Category Archives: AI in Education

Sean's Learner Journey
March 25th

Why I Created Learner Journey

It didn’t start with a product idea. It started with a belief.

A simple one: learning never ends.

Years ago, I found myself doing what many of us do without really thinking about it—I was teaching myself. Late nights, searching the internet, watching videos, reading articles, testing ideas, failing, trying again. No classroom. No teacher. Just curiosity and persistence.

That was my learning journey.

And somewhere along the way, I realised something important: the most powerful learning I had ever done wasn’t structured, packaged, or handed to me. It was something I created for myself.

That idea stuck.

A Domain Name… and a Bigger Idea

At the time, I owned the domain learnerjourney.com. It felt significant. Not because of the name itself, but because of what it represented.

Learning isn’t a course.

It isn’t a module.

It isn’t something you “complete.”

It’s a journey.

And yet, most systems treat it like a checklist—start here, finish there, tick the box.

I wanted to build something that reflected reality. Something that recognised that learning is continuous, personal, and evolving.

From Consumer to Creator

The real turning point came when I asked a simple question:

What if learners didn’t just consume content… but created it?

That’s where Learner Journey began.

Instead of teachers doing all the work, what if students could build their own learning paths?

A learning path isn’t complicated. It’s just a series of pages—text, images, videos, podcasts, quizzes—woven together around a topic. But when a learner creates it themselves, something changes.

They engage differently.

They think differently.

They own it.

A student revising for exams can build their own path.

Someone learning Spanish can mix podcasts, quizzes, and notes.

A professional can map out skills they want to develop.

Learning becomes active. Creative. Personal.

And most importantly – memorable.

The Power of Sharing the Journey

But learning, for me, was never just about the individual.

It was about connection.

So we built Learner Journey to be social.

Not in the noisy, distracting way most platforms are – but in a meaningful way.

You can share your learning path.

Others can follow it.

They can complete it.

You can see their progress.

You can message them, collaborate, improve.

It becomes a shared experience.

And at the end of that journey, there’s a certificate. Not just as a piece of paper, but as a signal – like a badge you earn in Scouts.

A micro-credential.

A proof of effort.

Something you can show the world and say, “I learned this.”

A Learning Passport for Life

One of the biggest frustrations I’ve always had with education is how fragmented it is.

You move from school to college.

From college to university.

From university to work.

And every time – you start again.

Your learning doesn’t travel with you.

I wanted to change that.

Learner Journey is designed to stay with you. A kind of lifelong learning passport.

Something you build over time.

Something you carry with you.

Something that grows as you grow.

Not owned by an institution—but by you.

The Bigger Vision

If there’s one thing I hope Learner Journey changes, it’s this:

That we stop seeing learners as consumers… and start seeing them as creators.

Yes, you can learn from other people’s journeys.

But the real magic happens when you build your own.

Because when you create your learning, you don’t just understand it.

You internalise it.

You personalise it.

You remember it.

And maybe most importantly—you enjoy it.

In the End, It’s Personal

Learner Journey is, in many ways, a reflection of how I learned.

Unstructured. Curious. Creative. Social.

It’s the platform I wish I had.

And if it works the way I hope it will, it won’t just help people learn more.

It will help them learn better.

On their terms.

In their way.

On their journey.

Founder of Sapio Ltd and a leading voice in AI and digital strategy, Laura Knight empowers education leaders worldwide to harness technology responsibly, build inclusive cultures, and turn innovation into real impact.
February 4th

AI Is Already in the Classroom – The Question Now Is How Schools Lead

The debate about artificial intelligence in education has moved on. At the AI in Education Institute event hosted at York St John’s University, there was little sense that schools were still deciding whether AI belonged in the system. That question, most delegates agreed, has already been answered in practice. The sharper, more pressing issue now is leadership: how schools make sense of AI’s growing presence, how they set boundaries, and how they retain professional judgement in a period of rapid change.

From the outset, the tone was measured rather than breathless. AI was discussed not as a future disruption, but as a present reality. More than half of teachers have used an AI tool for school work in the past week, according to figures referenced during the event. Only a small minority say they have never used one at all. AI, in other words, is no longer an experiment at the edges of education. It is already embedded in planning, feedback, administration and decision-making – often quietly, and not always consistently.

The keynote address from Laura Knight framed the challenge with clarity. The problem, she argued, is not access to technology, but confidence in its use. Teachers are experimenting, sometimes highly effectively, but not always openly. While many feel comfortable using AI tools, fewer feel fully at ease discussing how they use them with colleagues. That gap – between practice and shared understanding – is where risk, inconsistency and anxiety can take hold.

Rather than advocating sweeping policies or rapid roll-outs, the emphasis throughout the morning was on deliberate leadership. Schools were encouraged to be clear about purpose before they worry about platforms. Why is AI being used? Which problems is it intended to solve? And which decisions must remain firmly human? Without that clarity, there is a danger that schools chase the “next big thing”, adopt tools at speed, and lose sight of what teaching and learning are actually for.

Several speakers returned to the same underlying concern: velocity. AI systems evolve far faster than traditional school improvement cycles. Leaders are being asked to make decisions in an environment where accountability measures are still rooted in older models, and where professional development has not always kept pace. The result can be fragmented adoption – pockets of innovation alongside uncertainty, and sometimes silence.

From here, the conversation became more searching. One slide posed a deceptively simple question: are schools “winning or losing” when it comes to AI? Measuring success purely in terms of efficiency or productivity, delegates were warned, risks missing the point. Education is not an optimisation problem to be solved.

Humans, as one slide put it, are social, creative and brilliant – but also inconsistent, messy and flawed. That reality, speakers argued, is not something technology should attempt to erase. AI can support human decision-making, but it cannot replace the values that underpin it. Leadership, therefore, is not about removing uncertainty, but about holding it responsibly.

Much of this discussion centred on what was described as “the line”. Above it sit practices that are inclusive, transparent, equitable and values-aligned. Below it lie approaches that are opaque, exclusionary or misaligned with a school’s purpose. The difficulty is not that the line exists, but that it shifts as tools evolve. Drawing it – and redrawing it – is an ongoing act of judgement, not something that can be outsourced to software or policy templates.

This raises uncomfortable questions. Who decides what counts as appropriate use? Who is accountable when AI use drifts into compliance theatre, where policies exist on paper but not in practice? And who ultimately bears the consequences when technology reshapes learning in ways that were not fully intended?

Concerns about “intellectual offloading” also surfaced repeatedly. AI can reduce workload, but there is a difference between support and substitution. When systems begin to shape thinking rather than assist it, schools risk losing professional agency. Risks such as function creep, surveillance capitalism and long-term dependency were not presented as inevitabilities, but as outcomes that require active leadership to avoid.

From here, the focus turned inward – towards performance, feedback and growth. Used carefully, AI can act as a thinking partner rather than a shortcut. Leaders were shown examples of how it can create safe spaces for rehearsal and reflection: role-playing difficult conversations, stress-testing decisions, or drafting responses to challenging scenarios. The value lies not in producing perfect answers, but in sharpening judgement.

This reframes feedback. Instead of being occasional and high-stakes, feedback becomes ongoing, low-risk and developmental. Leaders can draft, critique, iterate and reflect – building confidence through repetition. Mistakes happen privately; learning happens continuously. But this only works, speakers cautioned, if leaders remain firmly in control of the process. AI can surface perspectives, but it cannot define priorities or values. That responsibility remains human.

The final section of the event widened the lens further still, returning to a question that had underpinned every discussion: what does it really mean to do the work? Not to adopt tools, write policies or meet compliance thresholds – but to take responsibility.

The closing focus on data stewardship and digital sovereignty made clear that this is where leadership becomes most visible. Schools were encouraged to move beyond passive acceptance of technology and towards active stewardship: mapping where data flows, assessing who has access, clarifying purposes, stress-testing assumptions and setting boundaries. Safeguarding, in this context, extends beyond physical and online safety to include pupils’ digital identities over time.

Delegates were urged to treat data as something held in trust, not something exchanged for convenience. That means asking difficult questions of suppliers, understanding contractual language, and resisting systems built on opacity or behavioural surplus. Vendor lock-in, it was argued, is not just a technical risk, but an ethical one – limiting future choice and narrowing professional autonomy.

Trust, speakers concluded, is built through visibility. Clear, accessible policies for staff, pupils and families are not bureaucratic add-ons, but signals of intent. Stewardship, when done well, becomes a public act of leadership – one that reassures communities that innovation is being handled with care rather than haste.

As the AI in Education Institute event at York St John’s University drew to a close, the mood was neither alarmist nor celebratory. It was pragmatic. AI is already reshaping education. The real question is whether schools lead that change with clarity and purpose, or allow momentum to make decisions for them. Doing the work, in this moment, means choosing values over novelty, judgement over speed, and responsibility over delegation.

Dr Beth Lane - York St John University launches national Institute of AI Education
February 4th

York St John University Launches National Institute of AI Education

York St John University has hosted the launch of the new Institute of AI Education, bringing together teachers, researchers, school leaders and policymakers to consider how artificial intelligence should be understood and used across England’s education system.

The event, held at the university’s Creative Centre in York, marked the formal introduction of a research-led initiative focused on embedding AI literacy, critical thinking and learner agency across classrooms, teacher training and leadership practice. Organisers described the institute as a “work in progress by design”, inviting schools and educators to help shape its direction from the outset.

Based in York, the institute will operate on a national “hub and spoke” model, supporting regional networks while working closely with schools, universities and researchers. Rather than positioning AI as a standalone subject, the approach aims to weave AI literacy through existing curricula.

Opening the event, speakers said the central question for education was no longer whether AI would have an impact, but how schools and systems could respond responsibly, equitably and in the long-term interests of children and young people.

That focus on people rather than technology set the tone for the day. In their founders’ address, co-founders Beth Lane and Narinder Gill shared personal journeys that reflected the institute’s wider values.

Dr Beth Lane’s Journey from leaving school at 16 to PHD in Computer Science

Dr Lane spoke about leaving school at 16 and starting work on a supermarket checkout before moving into industry, completing an apprenticeship and later returning to education to study computer science and complete a doctorate. Her story, she said, was a reminder that education systems must recognise potential at every stage of life, not only through traditional academic routes.

Narinder a people-first education leader and executive coach, focused on building resilient communities and helping schools and systems drive meaningful, lasting change.

Narinder Gill described a career shaped by public service and education policy, including work with the Department for Education, the Association of Education Advisers and regional leadership across Yorkshire and the Humber. Her experience highlighted the importance of strong systems, trusted professionals and local communities in turning innovation into meaningful change in classrooms.

Together, the founders argued that AI cannot be embedded effectively in education without being grounded in lived experience – of teachers under pressure, of learners who do not fit neat categories, and of communities navigating rapid technological change.

The institute’s ambition, they said, is not to accelerate adoption for its own sake, but to support thoughtful, ethical progress. Its work will focus on helping children learn not just how to use AI tools, but how to question them, understand their limitations and reflect on their own thinking and emotional responses.

As the launch drew to a close, the message was clear: the future of AI in education will not be shaped by technology alone, but by people, diverse pathways and a shared commitment to evidence, trust and collaboration.

How AI is changing the way assessments are created in education and training

For decades, assessments have followed a familiar pattern. A teacher or trainer designs a test, delivers it to a group, marks the results, and moves on. It is a system that works — but one that is time-consuming, inflexible, and often poorly matched to how people actually learn.

Artificial intelligence is now beginning to change that process. One platform at the centre of this shift is Learner Journey, which is using AI to help educators, trainers, and organisations create assessments that are faster to build, easier to adapt, and more personal for each learner.

From one-size-fits-all to personalised assessment

Traditional assessments are usually written for an “average” learner. In reality, classrooms and workplaces are made up of people with very different needs — from learners with special educational needs, to gifted students, to professionals who already have deep subject knowledge.

AI-powered assessment tools allow educators to start from a different place. Instead of writing every question from scratch, teachers can describe what they want to assess — a skill, a topic, or an outcome — and let AI generate a first draft of questions, quizzes, reflections, or tasks.

On Learner Journey, those assessments can then be adjusted instantly: simplified for one group, made more challenging for another, or rewritten in a different tone or reading level. The same learning objective can result in multiple assessment routes, all aligned but tailored.

Assessments built into learning journeys

Rather than treating assessment as a separate event at the end of a course, AI makes it possible to embed assessment throughout the learning process.

Learner Journey structures learning as a series of connected pages — combining text, audio, video, quizzes, and tasks. Assessments can appear naturally within these pages: a short reflection after a video, a quick check-for-understanding quiz, or a longer applied task at the end of a section.

This approach reflects how people actually learn. Frequent, low-stakes assessment helps learners test their understanding, while giving teachers and trainers a clearer picture of progress in real time.

Saving time, without losing professional judgement

One of the biggest concerns about AI in education is whether it replaces professional expertise. In practice, platforms like Learner Journey are designed to do the opposite.

AI handles the heavy lifting — drafting questions, suggesting rubrics, generating feedback prompts — while educators remain in control. Teachers can edit, refine, approve, or reject anything the system produces. The result is not automated assessment, but assisted assessment.

For busy teachers and learning designers, this can mean hours saved each week, particularly when creating multiple versions of the same assessment or updating content to reflect new requirements.

Clear evidence and better feedback

AI-generated assessments also make it easier to capture evidence of learning. Responses can be analysed to highlight strengths, gaps, and patterns across a class or cohort. Feedback can be more specific and timely, helping learners understand not just what they got wrong, but what to do next.

In schools, this can support inspection readiness and inclusive practice. In businesses, it helps link learning directly to skills development and performance.

A shift in how success is measured

The wider impact of AI-driven assessment may be cultural as much as technical. When assessments are easier to create and adapt, educators can focus less on administration and more on learning itself.

Instead of asking, “How do we test everyone the same way?”, the question becomes, “How do we help each learner show what they know?”

As AI tools like Learner Journey continue to develop, assessment is moving away from static tests and towards something more dynamic — a continuous conversation between learner, teacher, and technology.

The Skills System Just Changed. Why Learning Needs to Change With It.

There’s a strange habit in education: we keep trying to fix a twenty-first-century problem with a twentieth-century workflow.

We write long strategies about lifelong learning, digital skills, employer partnerships, modular study, technical excellence, flexible courses, and getting young people into good jobs. All great ideas. But behind the scenes, the same thing always trips people up:

Creating the actual learning.

You can’t deliver flexible learning with inflexible tools.

You can’t deliver modular courses with monolithic content.

You can’t reduce teacher workload by asking people to do even more work.

The government’s new skills plan says all the right things:

• Lifelong, modular learning

• Short courses aligned to real jobs

• Better digital and AI skills

• Clearer pathways from school to work

• Support for NEET learners

• More employer-led training

• Upskilling everyone, not just a few

But none of this sticks unless we fix the part nobody talks about: the creation of learning itself.

Because if it takes three weeks to build a course, the future they’re describing never arrives.

The bottleneck nobody mentions

In schools, FE colleges, universities and employer training teams, content creation is always the blocker. It’s slow. It’s manual. And it’s stuck in a world of templates, PDFs and PowerPoints.

Modular learning? Sounds great—until you realise someone has to build all those modules.

Short courses for adults? Perfect—until you remember most teams don’t have the capacity.

AI skills for every learner? Necessary—until you see how long it takes to create one lesson, never mind fifty.

If the new national skills system is a high-speed rail line, content creation is the old railway crossing holding everything up.

Learning needs a different workflow

Great platforms don’t solve problems by adding layers—they solve them by removing friction.

This is where AI isn’t hype, but hygiene.

The future learning system needs tools that let a teacher, lecturer or employer turn an idea into something useful in seconds, not weeks. A page, a quiz, a video, an illustration, a learning path. Done.

The future system requires the ability to build lots of content, quickly, because the demands of the labour market are not slowing down. AI literacy today. Construction tomorrow. Clean energy next year. Defence, cybersecurity, health, engineering—constant shift.

In this new world, the ability to generate learning fast becomes a national capability.

This is why we built Learner Journey the way we did.

From idea to learning page in seconds

Learner Journey isn’t trying to reinvent learning. It’s trying to reinvent the workflow.

Prompt → Page

Prompt → Quiz

Prompt → Video

Prompt → Learning Path

Not someday. Not with a team of designers.

Now. In seconds.

Teachers can finally build something without burning out.

Training managers can finally iterate instead of waiting.

Learners get learning that is current, contextual and aligned to emerging skills—not whatever was written three years ago.

This is what modular learning actually requires: modular creation.

The skills system is becoming modular. The tools need to be too.

The government is introducing:

• V Levels to replace the messy patchwork of vocational qualifications

• Technical Excellence Colleges to specialise in priority sectors

• A Lifelong Learning Entitlement for flexible, stackable study

• Sector skills packages for digital, AI, engineering, construction and defence

• Local Skills Improvement Plans driven by employer demand

• Youth Guarantee preventing young people from falling through cracks

• Apprenticeship units funded through the new Growth and Skills Levy

This isn’t random. It’s a sign of a system shifting from content-first learning to skills-first learning.

But skills-first only works if teams can build, adapt and update learning continuously. The status quo won’t get us there. Not with current workloads. Not with current resources. Not with current tools.

The system needs a faster way to build learning. A way that matches the pace of change.

We don’t need more tools. We need better ones.

The education sector has spent two decades collecting tools the way people collect gym memberships: optimistically.

But most tools add complexity.

Most tools add workload.

Most tools assume the hard part—creating the learning—is someone else’s problem.

Learner Journey flips the assumption. We treat the creation of learning as the main product, not a side feature.

When you reduce friction, people create more.

When you make creation fast, people iterate more.

When you make learning modular, people reassemble it into paths that make sense.

And suddenly everything the skills plan talks about becomes possible.

The future isn’t big courses. The future is small pages.

Small pages you can assemble.

Small pages you can update.

Small pages you can personalise.

Small pages learners can actually finish.

This is how you respond to a world where job roles shift every 18 months, and where digital and AI literacy are no longer optional.

It’s also how you support the people who have been left behind—NEET learners, adults with low confidence, learners with SEND—who don’t engage with big, overwhelming chunks of content but do respond to bitesize, guided progress.

Small pages build big futures.

The real shift in skills is a shift in speed

Governments can write white papers.

Universities can write strategies.

Colleges can create pathways.

Employers can fund training.

But unless the people on the ground can build learning at the speed the system demands, we stay stuck in the old world.

Future learning will not be built top-down.

It will be built page-by-page, path-by-path, by the people closest to the learner.

The only question is whether the tools they use will slow them down or speed them up.

Learner Journey is designed for speed.

Because when learning moves faster, people do too.