SRHE Blog

The Society for Research into Higher Education

Monthly Archives: June 2026


by Leave a comment

Designing together: what co-creation teaches us about human-centred innovation in higher education

By Bo Kelestyn

Lessons from working and publishing with students

In higher education (HE), we often ask students for feedback after the most important decisions have already been made. We ask whether a module worked, whether an event was useful, whether a policy was clear, or whether an initiative landed well. These questions matter. But they also reveal a limitation: students are often invited to evaluate their experience largely designed by others.

Co-creation begins from a different premise. It asks what might happen if students were involved earlier, not only as respondents or representatives, but as people capable of framing problems, imagining alternatives and producing knowledge about HE itself.

Through my work on Designing Together, a student-staff co-creation initiative focused on human-centred educational innovation, I have come to see co-creation not simply as a method for improving student experience, but as a practice of belonging, agency and shared authorship. When students help design, test, refine and communicate ideas, they are not only contributing to better educational provision. They are also experiencing what it means to be taken seriously as members of a learning community.

This matters because belonging is often treated as an outcome: something to be measured, improved or delivered through institutional interventions. But co-creation has taught me that belonging can also happen in the process itself. It can happen in a workshop, around a shared table, in a Padlet comment or Vevox word cloud, in an informal conversation, or in the moment when a student sees their idea shaping a project, publication or decision. Belonging is not only something universities design for students. It is something students and staff can shape together.

Four lessons have stayed with me.

1. Genuinely listen and “keep the door open”

Listening sounds simple, but in practice it requires intentional design. It is not enough to invite students into a room once, ask what they think, and consider the work done. Students need multiple ways to contribute, including ways that are informal, low-pressure and ongoing.

As a Director of Student Experience, I used Padlets and shared Teams spaces that allowed students to offer informal feedback, add ideas asynchronously and build on one another’s thoughts. This is a contrast to the often preferred surveys that make responses invisible once you click ‘submit’. I created a ‘Heard it on the Grapevine’ Padlet, for example, where students could post things they heard from other students and ‘fact check’ information about the programme, marks or policies before they become toxic rumours. As a Course Director, I set up small funds for student-led projects, signalling that ideas could move beyond discussion into action. As a lecturer, I carve out 10-15 minutes of ‘corridor time’ after teaching for informal conversations, creating space for trust, humour, uncertainty and relationship-building, all the things that rarely fit neatly into a student-staff liaison committee agenda, but often make meaningful collaboration possible.

Keeping the door open is important because students do not always know what they want to say at the exact moment we ask them. They may need time to reflect. They may want to see whether staff are genuinely listening before they speak candidly. They may have ideas that emerge only after a workshop, a conversation with peers, or an experience elsewhere in the university. Not to mention a whole spectrum of cultural differences, neurodiversity needs, and life circumstances that shape this too.  

A human-centred approach to co-creation recognises this. It treats listening not as an event, but as an infrastructure: a set of habits, spaces and relationships that make it easier for students to keep contributing.

2. Think joyful and win-win

Co-creation should be serious in purpose, but it does not need to feel heavy. Some of my most generative student-staff work happened when the atmosphere was creative, welcoming and energising. Small details like music, colour, and good food matter. Using pens, cards, prompts and materials that invite people to think with their hands as well as their heads. Or designing activities that feel purposeful (intentionally low tech) but also enjoyable. And, importantly, choices that show we have paid attention. “Pizza for students” has become almost a shorthand for engagement, but it is worth asking students what would actually make a session feel welcoming. The answer may be different from what we assume. In one of the student-led projects, for example, we got crepes and bubble tea, instead of pizza and Coke, and University-branded teddies instead of the usual Amazon/Love2Shop vouchers. This fundamentally reshaped that student-staff dialogue.

Joy is not a superficial add-on. It changes the quality of participation. When students feel relaxed, curious and valued, they are more likely to take creative risks. They are more likely to move beyond complaint into possibility. They are more likely to feel that they have not just given something to the institution but taken something away for themselves.

This is why co-creation should be win-win. Students should leave with more than the feeling of having been consulted. They should develop confidence, language, networks and skills. Applying design thinking to co-creation helps to boost problem-solving, collaboration, communication, teamwork skills, and even sustainability competencies. Staff should also learn, not only about student experience, but also about their own assumptions and biases. Good co-creation is mutually developmental. It creates value for the project, for the students, for staff and for the wider learning community.

3. Asking “what do you need?” is not enough

One of the most important lessons I have learned is that simply asking students what they need, although an important question, does not always produce the most inclusive or imaginative outcomes. The same goes for staff. This is not because we do not know our own experiences. We do. But direct questions can put people on the spot. They can privilege those who are already confident, articulate or familiar with institutional language. They can also lead to familiar answers, repeated frustrations, or what can feel like a “moan fest”. Not because we like being negative, but because the format invites critique without necessarily creating the conditions for reimagining.

Human-centred design-led co-creation is powerful because it changes the nature of the conversation. Rather than asking students to arrive with fully formed solutions, it creates a process through which ideas can emerge. Design thinking and facilitation tools such as scenarios, mapping activities and prototyping exercises help us move from experience to insight, and then from insight to possibility. They also make participation more inclusive: no one has to have the perfect answer immediately, and ideas can be built collectively.

This is where co-creation becomes more than consultation. It allows students and staff to reframe the problem together. What I have observed is that sometimes what first appears to be a request for more information is actually a need for belonging. I learnt this from the work of Professor Radka Newton, who often cites Disney’s ‘What time is the 3 o’clock parade?’ thinking. Sometimes what sounds like a complaint about communication is really about trust. Sometimes the most useful idea appears halfway through an activity, sparked by someone else’s comment, a visual prompt or a moment of shared recognition.

Human-centred innovation depends on this kind of emergence. It does not assume that the problem is already known. It creates the conditions for better questions to surface.

4. Close the feedback loop. Then open it again

One of the quickest ways to damage trust in student-staff partnership is to ask for input and then disappear. Students need to know what happened next. What was changed? What was not changed? Why? What is still being explored? Where did their contributions go?

Closing the feedback loop is a known challenge, but we should not hide from it because it communicates mattering and respect. It shows that student labour has been recognised. It also helps students understand the complexity of institutional change: the constraints, trade-offs and timescales that are often invisible from the outside.

But co-creation should not be imagined as a neat linear process: ask-listen-act-report back-finish. It is better understood as a cycle. Communicate, share, update and ask again. Return to students with prototypes, drafts, early findings or emerging decisions. Invite them to challenge what has been interpreted from their contributions. Make visible where their ideas have shaped the work.

I find this cyclical approach is especially important when working and publishing with students. Authorship is not just about whose name appears on a paper or blog. It is about how ideas are generated, developed, represented and credited. Writing and publishing with students requires explicit conversations about roles, expectations, confidence, time and recognition. It also requires care. Academic writing can be unfamiliar and intimidating, but it can also be a powerful site of belonging when students see that their experiences and interpretations are part of knowledge production.

In this sense, co-creation is not only a way of designing better educational initiatives. It is a way of changing the relationships through which HE understands itself. For me, the central lesson in projects like Designing Together is that students do not only belong in the university as learners, consumers or sources of feedback. They belong as thinkers, makers, collaborators and authors. When we create the conditions for genuine co-creation, we invite students to help shape the educational futures they are part of. If we believe those futures are to serve our students, we should be designing with, not for or to.

From the work of Susie Wise, we know that invitation is a moment of belonging and must be designed with care. It needs open doors, joyful spaces, inclusive methods and honest feedback loops. It needs staff who are willing to listen without defensiveness, share power without abandoning responsibility, and treat student insight as knowledge rather than anecdote, or worse, “a storm in a teacup”.

Co-creation will not solve every challenge in HE. But it can help us practise a more human-centred form of innovation: one rooted in relationship, imagination and shared purpose. Perhaps its greatest promise is not simply that it helps students feel they belong. It is that it invites us all to help make our universities places worth belonging to.

Dr Bo Kelestyn PFHEA FEEUK is an Associate Professor at Warwick Business School, where she teaches and researches at the intersection of design thinking, education, and digital innovation. 


by Leave a comment

From data to policy: building an evidence-based future for skills, work, and learning in Latin America

by Sabur Butt, Hector G. Ceballos, and Michael Fung

Latin America stands at a familiar crossroads. Once again, a technological revolution is reshaping how work gets done, what skills employers value, and how quickly the workforce must adapt. And once again, the region risks being a generation behind.

During the Third Industrial Revolution of the 1970s–1990s, East Asia invested decisively in microelectronics, computing, and technical education. Latin America, consumed by debt crises and macroeconomic instability, missed the wave. The cost was measured not only in lost output but in institutional habits of looking backward while others prepared to look forward. Today, the Fourth Industrial Revolution is unfolding faster than its predecessor, and the region’s central deficit is not money or talent. It is foresight leading to informed interventions.

A structural mismatch between work and learning

Industries now change in cycles of months. University curricula change in cycles of years. That gap is no longer a minor inefficiency; it is the bottleneck that determines whether a country prepares its workforce in time or trails behind it.

The numbers are sobering. Across the six largest Latin American economies, between 19% and 21% of workers face a high probability of automation-related displacement. Almost half work in informal jobs. University dropout rates exceed 50% in several countries, climbing as high as 76% in the Dominican Republic. Students perform consistently below OECD averages in foundational literacy and numeracy. By the time graduates from the educational system enter the labour market, there is already a structural gap between what they can do and what employers want.

What the region needs is not another labour-market report. It needs skills intelligence, a continuous, forward-looking system that informs policymakers what is rising, what is fading, and where the workforce can realistically move next.

Why traditional forecasting falls short

Most forecasting in the region still relies on expert panels, occupational surveys, and static taxonomies that take years to update. These tools were designed for a slower-paced world.

To illustrate the issue, consider how such static taxonomies treat “database management” as a single skill, when the real labour market is moving between MySQL, PostgreSQL, MongoDB, Redis, Cassandra, and now vector databases, each with a different demand trajectory. Or consider the noise in a single automotive dataset, where the same assembly-line job appears as “ensamblador de carrocerías”, “operador de ensamble”, “ensamblador automotriz”, and “técnico en armado de vehículos”. Human annotators cannot keep up; even expert raters disagree on whether two skill descriptions refer to the same thing.

By the time a traditional taxonomy recognizes “prompt engineering” as a skill category, the labor market has already moved on to whatever comes next.

A data-driven alternative, already running

In our paper, we describe an operational deployment at the Institute for the Future of Education at Tecnológico de Monterrey. It is not a proposal; it is a working system (See Figure 1).

Figure 1. The framework links real-time labour market signals to an AI-assisted, expert-validated skills intelligence layer, which in turn informs curriculum design,reskilling pathways, workforce policy, and governance.

The approach combines large language models with retrieval-augmented generation to build dynamic, hierarchical skill taxonomies that update themselves as new job postings flow in. Each new skill is matched semantically against the existing taxonomy. Known skills are normalized to canonical terms. Genuinely new ones are flagged, classified, and added.

In Mexico’s automotive sector alone, the system has mapped more than 11,000 skill variations across 220 hypernym categories, identified 847 unique skills clustered into 12 occupational groups, and tracked the rise of electric-vehicle competencies in real time. Generative AI skills surfaced in the data months before they appeared in any official classification.

The infrastructure required is modest. A taxonomy covering 10,000 skills across major sectors can be maintained on standard cloud infrastructure for roughly $500–1,000 USD per month, within reach of education ministries in developing economies.

From data to policy

Technology alone does not change a system. The harder work is institutional. To shorten the lag between detecting a skill shift and updating a training program (currently 18 to 24 months) in most regions, curriculum committees must meet more often, must accept real-time data alongside surveys, and procurement procedures must allow timely equipment purchases according to the emerging skills.

Governance matters equally. Sustainable implementations bring together labour ministries, education ministries, economic development ministries, national statistics offices, industry associations, and universities. Each contributes something the others cannot: data access, curriculum authority, methodological rigor, domain expertise, and research capacity. No single actor owns skills or intelligence; the legitimacy of the system depends on shared ownership.

Localization also matters. Global taxonomies like ESCO and O*NET are useful starting points, but they need to incorporate regional terminology, indigenous skill categories, and sector-specific competencies. A skill system that does not speak the local language of work will not be trusted by the people meant to use it.

We also acknowledge real-world limitations. Many countries still hire through newspaper classifieds, physical noticeboards, and informal networks. Supplier tiers and small enterprises seldom advertise online. A system built solely on digital postings produces a geographically and structurally biased picture. Integrating offline data sources, replicating the approach across countries, and validating its predictions over time are the necessary next steps.

What success would look like

Executed well, skills intelligence reshapes reskilling itself. Instead of generic, fixed-duration programs, workers receive personalized pathways: a manufacturing technician’s quality-control experience mapped onto automated-systems monitoring; a mid-career professional alerted 12–24 months ahead of emerging demand; a young job-seeker pointed toward a stackable micro-credential that the market will actually reward.

For Latin America, this is more than a technical upgrade. It is a chance to break a historical pattern of arriving late to every industrial revolution and start arriving prepared. The region has the data, the talent, and increasingly the tools. What it has lacked is the institutional capacity to anticipate. That capacity is now within reach.

The Fourth Industrial Revolution will not wait. But for the first time, neither does the evidence.

Reference: Butt, S, Ceballos, HG, and Fung, M (2026) ‘From Data to Policy: Building an Evidence-Based Future for Skills, Work, and Learning in Latin America’ Policy Reviews in Higher Education 

Sabur Butt is a research professor at the Institute for the Future of Education, Tecnológico de Monterrey. His work focuses on artificial intelligence, natural language processing, and dynamic skills taxonomies, with a particular interest in how AI-driven labour-market intelligence can inform education and workforce policy across Latin America.

Hector G Ceballos is Director of the Living Lab & Data Hub of the Institute for the Future of Education (IFE) at Tecnológico de Monterrey. His research spans data science, knowledge engineering, and educational analytics, with a focus on building evidence-based systems that connect higher education to evolving industry and labour-market needs.

Michael Fung is Executive Director of the Institute for the Future of Education at Tecnológico de Monterrey. He was formerly the Deputy Chief Executive at SkillsFuture Singapore (SSG). He led the development of a comprehensive education and training ecosystem under the national SkillsFuture movement, which has become a global benchmark and reference for workforce skills development and lifelong learning across society.


by 3 Comments

When papers become currency

by Carolina Guzmán Valenzuela

Over the last few months, I have found myself discussing academic publishing with young researchers in Germany and Chile. What struck me in both places was not excitement about ideas, journals or scholarly debates. It was anxiety.

At workshops on publishing strategies and scholarly journals (one at the HoFoNa Conference in Germany and another at the Institute of Education at the University of Chile) the conversations quickly moved away from writing itself and towards something far more pragmatic: survival.

Young researchers spoke about publishing in highly strategic terms. Which journals were ‘safe’? Which ones counted for postdoctoral applications and funding schemes? Which journals’ turnarounds were quick enough? Which journals offered the highest probability of acceptance?

Several participants openly discussed how they calculated publication decisions in relation to career survival. The question was often not where their work fitted best intellectually, but which journals were fast enough, prestigious enough and predictable enough to maximise their chances of securing a postdoctoral position, grant or future contract.

What I found quite revealing was how naturally many early-career academics now speak the language of optimisation. Quartiles, Article Processing Charges (APCs), turnaround times, indexing systems, impact factors and publication strategies are discussed with remarkable fluency. Many young researchers are being socialised into academia through the logic of strategic productivity before they have had the opportunity to develop a slower intellectual voice of their own.

And who can blame them?

Across many universities today, academic life has become increasingly precarious and accelerated. Temporary contracts, short-term postdoctoral positions, uncertain funding, metric-driven evaluations and intense competition have transformed publishing into something far more strategic than it was. In systems (such as Chile’s), where academic careers and funding schemes heavily depend on publications indexed in Web of Science (WoS) and Scopus, papers increasingly function as academic currency.

Under these conditions, it is not surprising that publishers promising continuous publication, high-volume output and relatively predictable editorial processes have expanded rapidly. This is one reason why publishers such as MDPI and Frontiers have become so deeply embedded within contemporary academic life. Some of their journals are indexed in WoS and Scopus, which count towards grants and promotions and contribute directly to institutional rankings and evaluation systems. In other words, they are not operating outside the university system. They are increasingly part of how the system itself functions.

It is fair to say, though, that some established journals are reporting turnaround times that are not radically different from publishers such as Frontiers or MDPI. Elements of acceleration and compressed editorial timelines are also becoming increasingly visible across the wider publishing ecosystem, suggesting that these dynamics are no longer confined to specific publishers.

In any case, average turnaround statistics do not fully capture broader differences in selectivity, publication scale, editorial oversight and peer review intensity. During my years as Coordinating Editor of Higher Education, manuscripts frequently went through several rounds of major revision over many months. Reviewer disagreement, editorial discussion and substantial intellectual reshaping were often central parts of the process. The deeper question, then, may not simply be speed itself, but whether meaningful scholarly judgement, rigorous peer review and sustained intellectual critique can realistically be maintained under conditions of industrial-scale publication.

This becomes particularly important in a publishing ecosystem increasingly organised around scale. Large editorial boards, continuous publication models and relatively low desk-rejection rates create a parallel publishing universe in which the formal conventions of academic publishing are maintained, but where critique, filtering and editorial curation risk becoming increasingly compressed and uneven.

APCs have also reshaped inequalities within academic publishing. Publishing open access in prestigious journals often depends on fees that remain inaccessible for universities and researchers in Latin America, Africa and other underfunded academic systems unless institutions are able to absorb the costs.

At the same time, substantial APCs are no longer confined to traditionally prestigious journals. Many high-volume publishing models also involve significant publication fees, suggesting that what many early-career researchers are increasingly paying for is not simply open access, but speed, predictability and reduced temporal uncertainty within an academic system governed by short-term contracts, funding deadlines and metric-based evaluations. In short, they are purchasing life chances.

The irony is difficult to ignore. The same universities and funding systems that demand constant productivity often make meaningful participation in prestigious publishing circuits governed by international rankings, indexing systems and performance metrics.

Meanwhile, reviewers, the invisible infrastructure sustaining the entire system, are visibly exhausted. Every week, I receive multiple emails asking me to review manuscripts within ten or fourteen days. Some are oddly urgent in tone, politely aggressive, reminding reviewers about editorial targets and turnaround times. Many read as though they were generated from the same automated template. At this stage, I rarely even reply. I simply delete them. What concerns me is not only the pressure itself, but how normalised this publication culture has become.

Sometimes the system reaches extremes. In Chile, recent controversies surrounding publication incentives revealed academics producing absurd numbers of WoS indexed papers while receiving substantial productivity-linked salaries and bonuses. In some cases, this meant publishing well over one hundred papers in a single year. The issue here is not simply individual behaviour. The deeper question is structural: what kind of national research funding system rewards institutions according to publication output and, in turn, transfers these pressures directly onto academics?

Artificial intelligence is likely to intensify these dynamics even further. AI did not create the culture of academic hyperproduction, but it is accelerating it dramatically. Faster writing. Faster reviewing. Faster summarising. Faster publishing. More output everywhere.  And less time for, or even interest in, thought as a result.

None of this means that traditional academic publishing represented an egalitarian system. It has long been shaped by oligopolistic publishers, exclusionary gatekeeping and profound global inequalities. Open access has unquestionably expanded the circulation of knowledge and enabled greater visibility for scholars outside elite institutions. Some forms of academic closure deserved to be challenged. But something important may also be getting lost.

During those workshops in Germany and Chile, I observed that many young researchers seemed caught between two incompatible temporalities: the time required for meaningful scholarship and the accelerated pace demanded by contemporary academic careers. That tension, more than any individual journal or publisher, surely represents one of the defining conditions of academic life today.

Carolina Guzmán-Valenzuela serves on the SRHE Governing Council. She is a Serra Húnter Fellow at the Universitat Autònoma de Barcelona (Spain) and Senior Research Fellow at the Universidad de Tarapacá (Chile). Her work focuses on higher education, epistemic justice, decolonial perspectives, and inequalities in global knowledge production, particularly in Latin America.