This blog was kindly authored by Rose Stephenson, Director of Policy and Strategy atHEPI.
It is the ninth blog in HEPI’s series responding to the post-16 education and skills white paper. You can find the others in the series here, here, here, here, here, here, here and here.
There have been oodles of column inches already published about the Post-16 White Paper, and many have rightly focused on the headlines: increased tuition fees, a return of targeted maintenance grants funded by an international students levy and a move towards more specialist institutions.
In this blog, I want to dive beyond these headlines, as the paper contains a number of further bold policy proposals, some of which could be transformational for the sector.
Break points
The White Paper places a strong focus on flexible learning, including a greater number of Level 4 and 5 qualifications. There is a specific target of at least 10% of young people going into Level 4 or 5 study, including apprenticeships, by 2040. Clearly, the Government wants to see more movement in this direction from the sector, adding:
We need to build clear and well-understood pathways at these levels [4 and 5], underpinned by qualifications that are easier to study close to home, which are both modular and flexible.
In terms of higher education providers, the Government sets out:
We will expect providers to offer more flexible, modular provision and strengthen progression routes from further education into higher education, supported by transferable credits. We will consult on making student support for level 6 degrees conditional on the inclusion of break points in degree programmes. This marks a significant shift towards a more inclusive and adaptable model of learning, empowering individuals to tailor their educational journey.
There is little detail, but it reads to me that the Government will consult on a proposal that students will only be able to access student loan funding for institutions that offer ‘break points’ at Level 4 and 5 of a full three-year degree.
This was also a recommendation from the Augar report, which outlined:
… providers with degree-awarding powers will be required to offer them [level 4 and 5 qualifications] as ‘exit’ qualifications if learners choose to leave a course early.
In my experience, most institutions now do this. If a student wants or needs to finish their studies at the end of their first year, for example, (providing they have passed the required modules), the institution would offer to award them with the Level 4 qualification that recognises their learning to date – most likely a certificate of higher education. However, ‘CertHEs’ are only routinely awarded ‘mid-degree’ if a student withdraws, and many students don’t know that there is an option to take a qualification at the end of their first year. One might wonder if providers could maintain this ‘consolation prize’ status quo. However, the paper goes further, stating:
The introduction of break points will ensure that learners are acquiring vital, usable skills in every year of higher education. It will give them the option to break down their learning, achieving a qualification at level 4 after the first year and level 5 after their second year of studies, while also ensuring institutions are incentivised to support those who wish to continue their studies. This will enable young people to ‘stay local and go further’ by connecting local provision at level 4 and 5 with internationally recognised degree-level providers, unlocking opportunity and ambition across every region.
I am reading between the lines here, but it looks as though providers may be expected to award students at the end of each year of learning, increasing awareness of stackable, flexible learning, and potentially a knock-on increase in student mobility between institutions. As with much of this White Paper, we await the details.
Accommodation
The white paper outlines:
We will work with the sector and others so that the supply of student accommodation meets demand, including increasing the supply of affordable accommodation where that is needed. We will work with the sector, drafting a statement of expectations on accommodation which will call upon providers to work strategically with their local authorities to ensure there is adequate accommodation for the individuals they recruit.
Firstly, this statement is a little ironic given that the Renters Reform Act that has just passed through parliament is likely to reduce small (generally one to two bedroom) off-street student housing provision – as outlined by Martin Blakey in his blog.
This feels woolly to me. What levers does the Government have to pull to increase the supply of affordable accommodation for students? If it does have any, why have these not been pulled already? The main driver of expensive student accommodation is that there are not enough houses (for the general population as well as students), allowing rents to be driven ever higher. Providers working strategically with local authorities won’t deliver more housing stock. (Unless the magic house bush grows alongside the magic money tree?)
We’ve seen a ‘Statement of Expectations’ previously, delivered by the OfS in relation to sexual harassment prevention and response on campus. This was an evaluated stepping stone on the way to regulation. Could there be an increased expectation on institutions to provide affordable accommodation as part of future regulation? A sensible ideology, perhaps. After all, we know students want and need cheap places to live. But given the financial position of many institutions, the resulting pause in capital building projects, the increase in commuter students and the impending decline in 18-year-old population numbers, I can’t see many subsidised student flats being built anytime soon.
Apprenticeship ‘units’
We have known since before the 2024 General Election that Labour wanted to expand the Apprenticeship Levy to become the Growth and Skills Levy. We see some more detail about this in the paper:
We want employers to be able to use the levy on short, flexible training courses.
Currently, apprenticeships are funded by the apprenticeship levy. Businesses with a pay bill of over £3 million pay 0.5% of this into the levy ‘pot’. Businesses can then use the levy fund to cover the cost of training apprenticeships. Since the introduction of the levy, the number of apprenticeship starts has fallen, and the age profile of apprenticeships has changed. Since 2015, proportionately more apprenticeships have been started by those aged 25 or over.
Source: Department for Education, Apprenticeships and traineeships data
So – the apprenticeship levy was, unintentionally, a good policy for lifelong learning; businesses wanted to reinvest their levy costs into their business and found that an effective way to do this was to upskill colleagues already employed in their organisation, often on higher or degree apprenticeships. The flip side of this meant that the intended outcomes of the policy, supporting school and college-leavers into apprenticeships, were stymied.
To tackle this, most Level 7 Apprenticeships were defunded, with the aim of pushing funding back towards younger learners and lower-level apprenticeships. So the move to ‘apprenticeship units’ feels undermining of this aim. Again, this is likely to be great for lifelong learning. Employers will be able to upskill their workforce, initially in ‘priority areas’ such as artificial intelligence, digital and engineering.
There is a limited pot of growth and skills levy funding, which has been fully or overspent for the last two academic years. So if the Government wants to increase apprenticeships for younger learners, it will need to expand this pot, and potentially ring-fence some of this. The potential for a bigger pot is hinted at:
We will work with businesses and employers over the coming months to ensure that the growth in skills levy author is developed to help meet their needs and incentivise further employer investment in training.
However, ring-fencing is not mentioned. The Government will need to put some guardrails in place here if they want to meet their target of two-thirds of young people going to university, further education or a ‘gold standard apprenticeship’ by the age of 25.
Conclusion
So, while some of these statements are bold, remember that White Papers set out proposals for future legislation; there is a long way to go before legislation is in place. Further, there are several places in the white paper where the Government doesn’t specifically propose legislation; instead, there’s a sense of just asking the sector nicely. This is all well and good, but in times of severe financial constraint, asking institutions nicely to take steps that will cost them money is unlikely to yield results.
Professor Adrian Wright, Dr Mark Wilding, Mary Lawler and Martin Lowe
Published:
A new major report from HEPIand the University of Central Lancashire reveals the realities of UK student lifeand highlights how paid work is increasingly an everyday part of the student experience.
Student Working Lives (HEPI Report 195), written by Professor Adrian Wright, Dr Mark Wilding, Mary Lawler, Martin Lowe, draws on extensive research to show how students are juggling study, employment and caring responsibilities in the midst of a deepening cost-of-living crisis. The findings paint a striking picture of students for whom paid work has become a necessity, not a choice. Findings suggest two-thirds of students work to cover their basic living costs, and 26% of students work to support their families.
The report looks at the type of work students are employed in, as well as the impact this has on their study. It calls for systemic reform across the higher education sector to design a higher education that moves away from assuming a full-time residential model, and supports student realities.
Artificial Intelligence is reshaping how school administrators, from K–12 principals to university registrars, manage operations, make decisions, and communicate with stakeholders. As resources tighten and expectations rise, AI tools for school administrators offer a powerful opportunity to do more with less. In the 2023–24 school year, a growing majority of K–12 staff are now using AI tools in their work. In a recent Ellucian survey, 61% of higher ed respondents said they’re already using AI, and about 80% cited productivity and efficiency as their main reasons for adopting it.
This isn’t just a tech trend. It’s a real shift in how schools function. AI can automate repetitive tasks, surface data-driven insights, and generate personalized communications. For busy administrators, that means less time on paperwork and more time supporting students and staff.
In this article, we’ll break down how AI is transforming educational management. You’ll see practical use cases, benefits like faster decision-making and streamlined workflows, and what to watch out for when it comes to ethics and implementation. Whether you’re running a district office or managing a registrar’s team, this guide will help you lead smarter and work more efficiently, with AI as your partner.
Are you ready to improve visibility, engagement, and enrollment?
Partner with HEM for solutions designed to help your institution stand out.
How AI Enhances Decision-Making for Administrators
How does AI help school administrators make better decisions? AI’s greatest strength in school management lies in transforming raw data into clear, actionable insights. Administrators regularly face overwhelming volumes of information, grades, attendance, budget reports, and surveys that can be difficult to parse manually. AI tools help by quickly identifying patterns that support evidence-based decisions.
Predictive analytics, for example, can forecast enrollment trends or flag early warning signs. A high school principal might spot which student groups are at risk of chronic absenteeism, while a registrar could project staffing needs for upcoming semesters based on historical data.
AI dashboards make this analysis easy to interpret. They can highlight underused programs, suggest reallocating resources, or model different outcomes to support strategic planning. If an extracurricular activity shows consistently low participation, the system might recommend shifting resources to better-performing initiatives.
The result is faster, more informed decision-making. With AI as a planning partner, administrators gain a sharper view of their institution and can act with confidence and precision.
Automating Routine Administrative Tasks with AI
What routine administrative tasks can AI automate in schools? From attendance logs to class schedules, school administrators are buried in repetitive tasks that sap time and focus. AI is stepping in to take care of the busywork, streamlining operations and giving staff space to lead more strategically.
Take attendance tracking. Instead of manual entry, AI-powered systems can log student presence through smart ID cards or facial recognition check-ins. These tools don’t just record absences; they spot trends. A sudden drop in attendance? The system flags it, prompting early intervention. Some schools now pair attendance with performance data to identify at-risk students before grades slip or disengagement deepens.
Scheduling is another pain point. Building a timetable involves balancing staff availability, room assignments, student choices, and course caps. AI algorithms solve this puzzle fast. In Boston, a genetic algorithm optimized school bus routes in under an hour, cutting 50 buses and saving $5 million annually. That same principle applies to class scheduling, resource allocation, and beyond.
Report generation also gets a boost. AI tools for school administrators can pull data and format it into accurate, ready-to-send reports, such as monthly summaries, performance dashboards, and compliance logs, without human input. Even tedious data entry tasks like processing forms or invoices are simplified through OCR-powered automation.
Need to review a long policy or school social media policy? AI tools now scan, summarize, and highlight what matters. Post-meeting? Transcription services like Otter.ai generate action items and summaries within minutes.
The impact is clear: by automating the everyday, AI frees up time for what truly matters, strategic thinking, collaboration, and student support.
AI for Communication and Writing in School Administration
Strong communication is central to effective school leadership. Yet writing everything from newsletters to policy updates can eat up an administrator’s already busy schedule. That’s where AI can step in, not to replace the human voice, but to support it.
Generative AI tools like Grammarly, ChatGPT, and Jasper are helping school leaders draft clearer, more consistent communications. Do you need to send a monthly update to parents? AI can suggest section headers, polish grammar, and help set the right tone. Drafting a memo to staff? AI can create a first version that administrators can refine for local context. These tools are especially helpful when writing in a non-native language or tailoring content to a specific reading level.
They also save time on summarizing. AI can distill a lengthy school board report into a concise briefing in seconds, or help craft sensitive messages with more precision. One district principal used AI to write a winter holiday letter. The tone was spot on, but the AI mistakenly referenced sledding, forgetting the school was in a warm climate. The principal simply edited it. This type of human oversight ensures accuracy while significantly reducing drafting time.
AI’s reach extends beyond written documents. Many schools and universities now use chatbots to handle FAQs around enrollment, deadlines, and policies. Georgia State’s “Pounce” chatbot reduced summer melt by 21 percent by keeping students engaged. CSUN’s “CSUNny” improved retention by providing 24/7 support. In K–12, chatbots answer parent questions or send automated reminders, freeing staff from phone call overload.
In short, AI acts as a communication partner, speeding up writing, strengthening clarity, and helping administrators stay connected without burning out.
Key Benefits of AI in School Management
When thoughtfully implemented, AI can significantly improve how schools are run, especially for administrators balancing limited resources, increasing demands, and time-sensitive responsibilities. Here are five key advantages that AI brings to school management.
Greater Efficiency and Time Savings AI handles repetitive, time-consuming tasks such as data entry, attendance tracking, report generation, and scheduling. Automating these processes minimizes errors and frees up valuable hours for principals and support staff to focus on more impactful activities, like supporting teachers, engaging with parents, and driving instructional improvements. According to the McKinsey report, AI tools can help educators and administrators reclaim 20 to 40 percent of their time previously spent on routine tasks.
Cost Savings and Better Use of Resources Schools often operate on tight budgets. AI helps by identifying operational inefficiencies and suggesting cost-saving alternatives. AI also helps in allocating resources more wisely, whether adjusting staffing based on predicted needs or identifying underutilized facilities to repurpose. These efficiencies help schools manage tight budgets. Schools can avoid unnecessary expenditures by relying on AI analysis to guide decisions.
Smarter, Data-Driven Decisions AI systems analyze student performance, behaviour trends, and resource utilization far more quickly than a human could. For instance, if data shows that a particular grade level is struggling in math, school leaders can intervene early with targeted support. Having these insights readily available leads to stronger decisions grounded in real evidence.
Stronger, Personalized Communication AI-powered tools like chatbots and automated messaging platforms allow schools to provide timely, personalized updates to parents and students. From attendance alerts to event reminders, these systems ensure important information gets delivered and acted on, without staff needing to make dozens of phone calls or send multiple emails.
Strategic Focus and Innovation By handling operational tasks in the background, AI gives administrators more bandwidth to focus on long-term priorities. Whether that’s improving school culture, mentoring educators, or piloting new programs, leaders can spend less time buried in paperwork and more time driving change.
Challenges of Implementing AI for School Administrators
What challenges do schools face when implementing AI tools? The potential of AI in education is vast, but unlocking it requires more than just installing a new tool. For school administrators, adopting AI often brings a mix of excitement and logistical complexity. Here are the key implementation challenges leaders should be prepared to navigate.
Upfront Costs and Infrastructure Needs Launching AI systems can involve steep initial costs. Schools may need to purchase licenses, upgrade hardware, or improve network connectivity. Basic requirements like reliable internet and compatible devices can be hurdles, especially in underfunded or rural districts. While grants or partnerships may offset expenses, planning for these investments is essential.
Staff Training and Resistance to Change AI adoption means changes in workflows. Teachers, clerical staff, and leadership teams must learn how to use new tools effectively. Resistance often stems from fear of job displacement or lack of familiarity. Providing professional development, starting with small pilots, and showing quick wins are all important steps in gaining staff buy-in.
Data Integration and Quality Issues AI is only as good as the data it works with. Many schools operate with siloed or inconsistent data systems. AI needs clean, well-integrated data to function properly. If attendance, grades, or behaviour logs aren’t standardized, outputs can be skewed or misleading. Administrators may need to revamp data practices and work closely with IT teams to ensure accuracy and consistency.
Ongoing Maintenance and Oversight AI tools aren’t set-it-and-forget-it. They require regular updates, monitoring, and occasional recalibration. Schools without dedicated IT support may struggle to sustain them. Assigning responsibility for AI upkeep and budgeting for long-term maintenance are key to success.
Human Trust and Role Clarity Some staff may worry that automation threatens their jobs. Others may be skeptical of the AI’s accuracy. Administrators should communicate clearly that AI augments human work, not replaces it, and maintain human oversight to ensure outputs are reviewed and contextualized.
Addressing these challenges proactively can turn early hurdles into long-term advantages.
Ethical and Privacy Considerations with AI in Schools
Alongside technical and logistical challenges, school administrators must carefully consider the ethical implications of using AI. Because education involves minors and sensitive data, ethical missteps can have lasting consequences. From student privacy to algorithmic bias, it’s essential to put safeguards in place that prioritize safety, equity, and transparency.
Data Privacy and Security AI systems often require access to student records, health information, and sometimes even biometric data. Feeding this information into cloud-based tools or algorithms increases the risk of misuse or breaches. Administrators must ensure that all systems meet rigorous data protection standards, and that families are informed about what data is collected and how it’s used. Best practices include strong encryption, regular audits, transparent data policies, and opt-out or deletion options when appropriate. Over-surveillance, like constant monitoring or facial recognition, can also undermine trust. Schools must strike a balance between data-driven insights and preserving a respectful learning environment.
Bias and Fairness AI systems trained on historical data can unintentionally reinforce existing inequalities. Predictive models used to identify at-risk students, allocate resources, or evaluate staff must be tested for fairness across race, gender, and socioeconomic status. If unchecked, biased outputs could deepen disparities instead of correcting them. Administrators should work with vendors to ensure diverse training data and conduct regular audits of AI decisions. Involving stakeholders, teachers, parents, and even students in reviewing AI use helps bring community accountability into the process.
Transparency and Accountability Schools should avoid “black box” tools that make recommendations without clear reasoning. Any AI system used to inform decisions, like admissions or discipline, should offer interpretable outputs and allow for human oversight. Clear policies must be in place to define who is responsible if the AI makes a mistake. Human judgment should always remain central.
Academic Integrity and Human Development Generative AI tools raise new questions about cheating, originality, and learning. Administrators must set clear guidelines on acceptable and unacceptable use, emphasizing that AI should support learning, not replace it. Over-reliance on AI for writing or problem-solving can weaken essential student skills. Responsible use requires balancing innovation with the core educational mission of developing thinkers and communicators.
Equity of Access AI should not become a new driver of inequality. If only well-funded schools can afford effective AI tools, achievement gaps will widen. Public institutions, nonprofits, and policymakers must work together to promote equitable access through shared resources, training, and support. Every student deserves the benefits of smart technology, not just those in the most resourced districts.
In short, the power of AI for school management must be matched with principled leadership. Ethical implementation demands vigilance, humility, and transparency, qualities that define the best
How to Implement AI in School Administration
Bringing AI into school administration is a strategic process, not a quick plug-and-play solution. To maximize its benefits and minimize disruption, education leaders need to approach AI adoption methodically. Here’s a roadmap for successfully implementing AI in school operations.
Assess Needs and Define Goals Start with a clear-eyed look at current workflows. What drains staff time? Where are inefficiencies or bottlenecks? Pinpoint specific areas where AI could make a meaningful difference, such as automating repetitive data entry or improving enrollment forecasting. From there, define measurable goals, like reducing schedule conflicts or increasing the speed of report generation. These targets will shape your entire implementation and help evaluate success.
Example: Katy Independent School District (Texas, USA): Facing a growing administrative burden, Katy ISD recognized that its support staff were “outnumbered” by high volumes of repetitive tasks (answering routine inquiries, data entry, etc.). District leaders set a concrete goal for their AI initiative: have AI handle roughly 30% of routine administrative inquiries – with 24/7, bilingual support – so that human staff can focus on high-value interactions. This target was born from a needs assessment of where staff time was being drained. By defining this goal (30% automation of inquiries), Katy ISD created a clear metric for success and a focused vision: use AI as a virtual assistant to improve responsiveness to families while freeing staff for more complex student and parent needs.
Research and Select the Right Tools Not all AI tools are created equal. Once you’ve identified priorities, explore tools designed for education. Look for platforms that integrate easily with your existing systems (SIS, LMS, HR) and are user-friendly for staff. Prioritize solutions with strong vendor support and a track record in the education sector. Talking to peer institutions or reviewing relevant case studies can offer valuable insights.
Example: University of Richmond (Virginia, USA): In higher education, institutions are also methodical in choosing AI for administrative use. The University of Richmond explicitly notes the “transformative potential of generative AI…in enhancing administrative efficiencies”, but pairs that excitement with careful evaluation criteria. In official staff guidelines, the university directs its administrative teams to critically vet AI tools for technical fit, security, and ethical considerations. Staff are encouraged to pilot new AI-based services (from chatbots to transcription tools) in a controlled manner – checking that any chosen tool aligns with data privacy policies and the university’s values.
Start with a Pilot Choose a small-scale pilot to test your chosen tool. This might mean introducing a scheduling AI in one department or using a chatbot for financial aid inquiries. Track outcomes closely—are tasks being completed faster? Are users more satisfied? Gather feedback and refine the approach before expanding. A strong pilot builds confidence and creates internal champions.
Example: Indianapolis Public Schools (Indiana, USA): IPS illustrates the wisdom of beginning AI adoption on a small scale. In the first year of its AI initiative, the district ran a pilot with just 20 staff members using a district-approved AI tool to handle some of their tasks. This limited pilot let IPS observe real-world uses and challenges (e.g., how an AI writing assistant might help draft reports) without impacting all schools. District leaders gathered feedback and saw improvements, which informed an official AI policy in development. This phased pilot approach gave IPS the chance to refine guidelines and train users in between phases.
Train Staff and Build Buy-In Training is critical. Provide hands-on sessions, user guides, and a forum for questions. Explain how the AI will support, not replace, staff, and share early successes. Framing AI as a helpful assistant rather than a threat makes adoption smoother. Emphasize the time-saving potential and how it frees up staff for more meaningful work.
Example: School District of Philadelphia (Pennsylvania, USA): Philadelphia’s public school system, in partnership with the University of Pennsylvania, launched a first-of-its-kind AI training pilot to ensure educators and administrators were on board and prepared. The program, called PASS (Pioneering AI in School Systems), was announced in late 2024 and offers multi-tiered professional development free to a pilot group of district staff. Crucially, PASS explicitly targets mindset and skill-building: it trains district administrators on strategic planning for AI, guides school leaders on implementing AI tools in their schools, and coaches teachers on using AI to enhance (not replace) instruction.
Scale Gradually and Integrate Thoughtfully With a successful pilot in hand, plan for phased implementation. Avoid overwhelming staff by rolling out AI features in stages: first attendance, then scheduling, then reporting. Make sure each step integrates well with existing workflows. Be prepared to revise outdated processes to accommodate the new tool, and keep communication open throughout the transition.
Example: Indianapolis Public Schools (Indiana, USA): After its initial small-scale pilot, IPS is deliberately not rushing into a district-wide rollout – exemplifying thoughtful integration. The district is entering a second pilot year with more staff and a new tool (Google’s Gemini chatbot), but has held off on immediately procuring a permanent, system-wide AI platform. This restraint is intentional: IPS leaders want to ensure any AI tool is truly effective and fits their needs before integrating it into all schools. They are also developing an AI Advisory Committee (including administrators, teachers, tech, and legal experts) to guide integration and update usage policies as the pilot expands. By scaling usage gradually – first 20 staff, now a larger cohort, still not yet student-facing – IPS can adjust its data integration, security settings, and training materials in parallel.
Monitor, Measure, Improve Implementation doesn’t stop at rollout. Regularly assess whether the AI is meeting your goals. Track KPIs like time saved, error rates, or satisfaction levels. Use this data to fine-tune the system and report outcomes to stakeholders. AI platforms often improve with use, especially those built on machine learning. Feeding back your school’s data will make them more effective over time.
Example: Deakin University (Victoria, Australia): Deakin’s IT and administrative teams exemplify continuous improvement with their AI-powered student services. The university’s digital assistant “Genie” was rolled out in stages and is closely monitored for usage and performance. Since launching across campus, Genie’s user base has more than doubled within a year over 25,000 students having downloaded the app, a metric the university tracks to gauge adoption. Deakin’s Chief Digital Officer noted they analyze conversation data: at peak times, Genie handles up to 12,000 conversations a day, and they review the top categories of student questions (e.g., timetable info, assignment deadlines). By identifying the most common inquiries, the team continuously updates Genie’s responses and adds new features. This ongoing measurement extends to quality checks – the university monitors whether Genie’s answers resolved students’ issues or if human staff had to follow up, informing further training of the AI.
Foster a Culture of Innovation Successful AI integration requires a mindset shift. Leaders should create an environment where staff feel empowered to try new approaches and share feedback. Celebrate wins, learn from setbacks, and reinforce that AI is a tool to enhance human capacity, not replace it.
Example: Cottesmore School (West Sussex, UK): This independent boarding school has embraced an innovation-first culture in its administration, particularly with AI. Headmaster Tom Rogerson gained international attention in 2023 for appointing an AI chatbot as an “assistant headteacher” – named “Abigail Bailey” – to support strategic decision-making. The move was less about the tech itself and more about signaling to staff and students that experimenting with new ideas is welcome. Rogerson frames the project as a well-being and innovation initiative: the AI assistant serves as a “strategic leadership mentor,” providing impartial insights, while human leaders remain in charge. In addition to this high-profile experiment, Cottesmore has hosted free AI conferences and masterclasses for educators. For example, the school ran an “AI Festival” where staff from Cottesmore and other schools tried out AI tools and shared ideas in a collaborative environment. By openly discussing both the opportunities and challenges of AI, and even inviting outside experts to weigh in, the headmaster created a safe space for his team to be curious and creative.
Implementing AI in school administration is an ongoing journey, but with a clear strategy and commitment to collaboration, schools can unlock new levels of efficiency, insight, and impact. The result is a smarter, more responsive administrative operation that supports the broader mission of education.
Final Thoughts
AI is transforming education management by enhancing, not replacing, the work of school administrators. It takes on time-consuming tasks, delivers faster insights from data, and strengthens communication with students, families, and staff. The result is more time for leaders to focus on strategy, mentorship, and school culture.
At HEM, we view AI as a vital part of a modern, responsive education strategy. Schools that adopt AI thoughtfully are better prepared to navigate enrollment shifts, budget pressures, and rising expectations. The key is clear planning, ethical use, and keeping people at the centre.
AI gives administrators the support they need to lead more effectively. With the right approach, it can elevate the quality and impact of school leadership.
Are you ready to improve visibility, engagement, and enrollment?
Partner with HEM for solutions designed to help your institution stand out.
Frequently Asked Questions
Question: How does AI help school administrators make better decisions?
Answer: AI’s greatest strength in school management lies in transforming raw data into clear, actionable insights. Administrators regularly face overwhelming volumes of information, grades, attendance, budget reports, and surveys that can be difficult to parse manually. AI tools help by quickly identifying patterns that support evidence-based decisions.
Question: What routine administrative tasks can AI automate in schools?
Answer: From attendance logs to class schedules, school administrators are buried in repetitive tasks that sap time and focus. AI is stepping in to take care of the busywork, streamlining operations and giving staff space to lead more strategically.
Question: What challenges do schools face when implementing AI tools?
Answer: The potential of AI in education is vast, but unlocking it requires more than just installing a new tool. For school administrators, adopting AI often brings a mix of excitement and logistical complexity.
Join HEPI for a webinar on Thursday 11 December 2025 from 10am to 11am to discuss how universities can strengthen the student voice in governance to mark the launch of our upcoming report, Rethinking the Student Voice. Sign up now tohear our speakersexplore the key questions.
This blog was kindly authored by Professor Colin Riordan, Secretary General, The Association of Commonwealth Universities.
Governments throughout the Commonwealth are faced with a familiar dilemma. Once seen as central to nation-building, poverty reduction and technological self-sufficiency, universities in many countries face scepticism and waning public support. At a time when cost of living pressures are relentless, institutions are increasingly seen as ‘a kind of elite luxury that the taxpayer pays for’, as Michael Ignatieff recently put it. But that narrative misses the point. New evidence shows that investment in higher education delivers measurable, long-term economic growth – the kind that no government can afford to ignore.
Education as economic infrastructure
The evidence is revealed in a new study, undertaken by London Economics at the request of The Association of Commonwealth Universities, to investigate the link between investment in higher education and economic growth.
The study found that a hypothetical 1% increase in the proportion of the population obtaining tertiary education qualifications (tertiary attainment) in 2025 would boost Commonwealth GDP by US$28 billion in 2029. That’s in addition to further increasing annual gains along the way, a clear sign that higher education returns compound over time.
Why does this matter? Well, it is clear that many, if not all, of the pressures on universities stem from a paucity of resources following on from the 2008 financial crisis (from which many large economies have still not recovered); from the Covid pandemic; and from an upturn in conflicts across the world that are costly drains on the public purse. The difficulties are exacerbated by locally specific problems, including natural disasters such as drought, flooding, and extreme weather events, as well as political events such as Brexit, trade wars, and political instability.
Governments have to find ways to restore their position in the face of these headwinds, and higher education can easily be depicted as part of the fiscal problem rather than of the solution. Demonstrating the return on investment in higher education will allow education ministers to go well-armed into the conference chamber with their finance ministers and national leaders.
Beyond the balance sheet
There are other economic arguments for universities, of course. Their knock-on effects through research and innovation, as employers, and as attractors of foreign direct investment, all come in addition to their core educational function. Universities improve public health outcomes, generate productivity gains, and strengthen civic life. But making the case for higher education as central to national prosperity is essential at a time when governments are facing seemingly intractable difficulties.
The message, then, is clear: far from being a luxury perk for the elite, expenditure on higher education is an investment in critical national infrastructure. Building opportunities in higher education equates to building a road to future prosperity. Unlike eye-catching projects involving new roads, railways, bridges or airports, however, increasing the proportion of the population with higher education qualifications requires a leap of the imagination, and an array of arguments to be marshalled.
Certainly, a clear vision of how the world will be different as a result of such an investment is critically important. Voters and populations want to know what difference more university places will make to their lives. It is up to politicians to set out that vision, but they themselves must first be persuaded, and so we must marshal further helpful arguments to support them.
A shared responsibility
Firstly, the investment does not have to come solely from the public purse. Tertiary attainment is the proxy that implies prior increases in expenditure on higher education, which could include private investment, partnering with overseas institutions, changing the proportion of the cost for which the individual is responsible, or imaginative loan schemes. Reformulating incentives and requiring efficiencies could certainly be in the mix. So, no education minister should need to envisage themselves going cap-in-hand to the finance department.
On the contrary, they can offer the prospect of contributing to the public coffers in due course. Depending on the size of the country and the proportion of tax take, this could range from the US$ billions in a country like India to hundreds of millions in Bangladesh and many tens of millions in Kenya.
A call to reimagine policy
In a country like the UK, the GDP boost of a hypothetical 1% increase in tertiary attainment in 2025 would amount to £4.9 billion in 2029. This means that increasing capacity in higher education is fiscally prudent as well as being the most important tool we have to future-proof the economy and improve productivity in an age of AI-driven technological transformation. But in low-income countries, the multiplier effect is even higher, and so the argument for investment is stronger still.
Commonwealth countries with rapidly growing youth populations face an urgent need to expand tertiary access if they are to harness their demographic dividend. Targeted investment in higher education is one of the most effective levers to drive inclusive, sustainable economic growth. The evidence supports stronger collaboration between governments, universities, and international funders to build tertiary systems that deliver for national economies.
With all necessary caveats in relation to correlation versus causation, the results of the London Economic analysis are compelling. Governments that embed higher education policy into national economic planning and industrial strategies, and invest in universities as economic assets and hubs for talent development, innovation and productivity, will do more than balance their budgets: they will secure their future.
This blog was kindly authored by Naomi Lumutenga, Executive Director and co-founder of Higher Education Resource Services (East Africa).
Despite commendable interventions in recent decades, a gendered leadership gap persists at varying levels within higher education institutions. In 2024, women led 27% of the top 200 universities in the US; 36% in the top UK universities; 55% in the Netherlands’ top 11; and 29% in Germany’s top 21. In contrast, female leadership was far less common in Sub-Saharan Africa: only two of Ethiopia’s 46 universities, two of Tanzania’s 60, and six of South Africa’s 26 public universities were headed by women. While some may argue that comparisons with Western institutions are unfair due to their longstanding systems, the disparity highlights persistent structural barriers to gender parity in university leadership. Shifting focus from individual to organisational transformation can deliver change. As an example, long-standing financial systems have been leapfrogged. Currently, it is quicker to wire money to and within many African countries, compared to Europe or the USA. Linear comparisons along time periods, to effect change, do not, therefore, tell the full story; the real focus should be on the political will from within universities to acknowledge the value in and shift leadership towards gender parity.
Our organisation, (Higher Education Resource Services East Africa) addresses gender equality in universities, as these institutions shape future leaders. Prestigious institutions like the University of Oxford have produced multiple prime ministers and policymakers across the globe, as the recent HEPI / Kaplan Soft Power Index demonstrates. In East Africa, notable alumni of Uganda’s Makerere University include past and serving national leaders like veteran Mwalimu Julius Nyerere and Benjamin Mkapa (Tanzania); Mwai Kibaki (Kenya); Paul Kagame (Rwanda); Milton Obote (Uganda); and Joseph Kabila (Democratic Republic of Congo). However, Makerere University (unlike the University of Oxford) has never had a female Vice Chancellor.
The structure and landscape of such institutions matter because they model frameworks and practices for the communities they serve. The persistent unequal representation triggered the work of HERS-EA that culminated, in part, in our recent publication.
Findings from our unpublished study conducted in 2024 across 35 universities in East Africa illustrated the situation starkly. This study was conducted by Makerere University in collaboration with HERS-East Africa, supported by the Bill and Melinda Gates Foundation. The aim was to analyse the underlying barriers that prevent women from progressing into leadership and, for those who advance, from thriving. While some of the findings might be culturally unique to East African contexts, the majority were acknowledged, at the annual Engagement Scholarship Consortium conference in Portland, USA (October 2024), as being relevant to any higher education institution. In Japan, for example, there is evidence of cultural pressure exerted differently when women seek promotion; as Kathy Matsui asserts, women decline promotional offers for fear of how they might be treated when/if they get pregnant.
Our study of premier universities in East Africa found that, despite gender equality policies, female leadership remains rare: only two of seven top universities had a female Chancellor (a ceremonial role), none had a female Vice Chancellor, and just one had a female Deputy Vice Chancellor (who was nearing retirement). With respect to enrolment, while most institutions claimed gender parity at admission, few tracked or reported gender disaggregated data at graduation or PhD completion, and evidence of tracking progress was limited.
PhDs, research leadership, and grant management are important for university leadership, so we highlighted these areas and addressed implicit institutional norms. Drawing on these lived experiences, we concluded that gender discrimination in university leadership persists through biased job criteria, age limits, and interview questions. Other barriers include a lack of accountability, inadequate strategies against sexual harassment, and poor support for women to complete PhDs.
Co-created recommendations included trialling an adapted equivalent of the non-punitive Athena Swan Charter, which develops a culture of self-assessment while mitigating potential backlash. The Athena Swan Charter was initiated in the UK in 2005, and it is gaining global traction. It provides a sliding scale of progression towards gender equality, from bronze to silver and gold. Other proposed interventions included providing writing bootcamps with childcare and research advisors present, away from family and other distractions. Aspects of the quota system and structural frameworks in Scandinavian countries were discussed, but while lessons can be learnt from these transformational shifts, the real stumbling block is the lack of political will for changing norms rather than individual women within East African institutions. However, change is possible. Rwanda’s post-1994 Genocide national policies include quotas, and they are revised every three years to assess progress towards gender equality in all sectors. Currently, women hold 61.3% of the total seats in parliament, and they occupy 66% of the total seats in cabinets. Overall, Rwanda is now considered one of the best achievers in the world for gender equality. Perhaps lessons can be learnt from Rwanda’s progress that can give us all reason to hope.
Join HEPI for a webinar on Thursday 11 December 2025 from 10am to 11am to discuss how universities can strengthen the student voice in governance to mark the launch of our upcoming report, Rethinking the Student Voice. Sign up now tohear our speakersexplore the key questions.
This blog was kindly authored by Dr Gary Jones, Dean of Student Success and Experience, Scholars School System, Dr Steve Briggs, Director of Learning, Teaching and Libraries, University of Bedfordshire, Professor Graeme Pedlingham, Deputy Pro-Vice Chancellor for Student Experience, University of Sussex, Dr David Grey, UKAT Chief Executive Officer and Professor Abigail Moriarty, Pro Vice-Chancellor Education & Students, University of Lincoln.
A recent analytic induction study (Grey & Bailey, 2020) defined personal academic tutoring in UK higher education as a “proactive, professional relationship between student and tutor sustained throughout the entire student journey.” This partnership involves “dialogue, metacognition, and a structured programme of activities” aimed at fostering student agency, self-efficacy, independent learning, and career and future goals.
Personal academic tutors play a crucial role by supporting students to “assimilate to the university environment”, facilitating learning and decision-making, reviewing progress, and providing essential information. They enhance both academic ability and emotional well-being through holistic support during one-to-one or group meetings at key academic moments. Personal academic tutors are described as “knowledgeable, approachable, helpful, patient, caring, reliable and non-judgmental” staff members who possess the skills to actively listen, instruct, and advise. They play a crucial role in supporting student success and outcomes.
HE size and shape is changing
The increasingly perilous position of economic sustainability in the UK higher education sector has meant that a growing number of institutions are instigating reviews of their ‘size and shape’. In turn, many providers face some tough decisions around what should be prioritised. We anticipate that multiple university senior leadership teams may review academic workload plan allocations during the 2025/26 academic year to ensure that academic staff time can be optimised. As such, consideration may be given to changing time allocations to prioritise teaching preparation and delivery, assessment, and research over personal academic tutoring. We argue that teaching and research should not be treated as more important than personal academic tutoring when allocating time. Nor should teaching and research time be reduced in favour of personal academic tutoring. Rather, we argue for equivalency and that time allocation for personal academic tutoring is an activity institutions should seek to protect, not cut.
The value of university education has become a sharper and often more critical question in media narratives, as well as for people considering studying in higher education. With the increasing cost of living and studying at university, the question of how universities can make the benefits to students as visible as possible is understandably at the forefront of many of our minds. We argue that personal academic tutoring is a critical part of achieving this through a strategic, purposeful, proactive, and student-centred approach that is informed by data rather than risking falling into a reactive approach.
The impact and benefit of personal academic tutoring
Personal academic tutoring plays a fundamental role in enhancing attainment and impacts the Office for Students’ metrics, which determine institutional success (such as the Teaching Excellence Framework, National Student Survey and Postgraduate Taught Experience Survey). Effective tutoring can be measured in many ways, but not least of these is the positive benefits for helping students to stay on course and be successful, directly supporting those key B3 continuation and completion rates. Effective personal academic tutoring is therefore a virtuous circle for improving student outcomes and experience, and can help give direct evidence of value to both current students and potential applicants.
Meaningful individualised relationships that encompass the entirety of a student’s learning journey are fostered through effective personal academic tutoring. Successful tutors nurture a sense of belonging and mattering, aid in navigating the complexities of the higher education study experience, cultivate vital analytical and transferable skills, and impact student career aspirations and employability. At its best, personal academic tutoring transcends traditional teaching methods by facilitating purposeful, structured interactions outside of learning, empowering student agency and promoting the holistic development of all students. As highlighted by NACADA, teaching beyond the curriculum and discipline can help to bring together and contextualise students’ educational experiences in terms of extending aspirations, abilities and lives beyond campus boundaries and timeframes.
Academic workload planning and personal academic tutoring
A recent UKAT senior leaders’ network group meeting provided a forum for discussions regarding allocating dedicated resources for personal academic tutoring in universities. Here, we explored the variation and inconsistencies across the sector regarding how universities operate their personal academic tutoring in terms of academic workload planning. Members reported that across institutions, resource allocation was often determined locally but was driven by central university policy. As the group engaged in thought-provoking dialogue, a critical question emerged: If we genuinely value the importance of learning beyond the traditional subject curriculum, why is personal academic tutoring often not prioritised to the same extent as other activities in the initial stages of academic workload allocation?
The case for a personal academic tutoring first mindset
Recognising there are institutional differences, possible common ways of addressing this challenge were discussed, considering the aforementioned financial constraints facing the HE sector. Abi presented to attendees a cup metaphor for academic workload planning based on her previous work. This suggests that, given the significance of personal academic tutoring on student outcomes, personal academic tutoring time should be the first thing built into an academic’s workload plan. She noted, however, that this is often not the case and time allocation for personal academic tutoring may be the last thing added into the workload ‘cup’ (behind teaching, assessment and research), in turn causing the cup to overflow and damaging the significance associated with personal academic tutoring. There was an overwhelming consensus that we should all adopt a personal academic tutoring first ethos in terms of academic workload planning. Accordingly, we encourage readers who will be undertaking academic workload plan reviews over the coming months to reflect on how they allocate personal academic tutoring time, particularly if personal academic tutoring has not historically been the first pour into the workload cup.
This blog was kindly authored by Professor Roger Brown, the former Vice Chancellor of Southampton Solent University and Dr Helen Carasso, Honorary Norham Fellow of the Department of Education at the University of Oxford. Their previous book, Everything for Sale? The Marketisation of UK Higher Education was published by Routledge in 2013.
It is eighth blog in HEPI’s series responding to the post-16 education and skills white paper. You can find the others in the series here, here, here, here, here, hereand here.
We need a reset to ensure the system can play its critical role in delivering provision aligned to the government’s growth and Industrial Strategy ambitions, support training at scale, deliver opportunity and outcomes for all, and reduce the persistent gaps in outcomes for the most advantaged students.
(HM Government, 2025, p.46).
As this statement of intent shows, the post-16 Education and Skills White Paper published last month has ambitious aims for the higher education sector in England. These are framed in the context of a wide range of proposals covering not only higher education but also further education and what used to be called ‘industrial training’. So far as higher education is concerned, the main proposals are:
To promote greater provider specialisation, including through greater collaboration
To increase financial sustainability and efficiency
To improve access and participation
To strengthen the incentives on providers to promote growth
To improve quality
Specialisation and collaboration
The Government wants to see greater specialisation: ‘over time there will be fewer broad generalist providers and more specialists’ (p.49). The White Paper seems to envisage two types of specialisation (a) by broad orientation, ‘teaching only’, ‘research’ and ‘teaching with applied research in specific disciplines’ (p.49) and (b) by discipline ‘a provider may decide to specialise across multiple disciplines or to focus on one or two where they are strongest’ (p.49). It is not clear how this will be achieved, but the White Paper speaks of ‘incentivising a more strategic distribution of research activity across the sector’ (p.50). This would be done through reforms to research funding. There will be a more permissive approach to collaboration on the part of the regulators. The Government declares that it will work with the Office for Students ‘to ensure there is a more robust process for market entry’ (p.50) but nothing is said about market exit.
Financial sustainability and efficiency
The White Paper confirms the earlier announcement by the Secretary of State that the undergraduate tuition fee cap for all providers will be increased in line with forecast inflation in the academic years 2026-27 and 2027-28. These ad hoc increases are intended to support the financial sustainability of institutions until legislation can be put in place to make such increases automatic. The Government will work with the sector to improve research cost recovery, with measures including improvements to TRAC (Transparent Approach to Costing) and support for collaboration and sharing of infrastructure. The White Paper also notes the potential of AI for dramatic improvements in research productivity. However, future Government support for research will be tied to ‘three distinct priorities’:
Protecting and promoting curiosity-driven research; supporting the delivery of government priorities, missions and the Industrial Strategy; and providing targeted innovation, commercialisation and scale-up support to drive growth.
(p.50)
Moreover, improving cost recovery may ‘result in funding a lower volume of research [but] at a more sustainable level’ (p.52) and the research assessment system will be reformed ‘to better incentivise excellence and support the Government’s vision for the sector’ (p.53).
Improving access and participation
There are signs that the Government has registered the scale of the financial pressures on students with maintenance loans increasing with forecast inflation each year. Means-tested maintenance grants for students from the lowest income households (funded by the new International Student Levy) will be introduced. However these will be confined to those who are studying courses that support the Government’s missions and Industrial Strategy. The long-awaited introduction of modular teaching funding through the Lifelong Learning Entitlement (LLE) will also be focused on ‘key subjects for the economy, informed by the Industrial Strategy’ (p.56). However, given that the LLE model is to be used to operate loans for all eligible home undergraduates, it is unclear what this will mean in practice.
To reduce administrative burdens, the regulation of Access and Participation Plans will be refined to focus on those parts of the sector where there is the greatest room for improvement. The Government will ‘develop options to address cold spots in under-served regions and tackle the most systemic barriers to access’ (p.57). It will also explore the reasons for the declining proportion of UK doctoral applicants in some fields. This could include reducing the financial barriers for those from lower socio-economic backgrounds.
Incentives for growth
The Strategic Priorities Grant will be reformed so as to align with the priority sectors that support the Industrial Strategy, the Government’s Plan for Change and future skills needs. Providers will be expected to review their curricula to increase flexibility and strengthen progression. Student support (i.e. eligibility for SLC loans) for Level 6 courses may be made conditional on the inclusion of accredited break points in degree programmes. Universities will be required to engage with Local Skills Improvement Plans. There will be ‘a new market monitoring function, drawing together key datasets to provide a clear, single picture of higher education supply and demand’ (p.61).
The Government has protected the overall funding of UKRI (at £8.8bn). It will continue to ensure that there is ‘the right balance’ between the three research funding priorities. Some of UKRI’s funding will be ‘pivoted to align to areas of strategic importance as described in the Industrial Strategy sector plans’ (p. 62).
The country’s ‘global leaders’ will be placed on a more sustainable footing through the linking of fee cap increases to quality (as discussed below) and the projected improvements in research cost recovery. The Government will work with the sector ‘to maintain a welcoming environment for high-quality international students’ (p.63). However, there will be tighter enforcement of visa approvals and monitoring of international students’ course enrolments and completions. Finally, providers will be encouraged to develop ‘civic plans’ that fit with their strengths and priorities.
Improving quality
Even though three-quarters of providers received Gold or Silver ratings in the last (2023) TEF, ‘we need to raise the bar across the system…with pockets of poor provision undermining the reputation of the sector’ (p.64). On the REF, the White Paper acknowledges the risk that research funding and assessment frameworks can incentivise ‘perverse behaviours’ with publication becoming ‘the main aim’ (p.65) (why did it take them so long?).
There will be an increase in the OfS’s capacity to conduct ‘quality investigations’. Ultimately, the Government will legislate to ensure that the Office is able to impose recruitment limits where growth risks poor quality and future fee uplifts will become conditional on providers achieving a higher threshold through the Office’s quality regime.
The Government will work with UCAS, the OfS and the sector to improve the quality of information for individuals ‘informed by the best evidence on the factors that influence the choices people make as they consider their higher education options’(p.66). An OfS review of its approach to degree awarding powers will include the role of external examiners and ‘the extent to which recent patterns of improving grades can be explained by an erosion of standards, rather than improved teaching and assessment practices’ (p.67). Employers will be consulted on whether the academic system is giving graduates the skills and knowledge they need for the workplace (p.67). Using the model of Progress 8 in the schools, the Government will work with the OfS to develop options for measuring and comparing progress in higher education.
The Government will also consider its approach to research assessment ‘to ensure it meets our needs and ambition for research and innovation’ (p.68). There will be a pilot ‘to seek better information on how our strategic institutional research funding is used’ (p.68).
The White Paper in its historical context
In our forthcoming book Every Student Has Their Price: The Neoliberal Remaking of English Higher Education,to be published by Policy Press next year, we identify the progression of reforms that have enable the marketisation of English higher education. These reforms to funding, regulation and market entry have enabled a significant growth in the number of competing higher education providers to more than 400 (see the December 2023 HEPI Debate Paper Neoliberal or not? English higher education in recent yearsRoger Brown and Nick Hillman).
The White Paper vigorously reaffirms the official view, evident in the 1985 Green Paper The Development of Higher Education into the 1990s (Department for Education and Science, 1985) that the role of higher education is first and foremost about meeting the needs of the economy: what Salter and Tapper many years ago termed ‘the economic ideology of higher education’ (The State and Higher Education, 1994). But whereas most previous White Papers have at least paid lip service to the wider functions of higher education this one doesn’t even bother. It is, in fact, the most wide-ranging attempt yet to tie the future development of the sector to the Government’s perceptions of the present and future requirements of the economy, and specifically the presumed requirements of the labour market.
The White Paper’s impacts can be expected to mostly reinforce those of the earlier reforms in at least six areas: demand and equity, supply, funding, the higher education workforce and the system.
Demand and equity
The White Paper is silent on the future size of the sector. So far, the neoliberal reforms have done little to check the huge increases in numbers and participation rates that we have seen. Nor have they made much difference to the continuing gaps in participation by different social groups or the tendency for students from wealthier backgrounds to go to better-resourced institutions. This is because – as nearly every independent analysis has shown – the major barriers to wider participation lie much further back in the education system and these in turn largely reflect the structure of our society and economy. So it is very hard to see the White Paper proposals making much difference to access or demand. But there are one or two warning signs. The stipulation that maintenance grants will be restricted to students on courses closer to the Industrial Strategy will not only constrain student choice but perhaps also reinforce the divisions between higher and lower tariff providers that were exacerbated by the abolition of the numbers limits in 2015. Is there perhaps another potential binary line here, with better off students free to pay to study humanities and social science at wealthier and more prestigious institutions and go on to well-paid jobs in the City or the professions, while poorer students are obliged to study ‘practical and applied’ subjects at less well resourced and less prestigious ones?
Supply
It is striking that there are no proposals for expanding the number of providers, indeed the White Paper envisages toughening the rules for market entry, as we have seen. The Government appears to assume that it will be existing providers that will cater for the cold spots in under-served regions, rather than new ones. This will at least mean some greater stability.
Funding
It seems highly unlikely that the proposals for fee indexation will be sufficient to redress the post-2016 funding squeeze, wean universities off of their reliance on international student fees (even without the tax represented by the International Student Levy) or restore the unit of resource in real terms. UUK analysis suggests that there will be an overall £2.5bn reduction in sector funding across the academic years 2024-25 to 2026-27 compared to 2023-24. Whilst the intention to improve research cost recovery is welcome, it will almost certainly be insufficient to reverse the long-term decline in research funding since 1980, and indeed the Government partially accepts this.
This combination of some additional funding, together with a strong drive towards increasing efficiency and encouragement for institutions to consider specialisation, collaboration and restructuring as options, is placed within the context of recognition that ‘the higher education sector is rightly and proudly autonomous’(p.53). This freedom, the Government states, has its consequences, so ‘the leadership of the sector must take responsibility for managing their institutions robustly and in the public interest’ (p.53). The OfS will therefore be supported to tighten the management and governance requirements of institutional registration. Indeed, there will be a ‘….focus on targeting sharp regulation where it is most needed, to drive the positive change required to maintain our world-leading higher education system.’ (p48)
Quality
The White Paper notes some of the quality issues that have arisen over the period, including grade inflation and (some) sub-contracting (franchising), most of which are in fact due to the combination of increased competition and reduced funding that has characterised the period of the reforms. The proposal that future fee increases should be linked to quality raises as many questions as it answers. Whilst this idea has often been floated in the past, it has not been seriously applied in the UK since the days of the Polytechnics and Colleges Funding Council when sector committees advised the funding council on the allocation of additional funded student numbers to ‘deserving’ institutions on a broadly disciplinary basis.
The proposal that the OfS should be able to confine future fee uplifts to ‘providers achieving a higher quality threshold through the OfS’s quality regime’ is also par for the neoliberal course. The potential weight that this places on TEF outcomes makes the current review of the exercise even more crucial, including the importance of designing a process that acknowledges the role of a variety of institutions offering forms of education that might be different but not automatically ‘better’ or ‘worse’.
The proposal that the OfS should review the degree awarding powers process and the role of external examiners in protecting standards also raises many questions. But the issue is the same, namely, how and to what extent can the traditional ways in which the academic community has, generally, successfully guarded its standards resist the combined pressures of competition, consumerism and inadequate funding.
The proposals on information for students continue with the hopeless – in the authors’ view – quest for the Holy Grail of information that will quickly and cheaply enable students and other ‘users’ of the system to make reasonable choices about subjects, courses and providers, the insuperable difficulties of which were explained at length in the HEPI Debate Paper referred to earlier. Similarly hopeless is the idea of a progress measure for higher education along the lines of Progress 8 in the schools. We can only sympathise with the hapless individuals who will be tasked with taking these ideas forward.
The proposal to review research assessment raises concerns that future exercises could be tilted, like research funding, towards greater emphasis on (a) impact, and (b) subjects considered most relevant to the Industrial Strategy. Haven’t the reforms to increase the role of impact in research assessment over the years already gone far enough?
Staff
The White Paper breaks new ground in one respect at least, in that the position of staff, and in particular the precarity of many early career researchers, is mentioned. However, what will happen here will depend very much on how much of a financial recovery there will be (if any), on how much system restructuring takes place and on what form any increased collaboration takes. If this takes the form of institutional mergers, we can expect more redundancies and potentially worsening of terms and conditions. The experience of mergers in HE indicates that the only significant, permanent savings come from disposing of assets: any savings on things like shared services are offset by the greater costs of the managerial coordination required.
The system
The Government clearly hankers after a more streamlined system that is both more efficient in its use of resources and offers a wider, or at least clearer, set of choices for students, employers and other ‘users’. As with so many other aspects of the White Paper we have been here before. In the early 1980s the old University Grants Committee consulted on designating the existing universities as ‘R’, ‘X’ or ‘T’, depending on their research intensity. The proposals were universally rejected. In the early 2000s, HEFCE toyed with the notion of dividing institutions into separate and distinctive groups depending on their overall orientation, but this also foundered. The institutions were almost all strongly opposed, the criteria and data for selection were insufficiently robust to be a basis for policy and the Funding Council anyway lacked the necessary powers. The same seems likely to be the case here, especially given the renewed emphasis on institutional autonomy built into HERA(2017).
Where does the sector go next?
In our forthcoming book, we argue that the post-80s reforms of higher education in England are a reflection of the key planks of neoliberalism: privatisation, marketisation and reduced claims on the taxpayer. The press release accompanying the White Paper speaks of it being a ‘landmark statement’. This it certainly is, if not in the sense seemingly meant by its authors. If the essence of neoliberalism is the subordination of all social and cultural activities to the needs of the economy, then this is indeed a ‘landmark’ document of which the authors of neoliberalism would have been justly proud.
This blog was kindly authored by Joseph Morrison-Howe, former HEPI intern and recent graduate of the University of Nottingham. This blog is the seventh blog in HEPI’s series responding to the post-16 education and skills white paper. You can find the others in the series here, here, here, here, here and here.
Tuition fees rising with inflation serves as a reminder that going to university is a significant financial commitment for the student. In the recent Post-16 Education and Skillswhite paper, the Government commits to making higher education more skills focused because ‘there is a disconnect between what individuals choose to study and the needs of the economy, which limits people’s earning potential’. To achieve this, the Government seems to be leaning towards interventionalist policies. However, since the individuals themselves are involved in a financial decision, then presumably the Government’s desire for growth – that is, boosting average incomes – is largely not at odds with the individual. Therefore improving knowledge and access to information, which makes the individual’s decision more informed, is a viable alternative to interventionalist policy, and the Government’s commitment to providing graduate earning’s data on UCAS could lead the individual to choose courses with higher earnings should they want, which is in line with the Government’s aims whilst improving choice rather than curtailing it.
The Ministerial Foreword to the white paper states that the Government’s ‘defining mission’ of growth ‘relies on providing real opportunities through education and training that lead to real careers.’ In terms of policy, this aim seems to be taking the Government in an interventionalist direction, in an attempt to align what they see as the skills required in the economy with the skills being learnt in post-16 education. For example, by making the modular use of Lifelong Learning Entitlement conditional on the chosen course being aligned with the Government’s Industrial Strategy the Government hopes to create a workforce that is more productive in the jobs that the labour market demands. A more productive workforce is one associated with higher incomes, and so by pushing people towards the skills set out in their Industrial Strategy, the government hopes to achieve growth.
Interventionalist policies such as this, although moderate, can have adverse effects, however. Through the above policy, the Government might succeed in fixing the mismatch of skills learnt and skills demanded by the economy. However, the government cannot consider how happy an individual will be from entering a particular profession, and thus, by prioritising financial returns over choice, the welfare of individuals may be neglected.
It is worth remembering that for each individual, going to university is a financial commitment, but there are several reasons why it is difficult to make an informed decision about the financial aspect of going to university. The financial decision comprises the costs and gains of attending. The costs are difficult to determine because repayment is determined by future earnings, which at 18 is a distant and uncertain prospect. The financial gains are likewise uncertain because of the huge variety between courses as well as individuals, but this uncertainty can be limited. In England, there is a lot of data available on average graduate earnings by course and educational institution. This information is currently available on the Discover Uni website, but is very rarely accessed (see Imperfect Information in Higher Education). Perhaps the disconnect discussed in the recent white paper ‘between what individuals choose to study and the needs of the economy’ could be fixed to some extent by ensuring that when individuals choose what to study, they are in an informed position about earning differentials associated with different courses and institutions. This way, the prospective student has the capacity to make an informed financial decision, but still has complete freedom to study without it being a solely financial decision.
In the white paper, the Government has committed to integrating graduate earnings data into the UCAS website, ensuring the data will be seen and used by more prospective students, as proposed in Imperfect Information in Higher Education. This approach of helping individuals make an informed choice about what and where to study, rather than taking a more interventionalist approach, as a way of fixing the disconnect between study and the skills demanded by the economy, is valuable because it preserves individual choice. Someone who values high pay in return for their studies could use this graduate earnings data to ensure that the course they choose has the capacity to provide this. Someone who wishes to study for the sake of the subject, or someone who wants to study something that leads to a particular low-earning job because it will make them happy, has complete freedom to make this choice. This policy, by preserving choice and improving access to information, can promote government aims such as growth whilst letting people choose what they want.
This blog was kindly authored by Andy Westwood, Professor of Public Policy, Government and Business at the University of Manchester. It is the sixth blog in HEPI’s series responding to the post-16 education and skills white paper. You can find the other blog’s in the series here, here, here, here and here.
Now we’ve had time to consider the post-16 white paper, we can think seriously about implementation and what’s needed to deliver its vision. Both in the governmental architecture that will oversee and drive it, and in the universities and colleges charged with its delivery. We know the overall vision is broad – the Departments for Education; Science, Innovation & Technology; and Work & Pensions have signed the strategy, but Business, the Treasury and the Home Office also retain interests in its success. As Philip Augar notes in the Financial Times, it’s right to prioritise such a ‘system-wide approach’. Labour will be hoping these proposals, alongside their industrial strategy, endure for the longer term and support both economic growth and improved living standards. But as Augar and Theresa May know, this cannot be guaranteed.
Overall, it’s a radical shift from the last decade in three specific ways – first bringing them all together into a coherent whole; second for a single system to be more planned and coordinated than market driven; and third, to intervene, shape and direct both institutions and provision within it.
Trailed in the PM’s conference speech in Liverpool, the white paper offers an expansive tertiary vision – with both R&D and welfare alongside teaching and learning. But ‘tertiary’ isn’t the term the Government prefers, and it doesn’t feature in the document nor in the speeches and statements that have launched it.
Nevertheless, the shift from markets and competition to specialisation, collaboration and direction is quite a departure from the reforms of 2010 and 2017. Not just scaling back competition between different institutions, but also the central assumption in the 2017 Higher Education and Research Act that new providers would be the ‘rising tide lifting all boats’ or that ‘market exit’ and institutional failure would be necessary parts. In place comes the Industrial Strategy and missions, deliberately driving the broader system, including both teaching and learning and research.
But how do we get from here to there? The white paper relies on a host of actors – colleges, universities, employers, individual learners – responding positively. It also requires dramatically improved coordination across government – not just across Whitehall but also between the agencies where much work will take place, including the Office for Students, UKRI, Mayoral Authorities and Skills England.
It is ambitious because this new vision is grafted onto existing infrastructure as well as to systems, incentives and behaviours. In particular, the OfS now has enhanced roles and powers, index-linked tuition fees, the access agenda, and the LLE. UKRI remains largely intact, but is also charged with directing more of its funding towards new government priorities. For all the complaints and problems, institutions have become used to these systems and cultures. For some, there may be enough to carry on as they are – managing risk and maximising income with current models, rather than adapting their existing strategies.
But the government wants to see change, setting priorities across both the economy and public services. There will be legislation – necessary to index fees but also to consolidate extra powers and levers across the whole post-16 system so that government can drive priorities more deeply and quickly. If specialisation and innovation aren’t happening quickly and skills aren’t being driven into the most important firms and sectors, then they can be ramped up. In neither economic nor political terms can the government afford to hang around.
But driving the system in particular directions requires a practical understanding of places, economies, firms and people that a more market-led system does not. This has to be created (or recreated), and the white paper relies on a mixture of recommendations – enhancing the powers and capacity of OfS and UKRI and also creating Skills England, the Industrial Strategy Council and the Labour Market Advisory Board.
As crucial to the reconfiguring of the broader architecture will be the priorities and institutional strategies of colleges and universities. Innovation, specialisation and growth cannot all be mandated from above. Successful industrial strategy and economic growth will also depend on strong institutions working strategically and creatively together with firms, sectors and in clusters. It will be these day-to-day relationships and actions that determine the ultimate success of the white paper’s vision.
This will be an important issue for existing colleges and universities, but also as new institutional forms emerge – ‘super’ or collaborating universities, new specialists and all when expected to come together in particular regions and places.
A lot depends on a reconfigured OfS, grafting these new powers onto existing remits and also building new capacity to drive change in FE, including at Levels 4 and 5 and through new Technical Excellence Colleges. Much will involve rediscovering the techniques and networks that HEFCE deployed. Often, this included sector expertise and the appointment of Derby Vice Chancellor Kathryn Mitchell to lead a review of ‘cold spots’ is a promising step.
It will be hard work and will involve building new capacity, incentives and insights, as well as rewiring governance, funding and regulation. But it will also require institutions to committo building new capacity and to develop strategies that can translate new objectives into practice. While many have planning and policy capacity, too much is tied up in compliance. So if we are building a system that, in the words of Michael Heseltine is ‘intervening before breakfast, lunch, tea and dinner’ – then we’d better make sure there is institutional appetite and capacity with which to do so.
The stakes are high. This isn’t just a new technical vision for delivering skills or knowledge to meet the needs of employers. Markets and competition have not helped us break out of the economic doom loop endured since the financial crisis. In turn, this has damaged the fabric of society as well as the life chances of too many people and places within it. Both colleges and universities will play a critical role in turning all of this around, but they will need the capacity and incentives to think and act differently. The white paper offers a new mission, but its success and longevity will depend on whether they decide they want to sign up.
The NHS faces a growing clinical placement crisis that threatens the future of its workforce. A new HEPI and University of London report calls for bold, system-wide reform to ensure students get the real-world experience they need to deliver safe, high-quality care.
HEPI and the University of London’s new report, Rethinking Placement: Increasing Clinical Placement Efficacy for a Sustainable NHS Future, which has been published with the support of the Council for Deans of Health, warns that the NHS cannot meet its ambitious workforce goals without bold reform of how students gain real-world experience. Co-authored by Professor Amanda Broderick and Robert Waterson of the University of East London, the report calls for a shift from simply creating more placements to delivering better ones—equitable, flexible, digitally enabled and aligned with the future of healthcare.
Drawing on innovation across London and beyond, the authors propose practical steps including simulation-based learning, new supervision frameworks and community-based models that can expand capacity without compromising quality. With over 106,000 vacancies across secondary care, the report urges policymakers, universities and NHS providers to act now to secure a sustainable, skilled and compassionate workforce for the next decade and beyond.
