing decisions and commitments dynamically over time.

Before diving in, I want to flag that what I am developing in this post (and elsewhere in this series) is grounded in organisational learning, strategy and governance theory and research, and in my own experience as an institutional leader. But systematic empirical evidence of how these governance practices could and do function in universities specifically is limited, and universities have structures, policy contexts and aims that are very distinct from both the public and corporate sectors. This blog series is building towards empirical research that will refine the ideas I’m proposing and test them against others’ experiences and practices. At this stage I offer these ideas as reasoned propositions for testing, not established findings.

You’ll be happy to know that the core argument in this post isn’t that universities need more bureaucracy and governance machinery. I think most already have too much process applied in too generic a manner. The risk management and quality assurance intentions are good, but the execution isn’t always optimal. The problem is that the wrong kind of deliberation can be applied to decisions, and that sometimes important decisions are not always made consciously.

Poorly calibrated governance, in which decisions of very different kinds move at roughly the same pace through similar structures regardless of what is at stake, is itself a source of institutional inertia. What future and change capability requires is purposefully calibrated governance, with less undifferentiated or unconscious deliberation and more deliberation of the right kind, surfacing and dealing with each decision at hand in a way that balances consideration with speed. This post discusses three connected areas that shape whether this is achievable: how institutions differentiate the tempo of different decisions; how they manage and conclude strategic portfolios; and how insights generated through permeability, including evaluation insights, reach the fora with authority and capability to act on them.

Governing decision speed

Future and change capability requires governance calibrated to what each decision actually needs. Universities can move quickly when circumstances require it, but speed without adequate deliberation, the right information or the right people in the room does not always produce good outcomes. Often, when decisions are made rapidly or reactively, there isn’t time to assemble the ingredients good decisions require. These include the right people with the right authority, the right data and analysis, and clear pathways for enactment. Deliberate pre-design of governance pathways for different kinds of decisions will allow institutions to respond well, rather than having to improvise or default to an existing pathway that doesn’t fit. We can and have done this well previously. For instance, many universities set up differential decision speed governance systems during COVID, and these worked well. Once the crisis was over, we mostly returned to the single-speed governance status quo.

Universities commonly apply similar governance processes to decisions that differ considerably in what they require. A proposal needing swift operational action may sit in the same committee queue as a long-term strategic commitment requiring deep deliberation. The speed at which each moves is shaped as much by funding cycles, political momentum and institutional sponsorship as by the nature of the decision itself. Necessarily, governance processes tend to be structured around annual calendars, committee schedules and funding timelines. Unfortunately these rarely align neatly with each other (how many of us have committed to an operational plan without the associated annual budget approved?) let alone with what individual decisions actually require. The result is a system that is simultaneously too slow and deep for some decisions, and too fast and shallow for others.

The organisational ambidexterity literature has long recognised that institutions that simultaneously pursue the exploration of new initiatives and the consolidation of established activities need different conditions for each. One way to approach this is to create distinct organisational units for these different purposes. Another is to cycle through periods of exploration and periods of embedding and consolidation. Neither translates straightforwardly to the university context. Unlike commercial organisations that can more cleanly separate exploratory from consolidating activities, universities are deeply integrated: different types of decisions and activities draw on the same academic and professional staff, the same infrastructure, and the same resourcing, and are governed by the same bodies.

A major review of UK higher education governance, conducted by Advance HE in partnership with the Committee of University Chairs and the Association of Heads of University Administration (2025), noted the tension between the pace that effective transformation requires and proper oversight obligations. Drawing on wide-ranging engagement with governors, chairs, institutional leaders and board secretaries, the review called for more deliberate differentiation between what warrants extended deliberation at board level and what can be resolved more quickly with appropriate authority, recognising that when everything receives the same level of scrutiny regardless of its strategic significance, governing bodies spend less time on the decisions that most warrant their attention.

Temporal architecture can address this misalignment through the deliberate design of different decision pathways, with different routes, authority structures and tempos for decisions that differ in their stakes, reversibility and legitimacy requirements. Mission-level and long-horizon commitments, about research concentration, pedagogic direction or the institution’s relationship with particular communities, need deep deliberation, broad consultation and extended timeframes proportionate to what is being decided. Portfolio adjustments need evidence-based, time-bounded consultation with clear decision rights and authority to conclude. Bounded pilots and experiments need delegated authority and built-in review triggers, with explicit assumptions and predetermined signals for continuation or adaptation. Designing these different pathways reduces overall deliberative burden. Decisions that warrant speed can move more quickly, and those that warrant depth can receive it.

Two governance challenges are likely to arise in any attempt to differentiate decision tempos. The first concerns escalation. When a bounded experiment succeeds and warrants serious institutional investment, scaling typically requires a different kind of decision from the one that approved the original pilot: different authority, a different funding stream and often an institutional case that the pilot phase was never required to build. Without designed escalation pathways, successful pilots can stall at this transition. Temporal differentiation must therefore address how decisions move between modes, not just how each mode is structured.

The second concerns classification. Whether something is treated as a mission-level commitment or a bounded experiment is not a neutral determination in a university. It involves questions about where legitimate authority lies and who is responsible for making the classification when that is unclear. In practice, establishing this requires deliberate discussion at executive level about which governance pathway applies to which kinds of decisions, and who holds responsibility for making that determination, ideally before, rather than during, the decision process itself. And the more bounded experiments a well-designed fast lane generates, the more important it becomes to manage what happens to them over time.

The capability to stop

Without deliberate management, a portfolio of initiatives can develop inefficiencies and redundancies, become misaligned with current mission and priorities, and generate sub-optimal outcomes. Individual initiatives may have been examined at launch or reviewed in isolation, but systematic review of the portfolio as a whole is often absent. Future and change capability requires the ability to adjust as circumstances change, and that adjustment comes through deliberate portfolio management.

Portfolio discipline is the active, ongoing management of an institution’s portfolio of initiatives and activities. It involves the deliberate decisions about what to continue, what to adapt, what to scale and what to pause or stop, made against explicit criteria rather than by default or inertia. It is the counterpart to the capability to start things, and in many universities it is considerably less developed.

Temporal differentiation, if it functions well, generates more bounded experiments, proofs of concept, prototypes, and pilots. Without portfolio discipline to complement it, it also generates more unexamined legacy. Each pilot, initiative and project that moves through the fast lane creates a potential new commitment. Without designed mechanisms for rapid evaluation and conclusion, the portfolio can grow through addition rather than managed choice. Alternatively, it can leave a graveyard of promising initiatives that were never properly examined, or that showed real potential but never found the resourcing or decision authority to advance further.

Portfolio accretion is a pervasive feature of university life. Each initiative made sense when it was launched. Collectively, accumulated initiatives create administrative complexity and progressively narrow the capacity for adaptation. The resourcing challenge this creates is not usually a straightforward competition between legacy and new. In my experience, legacy initiatives are typically funded through operational budgets and are driven by operational staff and operational KPIs; new initiatives may be associated with strategic / project KPIs and different funding sources (but not always). Because the two streams may not come into direct competition, the tension between them tends to stay below the surface. Staff sustain ongoing commitments while also driving new priorities, and the organisational area may attempt to absorb both simultaneously rather than to evaluate what might slow, pause or stop. When something does eventually conclude, it can be the initiative with least visibility or advocacy, regardless of its actual mission alignment or return.

Empirical research illuminates how universities actually make decisions about program closure, and how these conditions can play out in practice. Eckel’s well-known empirical study of program discontinuation at four US research universities in 2002 found that the determining factors were generally not performance evidence or mission alignment. Programs that were closed tended to be those with fewer institutional supporters and limited capacity to mount a defence during the review process, regardless of the criteria formally developed to guide it. Alex Usher’s commentary in 2025 suggests that Eckel’s research is still relevant, noting that degree closure decisions continue to be shaped by a combination of implicit criteria such as prestige/reputation and sponsorship. My take on this is that implicit criteria may well have some validity, but we need to have the courage to make these implicit criteria explicit, to make mission and impact central, and to make unpopular decisions if needed. Institutions need to define exit criteria in advance and design the process for making stopping decisions. Without those conditions, stopping decisions are less likely to align with what is truly important to an institution, and may be deferred or at least take longer to make.

I’d argue that stopping is a design problem. It requires agreed and shared criteria established at the point of commitment that define what would warrant continuation, adaptation or conclusion; regular portfolio review against those criteria; and reallocation mechanisms that direct freed resource toward current priorities rather than baseline absorption. Dickeson’s program prioritisation model is the most widely used practitioner framework for this in higher education. Its limitation is that it centres on metric-driven ranking (enrolments, cost per student, financial contribution) rather than mission or strategy-anchored judgement, or less tangible criteria such as reputation or public good. A complete assessment also requires weighing the costs and benefits of continuing against alternatives, including what the same resources could do if differently directed.

The distinction Argyris and Schon draw between single-loop and double-loop learning is useful here. Stopping an initiative well means questioning whether its founding assumptions were correct, not just whether it met its targets. Without predefined criteria, institutions can only adjust at the operational level, modifying delivery, adjusting timelines, tweaking scope, without asking whether the initiative should exist in its current form. Criteria established at the outset make that question structurally available when review comes around, helping move it from the domain of assumption and political negotiation to the domain of considered judgement.

Time-limiting pilots and programs by default creates a structural trigger for deliberate review, ensuring that continuation is a considered decision rather than the default outcome of inertia. These review triggers need to be calibrated to what is being reviewed. Activities that require years to develop and show impact warrant longer cycles; bounded experiments warrant shorter ones. Responsibility for setting and conducting these reviews needs to be clearly assigned. In many institutions this sits most naturally at executive or Provost level, with academic governance consulted on quality dimensions but not holding sole authority over continuation.

The reallocation mechanism is as important as the stopping decision. Even when institutions agree that something should conclude, freed resource does not always reach new priorities. It can be absorbed into operational costs or directed toward deficit reduction rather than strategic reinvestment. Again, this could be a helpful thing, but the decision needs to be conscious and a mechanism needs to be created for it.

Many pilots are conceived with eventual scaling in mind, but the infrastructure to make it possible is frequently less developed, with no designed pathway from trial to sustained investment. Anyone in higher education who has encountered either of the phrases ‘everything here is a project’ or ‘everything here is a pilot’ will know what I mean. Project staff are focused on producing deliverables within the funding period, not on building the case or the infrastructure for continuation beyond it. When project funding concludes, the resourcing to sustain or generalise what worked can be unavailable, and the governance mechanism to authorise and fund ongoing investment may be unclear or poorly aligned. The capability to scale requires not only criteria for what would justify moving from experiment to commitment, but decision authority capable of acting on that judgement, and planned resourcing pathways to do so.

For portfolio discipline to work, it should connect to identity throughout. Mission provides the principled basis for decisions about what to continue and what to relinquish, distinct from decisions driven by financial pressure or the advocacy of those arguing for particular initiatives at the time.

Insight pathways, feedback loops and institutional learning

Future and change capability depends on institutions learning from experience and adjusting over time, which requires insight from evaluation, data and practice to reach the people with authority to act on it. The third article in this series addressed how permeability enables insight to enter and circulate. This section addresses what happens to that insight once it exists. I think it’s fair to say that in practice, insight does not always flow naturally to the places where it can influence strategic direction.

Even where permeability has worked well and insight has been carefully gathered and analysed, the journey from insight to institutional decision can have more stumbling blocks than is often acknowledged or addressed. Evaluation may be designed primarily around compliance or outputs rather than outcomes and institutional learning. Evaluation design shapes what questions get asked and whose perspectives are sought. Insights may not reach the people with authority to act on them in a form or at a time that enables considered response. Or it may reach the right people through the wrong forum, such as a governance body with quality assurance responsibilities rather than one with authority over strategy and resourcing. None of this reflects a lack of good intent; it reflects the absence of up-front, deliberate design around how insight is created, routed, aggregated, translated, and acted upon across institutional boundaries.

Weick’s sensemaking framework is useful here. According to Weick, organisations actively construct meaning from information, shaped by existing commitments, identities and contexts. Degn’s application of the framework to higher education strategy shows how leaders simultaneously make sense of changing circumstances and actively shape how insight is interpreted across the institution. Insight pathways are therefore interpretive forums as much as information channels. Who has the standing to frame what reaches decision authority is a political question as much as a design one. Whether uncomfortable intelligence surfaces or gets managed away depends not only on how pathways are structured, but on the trust and psychological safety conditions the next post in this series (culture and capability) examines.

The sensemaking and organisational learning literature suggests that effective insight pathways tend to share four features. First, decision-makers need structured exposure to evidence through collective interpretation in light of institutional purpose, not just dashboard reporting. Second, the connection between evidence and decision is traceable, strengthening accountability and institutional memory. Third, decision outcomes feed back into what data is subsequently collected and what questions future evaluations ask, so that learning from one cycle shapes the design of the next. Finally, different forms of intelligence (quantitative data, qualitative feedback, experimental findings and professional judgement) are considered together rather than routed to separate forums.

A further challenge to designing effective insight pathways concerns synthesis and timing. Useful intelligence often exists across different parts of an institution (in faculties, research offices, survey and data units, student services and planning teams), but in dispersed and incompatible forms. Bringing it together in a way that informs strategic deliberation requires effort that is rarely assigned as an explicit institutional responsibility. In fast-moving environments the timing challenge compounds this. By the time insight has been gathered, synthesised and reached deliberation, it may already be outdated, which is a particular risk in areas like digital and AI disruption, international student market shifts or rapid policy change. Feedback cycles therefore need to be calibrated to the tempo of the decisions they serve and the intel they provide, which connects directly to the temporal architecture argument developed earlier in this post.

Most institutional feedback mechanisms are single-loop, reporting whether initiatives met their targets and prompting operational adjustment within existing assumptions. Double-loop feedback reaches strategic deliberation and asks whether the targets were appropriate, whether the founding assumptions held, whether the direction warrants revision. What we know from learning analytics research, and from examples like Arizona State University’s integration of student data with curriculum redesign and support, is that structured feedback between data and institutional practice can improve outcomes at the operational level. Whether universities have built equivalent feedback loops at the level of strategic governance is much less clear, and is part of what the empirical work this series is building toward will need to examine.

Sustaining direction

Temporal architecture, portfolio discipline and insight pathways with feedback loops are complementary and connected. The ‘fast’ track of decision-making depends on insight pathways to generate the evidence that informs continuation or adaptation; portfolio discipline depends on double-loop feedback to make principled recalibration possible. Temporal architecture shapes how quickly that feedback can reach deliberation. Each constrains and enables the others.

What this governance cycle makes possible, when it functions well, is what I described in the midpoint reflection in this series as institutional learning and recalibration. This is the institutional capability to connect experience, evidence and judgement over time, and it is, I’d argue, a large part of what future and change capability looks like in practice: a continuously renewed capacity to understand, adjust and act with purpose.

There is an elephant in the room that needs naming. The mechanisms described across this post (differentiated decision pathways, portfolio review cycles, evaluation frameworks, insight aggregation functions) do of course add their own governance overhead. Applied generically or without sufficient care, they risk generating exactly the administrivia they are designed to replace. My suggestion is that the same principle of calibration that applies to institutional decisions should apply to the governance mechanisms themselves. In the spirit of double-loop learning, this is a meta-level application of the framework’s own logic. The mechanisms must be proportionate to what is being reviewed, differentiated by stakes, and periodically evaluated for whether they are adding value or merely adding burden, and adjusted accordingly. Getting that balance right is not at all straightforward, and is part of what the empirical work this series is building toward will need to examine.

All of this depends on culture and capability, the organisational conditions that enable or undermine these structures in practice. None of these (whether dissent reaches insight pathways, whether stopping decisions can be made without prohibitive political cost, whether feedback revises strategic direction rather than confirming prior commitments) are questions that structural design can settle by itself. How institutions develop the culture and capability to use these structures well is where the series turns next.

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Future and change capability in higher education: A midpoint reflection

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From individual capability to institutional adaptability

This post marks the halfway point in my series on future and change capability in higher education. Rather than introducing a new component of the framework, I offer a brief sensemaking reflection on where this work has come from and why it matters now.

The beginning of this post is for any readers who might have known me and my work for a while and could be thinking, ‘Ruth Bridgstock’s work is about graduate employability, WIL and careers. Why is she writing about institutional change all of a sudden?’

There is logic to it, I promise, and a trajectory of thoughts and practice over a couple of decades.

My interest in future and change capability did begin with individuals, and graduate employability in a certain sense, and since then it has been helpful to align much of my work with employability policy and discourse, although my interests are deeper and broader.

My doctoral research examined how creative practitioners and graduates develop the capacity to navigate uncertain career paths across the lifespan. I was interested in how people manage learning, identity and professional direction in conditions of ambiguity and change. Over time, that inquiry expanded into questions about how individuals learn to lead and navigate innovation and transformation, as individuals and collaboratively.

My interests shifted into curriculum and pedagogy. I moved out of a research intensive career track and became a teaching-and-research academic, to explore whether I could teach the capabilities I was researching. I wanted to know: How might we design educational experiences that cultivate future and change capability in students? What do educators need in order to support, enable, and facilitate? Eventually, as I moved into institutional leadership roles, these questions led to deeper and more challenging ones.

What became apparent was that educational innovation was often being undermined by institutional structures not designed for learning or adaptation. I started to ask: if we truly want students and educators to be adaptable and capable, what must our educational institutions be and do? Significant change was clearly needed.

That progression – from individual capability to educator practice to institutional systems and architecture – has unfolded for me across research, academic leadership and large-scale educational transformation over the last 20 years. After two decades of exploration and experimentation, I have come to the conclusion that without an adaptable HE system with adaptable institutions within it, we cannot effectively enable educators and students to be future and change capable – and future and change capability is vital to our futures.

I no longer believe that future and change capability can be meaningfully developed at the level of the individual student without being actively constrained or enabled by educator practices and capability, and the institutional context.

My timing isn’t incidental. As I argued in post 1, artificial intelligence, funding volatility, workforce transformation, social change and policy reform have intensified the demand for adaptive capability in students and graduates, and at every level of higher education. What began as a question framed in terms of graduate employability has become a broader question about higher education’s sustainability, public value and long-term contribution.

The framework I present in this series integrates several strands: identity and differentiation; permeability and institutional learning; strategy, governance and risk; culture and capability; and engagement with external forces. Together, they outline a model of the future and change capable university.

The model below synthesises the elements developed across this series into an integrated framework for institutional adaptability.

The future and change capable university.

Identity and purpose sit at the core of the institution, anchoring distinctive contribution and long-horizon commitment (post 2). Around that core, strategy, governance, risk and enactment shape how choices are made, sustained and adjusted. Institutional permeability describes how boundaries are intentionally designed: how relationships, information and practice move across academic, organisational and sectoral domains (post 3). Permeability expands what the institution can see; decision architecture determines how insight is translated into action. Learning and recalibration connect experience, evidence and judgement over time. Culture and capability permeate the whole, enabling disciplined interpretation and collective decision-making.

The university operates within a broader ecosystem of policy, professions, technology, industry and community. These conditions cannot be controlled, but they can be engaged with deliberately. Future and change capability develops cumulatively through the alignment of identity, permeability and strategic judgement.

Here I am synthesising and building upon various streams of theoretical work — key contributions that come to mind are Senge’s learning organisations, the double-loop learning of Argyris & Schon, complex adaptive systems, learning ecosystems, innovation systems and triple helix models, and strategic management theory such as Mintzberg & Teece. I’m integrating and extending these for higher education by placing identity, public accountability, and decision architecture at the centre. This is a deliberate departure from capability framings that privilege responsiveness alone; in higher education, adaptability without identity quickly becomes incoherence. Adaptability becomes the cumulative outcome of aligned purpose, selective permeability, disciplined experimentation and governance under constraint.

Three posts in this series remain. They will examine decision architecture and processes in greater depth, explore how culture and capability enable decision-making under uncertainty, and consider how institutions can engage with shifting external conditions without losing coherence.

This model offers an emergent framework for thinking about purposeful institutional adaptability in contemporary higher education.

I invite critique, refinement and collaboration from colleagues who are exploring similar challenges. If the model is useful, I will translate its elements into practical tools to support institutional analysis, disciplined choice and sustained change.

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Adaptive Ecosystems: Designing University Permeability for Future and Change Capability in Higher Education

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This article is the 3rd in a series about making universities more future and change capable. Article 1 is here, and article 2 is here.

In previous posts, I argued that universities’ core challenge in navigating change is not resistance, but a lack of future and change capability: the institutional capacity to decide, deliberately and proportionately, when to change and when to hold steady, and to act coherently and sustain those choices over time.

Clarity of identity is foundational to future and change capability. But identity alone is insufficient. Universities must also consider how they are structurally connected to the environments in which they operate, and how those connections shape learning, judgement and action.

Universities operate within dense networks of policy settings, industries, professions, communities, technologies and social expectations. These relationships shape what institutions see, what they learn and what they are able to do. Adaptability requires institutional receptiveness to signals from their networks, particularly when those signals challenge established priorities or sunk investments.

All universities are embedded in ecosystems. The question for me is whether, and if so how, they have deliberately designed their institutional permeability within those ecosystems.

In this article, ecosystem refers to the broader network of relationships within which universities operate. Permeability describes how institutional boundaries are designed so that information, practice and collaboration move across them.

The term ecosystem requires care. Universities are not organic systems whose adaptation unfolds naturally through ecological interaction. They are public institutions with defined responsibilities and accountability obligations. Their adaptability depends on how deliberately they shape the boundaries through which they engage with others.

Universities generate knowledge, data and practice internally that must circulate effectively across academic and administrative domains. Boundaries determine how insight moves in both directions: how developments beyond the institution are taken up, and how internal expertise, research and experience inform strategy and external engagement. When those pathways are intentionally structured, information does not simply accumulate; it travels to places where it can inform deliberation and action.

This deliberate shaping of boundaries is what I mean by permeability, and it is what allows institutions to learn cumulatively rather than episodically. It refers to the intentional design of channels through which ideas, evidence and practice move across institutional domains and between the university and the wider ecosystem.

The following features illustrate how adaptive institutions design permeability in practice. The features are: relational infrastructure, shared expertise and co-design, structured experimentation, and informational permeability.

Relational Infrastructure

Relational infrastructure is one of the clearest expressions of institutional permeability. Most universities already possess substantial relational capacity, though often in uneven and fragmented forms.

Relationships exist across faculties, research centres, advancement teams, marketing functions and alumni networks. Advisory boards are convened, collaborations are formed and partnerships are announced. Yet these relationships frequently develop in parallel rather than in concert. They reflect local priorities, short-term projects or immediate resource needs.

Universities do not consistently treat relational infrastructure as an institutional capability in its own right. Where investment occurs, it is often directed toward short-term outcomes in recruitment, teaching, reputation or philanthropy. These functions are important, but relationships also represent deeper relational capital: accumulated trust, insight and shared experience that can inform institutional direction over time. That capital is not always recognised or mobilised as such.

Fragmentation is common in universities. Partnerships are distributed across organisational silos, information flows are incomplete and brokerage roles are inconsistently embedded in academic and strategic processes. Customer relationship management systems may exist, yet insight does not necessarily circulate beyond the units that generate it. Relational capital remains localised rather than institutional.

Permeability requires a more deliberate approach. It involves cultivating multi-stranded relationships that extend across research, teaching, innovation and engagement. It requires brokerage capacity that connects boundary work to strategic and academic processes. It depends on reciprocity: partnerships sustained through shared purpose and mutual benefit rather than transactional exchange.

Selectivity is equally important. Institutions cannot engage everywhere. The choice of relationships — which sectors, professions, communities and collaborators are prioritised — should align with institutional identity and long-term direction.

Where relational infrastructure is embedded in this way, it influences how the university defines problems, allocates resources and adapts over time. Relational capital becomes consequential when it shapes institutional trajectory rather than remaining an untapped asset.

Shared Expertise and Co-Design

Widespread co-design across an institution is another marker of permeability. It signals that boundaries are sufficiently open — internally and externally — for knowledge to be shaped collaboratively rather than transmitted in one direction.

Adaptability depends not only on access to information, but on how problems are framed and interpreted. Shared design processes influence that framing. When industry partners, community organisations, students and colleagues across faculties contribute to curriculum architecture, research priorities or program review, they reshape the questions being asked as well as the answers being generated. Misalignments between institutional assumptions and lived practice become more visible; constraints and opportunities surface earlier.

The value of co-design lies partly in epistemic expansion. Broadening participation reshapes how evidence is weighed and how institutional judgements are formed. It can narrow the distance between strategy and implementation, between professional practice and academic design, and between central priorities and local realities.

Participation in co-design relies on reciprocity. Contributors engage when they can see that their involvement will matter. For some partners, this may mean access to emerging talent or influence over curriculum direction; for others, it reflects professional stewardship or shared commitment to public purpose. Students may require payment for their time and expertise. Where outcomes are opaque or contributions have little visible effect, engagement weakens.

Not every institutional decision warrants co-design or collaborative shaping. The appropriateness of co-design depends on the object of design and what is at stake. Issues that depend on diverse expertise or shared ownership lend themselves to participatory processes. Others require timely executive judgement within established authority structures.

Structural tensions are unavoidable. Deliberative processes require time and coordination. Power asymmetries can distort participation. Conflicting stakeholder values may surface. Internal co-design — across faculties, central units and leadership — is often as significant as external collaboration. Without alignment across institutional domains, external insight struggles to gain traction.

Shared expertise strengthens institutional adaptability when participation is embedded within processes that connect contribution to institutional purpose.

Structured Experimentation

Adaptive and permeable institutions require structured experimentation: deliberate, bounded forms of variation through which new practices, configurations and partnerships can be tested before wider adoption.

Structured experimentation introduces controlled uncertainty into institutional practice.
Doing this well is demanding: it asks institutions to create space for learning in environments already stretched by workload, compliance and delivery pressures. It creates defined environments in which curriculum models, research translation pathways, partnership structures or organisational arrangements can be trialled at manageable scale. These environments are time-bound and linked to evaluation so that experimentation generates knowledge rather than simply activity.

Many universities already contain elements of this architecture. Curriculum sandpits allow academic teams to prototype new program designs. Applied research laboratories and translational hubs connect scholarly inquiry with partner practice. Incubator and accelerator programs support industry, student and staff enterprise while exposing institutional processes to emerging forms of work. Co-location within innovation precincts brings together researchers, educators, start-ups, established firms and community organisations in shared physical or virtual spaces. When intentionally designed, such precincts connect teaching, research and applied activity, enabling joint problem-solving and iterative development rather than episodic engagement.

These arrangements can be valuable because they make institutional variation visible and discussable. By clarifying what is being attempted, over what period and with what forms of evidence, institutions create conditions for informed judgement. Adaptation often depends on translating structured inquiry into practice.

Structured experimentation also helps manage tempo. Co-design and academic deliberation take time; external developments often move more quickly. Time-bound trials allow provisional responses while evidence accumulates. Institutions can adjust without committing prematurely to wholesale reform.

Interpretation of experiments remains centrally important. Evidence generated through trials must move into spaces where it can be weighed against mission, capacity and long-term direction. Where trials conclude without reflection, promising work dissipates. Where initiatives persist without clear evaluation, portfolios thicken without becoming stronger. Adaptive capacity depends on treating experimentation as part of institutional learning rather than as isolated activity.

When connected to relational infrastructure and aligned with institutional direction, structured experimentation strengthens permeability. It enables institutions to respond to change in ways that are deliberate, proportionate and cumulative.

Informational Permeability

Permeability expands what a university can see. Informational permeability determines whether that visibility sharpens judgement.

Adaptive institutions treat data, evidence and external intelligence as strategic resources. Insight takes multiple forms: institutional data about participation and performance; evaluative evidence from programs and experiments; sector-wide intelligence on labour markets, technology and policy; and knowledge generated through research and professional engagement. Most universities possess these forms of insight in some measure. Fewer integrate them deliberately.

Informational permeability rests on four interrelated practices.

Access. Relevant data and intelligence need to be accessible to those making consequential decisions. Fragmented systems, uneven analytical capability and restricted ownership limit awareness. Foundational data infrastructure and analytical expertise matter here, as does systematic engagement with external intelligence — labour market analytics, professional standards, technological developments and global higher education trends — rather than reliance on informal networks.

Interpretation. Insight requires collective sense-making. Patterns in student progression, research performance, demographic change, partnership outcomes or industry demand require contextual reading. Interpretation depends on forums in which evidence is examined in light of institutional purpose and capacity.

Translation. Information must be converted into practical implications. Labour market analysis may inform portfolio decisions; research capability mapping may shape partnership strategy; demographic shifts may alter recruitment and support models; technological developments may prompt redesign of services or investment priorities.

Use. Insight acquires institutional value when it influences decisions over time. This includes evaluating initiatives against explicit aims, discontinuing activity where outcomes are weak, consolidating where impact is demonstrable and adjusting where conditions shift. It also requires distribution: ensuring that relevant parts of the institution engage with and apply insight appropriately.

Together, these practices determine whether information shapes decisions about what to invest in, what to stop and what to reshape, or simply sits alongside them.

Arizona State University provides a useful illustration of informational permeability. Its investment in integrated student data systems linking progression analytics, curriculum design and support services has strengthened institutional responsiveness. The significance lies not only in technology, but in the alignment between information flows and institutional priorities. Insight informs redesign; redesign generates further insight; learning accumulates.

When data and intelligence remain fragmented, institutions respond in fragments.
In practice, institutions vary in how willing they are to confront what such insights reveal, particularly when it challenges established priorities or sunk investments.
When informational permeability is designed deliberately, insight travels, accumulates and sharpens adaptive capacity.

Conclusion: From Permeability to Capability

Adaptive capacity depends on the alignment between identity and permeability. Clarity of purpose anchors direction; permeability expands awareness. Together they shape the conditions under which institutions can learn deliberately rather than react episodically.

Relational infrastructure, shared expertise, structured experimentation and informational permeability broaden what institutions can see, test and understand. They create channels through which insight enters and circulates. Awareness alone does not constitute capability. Institutions must also be prepared to engage seriously with what that insight reveals, particularly when it challenges established priorities or settled assumptions.

The implications extend beyond individual institutions. A differentiated system strengthens permeability when institutions cultivate relationships and informational practices aligned with their distinctive missions. Policy settings are therefore important. When regulatory and funding frameworks assume uniform portfolios, relational and informational designs converge. When they enable differentiated contribution, permeability can deepen rather than fragment.

Many institutions can sense what is changing around them. Far fewer have deliberately designed the pathways that allow insight to accumulate, and the resolve to act on it thoughtfully.

The next article turns to how universities can design processes that translate institutional learning into deliberate, proportionate action over time.

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Identity Before Adaptability: Laying the Foundations for Future and Change Capability in Higher Education

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In my previous post, I argued that a central challenge facing universities in these times of flux is not resistance to change, but a lack of future and change capability. By this I mean the institutional ability to decide, deliberately and in time, when and what to change and when and what not to, and then to act on those decisions. This second piece considers a foundational condition for building that capability: clarity of purpose and identity.

Australian universities face constant pressure to adapt. Artificial intelligence, funding volatility, policy shifts and changes in student demand all demand response. Many commentators have pointed out that institutions are not built for speed or sustained change, and discussions about why often focus on process, structure, and culture. While these are important factors, I suggest that a key difficulty lies at the level of strategy, or deeper still, at the level of identity. Without a clear sense of purpose in an institution, too many changes appear equally urgent, equally plausible, and equally unavoidable, making coherent choice increasingly difficult.

Identity before adaptability

At the institutional level, future and change capability begins with shared clarity about what an institution exists to do, what it will prioritise, and what it will choose not to pursue as conditions evolve. Technical capability, financial capacity, and a skilled workforce all matter. However, in the absence of a coherent identity, even well-resourced institutions struggle to translate capability into sustained direction.

By identity I mean a clear articulation of purpose and long-term priorities that functions as a decision framework, with strategic and operational consequences. Identity shapes what we stop, what we scale, and how we allocate constrained time, budget, and political capital. It also informs how we respond to external pressure and internal opportunity.

As with individual identity, institutional identity emerges from a combination of self-awareness and contextual awareness. It synthesises understanding of distinctive strengths and values with knowledge of community needs, policy directions, and emerging opportunities. Institutional identities are not slogans or branding exercises. They are made visible through educational offerings, research agendas, engagement practices, and partnerships.

Importantly, institutional identity is primarily horizontal rather than vertical. It is not about tiering institutions by status or performance, but about purpose and mission. Institutions might orient themselves toward online lifelong professional learning; integrated academic and work-based education; modular skills development; deep regional engagement; or missions relating to environmental sustainability, health, or security. These are choices about contribution, not rank.

The future is diverse and fast-changing. It is increasingly clear that a single, resource-constrained institution cannot do everything or respond to everything effectively. Rather than maximising breadth, institutions need to make deliberate choices about a smaller number of priorities and pursue them well. Paradoxically, this selectivity strengthens adaptability by reducing noise and clarifying what matters when change is required.

It should be noted that clarity of identity does not remove short-term pressure. Universities will continue to face urgent demands arising from funding constraints, workforce challenges, and policy shifts. What identity provides is a basis for judgement: deciding which pressures to absorb, which to resist, and which warrant deeper adaptation. Without this shared basis, institutions risk treating all pressures as equally urgent, increasing fragmentation and strategic drift.

Starting with the sector: who are we and what are we for?

Institutional identity does not develop in isolation. Universities operate within systems that both enable and constrain what is possible.

At the sector level, fundamental questions remain unresolved: what does Australian society expect higher education to contribute over the long term? How does the sector understand its collective role in meeting those expectations? How can we design a system capable of responding to increasing complexity in technology, workforce demand, and social need?

Sector-level clarity is important because it shapes how institutions interpret external signals such as funding incentives, regulation, rankings, and reputational cues. Government policy settings play a significant role in shaping what kinds of institutional directions are seen as legitimate, fundable, and sustainable. While these settings inevitably shift with political priorities, they are most effective when underpinned by a shared understanding of what higher education is for and how it operates. In the absence of that foundation, short-term signals dominate and coherence erodes at both system and institutional levels.

Sector-level identity enables institutional positioning. Where it is weak or ambiguous, institutional identity is progressively diluted, and strategies become increasingly reactive.

The cost of trying to be everything

In many respects, Australian universities are strikingly similar. Many pursue growth in the same markets, compete for the same student cohorts, and seek recognition through the same measures of success. The result is duplication, dispersed capability, and rising internal complexity.

In some ways, duplication and breadth of activity are not problematic. In complex systems, some redundancy and slack can support experimentation, learning, and innovation. Difficulties arise when breadth reflects accumulated activity rather than deliberate choice, and when few activities are ever stopped. Under these conditions, inefficiency becomes structural rather than strategic. Cautious expansion happens across many fronts. Institutions grow widely rather than deeply, diluting focus and making it harder to sustain excellence or adapt coherently.

There are, however, signs of alternative approaches within the Australian system. Some institutions have begun aligning strategy around a smaller number of distinctive commitments, such as focused research concentrations, deep regional engagement, or industry-embedded education. Smaller providers often operate with clearer specialisation, orienting programs and partnerships around specific missions.

In these cases, identity starts to function as a lived decision framework rather than an abstract statement. Choices about investment, partnership, growth, and withdrawal are made with reference to mission rather than opportunity alone. This provides clearer signals to staff, students, and partners about what the institution is for and how success should be understood.

Such approaches involve trade-offs. They may require declining opportunities, narrowing scope, or resisting sector-wide trends. Yet they can also reduce internal friction, strengthen coherence across teaching, research, and engagement, and support more confident long-term investment. Where clarity is present, institutions are better positioned to adapt without repeatedly resetting direction.

Time horizons, strategic lurches, leadership, and trust

Institutional identity work unfolds over much longer horizons than those that typically govern university decision making. Three-year government terms, five-year strategic plans, executive contracts, and council appointments create short cycles of attention and accountability. In the absence of an enduring sense of purpose, these cycles can produce not strategic drift but strategic lurching: repeated shifts in direction as institutions respond to successive policy signals, leadership preferences, or funding pressures.

A coherent institutional identity evolves over time but provides continuity across these transitions. It enables institutions to adjust course without repeatedly redefining purpose, supporting cumulative rather than episodic strategy.

Clarity and continuity of identity are closely linked to trust. When priorities are diffuse or frequently changing, staff learn that effort invested in one direction may be under-supported or reversed. For students and partners, instability makes informed choices more difficult. For governments and communities, unclear identity weakens confidence that public investment aligns with public purpose.

Trust is built through consistency of intent. Adaptation is more likely to be supported when guided by stable institutional commitments. Identity functions as a durable reference point: core commitments remain relatively enduring, while their expression develops through evidence, experimentation, and learning. Identity work is therefore an ongoing institutional practice rather than a one-off strategic exercise.

Differentiation and the Australian policy context

A sector composed of institutions with clear, consistent, and complementary identities is a differentiated system. While differentiation is widely endorsed in principle, it is weakly supported by current Australian policy settings. Funding, regulatory, and accountability frameworks largely assume institutional homogeneity, while rankings reinforce convergence by rewarding comprehensive activity across a narrow set of indicators. Together, these dynamics encourage institutions to look alike and compete on similar terms.

The Australian Universities Accord has reopened important questions about sector purpose and coherence. One opportunity lies in moving beyond uniform expectations toward a more differentiated ecosystem. Mission-based or bespoke institutional compacts are often proposed as a mechanism for achieving this.

Mission-based funding has been widely criticised in Australia, and not without reason. In theory, such compacts align funding and accountability with clearly articulated missions rather than generic performance metrics. In practice, they have often drifted toward compliance or micromanagement, limiting their capacity to genuinely support differentiation.

International experience suggests that more effective approaches focus on a small number of long-horizon outcomes, include independent review, allocate meaningful funding to missions, and operate on stable review cycles. Differentiation can sit above a shared baseline of agreed principles around quality, equity, and regional provision. Specialisation at institutional level need not reduce student choice at system level when supported by credit portability, shared curricula, and cross-institution enrolment mechanisms. Rankings will continue to shape reputation, but institutions can rebalance internal success measures toward mission outcomes to reduce disproportionate strategic responses to marginal rank movements.

Historically, Australian higher education policy has prioritised comparability, growth, and comprehensiveness. While these settings have supported expansion and stability, they also make it difficult for institutions to pursue distinctive long-term missions with confidence or to adapt in conditions of ongoing complexity.

The work of institutional identity development

Institutional identity development is difficult work. It requires confronting legacy assumptions about breadth and growth, undertaking honest assessment of strengths and constraints, and making decisions that may be unpopular. Sustaining identity over time requires leadership and governance arrangements that treat purpose as enduring institutional work rather than branding or a static element of a strategic plan.

From identity to capability

A more future and change capable higher education system will not be achieved by expecting every institution to do everything, nor by relying on short cycles of reform or performance pressure alone. It requires institutions with clear, enduring identities that guide coherent choices over time, and a policy environment that enables difference without fragmenting the system as a whole.

When institutional purpose is stable, adaptation becomes more deliberate, trust more likely, and collaboration more feasible. Differentiation, understood not as hierarchy but as complementarity, allows institutions to contribute in distinct ways while collectively meeting public needs. In this sense, identity is not a constraint on adaptability but its precondition, providing a stable basis for judgement as universities navigate uncertainty, leadership change, and shifting societal expectations.

The next piece in this series turns to how clarity of identity can be translated into action and adaptability.

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In these disruptive times, universities don’t need to be less resistant to change.

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They do need a more advanced kind of capability for change.

As we embark on another working year, I’ve been reflecting on the challenges and opportunities facing universities in 2026. And yes, me being me it’s turned into a 1,700 word theory of change piece… there is also a conceptual model, and I have some practical ideas about implementation, which I’ll save to share later if they’re useful. But here’s the introductory piece.

Universities: facing disruptive change and increasing pressure to change
The higher education sector is now thoroughly familiar with the ‘universities are facing disruptive change’ narrative. Today, that narrative is most often associated with the sudden ubiquity of generative AI; before that, it was the pandemic. The underlying concern, however, remains the same: the business sustainability of universities. Other pressures in Australian higher education include policy-led financial constraints and shifting funding models, and intensifying institutional competition from within the sector and elsewhere. Taken together, these pressures don’t just strain university finances. They shape institutional decision-making, risk tolerance, and the kinds of educational trade-offs universities feel compelled to make.

This disruption narrative is often conflated with a related but distinct one: that higher education itself needs to change. This second narrative points to growing mismatches between what universities do and offer and what their stakeholders expect. In 2025, the decline in social license and erosion of public confidence and trust were key issues for the sector, driven by perceptions that universities have become overly corporatised and out of touch with community concerns. Some of the criticisms relate to universities’ difficulties keeping up with an increasingly diverse student population, meeting evolving learning needs, and catering to rapidly changing workforce skill requirements.

How can our students be more adaptable if we aren’t?
Across roles and initiatives that I’ve pursued in my career, there is a recurrent theme: leading and enabling change within institutions, with the overall aim of supporting learners to become more future- and change-capable. For instance, at my current institution I’ve worked with educators to embed work-integrated learning at every level of every undergraduate course; I’ve infused career development learning into the curriculum with positive impact on student engagement, retention, success and graduate outcomes; and most recently, I’ve been using data to personalise learning and student support within and beyond the curriculum.

Much of this work has involved connecting parts of the institution that do not naturally collaborate, partnering with industry, community, educators, and learners themselves, and working across entrenched silos and legacy processes in pursuit of transformation. Across these initiatives, the common challenge has been less about persuading individuals to change (although stakeholder engagement has been centrally important), and more about enabling universities to act coherently and responsively. Within universities we’ve all had innumerable ‘process wagging the dog’, ‘computer says no’, ‘ivory tower syndrome’ and ‘fiefdom mentality’ experiences that militate against change.

At a higher level, what I have noticed through my experiences is that to develop future-and-change capable learners and graduates who will be successful in their lives and careers, you need future-and-change capable educators, and in turn future-and-change capable institutions (and a policy context that enables all of the above). Put another way, it is very difficult to teach students to be proactive and adaptable when their educational experiences, programs, processes, structures and environments they encounter are reactive and rigid.

Change resistance: Not the enemy, necessarily
Universities are often described as change-resistant, and this is usually framed as a criticism. Actually, and this may seem to run counter to what I’ve just said – bear with me – I think that some change resistance in higher education can be a good thing.
Commitments to educational quality, consistency, and accountability are essential. Quality assurance requirements play a legitimate and necessary role in maintaining trust in higher education. Too much change leads to exhaustion and confusion.

Here’s where the nuance comes in. I’d argue that universities need to build our capability to know when (and how) to flex, and when (and how) not to. In many ways, we’ve erred on the side of non-change for a long time. Over time, layers of bureaucracy and administrivia have accumulated – often in response to past risks or policy pressures – without being revisited or tested against their ongoing value. I suggest that some of these structures are no longer proportionate to the quality aims they were designed to serve, yet they continue to shape what is possible, how quickly institutions can move, and where effort is expended. A good example here is course development and accreditation processes, which can sometimes be so glacially slow that once finally approved, a new course immediately needs to be redesigned to be relevant.

There is an important difference here between principled resistance, grounded in educational quality, equity, and accountability, and inertial resistance that persists simply because systems are difficult to change. In this sense, selective resistance is not a liability but a contributor to public trust and social licence, signalling that universities do not abandon core values in the face of every new pressure.

The deeper problem isn’t resistance to change, but that universities are not sufficiently future-and-change capable. Future-and-change capability is a distinct institutional capability, infused into all of our core activities at every level of the institution, that shapes how universities navigate uncertainty over time.

This isn’t another call for university agility, innovation, or cultural change alone. It is an argument about the fundamentals of institutional design – about embedding adaptive capacity into governance, systems, and everyday decision-making. It is a set of institutional capabilities embedded in structures, processes, and ways of working. A future-and-change capable university can make good, informed decisions with the future and the present in mind at every level of the institution, to change and adapt where needed or stay put when this is the best course of action.


Reactive, sustaining and transformative change
Universities can and do change. However, much change in universities remains reactive and mostly unexamined, triggered by external shocks and requiring extraordinary actions and measures. From the inside, reactive change can feel like a sudden sideways lurch: priorities shift, funding is reallocated, roles and structures are reshaped. The aim of reactive change is not transformation. It is usually about returning to a viable version of the status quo. Over time, this reactive pattern erodes staff trust, depletes morale, and weakens institutional memory, making subsequent change harder rather than easier.

Universities also pursue what might be described as sustaining change: proactive, incremental improvements intended to enhance existing practices, programs, or systems. While these initiatives are frequently well-designed and evidence-informed, they are less often structurally protected. Unlike routine continuous improvement, sustaining change often challenges existing power arrangements, resource allocations, or performance metrics, which can make it more vulnerable. When priorities shift, leaders move on, or funding and policy settings change, sustaining change initiatives can stall or disappear, sometimes irrespective of their impact or value. Often, what is missing is structural protection: stable funding, formal governance ownership, embedded roles, and alignment with core institutional processes.

It seems many of our institutions struggle to do any form of change particularly well. Reactive change is exhausting, disruptive and sometimes frightening for those affected. Sustaining change can be fragile and difficult to maintain over time. Change often seems to be something universities endure, rather than something they are structurally equipped to navigate, learn from, and build upon.


The deeper problem is not that universities resist change, but that they lack the capability to decide – deliberately, proportionately, and in time – when and how to change and when not to, and then to carry those actions through.

There are, of course, institutions that have pursued more substantial transformations successfully, including new models and modes of delivery, large-scale pedagogic change, deeply data-informed approaches to curriculum and student support, short-form credentials, and co-ordinated tertiary offerings across vocational and higher education. What makes these examples compelling is that these are instances where, despite universities’ change resistant and risk averse reputations, they have taken larger risks proactively in pursuit of meaningful change.

Also, we find in many of these innovations evidence that institutions have sought to meet sector policy priorities and business sustainability imperatives concurrently, while keeping core ideas around HE values, identity and purpose at the forefront (which might also, incidentally, help rebuild our social license). Success here takes courage and outstanding leadership, along with the right enabling conditions.

What is future-and-change capability? (AKA I finally get to the point)
But my thinking keeps returning to how higher education institutions (and the sector as a whole) can start to become more future-and-change capable in an ongoing way. Innovation cannot be a one-off project or even a periodic endeavour for universities, as disruptors, change pressures and opportunities continually emerge. Yet for many institutions, there remains a significant gap between acknowledging this need and having the institutional capability required to act on it consistently.

Proactive, conscious, deliberate and ongoing approaches to navigating change must become normalised in higher education. This begins with ensuring that we are continually looking around and ahead, experimenting, and connecting meaningfully with our communities, then interpreting what we are seeing. We need to sense-make actively from these experiences and make informed decisions about how to act that are also grounded in who we are and why we exist.

Universities also need to ensure that we have the capability to act – that we are equipped and ready to transform, adapt, or deliberately hold steady, and that we learn from our actions. This means building feedback loops that allow us to assess outcomes, adjust course, and sustain effective change over time, rather than repeatedly resetting in response to each new pressure.

I know that what I am calling for is a huge challenge for institutions and the sector, given the complexity of our internal and external contexts, and the constraints that we face. I also think it’s central to our survival and our ongoing place in society.

It means supporting students and staff to develop their own adaptive capabilities, while also building enabling adaptive institutional structures and processes. We must also recognise that no institution can do this work in isolation. Connecting and collaborating across boundaries – with other institutions, communities, and policy makers – is essential to building and sustaining an adaptive educational ecosystem. For senior leaders, this means shifting some of their attention from each initiative or transformational program to the harder work of building enduring institutional capabilities that allow universities to adapt with integrity and purpose over time.

If higher education is serious about preparing learners for uncertain futures, then the sector itself must become more future- and change-capable. This will never occur through episodic reform, but by building aligned, adaptive capability and action across learners, educators, institutions, and the systems that shape them.

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This piece could be the first in a short series exploring what future-and-change capability could mean for higher education institutions and the sector. As I mentioned up front I have further thoughts about what future-and-change capability involves, what it could look like in practice institutionally and sectorally, and how to surmount the challenges involved in becoming more future-and-change capable.

I’m keen to hear from colleagues about your experiences of institutional change, particularly when it has been effective (or has had effective elements), or where ongoing adaptation has been a feature. Are there examples that you know of from higher education or other highly regulated sectors containing large organisations where continual adaptation is done well? Please get in touch if you’d like.

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NB. I wrote this post as a scholar of higher education, without critique of any particular institution or initiative in mind.

AI use and post development disclosure: I wrote a first draft of this post and asked ChatGPT to edit it critically. I reviewed its changes and additions and threw them all out because (i) it failed to grasp important nuances in the argument and (ii) its contributions were all in its own (very characteristic) writing style, despite my requests that it follow mine.

I wrote a second draft and then asked ChatGPT to critique the 2nd draft paragraph by paragraph, looking for errors in argumentation and editorial issues. I made some minor editorial changes based on its recommendations. I shared this 3rd draft with some close friends and colleagues for their thoughts and made some more changes before publishing. This post is organically me, including any errors or annoying em dashes you see.

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