Tag Archives: Edtech

Glowing staircase leading to a bright doorway among geometric crystal shapes

Helping CEOs and investors work out what needs to change

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Being close to a problem can make it hard to see, for management and for boards alike.

Management knows the business in detail, which is a strength and can also be a limitation. Boards see the numbers but not always what sits behind them. Investors often have a view but not the time to test it. The result is that the first explanation for a performance gap tends to stick, even when it is only part of the story.

I’ve been a CEO and Chairman in learning and edtech, and I have seen how these conversations work from both seats. I’m now open to taking on a new strategic advisory assignment, particularly in education, publishing and information services.

What the work involves

  1. Working out what is driving the performance gap. This means looking past the headline metrics to the commercial and organisational causes underneath them.
  2. Testing the business plan, including assumptions nobody has questioned for a while. Assumptions that were reasonable at the time of the deal or the last strategy review are worth checking again.
  3. Identifying the changes that matter most. Usually that is a short list, and it helps just as much to be clear about what should be left alone.

How I work

I work as an independent, directly with the CEO and the investor or Chairman, so everyone sees the same analysis. I start with a few conversations and the numbers, and I give an honest view of what I find, including where I think the plan or the diagnosis needs to change. The aim is a clear set of priorities the team can act on.

Who it suits

It tends to suit CEOs who want an experienced sparring partner, and investors who want an independent view before or after a deal. It can also help boards that want a fresh read on a question they have been discussing for some time.

If you run or back a business where that would help, send me a message, either here, on LinkedIn, or through www.executive-mentor.com. A first conversation is easy to arrange, and it is fine if the outcome is that no outside help is needed.

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AI and Learning: There’s a Fraction too Little Friction

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I’ve been thinking quite a lot recently about what happens to learning when we introduce generative AI.

My concern is that if AI makes it easier to complete a task, are we also making it easier to avoid the thinking that gets us there?

That’s why I was interested in a recent paper looking at human-AI collaboration at scale.

AI, Claudius

The researchers analysed almost 250,000 real-world conversations with Claude. Rather than looking at what AI could do in a controlled experiment, they looked at what people were actually doing with it.

There’s quite a lot of learning going on.

In 67% of learning and upskilling conversations, Claude engaged in some form of teaching. This wasn’t just school or university work. Software development, health and lifestyle, and business were among the most common areas.

A pie chart illustrating that 67% of teaching is done by AI, alongside a bar graph detailing teaching methods: Mixed methods (61.1%), Step-by-step (17.4%), Explanation (12.8%), Example-driven (7.7%), Socratic questioning (0.6%), and Analogy/metaphor (0.4%). The graph also categorizes teaching domains: Health & Lifestyle (18%), Software development (18%), Academic coursework (15%), Business & entrepreneurship (12%), Creative content (10%), Legal & financial (10%), AI & data (9%), Career development (5%), and Harmful & sensitive (2%).

The most common approach was combining conceptual explanation with step-by-step guidance.

So far, so good. But teaching and learning are not the same thing. I can ask AI to explain how something works. I can also ask it to do the work for me. The two interactions might look superficially similar, but the consequences for learning are very different.

Then I read that almost half of the conversations involved some form of friction. The AI misunderstood the question, made a mistake, couldn’t do what the user wanted, or perhaps the user’s instructions weren’t clear enough.

Normally, we think of this as something technology should get better at eliminating. However, in 78.7% of these cases, users tried to recover from the problem, and when people challenged the AI’s reasoning, those attempts were successful 81.5% of the time.

This is much more interesting than the headline that AI can teach.

Resistance is not futile

Use of AI in learning often looks like this: Ask a question. Get an answer. Move on.

There is a more productive version: Ask a question. Get an answer. Notice something doesn’t make sense. Challenge it. Work through the disagreement. Correct the answer.

The second interaction looks rather like learning. There is effort, uncertainty, feedback. There is the possibility of being wrong. The learner still has to think.

Are we using AI to make learning more effective, or to make tasks more efficient?

A student who uses AI to produce a better piece of homework may well get a better piece of homework. But that doesn’t tell us whether the student has become better at the underlying task.

On the other hand, an AI system that helps a student formulate a question, tests their understanding, gives them feedback and challenges their reasoning could potentially be a very powerful learning tool.

The difference is what the human is doing.

The answer isn’t to keep AI away from learning. Quite the opposite. The potential is enormous. But we should be careful about celebrating every reduction in effort.

Effort is the point. Productive effort drives learning.

If AI removes all of it, we may discover that we have superficially made learning “easier” but also thrown the baby out with the bathwater.

AI can teach.

But can we use AI to make learning easier without taking the learning out of it.

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Coaching and Mentoring

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Today was my last day as Chairman of Infinitas Learning — and the end of an important chapter for me in educational publishing, following my earlier years as CEO of Sanoma Learning.

Those who know me well know how passionate I am about learning, and about the role organisations like Infinitas and Sanoma play in supporting learner outcomes and helping teachers in their vitally important work.

Following its acquisition by NPM Capital as lead investor, we have doubled the size of the business, including expanding into Portugal and Poland. Working on that growth — alongside the company’s digital and, more recently, its AI transformations — has been especially rewarding. There are enormous opportunities ahead to better support both teachers and students.

Most of all, I’ve valued the people. My colleagues at Infinitas and NPM Capital have been outstanding, and I’m genuinely grateful to have been part of the journey. I wish them every success for the future.

Over the past 15 years leading and chairing organisations in edtech and learning, I’ve accumulated hard-won experience in leadership, transformation, and what it takes to grow — both as an organisation and as a person. And I’m still very much learning. What continues to fascinate me is how much of leadership ultimately comes down to learning.

In the next phase, I want to put that experience to work more directly through coaching and mentoring, alongside my ongoing board commitments in edtech, including as Chairman of Ovivio.

Where I’d most like to help:
> Executive transition coaching — supporting leaders stepping into C-suite or senior roles for the first time.
> Strategic leadership — working through the real complexity of leading organisations through change.
> Personal effectiveness — helping leaders perform at their best.

For mentoring, my focus will naturally remain close to education and edtech (while avoiding conflicts with Infinitas or Ovivio). For coaching, the methodology is different, and I am keen to work more broadly across sectors — including healthtech and business services.

If any of this resonates, or if you simply want to catch up, feel free to reach out here or directly at: johnmartin@contentconnected.com

Looking forward to what comes next.

#learning #education #edtech #coaching #mentoring

Is the teacher still the ‘killer app’ in the age of AI?

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AI in education is often framed as a battle between humans and machines. Based on conversations with teachers, founders and investors over the past year, I believe the real opportunities lie in partnership, not replacement.

The OECD’s Digital Education Outlook 2026 frames AI’s role in relation to teachers across three paradigms: replacement, complementarity and augmentation. But there’s a second often overlooked dimension: institutional embedding.  Moats in education aren’t built on technology or data alone, but on alignment with pedagogical goals, curricula, regulations & governance, procurement processes and professional practice.

1. Replacement — The Productivity Play

In replacement, AI automates tasks historically done by teachers. For example, grading, summarising texts, preparing lessons, generating worksheets and providing basic feedback loops.

This is where much of today’s AI attention is focused. Tasks that were once labour-intensive can now be executed quickly using general-purpose large language models.

However,  technology that replaces discrete tasks can be easy to replicate.  Application-layer companies that don’t control workflow, data or distribution potentially become interchangeable.

2. Complementarity — Enhancing the Teacher

Complementarity is where AI does not replace teachers but meaningfully enhances their capacity. For example:

  • turning classroom data into real-time insights
  • tracking student progress against goals
  • flagging risks and opportunities
  • designing targeted interventions

Here, teachers retain judgement while AI expands insights and  sharpens execution. The result? More impactful and stickier solutions because:

  • the solution integrates with daily workflows
  • the value is tied to teacher judgement, not automation
  • switching costs rise as the technology adapts to context
  • integration with existing systems (LMS, assessment frameworks, schedules) deepens.

In Europe especially, where education systems are fragmented by language, standards and national curriculum requirements, this tailored integration is the key to durability.

3. Augmentation — Supercharging the Teacher

Augmentation involves human–AI co‑evolution: AI learns from teacher feedback over time, adapts to their pedagogical style, and augments their professional practice in ways that produce outcomes neither could achieve alone.

In theory, this is the next frontier.

But the evidence suggests caution. Recent cross‑sector analyses have found that human–AI teams often underperform the better solo performer — not because AI is weak, but because synergy is hard to design and requires:

  • structured feedback loops
  • task‑specific modelling
  • data that is pedagogically meaningful
  • long‑term usage and refinement.

These conditions are relatively rare — and do not emerge automatically from generic chatbots. Consequently, many augmentation efforts risk failing before a few succeed spectacularly.

This layer will be hard to build, slow to monetise, but potentially transformative if it materialises. The Holy Grail, but not for the faint-hearted investor.

But even the most advanced augmentation tools will fail if they don’t address a deeper challenge: institutional embedding.

The Overlooked Dimension: Institutional Embedding

If replacement, complementarity and augmentation describe how AI interacts with the teacher, the moat is arguably how deeply a solution embeds in the system.

Edtech solutions thrive where:

  • curriculum alignment exists
  • pedagogical norms reinforce its use
  • there are many rules and regulations
  • procurement frameworks are understood and effective go-to-market capabilities are developed and in place
  • teacher support boosts adoption
  • governance structures (schools, districts, ministries) endorse and fund it

Know-how about working with institutions and alignment with standards determine durability.

This is particularly true in Europe, where:

  • education is governed nationally and regionally
  • language and curriculum diversity creates product differentiation challenges
  • procurement cycles are long and complex
  • teacher autonomy is the norm.

A solution that is embedded institutionally — even if technically less advanced — will often outlive and outperform one that is technically stronger but misses the expertise around the institutions it is designed to serve.

This is where real moats are built.

The next edtech winners won’t rely on algorithms alone.  They’ll succeed by understanding that the best AI doesn’t replace teachers or even just work for them. It works with them.

Where do you see the biggest opportunities?

Looking forward >>

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It’s time to scale up European edtech

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Last week, Brighteye Ventures, a leading European investor in education technology, published the fifth edition of its European Edtech Funding Report. It looks like 2023 might be the trough of the cycle that peaked with the pandemic in 2021, and there are increasingly strong signals of a resurgence in investor appetite in 2024.

Reasons to be Cheerful

  1. After a period of decline, overall new venture funding for European edtech in 2023 surpassed the levels reached in 2020 ($1.2B vs $951M) and the number of deals increased on 2022 (288 vs 256).
  2. About 1/3 of all global edtech deals took place in Europe in 2023 (a record high proportion, up from 21% in 2019), indicating a high level of investor interest in the European market.
  3. International private equity and venture capital investors are currently holding a record amount of dry power, with $2586B ready for deployment at the top 25 PE investors globally.

Resilience?

From a European perspective, “resilience in the volume of deals” was driven by a rising number of deals under $4M, with over half of the completed deals being done at $1M or less. 

Bar chart illustrating deal counts by round size categories from 2017 to 2023, highlighting a notable increase in deals under $4 million.

On the micro level of individual businesses, this thinly spread funding might make some sense, yet on the macro level of the industry and the customer, it also highlights part of the European challenge, namely lack of scale. You have to wonder if something substantial and world-class will be built out of some of these tiny deals. Usually “recessions” (possibly a relative term in tech) are a good opportunity for industries to restructure, with strong firms building on their strengths and weaker firms going out of business in what is typically a healthy evolutionary process.

Enable and simplify the work of the teacher

According to some estimates there are currently about 27,500 edtech companies in the K-12 sector, obviously not all deployed in all schools, but it’s not uncommon for schools to use hundreds of digital products. Imagine the life of a teacher. Her first concern is leading a classroom of 25-30 children, which is no mean feat in itself. When she deploys a digital solution it needs to:

a) positively impact learner outcomes

b) be easy to use and

c) ideally save time that she can use for interacting with students.

A teacher is best served by a smaller number of well-performing and frequently-used solutions than a huge toolbox of occasionally-used options.

Build a European Champion

In my view, investors in European edtech should focus on increasing scale and building a handful of segment-specific European/International Champions. At scale, a European Champion has the resources in terms of talent, know-how and money to develop and deploy top-notch learning solutions, yielding excellent learning impact and delivering good financial returns. It’s my hope (and expectation) that a group of investors will take the opportunity at this early stage in the new economic cycle to take our industry and the services we provide to schools to the next level.

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How will AI impact teachers?

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Super-charger

ChatGPT has recently triggered tremendous excitement about AI and its potential impact on education. Much interest has focused on the learner experience, including the ability to personalise learning. There have of course also been concerns around cheating and plagiarism.

However, AI also has the potential to super-charge teachers.

According to McKinsey, 20-40% of current teacher time comprises tasks that could be automated. They estimate that teachers could re-direct approximately 13 hours per week towards activities that raise student outcomes and increase teacher satisfaction.  The tasks of preparing lessons, administration, evaluation and feedback are flagged as high potential for AI.

Love’s Labour’s Lost

These results echo those of Sanoma’s Learning Impact Survey, in which teachers indicate a desire to go digital in those areas which were most labour intensive, flagging essentially the same areas.  This suggests both that the opportunity is in these tasks and that the profession is looking for solutions.

present_vs_ideal

Teaching profession under pressure

The teacher is arguably the most positive intervention in education.  However the teaching profession faces significant challenges.  UNESCO estimates an additional 69m teachers need to enter the profession by 2030 to fulfil global demand.  In some parts of the world, teacher turnover is high, for example in parts of the USA annual teacher turnover exceeds 15%.  In the UK more than 80% of teachers are considering leaving the profession due to dis-satisfaction.

Higher impact & happier teachers needed!

Furthermore, on average teachers spend only half of their time actually teaching.  This represents not only lost productivity from the core task but is also demotivating for many teachers whose passion is to teach rather than the ancillary tasks around it.  Enabling teacher workflow could therefore not only increase productivity but also make the profession more attractive.

SVGZ-AI-boon-Ex1.svgz

$400bn impact & opportunity

The opportunity to solve this productivity gap is huge.  Measured in terms of financials, assuming global spending on education to be some $6trn, of which 45% is on K-12 education,  and of which 75% is spent on staff salaries, this implies a global spend on teaching/staff salaries of some $2trn per year.  A 20-40% uplift in productivity through AI could arguably be worth some $400-800bn per year in terms of paid and unpaid output!  Which is not to say that this is a saving governments could make or a revenue that education companies could earn, because a significant slice of that value should rightfully return to teachers through higher salaries and quality of life, and another part would rightfully get re-directed to teacher-student interaction to increase outcomes and professional satisfaction.

20%

Help the teacher to focus on teaching!

It’s my belief that the teacher will continue to be the killer app in education, and that the biggest opportunity to make not only a positive impact on learning and teaching in K-12 but also to build a successful business, is to enable the workflow of the teacher.  Probably by combining it with the other side of the same coin: the learn-flow (learning experience) of the student.  

Looking forward >>

It will be exciting to see how we deploy AI in the coming years for a positive impact on learning. Looking forward >>.

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Attention edtech champions! 

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EdTechX Awards 2022

EdTechX is currently running the 10th edition of the All Stars Awards. They’re a fantastic opportunity to see who’s shaping the future of edtech, with previous winners including the heroes at Kahoot!, Kognity, Busuu, OpenClassrooms and FutureLearn.

Learning, Earning and Yearning

They say there are three ingredients to the good life, learning, earning and yearning, which seems to have inspired the three categories this year:

  • Startup, for ventures with annual revenues of less than €5M, who have demonstrated stellar innovation and growth over the last year Apply here >>
  • Scale-Up for ventures with annual revenues over €5M who have delivered outstanding revenue growth momentum over the last 3 years Apply here >>
  • ESG & Impact for companies who can demonstrate positive ESG (Environmental, Social, and Governance) policies and impact strategies. Apply here >>

Summit Up

EdTechX is accepting applications right now – don’t miss the deadline of 30th April.  

Winners and finalists will be announced at the EdTechX Awards Ceremony during the EdTechX Summit on 23 June in London.

Looking forward >>

I’ve joined all of the EdtechX meetings to date and they’re a great place to network with the movers and shakers in the industry.  It’s also a perfect opportunity to visit London again 😊.

Paper – where efficacy meets equity

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I was excited to read about this $270M Series D round for Canadian-based ubiquitous tutoring solution Paper – where efficacy meets equity.

A thousand blossoms blooming

Bloom’s seminal work on the 2 Sigma Problem, carried out in the early 1980’s is a classic must-read for edtech ventures today. The outcomes of the research are startling, showing that an average student under tutoring performs about two standard deviations above the average performance of a conventional class. 

Or put another way, an average student following a tutoring program outperforms 98% of students in a conventional classroom!

Since then, the private tutoring market has grown significantly, although new regulations in China last year driven by concerns around equity and student well-being did have a significant negative impact on that market. 

Efficacy AND equity

The good thing about the private tutoring market is its efficacy – it raises learner outcomes.  The disadvantage however is that the rich tend to benefit disproportionately, because they can afford it. The resulting inequity can’t be a good design principle for the provision of education.

Since Bloom, the search has been on to provide solutions that yield similar efficacy at scale.  Paper is potentially such a solution.  For a fixed price, Paper sells licenses to schools and districts to make its online tutoring support available to every student, around the clock, with no cap on usage. Students can connect with a trained tutor for homework help, writing feedback and study support across all K-12 subject areas. Teachers at schools can access these sessions, see which students need support, and adjust their instruction accordingly.

I’m enthusiastic about this approach because it enables both efficacy and equity in education. The risk of inequity isn’t completed removed of course because richer schools might be more likely to adopt the solution than poorer.  Yet with most K-12 education systems funded publicly, that risk could be mitigated by policy. A second risk could be increased competition between schools and tutoring companies for teachers.  Yet the deployment of university students and new/re-entrants into the profession could also work to increase the overall talent pool of teachers available.

Looking forward >>

I’m very interested to see how Paper will grow in the coming years and believe there could be international potential for this type of solution.

BETTer Future

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I’ll be visiting London and BETT at the end of March (probably 22nd -24th).  As for so many of us this will be my first trade fair since the pandemic and I’m really looking forward to joining in real life again (never expected to be this enthusiastic about a trade fair, not even BETT 😊). It does feel like we are now emerging from the restrictions of the last couple of years and I’m excited to get out there again.

I’m especially interested to meet people from companies with strong market positions, from scale-ups and from investors in the education, edtech, science and healthtech spaces during my trip to London.

As of March I have some availability for advisory and interim work and have extensive skills and experience in leadership/leading change, digital/transformation and commercial/strategy work.  I have deep knowledge and networks across the European education sector.

I’m also open to become a Non-Executive Director of such an organisation, as long as this doesn’t conflict with existing work. Very flexible in terms of location.

Feel free to send me a message at johnmartin@contentconnected.com or DM me on social media if you would like to meet up in London!

Looking forward >>

#OpenForWork #Leadership #Education #Edtech #Science #Digital #Transformation

European edtech & the emergence of supplementary education

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The Brighteye Ventures Edtech Funding Report released last week evidenced a positive and increasingly broad-based development of the European edtech sector:

Venture capital funding tripled over the previous year, reaching some $2.5B.

A bar graph displaying annual transaction data from 2014 to 2021, showing the number of transactions and corresponding dollar amounts, with a significant increase in total value reaching $2.50 billion in 2021.

Average deal size also tripled to $8.4M, indicating increasing maturity of the sector.

A bar graph illustrating yearly transaction values and counts from 2014 to 2021, showing a significant increase in 2021 with $8.4 million from 299 transactions and 23.5% average growth.

Corporate Learning attracted the most funding ($926M), followed by K-12 ($659M) and Life-long/Consumer Learning ($652M), with Higher Education ($289M) and Pre-K ($136M) trailing. One possible reason being that B2C and B2B segments are sometimes seen as easier to sell into than B2G.

Bar graph showing funding distributions across various education sectors, including Pre-K ($136M), K-12 ($659M), Higher Education ($289M), Corporate learning ($926M), and Lifelong and consumer learning ($652M).

Six European markets raised more than $100M, up from just one market previous year.

Comparison of market funding data for 2020 and 2021, showing the UK leading in both years with significant funding amounts.

There were six deals in excess of $80M in 2021, up from one in the previous year

Table displaying education technology companies with columns for Company name, Headquarters (HQ), Cluster, Recent funding raised, Investors, and Valuation.

Go GoStudent!

The biggest round in Europe last year was in K-12 at Vienna-based tutoring company GoStudent which is currently driving a very rapid international expansion.

Logo of GoStudent featuring a stylized pencil and the text 'GoStudent' in a modern font.

(Online) tutoring has long been well represented amongst global edtech unicorns, with the heavy Chinese contingent prospering until the local market crash last year due to regulatory reforms. However, until recently online tutoring had not really taken off at scale in Europe, arguably because the European landscape is fragmented and both the quality of state-provided education and the cultural preference for equity, high.

Market for supplementary education likely to grow

I believe it’s likely that the global market for supplementary education (leaving China aside for now) will continue to grow strongly in the coming years, because:

a) It works

+ Positive impact on learner outcomes*
+ Potential to support teacher retention by reducing after-hours work for existing teachers hence making the profession more attractive
+ Potential to enable recruitment as teachers of university students, former teachers and other professionals, by first (re)-igniting their interest as a tutor,

and

b) There is growing demand for it:


+ More children attend schools than ever before, expanding the addressable market
+ There is increasing competition for top universities and jobs
+ Lower fertility rates boost spending per child
+ Growth in the number of families where both parents work, reducing the time available to help children with homework.

Beware pernicious effects


However, there are some potential pernicious effects should be mitigated:
– Rising inequality, since the rich can better afford it than the poor
– Unreasonable pressure on students
– Competition with schools for teachers, potentially undermining public education systems.

Public-private-partnerships?

In some European countries including the UK and The Netherlands, additional public funding was made available for supplementary education during the pandemic. I am interested to learn what impact these interventions have made and whether the combination of core and supplementary educational provision in the future might be a path to raising average learner outcomes and supporting disadvantaged students?

I’m interested to learn any insights you might have on this subject. Feel free to drop me a line.

*The outcomes of the research are startling: an average student under tutoring performs about two standard deviations above the average performance of a conventional class. Or put another way, an average student following a tutoring program outperforms 98% of students in a conventional classroom! 
https://lnkd.in/gDYHazw