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Why teaching models keep returning

18 September 2026

Every few years, a familiar pattern emerges. A new book captures attention; a framework gains momentum and schools begin discussing a different way to think about teaching. Yet many of these approaches share more similarities than differences.

Assessment for Learning promoted clear objectives and success criteria. Allison and Tharby’s Making Every Lesson Count highlighted challenge, explanation, modelling, practice, feedback and questioning. Rosenshine’s principles emphasised review, modelling, guided practice, questioning and checking understanding. More recently, Chiltern Learning Trust’s Great Teaching Framework has focused attention on securing attention, communicating meaning, driving hard thinking, scaffolding practice, utilising memory and checking for understanding.

Despite their different language, each model attempts to answer the same question: what do effective teachers do that helps pupils learn?

The recurring nature of these ideas should not be surprising. Strong teaching has always involved explaining clearly, helping pupils practise, checking understanding and building knowledge over time. New frameworks often reorganise established principles rather than replace them.

The real challenge is not deciding whether teaching models have value. It is deciding how schools should use them.

The three approaches schools tend to adopt

Schools often sit somewhere between three broad positions.

The first is formulaic. A particular model becomes the expected way to teach. Lessons follow prescribed routines and leaders look for specific techniques during observations and learning walks. Consistency becomes the priority.

The second is a framework approach. Teachers are encouraged to use evidence-informed principles, but they retain professional discretion over how those principles appear in different subjects, classes and contexts.

The third is freedom. Teachers choose their own methods with minimal reference to a whole-school teaching model.

Each position has strengths and weaknesses. Formulaic approaches can help schools where teaching quality varies widely. They provide a shared language and can establish minimum expectations quickly. Freedom allows experienced teachers to adapt their practice and develop approaches that suit their expertise. Frameworks attempt to balance both aims, providing direction without prescribing every decision.

In practice, the most effective schools often avoid the extremes. They offer enough structure to support teachers while leaving sufficient room for professional judgement.

Why technique alone is not enough

One of the most important insights from the Chiltern Learning Trust framework is that teaching is driven by purpose rather than technique.

A teacher may use cold calling to regain attention, check understanding or stimulate thinking. Another may use modelling to communicate ideas or scaffold practice. The technique remains the same, but the purpose changes.

This distinction matters because effective teaching rarely comes from following a script. It comes from understanding why a particular approach is needed at a particular moment.

A classroom is a complex environment. Teachers respond constantly to pupils’ misconceptions, levels of confidence, prior knowledge and engagement. These decisions happen quickly and often instinctively. Over time, experienced teachers build a repertoire of approaches and learn when each is most effective. A framework can support that decision-making. A formula can replace it.

When consistency becomes conformity

Schools understandably seek consistency. Pupils should receive a high-quality experience regardless of which class they join. Departments need common standards. New teachers benefit from clear guidance, but problems arise when consistency becomes conformity.

When every lesson must follow the same sequence, teachers can begin focusing on compliance rather than learning. The question shifts from “What do these pupils need?” to “Does this lesson fit the model?” That shift risks reducing teaching to a checklist.

Professional expertise develops through reflection, experimentation and adaptation. Teachers refine explanations, alter questioning techniques and modify activities as they learn more about their pupils. If every decision is predetermined, opportunities for professional growth become limited. The goal should not be identical lessons. The goal should be consistently effective lessons.

Looking beyond “I do, we do, you do”

The popular “I do, we do, you do” structure illustrates this challenge well. Used thoughtfully, it provides a powerful sequence for introducing new knowledge. Teachers model a process, guide practice and then release responsibility to pupils.

However, it should not become the only route through a lesson. In some situations, greater impact comes from reversing the sequence. Allowing pupils to attempt a task before direct instruction can reveal misconceptions, generate curiosity and create a stronger need for explanation. Struggle, when carefully managed, can become a valuable part of learning.

The most effective teachers understand the principle behind the model rather than treating the model as a fixed recipe. The question is not whether “I do, we do, you do” works. The question is when it works best and when another approach may work better.

Innovation often works because it is different

Many successful teaching approaches succeed because they offer something distinctive.

Time2Code provides an interesting example. Pupils learn through video instruction and progress at different rates. There are no traditional lesson objectives displayed at the start of each lesson and no requirement for every pupil to move through content simultaneously. The approach challenges several assumptions found in more conventional models, yet it has proved highly successful for many learners.

This highlights an important point. Effective teaching cannot always be predicted by asking whether a strategy conforms to a particular framework. Sometimes innovation emerges when teachers identify a problem and design a solution that breaks established patterns.

The same principle applies at whole-school level. An initiative that works brilliantly in one department may lose its effectiveness when copied everywhere. Context matters. Subject disciplines differ. Pupil groups differ. Teachers differ. An idea can be effective partly because it fills a unique need within a particular setting.

Avoiding the trap of educational fashions

Education continually generates new areas of interest, from Blooms and solo taxonomy, from Rosenshine to semantic waves. Most bring valuable insights. The mistake is not studying these ideas. The mistake is assuming that any single idea provides the answer to every teaching challenge.

Research should inform professional judgement rather than replace it. A teacher who understands cognitive load can make better decisions. A teacher who understands retrieval practice can strengthen memory. A teacher who understands modelling can improve explanations.

However, effective teaching remains more than the application of individual theories. It depends on the ability to combine principles, respond to context and make thoughtful decisions in real time.

The framework that supports professionalism

The strongest teaching models act as maps rather than satnavs. They identify important territory. They help teachers understand key principles. They provide common language for professional discussion. They support development, especially for those early in their careers.

What they should not do is dictate every turn. Effective teaching models help teachers think more deeply about their decisions. Ineffective teaching formulas remove the need to think at all.

That distinction may be the most useful test of any new initiative. If a model develops professional judgement, it is likely to improve teaching. If it demands unquestioning compliance, it risks becoming teaching by numbers.

The aim is not to create identical classrooms. It is to create classrooms where effective principles guide skilled professionals who understand when to follow a model, when to adapt it and when to do something completely different. That is where great teaching is most likely to be found.

 

Want to know more? Watch our latest video on ‘At the chalk face’ where Craig & Dave tackle a question that will probably make a few teachers nod, smile… and perhaps roll their eyes!

How much should schools dictate how teachers teach? Is it better to have a formula that everyone follows, a framework that provides guidance, or complete freedom to let teachers use their professional judgement?

They also get stuck into some bigger questions around pedagogy, cognitive load theory, semantic waves, teaching strategies and the science of learning. When does useful research become an overly prescriptive teaching formula? And are we sometimes so focused on ticking the right boxes that we forget the most important people in the classroom – the students?

Watch the video here.

 

Looking for resources to help make the new academic year easier? Explore our Craig’n’Dave Resource Centre for ready-to-use Computer Science teaching resources, or use Smart Revise to support effective revision and reduce workload.

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Do GCSEs doom students to fail?

11 September 2026

The start of a new school year brings a familiar ritual. Staff gather in the hall, coffee in hand, while senior leaders present the latest examination outcomes. Departments compare performance against predictions. School leaders consider the implications for accountability. Everyone asks the same question: did we do enough?

Behind those conversations lies a bigger puzzle. If teaching has improved so much over the last thirty years, why do headline GCSE outcomes now seem stubbornly resistant to further gains?

The answer is more complicated than many headlines suggest.

A long-term success story that is often overlooked

It is easy to look at recent GCSE results and conclude that little has changed. Yet the long-term picture tells a different story.

In 1993, around 54% of GCSE entries achieved a grade C or above, the equivalent benchmark used before the move to numerical grades. By the late 2000s that figure had risen above 70%. By the mid-2010s it was around 76%.

That represents a substantial improvement in attainment over two decades.

Those gains did not happen by accident. Schools became better at curriculum planning. Teachers gained access to research-informed approaches. Data analysis improved. Intervention programmes became more targeted. In short, the education system became significantly more effective at helping students succeed.

The real question is not why results have failed to improve. It is why improvement has become so much harder.

Understanding the grade 4 benchmark

Part of the confusion comes from the status of grade 4 itself. Technically, grades 1 to 3 are not failures. They represent a level 1 qualification. Students only fail a GCSE if they receive an unclassified grade. However, the practical reality feels very different.

Grade 4 is defined as a standard pass and grade 5 as a strong pass. Most employers expect a grade 4 in English and maths. Many post-16 routes depend upon it. Students who do not achieve a grade 4 in English and maths must continue studying those subjects after age 16.

As a result, grades 1 to 3 occupy an uncomfortable position. They are passes in qualification terms yet often fail to unlock the opportunities that students need. That distinction matters. A student with a grade 3 has achieved something meaningful, but the consequences of falling short of grade 4 can still be significant.

The resit dilemma

Only a relatively small proportion of resit students go on to secure the grade 4 they missed at school. For many young people, the experience becomes a cycle of repeated attempts with little improvement in outcomes.

This creates a difficult question for educators. If a student has spent eleven years in compulsory education without reaching the benchmark, is simply repeating the same qualification the most effective solution?

There are no easy answers, but it is increasingly clear that the debate extends beyond examination performance alone.

No, GCSEs are not designed to make a third of students fail

One of the most persistent myths in education is that GCSE grading deliberately limits the number of students who can achieve a grade 4. Even the Secretary of State for Education didn’t appear to understand this in a recent BBC Four interview.

The misconception usually lies in comparable outcomes. Because national results remain relatively stable from year to year, many people assume that a fixed proportion of students are doomed to fail. That is not how the system works.

GCSEs are primarily criterion-referenced qualifications. Students are assessed against a standard. There is no official quota that reserves grades for a certain percentage of candidates. In theory, if every student demonstrated the knowledge and skills required for grade 4, every student could receive grade 4 or above.

Comparable outcomes only exist to maintain consistency between exam papers sat in different years, not to impose a pass cap. If student attainment genuinely improves across the country, national outcomes rise.

The fact that roughly one-third of students consistently fall below grade 4 reflects patterns of attainment, not an administrative limit on success.

Why further improvement becomes harder

A useful way to think about educational improvement is through the idea of diminishing returns. Moving from 54% achieving the benchmark to 64% represents a major gain. Moving from 64% to 74% is harder. Moving from 74% to 84% is harder still.

The students who benefit most readily from improvements in teaching have largely already benefited from them. The remaining gap increasingly consists of students facing substantial barriers that schools cannot solve. These barriers might include:

  • Persistent absence
  • Low literacy on entry to secondary school
  • Special educational needs
  • Mental health difficulties
  • Housing instability
  • Caring responsibilities
  • Language barriers
  • Economic disadvantage

Excellent teaching remains essential. It can reduce the impact of these challenges, but it cannot remove them entirely. As schools have become better at teaching, external pressures have become more significant factors in determining outcomes.

The tug-of-war facing schools

Perhaps the best way to understand recent results is as a tug-of-war. On one side, schools continue to improve. Teachers have stronger subject knowledge, better resources and better approaches. On the other side sit factors beyond the classroom. Rising disadvantage, attendance challenges, literacy gaps and increasing levels of need all pull in the opposite direction.

The result is a system where enormous effort often produces modest gains. This does not mean teaching has stopped improving. It simply means that teaching is no longer the main factor limiting attainment for a significant proportion of students.

That distinction is important. A flat headline figure can hide years of genuine improvement in classroom practice.

Rethinking what success looks like

The persistence of the grade 4 barrier raises an important question: are we measuring the right thing?

Educators agree that every young person should leave school literate and numerate. The debate centres on how that should be assessed, and how students can be supported with limited assets.

One possible approach would be to separate essential literacy and numeracy skills from the wider GCSE English and maths specifications. A baseline qualification could focus on the practical skills needed for everyday life and employment, with students given multiple opportunities to demonstrate competence.

GCSE English and GCSE Maths could then become optional academic qualifications for students, much like French and Physics now, for those who wish to pursue deeper study.

Whether that model is desirable remains open to debate. Yet it reflects a growing concern that a single threshold currently carries too much weight for too many young people.

Looking beyond the numbers

The annual discussion about GCSE results often focuses on percentages, league tables and accountability measures. Those figures matter, but they can also obscure a more important reality.

The rise from 54% to around 67% over the past three decades represents genuine progress. Schools have become better at helping students succeed. Teachers have become more effective. Educational research has improved classroom practice.

At the same time, the final stretch of improvement is proving far more difficult than the first. The challenge facing education today is not simply how to teach better lessons. It is how to support the students whose barriers to success sit largely outside the classroom. Until that question is addressed, the annual September presentation is likely to end with the same uncomfortable conclusion: teachers move the dial, but it cannot solve every problem.

 

Want to know more? Watch our latest video on ‘At the chalk face’ where Craig & Dave unpack the reality behind GCSE results, comparable outcomes, grade boundaries and the way schools are judged on performance data. They explore why grade boundaries change, whether standards really are rising, and why the idea that a fixed percentage of students must fail is a major misconception.

We also get personal, sharing Dave’s experience supporting his own son through GCSE maths and the lengths parents sometimes have to go to when the system isn’t working for every learner. Its a great watch and one not to miss!

Looking for resources to help make the new academic year easier? Explore our Craig’n’Dave Resource Centre for ready-to-use Computer Science teaching resources, or use Smart Revise to support effective revision and reduce workload.

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Is AI a panacea?

4 September 2026

From experimentation to evidence

Artificial intelligence has moved beyond the early adopter stage in schools. Many teachers already use AI to make help with planning, assessment and communication. Students increasingly use AI for homework, revision, coding and independent study. The challenge is no longer whether AI belongs in education. The challenge is deciding how to use it well.

That is why the Department for Education‘s decision to fund the development of national AI benchmarks for schools is significant. Educate Ventures Research has been awarded a £300,000 contract to create a digital and data skills pathway that will establish minimum and aspirational standards for the use of technology and AI across education.

The aim is not just to encourage more AI use. The aim is to help schools identify what effective, safe and educationally valuable use looks like. In a fast-moving market full of competing claims, that clarity is badly needed.

For teachers, this marks an important shift. The conversation is moving away from excitement about new tools and towards professional standards, evidence and accountability.

Workload relief remains the biggest opportunity

Few issues have shaped education in recent years as much as workload. Planning, assessment, administration and communication place constant pressure on teachers’ time. AI offers genuine opportunities to reduce some of that burden.

Many schools already use AI to:

  • Draft lesson materials and worksheets.
  • Produce differentiated resources.
  • Generate reports and parent communications.
  • Support formative assessment.

These applications often save time, particularly when dealing with repetitive tasks. However, the most effective use of AI is not replacing professional judgement but strengthening it.

A useful approach is to treat AI as a critical friend rather than a content generator. Instead of asking it to write an entire lesson, ask it to review part of a lesson you have already designed. Ask it to identify misconceptions that may arise. Ask it to suggest alternative explanations. Ask it to challenge assumptions in a sequence of learning.

This distinction matters. AI works best when it improves teacher thinking rather than replacing it.

The danger of the shortcut mindset

The promise of workload reduction can sometimes create unrealistic expectations. It is easy to assume that generating a lesson, presentation or worksheet in seconds automatically improves efficiency and quality. Experience suggests otherwise.

Generic AI-generated resources often resemble work produced by an inexperienced teacher. They may contain accurate information, but they rarely reflect the personality, expertise and classroom awareness that make teaching effective. They tend to lack the examples, explanations, diagrams, humour and carefully structured activities that experienced teachers develop over years of practice.

Students are becoming surprisingly adept at recognising AI-generated content. When a resource appears generic or formulaic, engagement can suffer. Learners often respond best when materials clearly reflect the expertise and effort of the teacher standing in front of them.

The most successful teachers therefore use AI to enhance their professional practice rather than outsource it. The technology can accelerate preparation, but it cannot replace the human element that turns information into learning.

AI as a learning partner

The government’s long-term vision includes AI tutoring systems that strengthen teaching and provide better information about pupil progress. At first glance, this can sound ambitious. Yet there are already examples of AI supporting learning in productive ways.

When designed carefully, AI tutors can provide instant explanations, offer additional practice questions, check understanding and help students overcome learning barriers at the moment they occur. A pupil working on programming at home no longer needs to wait until the next lesson to ask a question. They can seek clarification immediately and continue learning.

This is particularly valuable in Computing. Many concepts become difficult because misconceptions go unaddressed for too long. An AI system that provides timely feedback can help students stay engaged and maintain momentum.

Crucially, the most effective AI tutoring tools do not simply provide answers. They encourage thinking. They prompt students to explain their reasoning, justify decisions and refine their understanding.

The goal should never be faster answers. The goal should be deeper learning.

When easier learning becomes weaker learning

The greatest educational risk is not that AI gets answers wrong. It is that AI makes learning feel complete when understanding remains shallow.

Students can now receive an explanation, a summary, a piece of code or a completed paragraph within seconds. While this improves productivity, it can also remove much of the struggle that builds long-term understanding.

Learning depends on effort. Retrieval practice, problem-solving and productive challenge remain essential components of successful education. If students habitually rely on AI to perform tasks for them, they may develop the appearance of competence without developing the underlying knowledge and skills. They can produce work that looks impressive while remaining unable to explain, evaluate or apply what they have submitted.

This concern is particularly relevant in Computing, where mastering programming, algorithms and problem-solving depends on sustained practice. AI can make learning easier without making learners better.

Schools therefore need clear expectations around when AI supports learning and when independent thinking must take priority.

Accuracy still requires human judgement

Another common misconception is that AI can be trusted simply because it sounds confident. It cannot.

Generative AI systems continue to produce factual errors, misleading explanations and fabricated references. The most effective users of AI adopt a questioning mindset. They challenge responses, seek verification and ask the system to critique its own output. They treat AI as a knowledgeable but fallible assistant rather than an unquestionable authority. Students need to be taught this explicitly and teachers need to be mindful not to diminish their own art of reflection.

This approach mirrors good teaching practice. Critical thinking remains essential whether the source is a textbook, a website or an AI model. The responsibility for accuracy still sits firmly with the teacher.

Safety, safeguarding and data protection

As AI adoption increases, safeguarding and data protection become even more important.

Schools should be particularly cautious about entering pupil data into AI systems. Information relating to individual students, SEND needs or behavioural records require careful handling and appropriate safeguards.

The temptation to use free AI tools can create unnecessary risk. In many cases, free services generate revenue by collecting data or using user interactions to improve future models. For schools, the principle should be straightforward: understand where data goes, who has access to it and how it is used.

A strong AI policy should sit alongside existing safeguarding, behaviour and data protection policies. The government’s planned benchmarks will prove especially valuable here. Many schools do not need more AI products. They need greater confidence that the products they use are safe, appropriate and educationally sound.

Teachers remain at the centre

One message appears consistently across government policy, school guidance and classroom experience: teachers remain central to education. AI can provide feedback. AI can suggest explanations. AI can generate resources. AI can support tutoring. What it cannot do is replace professional judgement, relationships and expertise.

Great teaching depends on understanding learners, responding to misconceptions, building confidence and creating meaningful learning experiences. Those are fundamentally human skills. The future of AI in education is therefore unlikely to be about replacement. It is more likely to be about amplification.

The schools that benefit most will not be those that automate everything. They will be the schools that use AI to multiply the impact of effective teachers. The new national benchmarks offer an opportunity to move beyond the current Wild West of AI adoption and towards a more thoughtful approach, where innovation is balanced by evidence, safety and sound educational practice.

Want to know more? Watch our latest video on ‘At the chalk face’ where Dave is joined by Kat Morgan (our Lesson Hacker), an edtech and AI expert, to take a closer look at how AI is really being used in schools right now. From lesson planning and fact-checking to AI tutoring, assessment and personalised learning, they explore what AI can genuinely offer teachers and students – and where we need to be much more careful.

Looking for resources to help make the new academic year easier? Explore our Craig’n’Dave Resource Centre for ready-to-use Computer Science teaching resources, or use Smart Revise to support effective revision and reduce workload.

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Why September nerves can be a good thing.

For many teachers, the final week of the summer holiday brings a mixture of excitement and apprehension. Results day has passed, new ideas are ready to be implemented, and a fresh academic year is waiting just around the corner. Yet even experienced teachers often feel a sense of nervousness as September approaches.

That feeling can be surprising. After all, if you have taught for years, led departments or mentored trainee teachers, surely you should feel completely confident by now. The reality is very different. Many teachers still wonder whether they have forgotten their rhythm in the classroom or whether their carefully planned lessons will work as intended.

Rather than seeing those nerves as a weakness, it may be more helpful to view them as evidence that you care. Teachers who want to do well are naturally concerned about getting the year off to a strong start. The goal is not to eliminate those feelings completely. Instead, it is to put systems in place that reduce avoidable stress and create a sense of control.

Start with the year, not the lessons

Many teachers spend part of the summer preparing resources and refining lesson materials. While lesson planning is important, it is often the practical demands of the school year that create the greatest pressure.

A useful starting point is to review the school calendar and identify the events that will matter to you. Parents’ evenings, assessment windows, data collection deadlines, mock examinations and school trips all have the potential to create workload spikes later in the term. One question can help guide your preparation: what will cause me stress in six weeks if I ignore it now?

Adding important dates to your diary at the beginning of the year provides a much clearer picture of what lies ahead. Teachers who stay on top of workload rarely possess a secret productivity trick. More often, they simply know what is coming before it arrives.

Think of it as laying railway tracks before the train starts moving. Once term begins, events come quickly and relentlessly. Planning ahead makes it much easier to stay in control.

Create one system and trust it

Organisation looks different for every teacher. Some prefer a paper planner. Others rely on digital calendars and spreadsheets. The specific tool matters less than having a system that you use consistently.

Maintaining your own personal planning system rather than relying entirely on multiple school platforms can reduce confusion and save time. Many experienced teachers keep their timetable, class lists, assessment records and key reminders in one place.

Colour coding can be particularly effective. Assigning colours to classes and using those same colours throughout your timetable, planner and mark book makes it easier to identify classes quickly and avoids mistaking one class for another in the same year group.

The same principle applies to student information. Having one personal mark book that contains all the information you use regularly creates a single point of reference. Instead of searching through several different systems, everything you need is immediately available.

The best organisational systems are often the simplest. If a system becomes complicated or time-consuming to maintain, it quickly becomes another problem rather than a solution. Craig and Dave both favour a spreadsheet, with one colour-coded worksheet for each class. Entering student names by hand can help you learn them more quickly at the start of the year. It is also worth adding any relevant student data but remember that pupils can surprise you. Use data to support your planning, not to create a self-fulfilling prophecy about what a student can or cannot achieve.

Protect planning time from administration

Few things disappear faster than a free period. A teacher might sit down intending to plan lessons, only to spend the entire time answering emails. One message becomes three. Three become ten. By the end of the period, no preparation has been completed.

Planning time works best when it is treated as protected time rather than spare time. Lesson preparation, curriculum planning and assessment tasks should take priority over administrative distractions whenever possible.

That does not mean ignoring emails altogether. It simply means handling them deliberately. Many experienced teachers find it more effective to process emails at specific points during the day rather than checking them constantly.

Teaching is already a profession driven by deadlines. Allowing every incoming message to dictate how you spend your time only adds to the pressure.

Establish routines from day one

The opening weeks of term often determine how much effort will be needed for behaviour management later in the year.

Clear routines provide structure for both teachers and students. Entry routines, seating plans, equipment checks, homework procedures and lesson endings all benefit from consistency.

Students rarely remember expectations simply because they were explained once. They need reminders, repetition and reinforcement. If a routine feels slow or awkward at first, resist the temptation to abandon it. Consistency is what makes routines effective.

This is especially important for ECTs. It can be tempting to focus on creative activities and exciting lesson ideas, but routines provide the foundation that allows those activities to succeed.

Students generally respond well when expectations are predictable. They know where the boundaries are, understand what is expected of them and can focus more effectively on learning.

Let consistency beat creativity

Teachers are naturally creative people. Summer often provides time to rethink schemes of learning, redesign lessons and experiment with new approaches. While that creativity is valuable, the first few weeks of term are not always the best time to prioritise it.

A highly consistent classroom is usually more effective in September than a highly creative one. Students benefit from familiar structures and predictable expectations. Once those habits become established, creative activities often have a greater impact because they take place within a well-managed environment.

This does not mean lessons should be dull. It simply means that consistency should come first. A powerful principle for the start of the academic year is this: consistency beats creativity in the opening weeks.

Mark strategically, not endlessly

Workload discussions often return to marking, and with good reason. Marking can quickly become one of the biggest sources of stress for teachers.

The temptation is to treat every piece of work as equally important. Unfortunately, that approach often leads to growing backlogs and increasing pressure.

Strategic marking is far more sustainable. Focus detailed marking on work that genuinely requires it. Use verbal and whole-class feedback whenever they can achieve the same outcome more efficiently.

Students need feedback. They need recognition when they produce strong work. They need guidance when they make mistakes. However, that does not always require lengthy written comments.

The most effective feedback is often immediate and personal. A short conversation during a lesson can have far more impact than a paragraph written in an exercise book days later.

The goal is not to mark more. The goal is to help students improve while maintaining a manageable workload.

Remember that everyone feels it

Perhaps the most reassuring lesson from experienced teachers is that nervousness never completely disappears.

Teachers at every stage of their career can feel uncertain before a new academic year begins. ECTs worry about teaching independently for the first time. Experienced teachers wonder whether they still have what it takes. Department leaders think about results, staffing and curriculum changes.

Those feelings are normal.

The difference is that experienced teachers learn to channel their nervous energy into preparation. They build systems, organise their workload and establish routines before students arrive.

The Scout motto offers a simple reminder that remains as relevant to teaching as ever: Be prepared.

You survived last year. With the right preparation, there is every reason to believe you will thrive this year too.

Want to know more? Watch our latest video on ‘At the chalk face’ where we both talk about our individual experience as teachers and returning to school after the summer break.

Looking for resources to help make the new academic year easier? Explore our Craig’n’Dave Resource Centre for ready-to-use Computer Science teaching resources, or use Smart Revise to support effective revision and reduce workload.

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Every teacher has a superpower, but do you know yours?

17 August 2026

“The average teacher explains complexity; the gifted teacher reveals simplicity.” – Robert Brault

Teaching is a curious profession. On the one hand, it is incredibly visible. Every lesson is played out in front of thirty young people who are often more than happy to tell you how well it is going. On the other hand, some of the most important aspects of great teaching are almost invisible, even to the teachers performing them.

A recent article by Sufian Sadiq in TES explored this challenge. Drawing on the work around didagogy, Sadiq argues that expert teachers frequently struggle to articulate exactly how they make decisions in the classroom. They are not consciously weighing up options moment by moment. Instead, they act through a combination of purpose, experience, professional identity and instinct.

That observation will ring true for many teachers. Most of us can think of colleagues whose lessons seem effortless. The students are engaged, the classroom feels purposeful and learning happens. Yet if you ask those teachers precisely how they achieve it, the answer is often far less clear than expected. Perhaps the reason is simple. The secret is not a particular technique. It is a superpower.

The teachers we never forget

Most teachers can immediately recall someone who inspired them early in their career. It might have been a head of year who combined empathy with absolute authority. A teacher whose classroom behaviour management appeared almost magical. A colleague who somehow knew every student in the school, along with their interests, aspirations and challenges.

What stands out about these people is that they are rarely identical. Their methods differ. Their personalities differ. Their subject knowledge, routines and classroom styles differ. Yet they often achieve similar outcomes. The common factor appears to be their ability to connect.

Whether describing highly effective classroom practitioners, successful pastoral leaders or outstanding mentors, the same theme surfaces again and again. The teachers who make the greatest impact were those who built genuine connections with young people while maintaining clear expectations and professional boundaries.

This goes beyond simply being liked. Students do not need teachers to be their friends. They need teachers who are fair, consistent and genuinely interested in them as individuals. When those foundations are in place, every other teaching strategy becomes more powerful.

Expertise is more than technique

One of the most interesting points in Sadiq’s article is the warning against “teaching by numbers”. Over the past decade, education has rightly benefited from a greater understanding of cognitive science and evidence-informed practice. Shared language around techniques such as retrieval practice, cold calling and scaffolding has undoubtedly helped professional conversations.

However, there is a danger in assuming that successful teaching is simply the correct application of a set of techniques. Any experienced teacher knows this is not true. Two teachers can use the same strategy in the same lesson with vastly different results. One generates enthusiasm and deep thinking. The other sees limited impact. The difference is often found in factors that are harder to quantify. Relationships. Credibility. Consistency. Authenticity. These are not alternatives to good teaching techniques. They are what make those techniques work.

Discovering your own superpower

If every effective teacher is different, perhaps professional development should focus less on creating identical practitioners and more on helping teachers identify and develop their unique strengths.

Ask a group of experienced teachers what their classroom superpower is and the answers are rarely the same. One teacher may excel at bringing industry experience into the classroom. Complex programming concepts become meaningful because they are connected to real applications in software development, banking, cybersecurity or engineering. Students begin to understand not only how something works, but why it matters.

Another teacher’s strength may be relentless reflection. They constantly ask themselves uncomfortable questions:

  • Why am I teaching this topic in this way?
  • Is it producing the outcomes I want?
  • What would happen if I tried something different?

This mindset turns teaching into an ongoing process of experimentation and improvement. Rather than accepting established practice at face value, reflective teachers continually look for better solutions. Both approaches can be enormously effective, despite appearing completely different on the surface. The important lesson is that neither teacher is trying to copy someone else. They are building upon their own strengths.

Why questioning the orthodox matters

Computing has always been a subject that rewards innovation, and perhaps the same should be true of Computing education. Many of the most successful developments in classroom practice have emerged because teachers were prepared to challenge assumptions.

Consider flipped learning. Traditionally, homework has been used to reinforce content already taught in lessons. The flipped classroom reverses this sequence, allowing students to encounter core knowledge before arriving in class and freeing lesson time for discussion, application and problem-solving.

Or consider retrieval practice. The goal is not simply to test knowledge but to strengthen memory by repeatedly revisiting key concepts over time. Students often encounter the same questions again and again because remembering is the point.

Programming education provides another example. Many teachers introduce subprograms relatively late because they are perceived as difficult. Yet some practitioners have found considerable success by teaching them early. The reasoning is straightforward: concepts that appear difficult become easier with sustained practice. Students who regularly work with subprograms from the beginning may stop viewing them as difficult altogether.

None of these approaches emerged because someone accepted conventional wisdom. They emerged because someone asked, “Why do we do it this way?”

The Computing teacher advantage

Computing teachers possess a unique opportunity in this regard because the subject naturally connects classroom learning with the wider world. Students often ask questions that begin with “When will I ever use this?” The strongest Computing teachers rarely struggle to answer.

Whether discussing algorithms, networking, databases or programming, they can connect learning to careers, industries and real-world applications. Students begin to see themselves not simply learning about technology but becoming creators, problem-solvers and innovators. Young people are more likely to engage when they understand how the skills they are developing relate to the wider world beyond the classroom.

Finding your unique selling point

Sadiq argues that professional development should help teachers understand their own decision-making more deeply. That is an important goal. Yet perhaps there is another question worth asking alongside it. What is your superpower?

Not the strategy that appears on a lesson observation template. Not the initiative currently being discussed in staff meetings. Not the technique everyone is talking about online.

What is the thing that students and colleagues remember about you?

Whatever it is, it is worth recognising and developing because great teaching rarely comes from becoming a copy of somebody else. It comes from understanding what makes you unique and using it to make a difference. If teaching is your product, then your superpower is your unique selling point. The challenge is making sure you know what it is.

Want to know more? Watch the latest ‘At the chalk face’ video where we go into more detail!

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A new direction for Key Stage 3 Computing

17 August 2026

For years, Craig’n’Dave have been associated primarily with GCSE and A-level Computing. Many teachers have repeatedly asked the same question: when will there be a Key Stage 3 offer? The answer has finally arrived with the launch of a new KS3 Resource Centre, available for £299+VAT for 12 months’ access to downloadable resources. More significantly, however, this is not simply another scheme of work. It represents a deliberate response to a changing curriculum landscape and a growing debate about what Computing should look like in the years leading up to GCSE.

Why KS3, and why now?

With national curriculum reform underway and growing attention being given to artificial intelligence, digital citizenship and digital literacy, there was an opportunity to rethink what a modern computing curriculum might look like. Rather than waiting for every detail of future reforms to be finalised, we felt schools needed support now, particularly given the likelihood that today’s Year 7 students could be among the first to experience reformed qualifications.

This reflects a challenge many Computing teachers recognise. Curriculum design cannot simply stop while waiting for official documents. Departments still need coherent plans, engaging lessons and a clear vision for progression.

Starting with principles, not lesson resources

Perhaps the most revealing part of the development process is what happened before a single lesson was written. Instead of immediately creating teaching materials, we spent months developing an intent, implementation and impact framework. This resulted in 58 guiding principles that would shape every subsequent decision.

For experienced classroom teachers, this approach will sound familiar. The most successful curricula are rarely built around activities. They are built around beliefs about learning.

The discussion highlights an important lesson for departments undertaking their own curriculum reviews. Before deciding what students will learn, it is worth agreeing why they are learning it and how that learning should take place. The framework became a reference point whenever design decisions became difficult, helping maintain consistency across units and avoiding the gradual drift that often occurs when resources are developed over time.

What will feel familiar?

Despite the emphasis on innovation, there was a conscious decision not to reinvent classroom practice. The resulting structure will look reassuringly familiar to most Computing teachers:

  • Teacher-led lessons with discussion, modelling and guided exploration.
  • Clear lesson objectives and learning outcomes.
  • Six-lesson units with possibilities to expand to longer terms.
  • A blend of online, unplugged, individual, paired and group activities.
  • Fully editable resources.

We were particularly conscious that many KS3 lessons are taught by non-specialist teachers. Rather than creating a framework that required extensive training to understand, we wanted something that could be picked up and taught with confidence from the outset.

That decision reflects a reality often overlooked in curriculum discussions. A brilliant curriculum that demands significant preparation time is not always a practical curriculum.

What makes this different?

While the structure may feel familiar, several features stand out.

The most distinctive is the decision to organise every unit around a career. Students are not simply learning about fake news, cybersecurity or image recognition. Instead, they adopt professional identities such as investigative journalist, cyber security consultant or computer vision engineer.

This is more than a cosmetic change. Each unit begins with a career-focused introduction, includes examples of people working in related fields and concludes with students receiving a career-themed outcome linked to their work.

Many Computing teachers will recognise the question that this approach attempts to answer: “Why are we learning this?”

Rather than treating careers education as an add-on, the curriculum weaves career relevance directly into the learning journey. Importantly, the focus is not on persuading every child to pursue a particular profession. Instead, it helps students understand where computing knowledge is applied in the real world.

Reducing workload without reducing expectations

Another notable feature is the focus on assessment.

One of the design principles was that marking should be meaningful rather than constant. Instead of generating assessable work in every lesson, students spend four lessons learning and exploring concepts before producing a final outcome in lesson five.

That final product becomes the piece of assessed work.

This reflects a concern shared by many teachers: the pressure to generate evidence can sometimes overshadow the learning itself. By concentrating assessment at key points, the scheme attempts to maintain accountability while reducing unnecessary workload.

Lesson six is then dedicated to reflection and improvement (DIRT). Students complete a knowledge quiz, review their work (or the work of a peer), identify areas for development and make improvements. The approach gives dedicated space to processes that are often squeezed into the final minutes of a lesson.

Teaching for curiosity and resilience

Rather than relying heavily on the traditional “I do, we do, you do” structure, many activities begin with exploration. Students are encouraged to investigate, discuss patterns and develop ideas before the teacher consolidates learning and addresses misconceptions.

The aim is not discovery learning for its own sake. Instead, it reflects a belief that students develop greater resilience when they are given opportunities to grapple with ideas before receiving formal explanations.

This is particularly relevant in Computing, where perseverance, debugging and problem-solving are central disciplinary habits. Teachers frequently talk about wanting students to become independent thinkers, yet curriculum design does not always create space for that independence to develop.

Literacy, vocabulary and inclusion

The scheme also places significant emphasis on literacy. Subject-specific vocabulary is explicitly identified and revisited throughout a unit, while knowledge retrieval forms an important part of the start of every lesson and the review process.

Equally noteworthy is the decision to avoid differentiation by task. Instead, the curriculum adopts an adaptive teaching approach. All students work towards the same objectives, with scaffolding and teacher intervention providing additional support where needed.

Whether teachers agree with that position or not, the decision is linked to a clearly articulated educational rationale rather than being included simply because it is fashionable.

Looking ahead

At launch, eight units are available, with further development planned over the coming years. The longer-term ambition is a comprehensive library from which schools can either follow a suggested pathway or construct their own bespoke curriculum.

Perhaps the most reassuring message for teachers is that we do not view the published materials as finished products. Curriculum reform will require adjustments, and we are committed to revisiting units as the national picture becomes clearer.

In a period when Computing education continues to evolve rapidly, that willingness to adapt may prove just as valuable as the resources themselves.

Finding out more

Teachers wishing to explore the new Key Stage 3 offer can find details, curriculum pathways and the accompanying intent, implementation and impact framework on the Craig’n’Dave website (craigndave.org). The KS3 Resource Centre currently provides access to the first eight units, with additional content planned.

 

Want to know more? Watch our video on ‘At the chalk face’ where we go over all the details.

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Four revision techniques that actually work

8 July 2026

The goal of revision is simple: retrieve knowledge efficiently while avoiding cognitive overload. The habits below help students revise in a way that strengthens long‑term memory rather than wasting time on ineffective strategies.

✅ DO: effective revision habits

  • Start revision early.
  • Work in 20–30-minute focused blocks with 5‑minute breaks.
  • Stop after 3–4 blocks to avoid fatigue.
  • Use each block for one specific retrieval‑based task from the four techniques below.
  • Use the four techniques across many sessions.
  • Mark your own work using official mark schemes.
  • Find a quiet, distraction‑free space.

❌ DO NOT: common ineffective practices

  • Do not reread notes, knowledge organisers, or revision guides.
  • Do not highlight or underline notes.
  • Do not rely only on multiple‑choice questions.
  • Do not cram.
  • Do not revise a single topic for long periods.
  • Do not multitask (music with lyrics, messaging apps etc).
  • Do not rely on AI marking.

 

Four revision techniques that actually work

1. Self‑testing with Cornell notes (active recall through reconstruction)

Students should use the Cornell notes created during learning to drive retrieval practice.

How to do it:

  1. Cover the main notes so only student‑generated questions and 8 key words remain visible.
  2. Use the key words as prompts to reconstruct the full notes from memory.
  3. Use the questions to check for depth and completeness.
  4. Uncover the original notes and compare:
    • Identify gaps.
    • Note missing steps.
    • Improve explanations for next time.
  5. Repeat this activity in a later revision block to strengthen the memory.

Why it works:

This is active recall, which significantly outperforms passive review methods. Reconstructing notes from prompts strengthens memory, improves metacognition, and provides clear insight into what still needs practice.

If students did not use the Cornell method during their course, they can use text books, Craig’n’Dave videos, knowledge organisers or revision guides as their reference material to make notes first.

 

2. Brain dumps with spider diagrams/mind maps

Use this to vary retrieval practice and avoid duplicating the Cornell notes process.

How to do it:

  1. Place the topic title in the centre of a blank page.
  2. From memory, create branches for all ideas, terms, diagrams, processes, and examples.
  3. Compare with class notes, textbooks, knowledge organisers or revision guides.
  4. Add missing content in a different colour.
  5. The missing branches form a priority list for the next revision cycle.

Why it works:

This technique uses visual, non‑linear retrieval to organise knowledge and reveal gaps. It’s low‑stakes, promotes metacognition, and strengthens recall.

 

3. Key‑term review using Smart Revise “Terms” Mode (Leitner System)

Flashcard practice works when spaced and retrieval‑based. Smart Revise automates this.

How to do it:

  • Use Smart Revise → Terms mode to practise vocabulary and definitions.
  • Initial flipping is passive; once confident, switch to interactive mode to write definitions.
  • The built‑in Leitner system increases practice of weaker terms and reduces repetition of mastered ones.
  • Review a small number of Terms every day, ensuring spacing.

Why it works:

Spaced retrieval is one of the most reliable ways to build long‑term retention. The Leitner system ensures time is focused on weaker areas, making revision more efficient.

If students don’t have Smart Revise they could be supplied with flashcards. Be wary of students making their own cards because they may miss some concepts, write incorrect definitions or misconceptions.

 

4. Practice papers under exam conditions + Smart Revise “Advance” mode

Past papers are essential but limited. Smart Revise adds extra high‑quality questions.

How to do it:

  • Sit timed papers with no notes and no assistance.
  • When past papers run out or you need variety, use Smart Revise Advance mode or Tasks to generate exam‑style questions.
  • Always self‑mark or use Smart Revise peer marking using mark schemes. Do not use any AI marking options for revision. It is too unreliable.

Why it works:

Exam‑condition practice improves retrieval fluency, timing, and confidence. Marking answers with real mark schemes deepens understanding of criteria and strengthens memory through deliberate error‑correction, something AI marking cannot replicate reliably.

 

How to Use Revision Guides and Knowledge Organisers

Treat revision guides and knowledge organisers as reference tools, not revision techniques.
Use them to:

  • Check whether a brain dump covered everything.
  • Check whether notes are good enough for self‑testing.

They are supporting resources, not methods.

 

Should Revision Be Fun?

Effective revision is meant to be cognitively demanding. Enjoyable, game‑like activities often feel productive but reduce the desirable difficulties needed for durable learning.

Fun has a place during initial learning, but revision works best when it involves effortful retrieval, not entertainment. Making the activity memorable can sometimes overshadow the knowledge itself.

The most effective revision techniques are rarely the most entertaining, but they consistently produce better long‑term results.

 

Want to know more? Check out our ‘At the chalk face’ episode on YouTube.

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The Year 7 dip: why enthusiasm fades – and how to rebuild it

7 July 2026

Every secondary teacher knows the feeling. A Year 7 class arrives in September full of enthusiasm — hands up, eyes forward, eager to please. Fast forward a few months, and the same class can feel markedly different: quieter, less responsive, occasionally resistant.

Writing in TES, David Thomas, CEO of Axiom Maths, describes this familiar experience. His research suggests that, by the summer of Year 7, students are significantly less likely to enjoy Maths than they were in Year 6. What is striking is not just that this happens, but how quickly — and how unevenly.

Yet as many classroom teachers will recognise, this pattern is not confined to Maths. It can affect Computing too, albeit playing out on a slightly different timeline.

When the shine wears off

Thomas identifies the spring term, between Christmas and Easter as the critical point where engagement drops most sharply. With multiple lessons a week, Maths provides fertile ground for this decline to emerge quickly.

In Computing, Craig and Dave suggest the change is often delayed. With fewer curriculum hours, students tend to sustain their enthusiasm through Year 7. But the dip still comes.

Year sevens are generally keen all year, but it’s when they come back in Year 8 that you really notice the shift. They’re more comfortable in the school and more complacent about learning.

This is a useful reminder, the issue is not tied to a specific term, but to a broader transition. As students settle into secondary school, the initial novelty fades and deeper challenges begin to surface.

The balancing act teachers know too well

One of Thomas’s key findings centres on the tension between repetition and pace. Teachers must reconcile wildly different starting points, often reteaching content to establish a common foundation.

In principle, this is sound pedagogy. In practice, it can be deeply frustrating for students with some thinking, “We’ve already done this — why are we still here?” Others are completely bamboozled and trying to keep up.

In Computing, this disparity can feel even more pronounced. Pupils arrive with highly variable experiences — from those who have explored coding in depth to those who have barely used a keyboard. The result is a classroom where boredom and anxiety coexist.

The danger lies in assuming that this tension is unavoidable. While it may not be fully solvable, thoughtful planning, adaptive tasks, extension pathways, low-threshold/high-ceiling activities can mitigate its impact.

 

Confidence: the slow erosion

If the mismatch of difficulty is the spark, then loss of confidence is the slow-burning fire. Thomas’s research highlights a growing confidence gap — one that emerges before any clear attainment gap. Teachers see this every day, though often in subtle ways. In Year 7, when you pose a question to the class, it’s “me, me, me” — hands shooting up. By Year 8, some students just… stop. They don’t want to put themselves out there anymore.

What changes is not just academic confidence, but social awareness. Participation becomes risky. It is no longer about impressing the teacher, but about fitting in with peers.

This creates a difficult tension. The very behaviours that support learning — asking questions, making mistakes, persevering — are precisely those that can feel socially uncomfortable. Left unchecked, this quiet withdrawal becomes self-reinforcing. The more you think students don’t want to engage, the less you push it, and the less you push it, the less they do. It becomes a downward spiral.

Classroom climate: more than behaviour management

Thomas also identifies a decline in classroom climate — reduced collaboration, less effective listening, and increased disruption. This is not simply a behaviour issue, but a cultural one. Being “too cool for school” changes everything.

Once that shift takes hold, even well-planned lessons struggle to land. Group work becomes harder to sustain. Discussion loses its richness. Students who want to engage can feel inhibited by those around them. However, sustaining high expectations is essential, even when it feels difficult. The moment you lose heart, they lose heart.

The unequal recovery

Perhaps the most concerning aspect of Thomas’s findings is what happens next. Some students begin to re-engage — but this recovery is not evenly distributed. More advantaged pupils are more likely to regain enjoyment. Others remain disengaged, widening the gap in both attitude and, eventually, attainment.

Teachers recognise this pattern, even if they do not always name it explicitly. Some pupils find their way back through extracurricular activities or additional support. Others drift further away. For a long time, both teachers and students have responded to this by asking whether the curriculum is truly fit for purpose for all learners.

This tension sits at the heart of inclusive teaching. The goal is not universal passion, but universal opportunity.

Beyond “teenagers being teenagers”

A common explanation for declining motivation is adolescence itself. Hormones, identity, social pressures all play a role, but we should caution against using it as a catch-all explanation. Instead, perhaps there is a deeper mismatch between student needs and school structures.

As adolescents develop, they increasingly seek:

  • autonomy — choice and independence;
  • competence — a sense of progress and success;
  • belonging — connection and identity.

Yet, secondary schools can often drift in the opposite direction creating environments that are controlling, performance-focused which results in spoon-feeding and impersonal. Then we’re surprised when motivation drops.

This is not an indictment of individuals, but of systems. Teachers operate within demanding structures — large classes, heavy workloads, constant pressures. It is easy to fall into cycles of survival rather than reflection. But awareness is a starting point.

Rebuilding the spark

The motivation dip is not inevitable. Nor is it irreversible. If anything, the research and classroom reflections suggest that there is a crucial window — particularly towards the end of Year 7 where small, deliberate shifts can have lasting impact.

Some principles stand out:

  • Protect confidence early
    Notice the students who have gone quiet. Create opportunities where success feels visible and safe.
  • Guard the classroom culture
    Maintain high expectations for participation and collaboration, even when it is challenging.
  • Keep the subject ‘alive’
    Don’t strip out engaging activities simply because they are harder to manage.
  • Offer meaningful challenge
    As Thomas argues, the answer is not easier content, but richer experiences — problems that genuinely engage curiosity.

A profession worth backing

Ultimately, this is as much about teachers as it is about students. Sustaining engagement requires energy, reflection and, at times, resilience. Teaching is not a theoretical exercise. It is lived, complex, and often messy, but within that complexity lies opportunity. The patterns we see are not fixed; they are shaped by the environments we create. While no classroom is perfect, every classroom has the potential to shift the trajectory. The Year 7 dip may be predictable, but it is also preventable.

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The social media debate: What it really means for schools

20 June 2026

There is a growing sense that something significant is about to change in how young people access the online world. Political rhetoric has intensified, pressure from parents has mounted, and governments—both in the UK and abroad—are increasingly signalling that intervention is inevitable. For secondary school teachers, this raises an important question: what will all of this actually mean in the classroom?

At first glance, the issue appears straightforward. Social media is linked to harm; therefore, restrict access. But as with so many aspects of education and technology, the reality is far more complex.

Good intentions, complicated realities

It is difficult to argue with the motivations behind potential reforms. Concerns around online challenges, grooming, abuse, and the wider impact on young people’s mental health are real and well documented. Some medical bodies have even drawn comparisons between social media and smoking, citing links to sleep deprivation, anxiety, and increased exposure to harmful content.

Politically, the tone is clear. There is a sense that action is no longer optional. The idea of a “game changer” has been publicly floated, suggesting that incremental change may no longer satisfy public demand for stronger safeguards.

However, international examples show how difficult implementation can be. In Australia, where restrictions have already been attempted, young people have continued to access social media through workarounds. Criticism has also emerged over which platforms were included or excluded from bans, highlighting a deeper issue: regulation is only as strong as its definitions—and those definitions are increasingly unstable.

The definition problem

At the heart of the debate lies a deceptively simple question: what is social media?

A decade ago, the answer might have seemed obvious. Platforms like Facebook, Instagram, or Snapchat. Today, that clarity has disappeared. The boundaries between “social” and “educational” technology are blurring at speed.

Consider the following:

  • A large language model providing conversational feedback to a student.
  • An AI tutoring platform offering personalised guidance.
  • A shared Word or Google document used collaboratively.
  • An educational YouTube video with comments enabled.
  • A revision platform encouraging regular engagement.

All of these involve interaction. All enable communication, either with other users or with AI systems that simulate human response. At what point does that interaction become “social”?

This is not simply a philosophical question; it has practical consequences. If legislation attempts to restrict “social media”, it risks sweeping up tools that are now integral to teaching and learning. Increasingly, the same features that make platforms engaging—interactivity, collaboration, responsiveness—are precisely the features that make them pedagogically valuable.

The uncomfortable truth is that there is no clear line anymore. The category of “social media” has expanded to the point where it overlaps with almost all digital tools students use.

The teacher reality

For teachers, the debate is not really about banning phones. Schools have already grappled with that issue in various forms. The emerging conversation is about banning or restricting software—and that presents a very different set of challenges.

In practice, stricter controls could bring a range of unintended consequences:

  • Safeguarding complexities: Age verification systems may be introduced, potentially requiring students to provide personal data or biometric information.
  • Consent fatigue: Schools could face increasing administrative burdens as they manage permissions, accounts, and compliance requirements.
  • Onboarding friction: Even simple tasks, like signing up to a revision platform, may become more cumbersome, reducing lesson efficiency.
  • Digital overload: Teachers may spend more time troubleshooting access issues than delivering learning.

Anyone who has tried to get a full class logged into an online platform understands how fragile that process can be. Add layers of verification, restrictions, or blocked functionalities, and the risk is clear: many teachers may simply abandon these tools altogether.

This raises a critical question. At what point does protection begin to undermine the very educational experiences it is meant to support?

The risk of unintended consequences

There is also a broader concern that outright bans could push behaviour underground rather than eliminate it. If students are determined to access social platforms—as evidence suggests they are—they will find alternative routes.

These may be less visible, less regulated, and ultimately more dangerous.

For example, a shared document or file link can quickly become a hidden communication space. Without oversight, such environments could replicate the very risks that legislation is trying to address, but without the safeguards that established platforms at least attempt to provide.

This is the paradox at the centre of the debate: restricting access may reduce exposure in theory, but in practice it may simply relocate it to harder-to-monitor spaces.

Possible directions for change

While no single solution has emerged, several approaches are being explored. These range from technological controls to cultural shifts in behaviour.

Some proposals include platform-level changes such as removing auto-play or endless scrolling features, both of which are designed to increase user engagement. Others involve structural interventions, like age verification at the device or app store level, or even curfews that limit overnight usage.

There is also increasing interest in reframing the issue as a public health concern. Encouraging conversations about screen time in medical settings, collecting data for research, and educating families about usage patterns all point towards a more holistic approach.

At the same time, there are calls to place greater responsibility on technology companies themselves—requiring them to design safer systems rather than relying solely on user behaviour or external regulation.

Where does this leave schools?

For now, uncertainty remains. Yet one thing feels certain: the direction of travel is towards increased regulation, not less.

In this context, schools may need to hold onto a few key principles:

  • Digital literacy remains essential. Even if access is restricted, understanding online environments will still be crucial for young people.
  • Education cannot rely solely on prohibition. Students will encounter these technologies eventually, and they need the skills to navigate them safely.
  • Balance will be critical. The challenge is not just to protect students, but to do so in a way that preserves the benefits of digital learning.

Ultimately, the debate is not just about social media, it’s about how we prepare young people to live in a digital world that is constantly evolving.

A conversation worth having

Perhaps the most important takeaway is that there are no easy answers. The question is not whether young people should be protected online, there is universal agreement on that point. The question is how to do so effectively, without creating new problems in the process.

For teachers, this is not an abstract policy discussion. It is a daily reality, lived out in classrooms where technology is both a powerful tool and a potential source of risk.

As the conversation continues, one question remains open, and vital:

Where should we draw the line between learning tools and social platforms?

It is a question that policymakers, educators, parents, and students will need to answer together.

Want to know more? Check out our ‘At the chalk face’ episode on YouTube.

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Coding in the age of AI: Why it still belongs in the classroom

19 June 2026

Every few years, education is visited by a familiar prediction: an aspect of a subject is declared obsolete, overtaken by technological advance. Recently, that spotlight has fallen on coding. With AI tools now able to generate functional code in seconds, some are asking a seemingly logical question: if machines can code for us, why should students learn to do it themselves?

It’s an appealing argument, particularly in a profession that has weathered repeated waves of technological enthusiasm, but it is also fundamentally flawed. Not because AI won’t reshape coding — it undoubtedly will — but because coding has never been solely about producing future programmers.

If anything, AI strengthens the case for teaching coding, rather than weakening it.

Coding as a way of thinking

One of the most persistent misunderstandings about coding is that it is simply a technical skill — a matter of writing commands and producing working programs. In reality, coding is better understood as a form of cognitive training.

When students learn to code, they are developing a set of mental habits that extend far beyond the screen: problem solving, logical reasoning, hypothesis testing, creativity within constraints, and resilience through iteration. A bug is not just a mistake; it becomes a prompt for investigation. Students are required to test ideas, refine their thinking, and persist through failure.

Coding functions almost as a “prosthesis” for thinking — extending a student’s ability to engage with difficult ideas. It creates an environment where trial and error is not only accepted but encouraged, helping students to build confidence and capability.

These are not incidental by-products of coding. They are the point.

Importantly, these are precisely the skills that will matter most in a world shaped by AI. As tools become more capable of producing outputs instantly, the human role shifts towards evaluating, questioning, and improving those outputs. Coding cultivates the kind of thinking required to do exactly that.

In an AI-infused world, the question is not whether students can generate answers — but whether they can understand and assess them.

Curriculum reform isn’t retreating — it’s reinforcing

Recent curriculum developments underline this point. The 2025 Curriculum and Assessment Review makes it clear that computing — including programming — is not being phased out. Instead, it is being strengthened.

The rationale is straightforward: digital skills are essential for participation in modern society. From healthcare to law, logistics to the creative industries, technology underpins every sector of the economy. Students need to understand not just how to use technology, but how it works.

The planned 2028 curriculum reflects this shift. A broader, more future-facing Computing GCSE will replace the narrower Computer Science qualification, embedding programming within a wider framework of digital literacy, data, systems thinking, and computational reasoning. At the same time, proposals for new qualifications in AI and data science further reinforce the importance of coding as a foundational skill.

This is not a retreat from coding. It is a recontextualisation — recognising that coding is part of a larger ecosystem of digital understanding.

The workforce problem no one is talking about

Beneath debates about AI replacing programmers lies a quieter, longer-term risk: the erosion of the talent pipeline.

Every experienced developer begins as a novice. Those early stages — writing basic programs, making mistakes, learning through practice — are essential. If AI begins to replace entry-level coding tasks, and education responds by scaling back programming, we risk creating a generation with limited understanding of how systems actually work.

AI can generate code, but it cannot take responsibility for it. It cannot fully ensure that systems are secure, ethical, or sustainable. It cannot fully anticipate the societal consequences of the technologies it helps create.

Human expertise will still be required — but that expertise must be developed over time. Without continued emphasis on coding education, that pipeline may falter.

More than code: the meta-skills that matter most

When students write programs, they are not just learning syntax. They are developing transferable skills that will shape their broader lives: attention to detail, abstraction, decomposition, adaptability, and evaluation.

These meta-skills are increasingly valuable in a world where information is abundant and rapidly generated. The ability to approach unfamiliar problems methodically, to break them down, and to refine solutions is vital — not just in computing, but in everyday decision-making.

Evidence suggests that students who engage with coding from an early age often demonstrate stronger analytical and problem-solving abilities. More importantly, they develop ways of thinking that persist into adulthood.

In a landscape where AI can produce answers at speed, human value lies in asking the right questions — and in recognising what makes a good answer.

So, should we still teach coding?

The real question is not whether AI can write code. It increasingly can. The more important question is whether students will understand the systems that shape their lives, think critically about the tools they use, and develop the cognitive flexibility needed to navigate change.

Coding remains central not because every student will become a programmer, but because no student can afford to be digitally illiterate.

AI may transform how software is written. It will not replace the human capacities that coding develops: thinking, questioning, creating, adapting. Those remain at the heart of progress — and will continue to be so.

Rethinking assessment: the future of the NEA

If coding is to remain central, then assessment must evolve alongside it. Nowhere is this more evident than in the future of the A level Computer Science non-examined assessment (NEA).

Rather than replacing the NEA with a written exam — and losing the creativity and practical programming it fosters — there is a compelling case for reimagining it to reflect the realities of modern development. AI should not be excluded; it should be embraced as part of the process.

A future NEA could place AI at the heart of problem-solving, with students demonstrating how they work alongside these tools rather than independently of them. Instead of producing lengthy written reports documenting every stage, students might maintain a concise, structured development diary — potentially even as a video record — capturing their thinking and decision-making.

This process could be organised around a series of stages we call. “CODEAI”:

  • Create: Developing an initial solution to a problem.
  • Orchestrate: Collaborating with others and with AI tools.
  • Debug: Integrating components and resolving issues.
  • Experiment: Exploring alternative approaches and improvements.
  • Adapt: Refining and modifying generated code.
  • Improve: Enhing the final solution to better meet user needs.

Such an approach preserves what makes the NEA valuable — creativity, independence, and problem-solving — while aligning it with the evolving reality of coding in an AI-supported world.
Coding is not disappearing. It is changing — and education must change with it.

By keeping coding at the heart of the curriculum and adapting how we teach and assess it, we ensure that students are not just passive consumers of technology, but active, critical participants in shaping its future.

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Why Do So Many Teachers Leave Teaching?

17 June 2026

If you ask almost any secondary teacher in England why colleagues are leaving the profession, you’ll likely hear a familiar answer: “It’s not the teaching — it’s everything around it.”

That simple line captures a much deeper and more complex story. One that blends policy, workload, school culture, and personal experience. To really understand it, we need to go beyond statistics and look at the lived reality of teachers themselves.

Two such stories, that of Craig and Dave, former teachers turned education resource providers offer a powerful lens through which to explore the issue.

The big picture: what the data tells us

Across Department for Education research and national surveys, five consistent drivers explain why teachers leave:

  • Excessive workload.
  • Stress and poor wellbeing.
  • Pupil behaviour challenges.
  • Pay and financial considerations.
  • Leadership, accountability, and working conditions.

At the top of that list, by a considerable margin, is workload. Around 90% of teachers considering leaving cite it as a factor, and it’s not difficult to see why.

The job is no longer just teaching. It is planning, marking, data entry, behaviour logging, meetings, emails, evidence-gathering, and more. Individually, each demand is reasonable. Together, they become overwhelming.

But statistics only take us so far. What does this actually feel like?

Craig’s story: when the job becomes too much

Craig didn’t go into teaching expecting to leave. Quite the opposite, he loved it. He progressed quickly, becoming head of department and taking on additional responsibilities. On paper, it looked like success.

But beneath the surface, something was changing.

“I didn’t notice it happening… it chipped away at me.”

The workload wasn’t just heavy, it was relentless. Leadership expectations, accountability measures, and administrative tasks accumulated to the point where prioritising became impossible. At one stage, Craig found himself asking his line manager a simple question:

“What do you want me to do first?”

The answer? Everything.

This is exactly what the research highlights: workload isn’t just about long hours, it’s about competing, often unrealistic demands. Teachers are expected to plan meticulously, mark extensively, track data, attend meetings, respond to initiatives, provide evidence and react to constant accountability pressures all at once.

Eventually, the impact became personal. Craig describes a gradual slide into stress, anxiety, and ultimately medically diagnosed depression. Crucially, it wasn’t the classroom that caused it.

“The bit I loved, the teaching, I was doing less and less of.”

This aligns closely with national findings: many teachers report that they still love teaching itself but cannot sustain the conditions around it.

At his lowest point, Craig found himself walking into lessons unprepared. Not through laziness, but exhaustion.

“What did we do last lesson? … That wasn’t for them, it was for me.”

For a conscientious teacher, that moment is deeply uncomfortable and it creates a vicious cycle. Overwork leads to underperformance, which leads to guilt, which worsens wellbeing.

Eventually, Craig had to step away from full-time teaching, but his story doesn’t end there.

When stripped back to just teaching — no meetings, no excessive admin, no leadership burden — he rediscovered what he loved.

“I fell back in love with the profession.”

That contrast is telling.

Dave’s story: When leadership and culture don’t align

Dave’s journey out of teaching took a different path, but points to another key factor in teacher attrition: leadership and working culture.

As an experienced assistant headteacher, Dave was at a career crossroads, considering promotion to deputy head. But a series of interactions made him question whether he wanted to continue.

One moment, in particular, stood out: a meeting about attendance.

Dave wanted to discuss strategies, student stories, and impact. His headteacher wanted a number — nothing more.

“What’s the percentage attendance in Year 8?”

Repeatedly, the conversation was reduced to data rather than professional dialogue.

“A number’s arbitrary… what matters is how we improve it.”

This clash reflects a broader issue identified in research: high-stakes accountability systems can shift focus away from meaningful teaching and leadership toward metrics, compliance, and evidence.

For Dave, it wasn’t just disagreement, it was a signal.

“I knew… I couldn’t work for this man anymore.”

Leadership style and professional trust are critical. When teachers feel reduced to data managers rather than educators, dissatisfaction grows.

Research supports this: lack of autonomy, rigid systems, and poor leadership culture are major contributors to teachers leaving the profession. Teachers want to feel trusted, valued, and able to exercise professional judgement.

When that’s missing, even senior leaders walk away.

It’s not just one thing, it’s the accumulation

What both stories make clear, and what the evidence strongly supports, is that teachers rarely leave for a single reason.

It’s not just workload.
It’s not just stress.
It’s not just leadership.

It’s the accumulation.

Consider a typical week:

  • Teaching multiple classes across different year groups.
  • Planning lessons and resources.
  • Marking hundreds of books or assessments.
  • Logging behaviour incidents and following up.
  • Entering and analysing data.
  • Attending meetings and CPD sessions.
  • Communicating with parents.
  • Preparing for inspections or internal reviews.

Now layer on emotional demands: supporting students, managing behaviour, dealing with safeguarding concerns.

Then add accountability pressures and limited recovery time.

The result? A job that routinely stretches into 50–60+ hours per week, spilling into evenings and weekends.

As Craig described, the consequence is not just tiredness, it’s a gradual erosion of capacity, motivation, and wellbeing.

Why teachers stay — until they can’t

One of the most striking points from both Craig and Dave’s stories is that they didn’t leave because they didn’t care. They left because they cared too much to continue as they were.

Craig and Dave both felt “trapped”. Aware that teaching offered:

A stable salary.

A strong pension.

Job security.

Familiarity.

It also required a unique skillset, and how easy was this to transition into other sectors?

These are powerful anchors. For many teachers, they delay the decision to leave, but when the job begins to affect health, relationships, and self-worth, those anchors can start to feel like weights.

So… why do so many teachers leave?

Because the job, as it is currently experienced by many, has drifted away from its core purpose.

Teaching should be about:

Inspiring students.

Explaining ideas.

Building relationships.

Making a difference.

Instead, too often it becomes:

Managing systems.

Producing evidence.

Meeting targets.

Surviving workload.

One thing very clear. Teachers don’t leave because they stop loving teaching. They leave because the conditions make it unsustainable.

A final thought

Both Craig and Dave still work in education. They still visit schools, support teachers, and engage with students. They didn’t leave education — they left the full-time classroom as it had become.

Perhaps that’s the most important reflection of all. If we want to retain great teachers, the question isn’t “Why are they leaving?” It’s “What has changed that made staying so difficult?”

Want to know more? Check out our ‘At the chalk face’ episode on YouTube.

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Taking the next step

22 May 2026

From the outside, teaching careers often look deceptively linear. You qualify, you gain experience, and then you take your first promotional step before landing a Head of Year or Head of Department role. Then, if ambition and opportunity align, you step into senior leadership. In reality, most teachers discover very quickly that the path is anything but straight. Along the way, opportunities present themselves that sit awkwardly to the side of that ladder: paid projects, secondments, temporary leadership posts, governor roles, mentoring, outreach work, exam marking, subject associations, or county‑wide responsibilities. 

The question ambitious teachers quietly ask is, “Should I apply for roles that don’t clearly lead to senior leadership?”

Early on, it’s tempting to measure every opportunity purely in terms of progression. Will this role make me more promotable? Will the head notice? Will it be a direct route to SLT? That mindset is understandable, especially when the workload is high, time is finite, and you are keen to move up the ladder. However, teaching careers are long, and if you try to take the direct route, there’s a risk of missing roles that make you better, happier, and more intellectually alive in the classroom. 

Paid roles that pay back differently 

Some paid roles sit in this grey space. Exam marking is a perfect example. Financially, it rarely justifies the hours. Working through holidays for what often feels like a modest reward. Yet, the professional value can be immense. Hearing the conversations examiners actually have about scripts, ambiguity, and standards fundamentally changes how you teach exam classes. One year of marking can sharpen your instincts more than a decade of reading the specification. It may not move your application closer to SLT, but it can transform outcomes for your students and your confidence, both of which are essential for your future prospects. 

Other paid opportunities, like freelance authorship or curriculum development, offer a different return. Writing resources for external organisations rarely help you manage people or lead whole‑school initiatives, but it stretches you intellectually, connects you with wider professional communities, and occasionally pay far better than internal school roles. Crucially, it reminds you that teaching expertise has value beyond your own building. That realisation alone can be career‑shifting. 

When schools invent a role around you 

Sometimes schools create bespoke roles tailored to individual strengths. These can be exhilarating and risky. Reducing contact time to innovate and lead specialist work can reignite enthusiasm and allow you to make a visible difference. Yet these roles can also stall progression if they remove you from the experiences senior leaders ultimately value: line management skills, accountability for results, and genuine whole‑school impact. When viewed too narrowly, these posts can feel like a leap forward; viewed later, they may look like a sideways detour. 

Voluntary roles and the hidden power of professional growth 

Voluntary roles carry even more tension. Mentoring trainees, for example, offers no additional pay and little formal recognition. Don’t be too quick to write them off, the professional development is profound. Being responsible for another adult’s growth forces you to articulate your practice, confront your blind spots, and model what you believe good teaching really is. For many teachers, mentoring reshapes their identity — from competent practitioner to reflective professional. It won’t guarantee promotion, but it can quietly raise the ceiling of your own practice. 

Governance roles similarly operate beyond the classroom. Serving as a governor whether in your own school or elsewhere offers insight into budgets, accountability, politics, and long‑term strategy. You see how decisions are made, why compromises happen, and how leadership thinks under pressure. For teachers curious about the bigger picture, it can be eye‑opening. It also demands time, emotional energy, and a tolerance for paperwork! Taken on lightly, it becomes draining; done well, it can reshape how you understand schools as institutions. 

Subject networks, national roles, and the Risk of overreach 

National subject networks and professional bodies occupy another interesting space. They rarely lead directly to promotion within your school, and headteachers may value them only insofar as they benefit results locally, but the professional renewal they bring by working with passionate specialists can be career‑defining. These roles remind teachers that schools can be insular places, and that professional identity doesn’t have to stop at your department door. The risk, again, is overcommitment. Even meaningful work becomes problematic if it competes with your core responsibilities. 

Perhaps the most powerful “sideways” opportunities come in the form of temporary leadership, particularly maternity covers or short‑term secondments. These occupy a unique middle ground. They may be temporary, but they offer genuine exposure to senior leadership realities—decision‑making, scrutiny, pace, and pressure. They are as close to a “try before you buy” model as teaching gets. Done well, they provide evidence that no interview answer can match. Done badly, they can be career‑limiting. Rare is the experience that doesn’t teach you something vital about yourself. 

So how should teachers decide? 

The key is intention. Roles that are not direct pathways to SLT are still worth taking, but for the right reasons. 

Ask yourself: 

  • Will this make me better at my core job? 
  • Will this broaden my understanding of education? 
  • Will this allow me to change practice and evidence making a difference? 
  • Will senior leadership genuinely value this work? 
  • Do I actually have the time to do it properly? 

If the answer is “yes” to at least some of these, the role may be invaluable, even if it never appears on an organisational chart. 

Teaching careers are rarely ladders. They’re more like networks of paths, some of which loop back, intersect, or dead‑end. Not every detour is a mistake. Some are where professional growth actually happens. The real risk isn’t taking the wrong role. It’s taking roles without being honest about why you’re taking them and what you’re expecting them to give you in return. 

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What is Chip Binning?

Understanding the Silicon Sorting Hat of CPUs

8 April 2026

Ever wondered why processors like Ryzen 9 cost more than Ryzen 5, even though they look pretty similar? The answer lies in a clever process called chip binning — essentially, the art of sorting silicon chips after production to separate the stars from the rest.

Baking Silicon Cookies: A Simple Analogy

Imagine you’re baking 1,000 cookies. They all look alike, but some come out golden and chewy, while others might be a bit burnt or crumbly. Chip binning is a bit like that — but instead of sugar and flour, it’s silicon and electrons being tested. 

When manufacturers slice a large silicon wafer into hundreds of tiny processors, not all chips are created equal. Some perform faster and use less power — these are the “golden” chips. Others work well, but only if you don’t push them too hard.

Why Do Chips Get “Binned”?

After production, each chip is rigorously tested. The best performers earn premium titles like “Ryzen 9” or “Core i9” — these are the five-star biscuits of the tech world. Chips that don’t quite make the cut get repackaged as “Ryzen 5,” “Core i5,” or even the more modest “Pentium.”

Importantly, the cores or speeds you see on your CPU label are genuine. You can’t unlock hidden performance by fiddling with the BIOS—those disabled parts are either broken or physically removed. It’s like buying a chair with missing legs and hoping it will magically grow back.

The Benefits of Chip Binning

Chip binning helps reduce waste and maximise profits, ensuring that processors meet different needs and budgets. Thanks to this process, consumers get a range of CPUs that balance performance and price.

So, the next time you pick up a “binned” chip, remember you’re essentially getting the best available chip in that batch — the teacher’s pet of the silicon classroom, complete with all A*s but no free biscuit.

Want to learn more about how your computer’s brain really works? Check out our Lesson Hacker YouTube video.

For more Lesson Hacker videos, check out the CraignDave YouTube playlist HERE.

Visit our website to explore more cutting-edge tech news in the computer science world!

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It’s not in the mark scheme

27 March 2026

When “not in the mark scheme” doesn’t mean wrong – what Quicksort teaches us about accepting valid alternatives 

A question that surfaces every revision season is this:
“If a student’s answer isn’t in the mark scheme, can they still get credit?” 

Happily, the answer is yes. 

Mark schemes guide examiners toward expected answers, but they’re not exhaustive. A response that demonstrates the required understanding, even if expressed differently, should still earn marks, and examiners are trained to recognise valid alternatives. 

Few topics illustrate this better than the story of the Quicksort, and the many ways students might correctly perform it. 

Remembering Tony Hoare, creator of Quicksort 

It felt fitting to reflect on this, following the sad news that Professor Sir Charles Hoare (“Tony Hoare”) passed away peacefully on 5 March 2026 at the age of 92. Hoare is widely regarded as one of the greatest thinkers in the history of computing. His most famous contribution was the Quicksort, the algorithm that has sparked more A level debates and classroom disputes than possibly almost any other. 

The origin story is wonderfully humble. In 1959, while studying machine translation at Moscow State University, Hoare needed a fast way to sort Russian words. Bubble sort wasn’t going to cut it. So, armed with paper and pencil, he devised Quicksort. Ironically, he couldn’t actually implement it, the language he was using, Mercury Autocode, was too limited. 

When he returned to England and joined Elliott Brothers in 1960, one of his first tasks was to write a Shellsort. After completing it, he casually mentioned to his boss that he knew a faster method. His boss responded with a sixpence bet – one Hoare won when Quicksort outperformed all expectations. 

So why don’t students’ Quicksorts match the mark scheme? 

Quicksort isn’t a single algorithm. It’s a family of algorithms. Researchers and engineers have created hundreds of variants, each valid, each useful, each “Quicksort.” 

This naturally leads to classroom friction: 

  • “That’s not how we learned it in Maths!” 
  • “But my teacher said the pivot never moves!” 
  • “This example is nothing like the mark scheme…” 

The truth is: students aren’t wrong. Teachers aren’t wrong, and neither is the mark scheme! They’re often just using different, but valid variants. That’s exactly why rigidly expecting a single form of Quicksort can result in unfairly penalising correct answers. 

What teachers should really look for with algorithms 

Don’t advise students to memorise code blocks. Instead of matching specific code, teachers and students should look for the essential components that all Quicksort variants share: 

  1. A pivot selection strategy

Common approaches include: 

  • First element 
  • Last element 
  • Middle element 
  • Random pivot 
  • Medianof3 
  • Medianof5 
  • Tukey’s ninther 
  • Adaptive schemes (e.g., introselect) 
  1. A partitioning scheme

Popular methods include: 

  • Hoare partition – efficient, uses two indices 
  • Lomuto partition – conceptually simple, uses one index 
  • Bentley–McIlroy 3way – excellent for data with many duplicates 
  • Dualpivot – used in Java’s standard sort 
  1. A recursive divide-and-conquer structure

Often supported by implementation choices such as: 

  • Tailrecursion elimination 
  • Cutoffs to insertion sort 
  • Memory layout optimisations 
  • Parallel variants 
  • Introsort hybrids 
  • Cacheoblivious versions 
  1. A base case

The recursion stops when a sub list contains 0 or 1 elements. 

  1. Combination of the results

When all partitions are sorted, the fully sorted list is formed. 

 

Where the confusion really comes from 

Most disagreement stems from the popularity of two different partitioning approaches: Hoare or Lomuto, and the fact that many teachers were taught one or the other. 

To complicate things further a visualisation called the “Hungarian dancers” (thanks to a viral YouTube video) uses the first element as the pivot but allows it to move during partitioning meaning it’s not a pure Hoare partition, it’s a variant that is inefficient but can make it easier to visualise what the pivot is doing. 

So, when a student’s working doesn’t match what’s in the mark scheme or what you’ve seen before, remember: it may still be a perfectly valid algorithm. 

Want clear, classroom-friendly examples? 

To support teachers CPD, we’ve included full walkthroughs of the Hoare, Lomuto, and the Hungarian variant with code in Python, C#, and Visual Basic in our book:
👉 https://www.amazon.co.uk/dp/B09NRBS8ND 

Oh, and that documented meeting between Tony Hoare and Nico Lomuto we included? That’s just fiction! …but Tony did win the sixpence from his boss! 

Check out the ‘At the chalk face’ podcast for more!

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VEX Robotics is inspiring the next generation of Computer Scientists

VEX Robotics – Bringing computing to life

18 March 2026

If you’ve ever wondered how to make computing more engaging for your students, you need to know about VEX Robotics

Their mission is simple: make engineering, computing, and STEM learning accessible, fun, and hands-on. Whether it’s building and programming a robot for an extracurricular club or preparing a team for a competitive challenge, VEX supports teachers every step of the way with guides, CPD resources, and online tools, all enabling us, the teachers, to bring coding to life. 

VEX has rapidly become a global leader in educational robotics. Originally focused on building parts for competitive robotics teams, VEX has expanded to provide hardware, software, and teaching resources for learners from early years right through to A-level, and all of us at Craig’n’Dave love them! 

From classroom robotics to competition

For teachers who feel intimidated by the word “competition,” VEX makes it easy to start small. Their classroom robots are designed to be plug-and-play, letting students explore programming concepts, sensors, and AI without worrying about complicated setups or fragile equipment. You can start with block-based coding, and when ready, move on to Python, making robotics accessible for all levels.

Even their competitive programs, like VEX IQ (Key Stage 2–3) and VEX V5 (KS3–5), emphasise collaboration over rivalry. Students are randomly paired with other teams, requiring them to work together, mentor each other, and strategise as a team. The result? Students not only apply computing and design skills but also gain soft skills like communication, problem-solving, and teamwork—the very skills employers and educators value most.

In the latest episode of At the Chalkface, Craig and Dave sit down with Chris from VEX Robotics to explore all things robotics in computer science and why it really matters.

Want to know more about VEX Robotics? Check out their website HERE 

 

VEX Robotics is at the Festival of Computing 2026

We’re thrilled to announce VEX Robotics as a Main Sponsor of this year’s Craig’n’Dave Festival of Computing, the UK’s biggest secondary computing festival. 

At the festival, you can:

  • Explore the VEX stand and see what they have to offer
  • Attend their CPD session, “AI Vision in Robotics – World Cup Fever Edition”
  • Discover how to introduce robotics in your classroom or after-school club.

VEX is also sponsoring the fantastic pre-event curry supper held at Bromsgrove School.

A special ticketed social the night before the festival. It’s a great way to enjoy a fun evening of networking, conversation, and inspiration. Spaces are limited, so grab your ticket while you can. 

Curry night tickets available HERE.

Why you should attend

The Craig’n’Dave Festival of Computing 2026 is all about inspiration, innovation, and collaboration

Whether you’re looking to refresh your computing lessons, spark excitement with hands-on projects, or explore cross-curricular links this is the event for you. 

With engaging CPD sessions and keynote talks, a Marketplace packed with leaders in computing education—including VEX Robotics—and plenty of opportunities to connect with fellow educators, it’s an experience no teacher will want to miss.

Get your festival tickets now.

Reserve your curry night ticket while spaces last.

 

Want to know more about the Festival of Computing? Check out all the details about the day HERE

Want to check out the full interview with Chris from VEX Robotics on our At the Chalkface YouTube channel and hear all about how VEX is shaping computing education?

Watch the video HERE.

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Handwriting and embodied cognition

Think handwriting is dead in the age of keyboards, screens, and AI? Think again!

20 February 2026

In recent years, teachers have rightly questioned the purpose and design of homework. Should it reinforce what was taught in the lesson, or should it prepare students for the next lesson? Does homework meaningfully improve learning—and if so, what should it look like? 

Craig’n’Dave’s approach at GCSE and A level offers a practical answer: homework that prepares through concise instruction, encodes through handwriting, and consolidates through structured retrieval—so preparation and reinforcement work as a single loop. This recognises a key idea proposed by Alex Quigley, “in an AIfirst world, handwriting is not an anachronism but an aid to thinking and remembering that should sit alongside technology, not be displaced by it.” https://alexquigley.co.uk/learning-by-hand 

Handwriting as a cognitive engine 

With Craig’n’Dave homework, students begin by hand‑copying from what they see on the screen as they pause a video when the “take notes” icon appears. This is intentional. It makes the task low‑stakes, clear, and achievable for all learners without additional help. Every student can get started; no one is locked out by gaps in prior knowledge or confidence. From there, the Cornell structure guides students beyond transcription:

  • Notes – initially copied, illustrating and teaching students how to distil information.
  • Questions – students turn their notes into prompts that they can self‑test with later.
  • Key terms – students identify up to eight essential vocabulary items, creating a high‑utility glossary aligned to the topic.

This journey from copying to curating mirrors Alex Quigley’s argument that handwriting is an “essential aid to thinking and remembering,” not merely an old approach. He situates it within embodied cognition: the physical act of writing engages perceptual–motor systems that bolster memory and comprehension and helps students generate meaning.

Crucially, the rationale isn’t just conceptual. A growing body of evidence shows that handwriting triggers richer, more widespread brain connectivity than typing, supporting memory formation and information encoding. A recent EEG study found far more elaborate connectivity during handwriting than keyboarding—exactly the kind of deeper processing that Quigley argues we risk losing if we sideline pen‑and‑paper practices.

Quigley’s key point deserves to be foregrounded here. Handwriting slows thinking down in productive ways and strengthens encoding into long‑term memory.

Technology as the gateway, not the destination 

Craig’n’Dave videos are deliberately short

– capped at around 12 minutes – and focused solely on what matters for the specification. This is important because cognitive load matters. Long, meandering explanations increase the risk that students disengage or fail to identify the core ideas. Video, used in this way, offers three advantages that traditional teacher exposition cannot:

  • Control – students can pause, rewind and rewatch, removing the “one-shot” nature of teacher talk.
  • Accessibility – subtitles and translation into over 80 languages provide genuine support for EAL and many SEND learners.
  • Relevance – video aligns with how students already consume information, increasing the likelihood of initial engagement.

However, Craig’n’Dave’s model is careful not to confuse engagement with learning. The video is not the endpoint. It is the input. This distinction matters because, as Quigley reminds us, “learning improves when students move beyond passively receiving information and instead select, organise and transform it—something technology should enable but not replace.”

The eyes–brain–hand reinforcement loop

The Craig’n’Dave approach to outside-inside classroom activities creates a deliberate reinforcement loop.

Outside the lesson:

  1. Eyes watch the video.
  2. Brain processes and selects.
  3. Hand writes and organises (copy → question → key terms).

Inside the lesson:

  1. Eyes read the same notes.
  2. Brain reprocesses the same ideas.
  3. Hand applies them in tasks.

The same content is encountered repeatedly, but through different cognitive actions—watching/listening, writing/structuring, reading/applying—producing the reinforcement model that pairs preparation with consolidation. This design is exactly what Quigley advocates: use technology but also require students to embody the learning through handwriting so that ideas are encoded and retrievable.

Smart Revise: retrieval, vocabulary and reasoning 

The third component completes the picture and ensures that knowledge sticks. Smart Revise, Craig’n’Dave’s online platform has three modes students must also engage with to meet their weekly goals as part of their homework diet.

  1. Quiz – multiple‑choice questions to check understanding and surface misconceptions.
  2. Terms – flashcards to reinforce precise vocabulary (vital in computer science).
  3. Advance – typed answers to develop explanation and reasoning.

Where the video supports initial understanding and handwriting supports encoding, Smart Revise delivers retrieval and consolidation. This is where the Eyes–Brain–Hand loop pays off: students don’t just “review”—they retrieve content that has already been processed and embodied through handwriting, which research associates with stronger memory performance than typed note‑taking.

Why this matters for Computer Science 

Computer science demands:

  • Dense, technical vocabulary.
  • Abstract concepts (e.g., CPU architecture, memory, protocols).
  • Precise reasoning in written explanations.

Craig’n’Dave’s homework model maps neatly onto those demands. Video clarifies abstractions. Handwriting transforms exposure into memory through Cornell notetaking—leveraging the embodied cognition benefits. Online recall with Smart Revise secures terminology and strengthens reasoning. Nothing is excluded. Nothing is overused. Technology opens the door, handwriting does the cognitive heavy lifting, and retrieval locks learning in.

The best of all worlds

Rather than choosing between reinforcement or preparation, digital or traditional, Craig’n’Dave’s approach intentionally combines the strengths of each. This is precisely the balanced ecosystem Quigley calls for: keep the affordances of technology, but do not abandon the memory‑forming benefits of writing by hand.

Want to know more? Watch our At the chalk face video here.

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