Through the annual Student Academic Experience Survey (SAES), HEPI and Advance HE collect data on the experiences and attitudes of care-experienced students. We are in a constant process of iterating and improving the SAES, and in 2024, a close reading of our data from previous years suggested a higher number of respondents than expected were saying they had experience of care. To make sure we were capturing the right students, we refined the question as follows:
Have you been in care? Select yes if you’ve ever lived in public care or as a looked-after child, including:
with foster carers under local authority care
in a residential children’s home
being ‘looked after at home’ under a supervision order
living with friends or relatives in kinship care
Note: This does not refer to time spent in boarding schools, working in a care or healthcare setting, or if you are a carer yourself.
In 2024, nearly 900 of the roughly 10,300 respondents to the SAES – still quite a high number, but significantly fewer than the previous year – said they had experience of care. What do the data say about their experiences in higher education? (Note that the margin of error for any subset will be higher than the margin for the whole survey sample, which is around 1%.)
On subject choices, care-experienced students in the SAES were somewhat more likely to be studying Medicine and Dentistry and subjects allied to Medicine, which is consistent with sector-level data. They were also more likely to be studying Engineering and less likely to be studying Business, Social Studies and creative subjects.
In addition to the challenges faced by having experienced care, these students were also less likely to come from the highest quintiles of participation in higher education (POLAR) than other students and more likely to have a disability (45%, compared to 30% of other students) but less often described themselves as first in family (25%, compared to 32% of other students).
This probably informs many of their responses throughout the survey. For example, like other students taking courses like these, care-experienced students have more contact hours and do more hours of independent work (a total of 41.5 hours) than students without experience of care (36 hours on average). Likewise, more than half of care-experienced students use AI at least once a week, compared with less than a third (30%) of other students. This is as expected, given that saving time is a primary reason students use AI tools.
Perhaps surprisingly, care-experienced students report higher scores on wellbeing measures, like happiness and life satisfaction. (For example, they average 7.08 out of 10 for whether the things they do are worthwhile, compared to 6.74 for other students.) However, they also report higher rates of anxiety and loneliness than students without experience of care, averaging 5.29 out of 10 for feeling anxious compared with 4.48 for other students.
Care-experienced students are more likely to have considered withdrawing: 38% compared with 24% of all students. When asked for their main reason why, they cite mental health as the primary challenge, but at a lower rate than students without experience of care. Instead, they were more likely to mention workload – either a higher or lower volume than expected – or their physical health.
These data also suggest that care-experienced students face an altogether more challenging context. Some 58% of care-experienced students say they travel 10 miles or more to get to university, compared with only 31% without experience of care travelling the same distance. This may be because the benefits some care-experienced students get can be contingent on living within a particular local authority. Care-experienced students reported living alone or with family at higher rates than other students.
Additionally, care-experienced students may need to remain at home to provide for family members at higher rates. Almost all care-experienced students (80%) do some paid work during term-time, compared with 55% of other students. This is most often to supplement their income. But more than one-third of care-experienced students (35%) work to support friends or family financially.
A third (33%) say the cost-of-living crisis has affected them ‘a lot’, compared with 27% of other students. Care-experienced students are also nearly twice as likely to depend on scholarships or bursaries to cover their costs, which could also show that such funds are being effectively targeted towards students who need them.
In summary, care-experienced students are more likely to take certain Health and Science subjects, live further from their institution, are more likely to be working to support their families and are affected more by cost-of-living difficulties. These challenging findings help to explain why care-experienced students withdraw from higher education at higher rates.
Clearly there is more that institutions and government can do to support this group of students. The TASO report recommends, for example, working closely with local authorities to ensure care-experienced students have reliable access to accommodation, both during and outside of term-time. And as Paige Mackenzie wrote for us in 2022, the holidays can be a ‘really lonely time’ for care-experienced and estranged students and it helps when staff reach out.
On the eve of the release of HEPI’s Student Generative AI Survey 2025, HEPI hosted a roundtable dinner with the report’s sponsor, Kortext, and invited guests to discuss the following essay question:
How will AI change the university experience for the next generation?
This was the third roundtable discussion we have hosted with Kortext on AI, over three years. Observing the debate mature from a cautious, risk-averse response to this forward-looking, employability-focused discussion has been fascinating. We spent much of the evening discussing a potential pivot for teaching and learning in the sector.
The higher education sector places the highest importance on creating, collecting, and applying knowledge. ‘Traditional’ assessments have focused on the recollection of knowledge (exams) or the organisation and communication of knowledge (in essays). The advent of search engines has made acquiring knowledge more accessible, while generative AI has automated the communication of knowledge.
If knowledge is easily accessible, explainable, and digestible, which skills should our graduates possess that cannot be replaced by ChatGPT, now or in the future? It was suggested that these are distinctly ‘human’ skills: relationship building, in-person communication, and leadership. Are we explicitly teaching these skills within the curriculum? Are we assessing them? Are we rebalancing our taught programmes from knowledge to irreplaceable skills to stay ahead of the AI curve?
And to get a bit meta about it all, what AI skills are we teaching? Not just the practical skills of application of AI use in one’s field, but deep AI literacy. Recognising bias, verifying accuracy, understanding intellectual property rights and embracing digital ambition. (Professor Sarah Jones of Southampton Solent University has written about this here.)
Given recent geopolitical events, critical thinking was also emphasized. When and why can something be considered the ‘truth’? What is ‘truth’, and why is it important?
Colleagues were clear that developing students’ knowledge and understanding should still be a key part of the higher education process (after all, you can’t apply knowledge if you don’t have a basic level of it). In addition, they suggested that we need to be clearer with students about the experiential benefits of learning. As one colleague stated,
‘The value of the essay is not the words you have put on the page, it is the processes you go through in getting the words to the page. How do you select your information? How do you structure your argument more clearly? How do you choose the right words to convince your reader of your point?’
There was further discussion about the importance of experiential learning, even within traditional frameworks. Do we clearly explain to students the benefits of learning experiences – such as essay writing – and how this will develop their personal and employability skills? One of the participants mentioned that they were bribing their son not to complete his Maths homework by using ChatGPT. As students increasingly find their time constrained due to paid work and caring responsibilities, how can we convince students of the value of fully engaging with their learning experiences and assessments when ChatGPT is such an attractive option? How explicitly are we talking to students about their skills development?
There was a sense of urgency to the discussion. One colleague described this as a critical juncture, a ‘one-time opportunity’ to make bold choices about developing our programmes to be future-focused. This will ensure graduates leave higher education with the skills expected and needed by their employers, which will outlast the rapidly evolving world of generative AI and ensure the sector remains relevant in a world of bite-sized, video-based learning and increasing automation.
Kortext is a HEPI partner.
Founded in 2013, Kortext is the UK’s leading student experience and engagement expert, pioneering digitally enhanced teaching and learning in the higher education community. Kortext supports institutions in boosting student engagement and driving outcomes with our AI-powered, cutting-edge content discovery and study products, market-leading learner analytics, and streamlined workflows for higher education. For more information, please visit: kortext.com
Professor Lisa-Dionne Morris is Professor of Public & Industry Understanding of Capability Driven Design in the School of Mechanical Engineering, and the Engagement Champion for the EPSRC EDI Hub+, at the University of Leeds.
Women in higher education and industry leadership, especially in Engineering and STEM, have reshaped academia and industry through groundbreaking contributions. Over the past two centuries, they have advanced knowledge, dismantled systemic barriers, and set new standards in innovation and leadership. Yet Black women remain significantly underrepresented, highlighting the urgent need for institutional change.
After all, when we lack diversity, we limit our ability to evolve and tackle the challenges of a rapidly changing world.
These disparities highlight the urgent need for fundamental change to ensure equitable access to opportunities and resources.
The 200-year journey of Black women in academia has been shaped by structural barriers but also by resilience and advocacy. Initiatives like the Black Female Academics’ Network and the national EDI Hub+, led by the University of Leeds, have played pivotal roles in championing change and providing visibility and support for Black women in academia and higher education leadership. But the reality is that real change comes not just from support networks but from institutions and governance bodies truly committed to transformation through policy implementation and its incorporation into operational management.
Black women have broken barriers in education, research, and industry, driving policy changes and fostering inclusivity. They have led pioneering research, challenged outdated structures, and risen to leadership in historically non-diverse sectors. In Engineering and STEM, figures like Dr. Aprille Ericsson, the first Black woman to earn a PhD in Mechanical Engineering from Howard University, have held key roles at NASA. Yewande Akinola, a Nigerian-born engineer, has advanced sustainable water systems while advocating for diversity. In the UK, Professor Esther Akinlabi has made significant contributions to academic leadership, engineering, research, and advocacy.
These Black women, and countless others, have played critical roles, and yet their paths have not been easy. They have faced barriers, from being underestimated in their abilities to encountering biases that make progression in academia and industry far harder than it should be. It is important to highlight their successes but equally crucial to recognise the dramatic shifts needed to create a more inclusive landscape.
As the first Black female professor in the School of Mechanical Engineering at the University of Leeds, I have witnessed firsthand the impact of underrepresentation on individuals and institutions. Without diverse voices in leadership, we lose perspectives that drive innovation and meaningful change. True equity and inclusion require representation at the highest levels, where policies and practices are shaped.
Mentorship and networking are vital for career progression, yet many Black women in academia and industry lack mentors with shared experiences. Institutions must formalise support systems rather than relying on individual efforts. A cultural shift is needed, one where diversity is not just discussed but reinforced through real structural changes that create lasting opportunities.
Breaking barriers is not just about individuals but about how institutions respond. Are they fostering environments where Black women can thrive? Are they tackling unconscious bias in hiring and promotions? Are they offering real support for retention and advancement beyond just celebrating ‘firsts’? It’s time to move from symbolic gestures to tangible change that empowers the next generation in academia and industry.
The legacy of Black women in academia and industry extends beyond their achievements to the opportunities they create for future generations. Recognising and amplifying their voices is essential. Their contributions must be seamlessly woven into the broader narrative of advancement and innovation in women’s higher education and industry leadership.
Much work remains. Representation is not enough; true progress requires dismantling barriers to access and opportunity. Black women in academia and industry, especially in Engineering and STEM, must be empowered, supported, and able to lead without the constant need to justify their place.
The goal should be that, in the future, their contributions are not exceptional but expected, and their presence in leadership roles is not a rarity but the norm.
It’s International Women’s Day. Today on the site, Professor Lisa-Dionne Morris explores the critical role of Black women in academia and industry leadership, particularly in Engineering and STEM, highlighting their groundbreaking contributions and the systemic barriers that persist. Read that piece here.
Below, HEPI’s own Rose Stephenson challenges us to look at ‘the other side of the coin’ in the fight for gender equality – you can read that piece below.
Firstly, Happy International Women’s Day 2025.
The theme this year is ‘Accelerate Action.’ It’s a great theme, and to accelerate action in terms of gender equality, we have got to focus more on ‘the other side of the coin’. Let me explain three examples:
1. We should do more to ensure that parenting is supportive and inclusive of fathers.
Joeli Brearly, outgoing CEO of Pregnant then Screwed, recently gave evidence on Shared Parental Leave in parliament. She stated:
‘It’s time we asked ourselves a fundamental question about what sort of society we want this to be. Do we want to continue to perpetuate outdated and harmful gender stereotypes that tell us it is women who do the nurturing and the caring and the childrearing and are the homemakers and that men just need to pull their socks up and get back to work? They are strong, stoic breadwinners and don’t need this time [parental leave] to nurture and care for their family. The mental health of men in this country is in crisis. Boys are saying they feel lost and disconnected, and it’s no wonder when our laws are literally telling them: “you don’t need time to nurture and connect with your family.”’
Inclusive parenting is good for dads, it’s great for kids, and it benefits Mums, too. My mantra is, ‘We will never have equality in the workplace until we have equality in the home’. Until we reach a point where an equal number of dads leave work in time for the school run, take time off for holiday care, or work part-time and flexibly, we will never reach parity in the workplace. And why would we want to? If women collectively reach equal pay, equal status and the resulting equal responsibility at work yet continue to shoulder most domestic and childcare duties, we have significantly undermined progress towards equality.
The HEPI report I published last year, Show Me the Money, an exploration of the gender pay gap in higher education, demonstrated the importance of increasing paid paternity leave as a lever for narrowing the gender pay gap. If your institution is monitoring the uptake of senior or professorial roles by gender, are they also monitoring the uptake of post-birth parental leave, shared parental leave and statutory parental leave by the same measure? Is there monitoring and reporting on the genderisation of part-time work applications, flexible working requests and the granting of these requests? That is ‘the other side of the coin’ and we should not underestimate the hurdles fathers may have to overcome to ask – or be granted – the flexibility we more commonly expect for mothers.
2. We should encourage boys and young men to work in teaching and social care roles to the same extent that we encourage women to work in engineering and tech.
When working as a secondary and sixth-form science teacher, I undertook a project at my school that challenged pupils to critically think about the subject choices they were making at GCSE and A-Level and how this might be affected by gender stereotyping. There was plenty of support and encouragement for female pupils in science and maths subjects (as there should be). However, there was a notable vacuum in the equivalent campaigns to open up opportunities for boys.
I witnessed first-hand how the gendering of subjects and occupations suppressed the potential of young men. One boy in my tutor group desperately wanted to complete his work experience at a hair salon. This pupil would have benefitted from a ‘hook’ that could have driven his interest in education and the future world of work. Unfortunately, his family disapproved of his choice, and he spent his work experience on a building site. This did nothing to enhance his motivation towards education or work. This was a valuable opportunity for a disengaged young man to pursue something that genuinely sparked his interest, and I have no doubt he would have excelled at. However, this opportunity was lost because it was not deemed ‘masculine’ enough. This was one example, but the boys I taught were quite open about feeling they couldn’t choose the subjects they wanted. There was an element of ‘acceptable’ choices.
It is tragic that in 2025, UK society is still limiting the possibilities for young men to follow their real interests. As a sector, we should push hard against the narratives perpetuating this. Again, if your institution is monitoring and encouraging the uptake of subjects such as engineering or coding for female students, are they also monitoring the update of nursing courses by male students? Are there considerations of male uptake and completion of courses in your Access and Participation Plans?
3. We should consider developing ‘Men’s Leadership’ courses.
I’ve been lucky enough to partake in various forms of ‘Women’s Leadership training’ run by Advance HE and the Women’s Higher Education Network (WHEN), among others. Of course, non-gender-specific leadership training is available. However, women’s leadership courses have existed due to the historic and ongoing underrepresentation of women in leadership positions. Further, they provide a female-only space for women to develop their leadership skills.
I vividly remember being told by a presenter on the Advance HE Aurora programme to ‘have heft’ and ‘take up space’. (I replay this memory regularly in all the privileged but occasionally intimidating speaking and media events I undertake in my current role.)
But as we move closer towards gender parity – and I know there is more work to do – should we be thinking about the other side of the coin? Women’s leadership courses can often focus on developing traits deemed to be held by traditional, therefore male, leaders. Having more confidence, making your voice heard, etc. Now that most of society accepts that women can also make great leaders – and there are many stand-out examples in the higher education sector – where is the equivalent training for men?
Where are the male leadership courses that teach men the skills of making space for others, speaking inclusively, building relationships, the importance of being a mentor, and using coaching techniques to build confidence in their colleagues? Surely, some male colleagues who wish to become leaders can learn skills that may be (stereotypically) more prevalent in female colleagues, and developing these skills would benefit everyone.
And sure, some men will already possess these skills, just like some women have a natural ability to take up space. My question is, if we accept that women are socialised in a particular way to be missing some leadership or workplace skills, then can we accept that for men? Do we value stereotypically ‘female’ leadership skills enough to offer a platform for developing these skills in male colleagues? Further, should leadership courses for men include panels discussing how to balance leadership roles with childcare responsibilities? (And yes, those panels exist in women-in-leadership courses) Perhaps when we get to this point, we really will be considering the other side of the coin.
If you found this blog interesting, you may wish to look back at some of our previous International Women’s Day blogs:
HEPI has also published the report:
HEPI will soon publish an updated report on educational achievement by boys and young men, a significant and long-standing issue that has been largely ignored by policymakers. The report considers the consequences for individuals and societies and proposes several levers that could be used to drive change. This report will be published this month – March 2025. If you haven’t already, sign up for our blog below to get this report hot off the press.
If you wish to write a blog for International Men’s Day on November 19th, submissions are very welcome.
The path from early promise to widespread impact requires one thing and one thing only: scalability – the capacity to grow and expand in a robust and sustainable way. Put simply: you can only change the world at scale.
To tackle inequality in higher education, we need scalable interventions. The interventions that make the biggest difference will be those that we can successfully expand from a small group to a much bigger one.
Across many policy areas, ideas that appear promising after being tested at a small scale often have a much lower impact when expanded. Existing evidence suggests the majority of interventions – somewhere in the range of 50% to 90% – will have weak effects when scaled. This is what the economist John List terms a ‘voltage drop’: ‘when an enterprising idea falls apart at scale and positive results fizzle’.
Interventions in higher education are frequently designed at either the module or school level, with the intention to eventually scale up. Often, interventions are started by a single enthusiastic practitioner, who then tries to scale up the intervention later on. For example, a student support programme may go from being implemented within the school of psychology to across the whole institution. Similarly, policymakers may seek to scale an idea that was successful at one institution by implementing it across a range of other institutions.
As a result, higher education emerges as a prime area where we should consider the intended scale of implementation from the outset. While many interventions struggle to scale, List argues this challenge is surmountable by building into our processes an understanding of five key factors that impede scaling.
1. False positives
The first major cause of voltage drops is the prevalence of false positives: concluding there is a significant effect when there is not. False positives can arise in a manner of ways, but we can split them into three categories: statistical error, human error, and fraud.
We can go a long way to addressing this trifecta of false positives by embracing the open science movement. Key tenets of this approach include pre-registration of trials, independent evaluation, and open publication of data and code. Opening our research up in this way not only helps to prevent fraud (more prevalent than we might think in academia) but also encourages more collaboration with peers and enables others to build on your work.
2. Know your intended audience
When testing your intervention, consider whether this initial group is representative of the broader population you hope to impact. If the intervention is not designed for only one group, we should not test it with only one group.
For example, say we trial an intervention with Engineering students before rolling it out across the institution. This could cause difficulties if Engineering students are different from the wider population we are interested in. It may be that the intervention only works on our sampled population (in this case Engineering students) and no longer works when we roll it out to the entire student population.
3. Spillovers
Interventions often give us evidence of what works at a small scale, but it is difficult to anticipate how this could change when an intervention becomes a large-scale movement.
This is particularly important when we look at scaling interventions from one institution to many. We should consider that the positive effects of an intervention at the institution level may disappear once the programme is scaled further. For example, consider a career guidance programme that improves graduate outcomes at an institution. When rolled out across the country, it may alter the dynamics of the graduate labour market in such a way that the original benefits are negated.
4. Is the success due to the practitioner, or the idea?
We should consider whether the intervention, as tested, accurately reflects the characteristics it will have when deployed widely.
The key analogy here is one of chefs and ingredients. If the reason behind a restaurant’s success is its ingredients, it will be more likely to scale well, as the ingredients can be scaled across many branches. But a restaurant will struggle to scale if its success is down to the unique magic of the chef.
Similarly, an intervention may fail to scale if we can mainly attribute its positive impact to a practitioner’s individual brilliance at a specialised skill: the talented practitioner cannot be so easily scaled.
5. Rising costs
If the costs grow disproportionately with the intervention, it will struggle to scale. For example, at a small scale, it may be relatively easy to find an effective practitioner who can deliver the intervention as it was intended and have a high impact on students.
But, as we’ve seen, if the success of a programme rests on the talent of practitioners, this is unlikely to scale well. As the intervention scales and hires more staff, finding staff who can have the desired impact will become increasingly difficult and expensive.
Moving towards having an impact at scale
It is a worthwhile pursuit to make incremental but meaningful changes that improve the lives of students. Many practitioners, not to mention students themselves, will be able to attest to the difference a small-scale intervention can have on a student’s life, helping to break down barriers, narrow gaps and open up doors.
But to move the dial on inequality in higher education, we should build considerations around scaling into our interventions. In doing so, we can move our focus towards building an evidence base that helps us make a much larger change. By making this move, we can realise List’s powerful assertion: ‘you can only change the world at scale’.
The modern digital era has brought with it a world of remarkable changes and developments in the information space that today’s students are well-placed to enjoy. The search engine as you know it is changing and adapting to these changes, with old methods and processes giving way to newer, more effective ones.
While traditional Search Engine Optimization (SEO) remains essential, Generative Engine Optimization (GEO) is emerging as a complementary strategy for AI-driven search experiences. With AI-powered search engines like Google’s Gemini and ChatGPT transforming how prospective students find information online, today’s schools must adapt or risk being swept under the radar.
Keen on increasing organic traffic and leads?
Optimize your site, attract students, and elevate your visibility with our specialized SEO strategies.
The Evolution of Search in Education Marketing
Now, a few well-placed keywords are not enough. Although about 91% of today’s organizations still make significant marketing-related gains from SEO, the rules are fundamentally different now. Today’s prospective students use the search engine in ways that are quite unprecedented.
While traditional search engines serve up lists of links, AI-powered search engines deliver direct answers. Even better, they deliver such complete conversational responses that you do not need to visit a website. There’s a dual approach to this process: maintaining strong SEO foundations while embracing the emerging power of GEO.
Educational institutions stand to gain from this development. Prospective students can conduct exhaustive research without contacting an admissions office. By tapping the search button, they can get answers to vital questions about program details, application requirements, and career outcomes.
SEO: Still the Foundation of Digital Visibility
While AI is visibly gaining momentum, SEO remains an important tool. When executed properly, it can produce these benefits:
Enhanced Visibility: Optimised content drives organic traffic, increasing inquiries and applications to your school. Recent industry sources report that schools that invest in comprehensive SEO measures enjoy a significant improvement in conversion rates.
Better User Experience: With clear metadata, logical headings, and mobile-friendly designs, students can find information better on websites. The results include longer site visits, lower bounce rates, and higher engagement, which can help boost search rankings further.
Established Authority: By creating comprehensive content, you’re signalling to search engines and users that your school is knowledgeable and can be trusted. It gives a sense of authority that can ultimately boost your school’s profile.
What is the difference between SEO and GEO marketing? The key difference between SEO and Generative Engine Optimization marketing lies in their focus and approach. SEO is used for traditional search engines, and GEO is used for AI-Driven searches:
SEO optimizes content for traditional search engines (Google, Bing) to improve rankings in organic search results using keywords, backlinks, and technical SEO strategies.
GEO marketing optimizes content for AI-driven search experiences (Google SGE, ChatGPT), ensuring content is AI-friendly, conversational, and structured for retrieval by generative AI models.
While SEO targets search engine algorithms, GEO marketing tailors content for AI-driven responses and voice search interactions.
Effective SEO Strategies for Education
The optimization approaches discussed below have been proven to be used by the most successful institutions.
Strategic On-Page Optimization:
Using long-tail keywords like “best MBA programs in Canada for working professionals” can help capture niche audiences.
Content Authority:
Create in-depth guides and case studies addressing the nuanced questions that prospective students typically ask. So, instead of just listing program requirements, develop extensive resources that cover career paths, industry connections, and student outcomes.
Mobile Optimization:
A responsive design is a must-have, thanks to most searches now happening on mobile devices. This holds true for young people who use smartphones to explore their educational options.
Schema Implementation:
Structured data markup can help search engines interpret your content much better. An education-specific schema like EducationalOccupationalCredential or EducationalOrganization can boost your program’s visibility in search results.
Local SEO:
Institutions with physical campuses need to optimize for local searches. This includes claiming and maintaining Google Business Profile listings, building local citations, and creating location-specific content highlighting campus facilities and community connections.
The AI Search Revolution: Understanding GEO
What is Generative Engine Optimization (GEO)?
More pertinently, what is GEO in SEO? Generative Engine Optimization in SEO refers to optimizing content for AI-driven search engines and generative AI models like Google’s Search Generative Experience (SGE) and ChatGPT. It focuses on structuring content for AI retrieval by using natural language, clear formatting, authoritative sources, and relevant keywords to improve visibility in AI-generated responses.
The way we interact with information today has changed drastically, courtesy of AI-powered search engines. You can now get direct, synthesized answers culled from several sources, so you don’t have to click through multiple links. The way this happens is in these three steps:
AI models scour the web for relevant information, searching from institutional websites to educational forums and third-party resources.
They blend this information into coherent, structured responses that address the specific query and can often include details from multiple sources.
Users will now get conversation-like answers without having to visit individual websites. These answers often come complete with citations or even visual elements.
Mastering GEO for Education Marketing
Imagine asking an AI assistant for the best digital marketing courses or top universities for business programs—and your institution doesn’t appear. That’s where Generative Engine Optimization (GEO) comes in.
What is GEO in digital marketing? GEO in digital marketing optimizes content for AI-driven search tools like Google’s Search Generative Experience (SGE) and ChatGPT. Unlike traditional SEO, which focuses on ranking in search engine results, GEO ensures your content is structured, conversational, and AI-friendly, making it more likely to surface in AI-generated responses.
As AI search adoption grows, Generative Engine Optimization is becoming critical. Prospective students are no longer just typing keywords into Google; they’re asking AI assistants for tailored recommendations. If your institution isn’t optimizing for AI-driven search, you risk being invisible in the conversations shaping students’ decisions.
That’s why mastering GEO for education marketing is no longer optional—it’s essential. Schools, colleges, and universities must adapt their digital strategies to ensure AI models recognize their programs, faculty, and unique offerings. Ignoring this trend means missing out on valuable opportunities to engage with future students where they’re already searching.
Focus on these strategies if you’re looking to succeed with GEO:
Answer-focused Content: Use a Q&A format to create clear and concise responses to common questions. Instead of burying tuition-related information in program pages, provide direct answers to questions like “How much does it cost to attend [School Name]?”
Authoritative Information: Provide precise, updated information and only cite credible sources. You can reference accreditation bodies, link to relevant research and put out consistent information across all digital channels.
Comprehensive FAQs: Use detailed FAQ sections to cover key topics like admissions and campus life. Using proper schema markup, structure these sections so that AI tools can pull information straight from your authoritative source.
AI-Friendly Schema: To make your content more machine-readable, use FAQ, Course, Event, and Speakable schemas. This way, AI systems can connect the different pieces of information contained on your site.
Multichannel Distribution: Let your content be shown across platforms like YouTube, LinkedIn, and Quora to gain more visibility. Because AI search engines pull material from varying sources, a consistent message across your channels will help your school be represented the right way.
Example: This screenshot captures Google search results for “Does ATC Toronto offer an auto detailing program?” It includes a prominently featured snippet directly answering the question on the left side of the page, and AI search results also answer the question on the right.
Here are our best tips for creating suitable content for traditional and AI-driven searches:
Create Optimal Content:
Optimize Your Content Structure because human readers and AI algorithms will benefit immensely from clear organization.
Create a logical hierarchy using descriptive headings and subheadings. For example, move your program pages from a general overview to curriculum, faculty, career outcomes, and other specific details.
Incorporate bullet points and numbered lists for easy scanning. This is particularly important for details about admission requirements, application deadlines, and program benefits.
Implement appropriate schema markup to help search engines understand your content.
Let your content have a clear content hierarchy that guides users from general information to specific details.
Focus On Quality and Engagement
It is important to create high-quality content that addresses user intent. Follow these strategies:
Reach out to prospective students with answers to their most asked questions. Correctly predict and sort out their needs across all decision-making stages.
Balance authoritative information with a conversational tone. Do this while avoiding academic jargon and maintaining the appropriate level of sophistication for your target audience.
Use short paragraphs and clear language to make your content readable. Also, blend concise, direct answers with in-depth guides.
Let your student testimonials, faculty perspectives, and alumni success stories feature authentic voices as they can help humanize your institution.
Example:The University of Toronto has a section on its website that features testimonials from current students, alumni, and staff, helping to boost the school’s image with genuine feedback.
Modern search optimization has gone past keywords, and here’s how:
Develop comprehensive pillar pages that cover broad topics like “Graduate Programs” or “Student Life” with links to more specific content. Use natural language mirroring how people speak and search. Incorporate variations and related as opposed to repeating the same keywords.
Create content clusters that address related topics and questions. Also, you can link between them to establish topical authority and help users navigate your site.
Consider the semantic field around educational topics, including synonyms, related concepts, and commonly associated terms.
Example: Here, R-MA demonstrates its mastery of semantic SEO with this Student Life page. Apart from providing a general overview of the school’s Student Life Program, the page also contains links to specific aspects of the program.
One of the biggest threats to education marketers is the rise of zero-click searches, where users get answers without visiting your website. Nearly 65% of Google searches now end without clicks to any websites. This trend is particularly problematic for institutions relying on website traffic for lead generation.
Here’s a quick look at how Zero-Click searches show up in search engines:
Featured Snippets: This displays key information directly in results, answering questions about application deadlines, tuition costs, and program requirements without requiring clicks.
Voice Search: Conversational queries often receive single, direct answers, particularly for straightforward questions like “When are applications due for [School Name]?”
AI Summaries: New tools seek to compile information from multiple sources into one response. Synthesizing details about educational programs without directing users to specific institutional websites.
Strategies to Combat Zero-Click Searches
Optimize the content for featured snippets: Structure content to rank better by directly answering questions.
Implement FAQ Schema: Mark up Q&A content with the right schema so your answers appear more in search results.
Create must-click content: Create resources that resonate with the users, including calculators and virtual campus tours.
Leverage Rich Results: Using structured data, enhance how your content appears in search results so it’s more appealing and clicked.
Focus on Complex Questions: Target those queries that you can’t answer in a snippet, those that need you to go further into your school’s offerings.
Example: Oxford University enhances its FAQ sections using structured data. By doing so, their answers are featured directly in search results—ensuring that key information about admissions and tuition is visible in a zero-click environment.
With voice assistants becoming more popular, optimizing for spoken queries is becoming increasingly important. Over 27% of searches are run through a voice interface, mostly among the younger generations. Here are some voice search best practices to use to this effect.
Use natural, question-based keywords that match how people speak, such as “How do I apply to [School Name]?” rather than “application process.”
Voice search is predominantly mobile-driven, so make sure your site is mobile-friendly and fast-loading.
Creating Conversation-Ready Content
To create conversation-ready content, you’ll need to follow certain rules. Our best tips include writing in short, digestible paragraphs that voice assistants can easily read aloud.
You must provide direct answers to common questions to start each relevant section. Another key tip is to create how-to guides and FAQ sections that fit with voice queries.
Let your content follow a conversation-like style, just like prospective students engage. There should be relevant context to match every user request, and the information provided should be clear and concise for the best results.
Essential Tools and Emerging Trends
To stay competitive in educational marketing, you need the right tools and awareness of emerging trends. Here are some must-have SEO and GEO tools.
Google Search Console: Monitor performance and identify opportunities by tracking how your pages appear in search results and which queries trigger their appearance.
SEMrush: Research keywords and analyze competitor strategies while paying particular attention to education-specific terms and competing institutions.
Ahrefs: Track backlinks and content performance, building a strong link profile that enhances your institution’s perceived authority.
Schema Markup Generators: Create and validate structured data to improve how search engines interpret your content.
Mobile Testing Tools: Ensure optimal performance across all devices, recognizing that many prospective students research educational options on smartphones.
Trends Reshaping Education Marketing
AI-Generated Search Summaries: By focusing on direct answers instead of posting traditional link listings, your search results appear faster and function better.
Voice Search Growth: This accounts for over 27% of all searches, mostly among younger demographic groups.
Engagement as a Ranking Signal: User interaction affects visibility, with metrics like time on site and interaction rates affecting search performance.
Video Content Prominence: Educational videos are gaining importance in search results, particularly for how-to and explanatory content about programs and campus life.
Social Proof Integration: With reviews, testimonials, and user-generated content, you can create more impact in traditional and AI-driven search results.
The Human Element: Storytelling in a Digital World
Although technical optimization remains crucial, education marketing relies heavily on human connection. The schools that balance data-driven strategies with authentic storytelling that resonates with prospective students succeed.
If you’re looking for a means to build student trust in your offerings through authenticity, here’s how to go about it.
Share real student success stories and testimonials that show how transformative your educational programs are.
Highlight those unique program features and opportunities that differentiate your institution from competitors.
Maintain transparency and avoid excessive jargon. Focus on pointing out what makes your institution special.
Create content that addresses the emotional aspects of the educational decision.
Example: Here, AAPS masterfully emphasizes the transformative power of its program by highlighting the experiences and successes of a student, recounted by the student herself.
Use analytics to inform content strategy, identifying topics and formats that resonate with your target audience.
Enhance text with visual and interactive elements that engage users and encourage deeper exploration of your offerings.
Personalize messaging for different audience segments, with their varying priorities and concerns.
Test and refine approaches based on performance data, continuously improving your digital marketing effectiveness.
Embracing the Future of Education Marketing
As the digital outlook for today’s educational market continues to evolve, schools must continually adapt to remain competitive. The future of search engines belongs to those who can master both SEO and GEO to produce results that drive and direct conversations.
The tide favours schools whose content resonates with traditional search engines and AI-powered platforms. The target is to position your institution for this kind of leverage, and that’s the essence of this piece.
Ready to transform your digital presence? Start optimizing today and watch your institution’s story unfold—one search at a time.
Keen on increasing organic traffic and leads?
Optimize your site, attract students, and elevate your visibility with our specialized SEO strategies.
Frequently Asked Questions
Question: What is the difference between SEO and GEO marketing?
Answer: The key difference between SEO and Generative Engine Optimization marketing lies in their focus and approach. SEO is used for traditional search engines and GEO is used for AI- Driven searches.
Question: What is GEO in SEO?
Answer: Generative Engine Optimization in SEO refers to optimizing content for AI-driven search engines and generative AI models like Google’s Search Generative Experience (SGE) and ChatGPT.
Question: What is GEO in digital marketing?
Answer: GEO in digital marketing optimizes content for AI-driven search tools like Google’s Search Generative Experience (SGE) and ChatGPT.
Dr Elizabeth Morrowis Research Consultant, Senior Research Fellow Royal College of Surgeons in Ireland, & Public Contributor to the Shared Commitment to Public Involvement on behalf of National Institute for Health and Care Research.
Professor Fiona Ross CBE is Professor Emerita Health and Social Care Kingston University, Deputy Chair Westminster University Court of Governors & Trustee Great Ormond Street Hospital Charity.
Commitment and Motivation for Inclusive Research
The commitment to inclusivity in UK research cultures and practices will endure despite political shifts abroad and continue to thrive. Rooted in ethical and moral imperatives, inclusivity is fundamentally the right approach. Moreover, extensive evidence from sources such as The Lancet, UNESCO and WHO highlights the far-reaching benefits of inclusive research practices across sectors like healthcare and global development. These findings demonstrate that inclusivity not only enhances research quality but also fosters more equitable outcomes.
We define ‘inclusive research’ as the intentional engagement of diverse voices, communities, perspectives, and experiences throughout the research process. This encompasses not only who conducts the research but also how it is governed, funded, and integrated into broader systems, such as policy and practice.
Beyond higher education, corporate leaders have increasingly embraced inclusivity. Research by McKinsey & Company shows that companies in the top quartile for gender diversity are 25% more likely to outperform their peers in profitability, while those leading in ethnic diversity are 36% more likely to do so. This clear link between inclusivity, innovation, and financial success reinforces the value of diverse teams in driving competitive advantage. Similarly, Egon Zehnder’s Global Board Diversity Tracker highlights how diverse leadership enhances corporate governance and decision-making, leading to superior financial performance and fostering innovation.
Inclusion in research is a global priority as research systems worldwide have taken a ‘participative turn’ to address uncertainty and seek solutions to complex challenges such as Sustainable Development Goals. From climate change to the ethical and societal implications of Artificial Intelligence (AI), inclusive research is a track that ensures that diverse perspectives shape solutions that are effective, fair and socially responsible.
Take the example of AI and gender bias – evidence shows that women are frequently not included in technology research and are underrepresented in data sets. This creates algorithms that are biased and can have negative consequences of sensitivity, authenticity, or uptake of AI-enabled interventions by women. Similar biases in AI have been found for other groups who are often overlooked because of their age, gender, sexuality, disability, or ethnicity, for example.
Accelerating Inclusion in UK Research
A recent horizon scan of concepts related to the UK research inclusion landscape indicates domains in which inclusive research is being developed and implemented, illustrated by Figure 1.
Inclusion is being accelerated by the Research Excellence Framework (REF) 2029, with a stronger focus on assessing People, Culture, and Environment (PCE). REF 2029 emphasises the integration of EDI considerations across research institutions, with a focus on creating equitable and supportive cultures for researchers, participants and communities. The indicators and measures of inclusion that will be developed and used are important because they can encourage diversity of perspectives, knowledge, skills and worldviews into research processes and institutions, thereby increasing relevance and improved outcomes. All units of assessment and panels involved in the REF process will have guidance from the People and Diversity Advisory Panel and the Research Diversity Advisory Panel. This means that inclusion will develop in both the culture of research institutions and the practices that shape research assessment.
The National Institute for Health Research, which is the largest funder of health and social care research, has pioneered inclusion for over 30 years and prioritises inclusion in its operating principles (see NIHR Research Inclusion Strategy 2022-2027). NIHR’s new requirements for Research Inclusion (RI) will be a powerful lever to address inequalities in health and care. NIHR now requires all its domestic commissioned research to address RI at the proposal stage, actively involve appropriate publics, learn from them and use this learning to inform impact strategies and practices.
Given the learning across various domains, we ask: How can the broader UK system share knowledge and learn from the setbacks and successes in inclusion, rather than continually reinventing the wheel? By creating space in the system between research funders and institutions to share best practices, such as the Research Culture Enablers Network, we can accelerate progress and contribute to scaling up inclusive research across professional groups and disciplines. There are numerous examples of inclusive innovation, engaged research, and inclusive impact across disciplines and fields that could be shared to accelerate inclusion.
Developing Shared Language and Inclusive Approaches
Approaches to building inclusive cultures in research often come with passion and commitment from opinion leaders and change agents. As often happens when levering change, a technical language evolves that can become complex and, therefore, inaccessible to others. For example, acronyms like RI can apply to research inclusion, research integrity and responsible innovation. Furthermore, community-driven research, public and community engagement, and Patient and Public Involvement (PPI) have become synonymous with inclusive research, and such participation is an important driver of inclusion.
The language and practices associated with inclusive research vary by discipline to reflect different contexts and goals. This can confuse rather than clarify and form barriers that possibly get in the way of trust and more effective inclusion strategies and practices. We ask: How can we establish shared understanding, methods of participation, accountability pathways and mechanisms that will promote inclusion in the different and dynamic contexts of UK research?
With over 20 years of experience in the fields of inclusion and equity, like other researchers, we have found that interdisciplinary collaboration, participatory methods, co-production, and co-design offer valuable insights by listening to and engaging with publics and communities on their own terms and territory. An inclusive approach has deepened our understanding and provided new perspectives on framing, methodological development, and the critical interpretation of research.
Final reflection
Key questions to overcome EDI cynicism are: How can we deepen our understanding and integration of intersectionality, inclusive methods, open research, cultural competency, power dynamics, and equity considerations throughout research processes, institutions, and systems? There is always more to learn and this can be facilitated by inclusive research cultures.
To tackle the major challenges facing society, cross-disciplinary research may be necessary. However, conducting this type of research requires researchers to overcome functional silos. Various factors, such as differing incentives, cultures, terminologies, and jargon, can lead to opportunistic or counterproductive behavior. So, how can cross-disciplinary research be conducted effectively to advance knowledge and understanding? To answer this question, we will first explore the processes of theorizing. Next, we will discuss ways to break down cross-disciplinary barriers. Finally, we will offer practical guidelines for successfully conducting cross-disciplinary research.
First, we argue that the theorising process developed by Brodie and Peters (2020) provides guidelines for undertaking cross-disciplinary research by integrating general theoretic perspectives and contextual research to develop midrange theory. Midrange theory bridges the theoretical domain of knowledge and the applied domain of knowledge (Figure 1). The paradigmatic perspective provides the outer ring for the recursive theorizing process between general theory, midrange theory, and applied research.
Figure 1: Domains of knowledge and levels of theory
By employing the aforementioned theorising process, senior management can demonstrate to researchers that there are various ways to develop and apply midrange theory. The primary general theoretical perspective can connect directly with midrange theory, but alternative general theoretical perspectives can also offer routes that lead to other midrange theories. These alternative pathways can eventually converge on a focal midrange theory that can be utilised in research (as shown in Figure 2).
Figure 2. Interfaces for theorizing
Second, we propose ways to break down barriers to cross-disciplinary research. Senior management should recognize that research teams do not necessarily have to consist of cross-disciplinary researchers. Instead, teams should be composed of experts from their own disciplines who possess enough familiarity with the research problem and a basic understanding of each other’s fields to enable effective communication. A team of mono-disciplinary experts with a strong mix of skills and effective communication abilities is more advantageous than a team of cross-disciplinary researchers who lack sufficient experience or expertise.
Senior management should also recognise that research is typically mono-disciplinary. For instance, a cross-disciplinary grant application might struggle because the reviewers are often mono-disciplinary experts who may not grasp the cross-disciplinary elements or recognize the value of collaborative research. Therefore, senior management should encourage their researchers to take on riskier, but potentially rewarding, collaborations with peers from vastly different disciplines.
Senior management’s efforts to support and reward cross-disciplinary research can sometimes be misguided, as cross-disciplinary work should not be pursued as an end in itself. Imposing a vaguely defined cross-disciplinary agenda on researchers can lead to wasted efforts or, at best, projects that are difficult to fund or publish. A more effective approach would be for senior management to encourage researchers to start with the research problem, determine which problem class it falls into, and assess whether the problem is significant or complex enough to justify cross-disciplinary work, especially when questions arise that require expertise from multiple fields. Most importantly, and often overlooked, senior management should avoid the temptation to reward cross-disciplinary research solely for its own sake. It is far more advantageous to create an environment where researchers excel in their own disciplines while being rewarded for occasionally taking on larger cross-disciplinary challenges.
Third, the following practical guidelines can help break down barriers and create an environment that encourages cross-disciplinary research. For instance, researchers should be encouraged to present their work outside their own discipline, as this can enhance visibility, generate fresh insights, and open up opportunities for future collaboration. Senior management could promote participation in initiatives that address major societal challenges and incentivise researchers to engage with practitioners and the broader community. They should also prompt researchers to consider how their theoretical knowledge could be applied to real-world problems faced by policymakers, practitioners, and consumers.
Senior management could encourage research groups to formulate clear and well-defined research questions that accurately identify the specific problem class and knowledge gap. This approach will help determine whether expertise from multiple scientific disciplines is necessary. Refining a knowledge gap into a focused research problem can attract potential collaborators and offer context and direction for the collaborative research.
When two or more scientific disciplines are involved, it may be unclear who should provide guidance. Senior management could form a leadership team that can bring in additional members to offer expertise as needed.
On today’s HEPI blog, Adam Lindgreen, C. Anthony Di Benedetto, Roderick J. Brodie, and Michel van der Borgh explore how researchers can successfully navigate the challenges of cross-disciplinary research to address major societal issues. If you’ve ever wondered how experts from different fields can effectively collaborate despite differing terminologies, cultures, and incentives, this blog offers practical strategies and insights. You can read the blog here.
Below, Dave McCall and Zoë Allman discuss what AI means for those students seeking to undertake placements while they study.
Generative AI is transforming student placements. Year-long industry placements offer professional growth and employability, bridging academic learning and practical experience. Supported by universities, students are encouraged to maximise learning opportunities in the workplace and reflect on their experiences.
We increasingly find students using AI in placement applications, mirroring its role in their academic journey and in preparation for graduate employment. We consider how AI is used (and embedded) to improve the chances of securing a placement through searches, applications, and interview preparation, while also recognising the challenges this presents.
Placement Searching
AI algorithms shape how students search for placements. Platforms like LinkedIn and Glassdoor recommend opportunities tailored to users’ profiles and preferences, streamlining the process. However, this personalisation may also limit exploration, narrowing exposure to diverse job types and industries. The National Association of Colleges and Employers highlights how reliance on AI-generated job recommendations might lead students to miss opportunities, whilst the USA-based National Association of Colleges and Employers highlights how students might miss diverse opportunities by relying exclusively on AI-generated job recommendations.
Not Forgetting ChatGPT
Generative AI tools, such as ChatGPT, have become popular with students when developing search strategies, alongside drafting emails, generating lists of companies in niche fields, or refining search terms for specific industries. While useful, such tools demand a certain level of digital literacy to optimise outputs effectively. Research indicates AI’s effectiveness is limited by the quality of user prompts, underscoring the need for universities to provide AI literacy training to help students optimise their interactions with these tools while addressing the potential digital literacy skills gap. Targeting this developmental training in placement searching and application is critical for ensuring positive experiences on placement and future graduate outcomes.
AI Applications
Having been used in searches, AI is increasingly used as students develop their placement applications. Students employ generative AI to draft and tailor CVs and cover letters, quickly generating professional documents. Tools like Resumé Worded enable students to format and optimise applications for use in Applicant Tracking Systems. While efficient, over-reliance on AI risks producing applications lacking originality; a reliance on AI raises concerns about authenticity and self-reflection. AI use can lead to generic applications, potentially reducing a student’s ability to articulate their individualised experiences, values, and what they bring to the placement role.
Universities can address this by supporting students to understand how to balance AI-assisted optimisation with authentic self-expression. Workshops encouraging reflective practices help students integrate personality in applications, with feedback reinforcing human input.
Preparing for Interview
AI’s role in interview preparation is multifaceted, simulating interviews through generating questions and offering feedback. A student preparing for an engineering placement might use ChatGPT to generate technical and behavioural questions, refining responses through iterative feedback. AI-powered simulations offer ‘real-time’ feedback, enhancing confidence.
Beyond verbal preparation, AI tools like HireVue analyse tone, facial expressions, and word choice. While these technologies offer valuable insights to employers regarding applicants, they also introduce potential ethical concerns, including the possibility of bias in AI-driven evaluation. While providing valuable employer insights, these technologies raise ethical concerns, including AI-driven bias.
Levelling the Playing Field?
AI tools can help students practice and enhance their skills and experiences but also raise concerns regarding accessibility and equity. Access to advanced AI tools and the digital literacy required to use them effectively is not necessarily evenly distributed among students. This digital divide could exacerbate existing inequalities, particularly for students from underrepresented backgrounds. Universities play a vital role in educating students to understand the capabilities and limitations of AI tools, enabling them to use these technologies effectively and ethically.
Working with Employer Partners
Collaboration with industry partners remains essential. Understanding AI’s influence on recruitment strategies allows universities to align student support with industry expectations, preparing students for contemporary hiring processes.
AI is undeniably reshaping the employability landscape. However, its integration challenges traditional career development approaches, raising equity, ethics, and authenticity concerns. Universities must adapt by equipping students with skills such as effective prompt engineering to navigate AI-driven processes. Recent reports highlight the need for universities to prepare students for AI-driven assessments, combining technical proficiency with critical thinking and ethical awareness. Aligning employability programs with these insights enables students to harness AI’s full potential while maintaining human-centred career development.
As AI transforms placement applications, universities play a pivotal role in preparing students for this reality. By promoting AI literacy and reflective practices and addressing equity and ethics, universities can empower students to approach placement applications with confidence and integrity. AI should serve as an enhancement tool rather than a barrier. Supporting students in understanding and appropriately using AI tools best prepares them for achieving professional aspirations.
Millions of international students have used the ApplyBoard platform to search for international study opportunities.[1] For many of these students, searching for courses in Australia, Canada, Ireland, the United Kingdom, and the United States is one of the first steps in their study abroad journey. This proprietary search data reveals a leading indicator of changing student preferences.
What UK Fields of Study did International Students Search for in 2024?
After the Sunak Government announced the tightening rules on international student dependants and a review into the graduate route, the UK saw a significant contraction in interest from international students in 2024—applications declined by 14% year-over-year, while dependant applications dropped by 84%. The good news for a struggling sector is that early signs point to positive momentum in 2025, with higher enrolments for many of the institutions that offer a January intake. Enroly data suggests a 23% increase in January 2025 compared to January 2024, and ApplyBoard has experienced growth at three times this rate.
ApplyBoard’s search trends reinforce these early signs: interest in UK courses jumped 25% in 2024 vs. 2023. With search behaviour often signaling future application trends, this surge suggests the UK’s positive momentum in early 2025 could continue throughout the year. Beyond this overall growth, shifting field-of-study preferences highlight how international applicants are adapting to the UK’s changing landscape:
Health fields saw the largest proportional increase among UK searches, climbing nearly four percentage points to 12.8% of all searches. This growing interest aligns with the UK’s expanding healthcare sector, which is projected to add 349,000 jobs by 2035, growing 7% from 2025. Likewise, the information technology sector is expected to grow 8% over the next decade, which aligns with shifting student preferences—ApplyBoard platform data shows Engineering and Technology accounted for 17% of searches in 2024, up two percentage points year-over-year.
Interest in the Sciences also expanded, rising from 13% in 2023 to 16% in 2024. Alongside the gains in Health and Engineering and Technology, this shift underscores how international student priorities are increasingly aligning with long-term global workforce demands.
How International Students are Navigating UK Study Fields
This alignment comes at a time when interest in UK courses is rising. Interest in UK courses grew significantly among several key student populations in 2024, with searches from students in Bangladesh, Sri Lanka, Ghana, and Saudi Arabia doubling year-over-year. Meanwhile, student searches from Nigeria and Pakistan saw substantial gains, rising 66% and 40%, respectively. However, searches from Nepalese students experienced the most dramatic increase, with searches tripling compared to 2023.
Further supporting the possibility that the UK’s positive momentum in January 2025 will continue throughout the year, searches from most key student demographics reached an all-time monthly high in either December 2024 or January 2025.
The graphic below illustrates how major student populations explored different fields of study in the UK on the ApplyBoard platform last year:
Student interest in Health fields was strongest among Ghanaian (22%), Nigerian (20%), and Saudi Arabian students (16%). Compared to the previous year, the share of searches for this field rose by six percentage points among Ghanaian students and five percentage points among Nigerian students. Additionally, the proportion of Health searches among Sri Lankan students doubled over this period.
By comparison, the Sciences were a priority across all nine student populations, making up at least 14% of UK course searches. Students from Pakistan (18%), Saudi Arabia (18%), and Bangladesh (16%) had the highest proportion of Science-related searches. Notably, seven of the nine key student populations devoted a greater share of their searches to the Sciences in 2024 than in the previous year.
Engineering and Technology also accounted for at least 14% of searches among these major student populations, although Sri Lankan (29%), Saudi Arabian (26%), and Chinese (23%) students showed the highest engagement in this field. Additionally, eight of the nine key student populations allocated a larger share of their searches to Engineering and Technology in 2024. As student interest in UK courses continues to grow, institutions can strengthen their appeal by aligning their portfolio with evolving student priorities and workforce needs.
The UK’s Edge: Where Student Interest Outpaces Canada and the US
Understanding where the UK sees higher proportional interest in key fields of study compared to Canada and the US can reveal important competitive advantages for institutions and better inform strategic recruitment strategies. This interactive visualization allows you to explore student interest by field and destination, filterable by top student populations:
Health-related fields accounted for 25% of searches for UK institutions among Filipino students—three percentage points higher than their searches for Canada and the US. Likewise, 22% of Ghanaian students were interested in UK-based Health courses, outpacing the interest shown for both Canadian (21%) and American (20%) options.
In Engineering and Technology, 29% of Sri Lankan students’ searches for UK courses were in this field—matching their interest in US study but well surpassing their searches for Canada (24%).
Social-related fields like Law, Social Sciences, and Teaching captured 10% of Pakistani searches for the UK, outpacing that for Canada (6%) and the US (7%). A similar trend occurred among Bangladeshi students, with 10% of their UK-based searches occurring for social-related fields compared to 7% of Canada and 6% for the US.
Leveraging Search Trends to Shape Future Recruitment
Search trends serve as a leading indicator of shifting student interest, often signaling future application patterns. The surge in searches for UK courses—particularly in high-demand fields like health, engineering, and sciences—suggests a growing alignment between student priorities and workforce needs. By analysing these trends, institutions can proactively refine course offerings and recruitment strategies to attract top international talent. As demand continues to evolve, leveraging real-time search insights enables institutions to stay ahead of market shifts, ensuring they meet student expectations while strengthening their global competitiveness. Understanding where the UK holds a competitive edge will be key to optimizing outreach and course development in 2025 and beyond.
[1] In the past, ApplyBoard platform search data was generated based on button clicks on a page, while the new search data is generated by any changes made to the page’s filters (destination, field of study, etc.) As a result, the new search count, if tallied using the previous search data approach, would be significantly inflated compared to the original search count. To make the search counts more comparable, we changed our methodology as of August 2024 to use unique entries per user within each hour.
