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If a NOT gate turns zero into one, where does that one come from?

15 October 2026

Understanding the electricity behind logic gates

It sounds like a trick question from a GCSE Computer Science exam: if a NOT gate turns a zero into a one, where does that one actually come from? Surely computers can’t create something from nothing?

The answer lies in understanding what zero and one really mean in digital logic. A logical zero doesn’t mean there’s no electricity. Instead, it represents a specific voltage level, usually close to zero volts. A logical one represents a voltage closer to the chip’s supply voltage.

In other words, the electricity was there all along!

How does a NOT gate work?

A NOT gate is one of the simplest logic gates in Computer Science. Its job is to invert its input: if the input is 0, the output is 1; if the input is 1, the output is 0.

But how does it achieve this physically?

Inside a modern NOT gate is a circuit called a CMOS inverter, built using two types of transistor: PMOS and NMOS. These tiny electronic switches connect the output to either the power supply, known as VDD, or ground.

When the input is low, the PMOS transistor switches on while the NMOS switches off. This connects the output to the power supply, producing a logical 1.

When the input is high, the opposite happens. The PMOS switches off and the NMOS switches on, connecting the output to ground and producing a logical 0.

The NOT gate isn’t creating electricity. It’s simply controlling where the output voltage comes from.

From tiny transistors to powerful processors

This simple process is fundamental to modern computing. Billions of transistors work together inside CPUs, following carefully designed patterns to process data and carry out instructions.

When we talk about a processor making decisions, we’re ultimately talking about electronic circuits switching between different voltage levels.

Understanding how transistors work helps students connect the theory of logic gates and Boolean logic with the physical components inside a computer. It’s a great example of how abstract Computer Science concepts translate into real-world technology.

Why zero and one aren’t quite so simple

There’s one final detail worth understanding: digital logic uses voltage thresholds rather than requiring perfectly exact values.

A logical 0 doesn’t always have to be precisely zero volts, and a logical 1 doesn’t have to equal the supply voltage exactly. Circuits use defined voltage ranges to decide whether a signal should be interpreted as high or low.

These thresholds help computers handle small variations in voltage and electrical noise reliably.

So, the next time someone asks where the 1 comes from when a NOT gate receives a 0, remember: the chip was powered the whole time. The gate simply switches the output to the appropriate voltage level.

Watch the video and explore more

Watch the video to see how a NOT gate works and discover the electronics behind digital logic.

Visit the Craig’n’Dave website at Craigndave.org for more Computer Science videos, teaching resources and revision tools to support your learning.

 

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Ofsted after the Big Listen: have the rules changed, or just the packaging?

9 October 2026

When Sir Martyn Oliver became His Majesty’s Chief Inspector in January 2024, many school leaders felt a sense of optimism. Here was someone who had led schools himself, understood the realities of headship and appeared committed to rebuilding trust between Ofsted and the profession.

What followed looked significant. The Ofsted Big Listen invited feedback from across education. It generated 132 actions designed to improve inspection, strengthen relationships with schools and reduce unnecessary pressure. Consultation followed, leading to the introduction of the new report card system.

Yet less than a year after the reforms were introduced nationally, a striking question remains: why are so many school leaders still asking whether Ofsted is fit for purpose?

The answer may lie in the difference between changing a framework and changing a culture.

The problem may never have been the single-word judgement

The Big Listen identified widespread concern about headline grades. Ofsted’s solution was to remove the overall effectiveness judgement and replace it with a report card containing multiple graded areas. The intention was clear: provide parents with more information and create a fuller picture of school performance. From Ofsted’s perspective, this was a substantial reform.

Many school leaders, however, appear to have been worried about something different altogether. Their concern was not simply that inspections produced a single grade. It was that inspection itself had become a high-stakes process carrying significant professional, emotional and organisational consequences.

This distinction matters. If the problem is a single-word judgement, replacing it with multiple grades makes sense. If the problem is the pressure attached to inspection, adding more graded categories may simply create more opportunities for schools to feel they have fallen short.

The NAHT’s recent survey suggests many leaders believe exactly that. Among more than 5,300 respondents, 72 per cent felt inspection had worsened over the previous year, while only 7 per cent believed it had improved. Whether one agrees with that assessment or not, those figures are difficult to ignore.

More grades do not automatically create more trust

Supporters of report cards argue that they provide greater nuance. A school may perform exceptionally in some areas while needing support in others. Parents gain a richer understanding than they would from a single overall label. That argument has merit.

The difficulty is that grading still sits at the heart of the system. Schools are now judged across several categories rather than one. Leaders who worried about the consequences of inspection have not necessarily seen the stakes reduced. Some believe they have simply been redistributed.

James Pope, founder of HeadsUp4HTs, captured this concern neatly when he argued that education has removed one-word judgements without removing one-word thinking.

The phrase resonates because it highlights a deeper issue. Accountability is not only shaped by the labels that appear in reports. It is shaped by how inspectors gather evidence, how schools experience the process and how findings are interpreted by parents, media and policymakers. Changing the format of a report is relatively straightforward. Changing perceptions built over decades is much harder.

Inspection culture matters as much as inspection framework

Many leaders are not arguing against accountability. Few people in education would suggest publicly funded institutions should operate without scrutiny. The real debate centres on what effective accountability looks like.

A recurring concern is that inspections can feel driven by compliance rather than professional dialogue. Where schools perceive inspectors as arriving with an emerging narrative already in mind, trust quickly disappears. Any accountability system becomes problematic if leaders believe evidence is being used primarily to confirm conclusions rather than explore them.

This concern surfaced in NAHT testimony, where some leaders felt inspectors were reluctant to engage with evidence that challenged their initial views. Whether that perception is always accurate is almost beside the point. Trust depends not only on fairness but also on schools feeling that fairness exists.

Experience suggests that schools respond best when challenge is accompanied by curiosity. A supportive external review should uncover strengths that data alone cannot reveal, while also identifying weaknesses that require attention. That balance is difficult to achieve when the process begins with suspicion.

Schools are more than examination outcomes

Inspection debates often return to results because results are measurable. Yet schools accomplish far more than delivering examination grades. They build confidence. They develop character. They create opportunities. They support families. They help young people discover talents, interests and ambitions that may shape the rest of their lives.

Academic achievement remains important. Strong literacy, numeracy and subject knowledge open doors. No sensible accountability system would ignore these outcomes. The challenge comes when educational success becomes narrowly defined.

A school serving a highly disadvantaged community may transform life chances in ways that are not fully captured by performance measures. Another may excel at inclusion, attendance, wellbeing or community engagement. These achievements matter enormously, even when they are harder to quantify.

This is why many leaders continue to argue that context must play a larger role in inspection. A fair system should recognise not only what a school achieves, but also the circumstances in which those achievements occur.

The wellbeing question refuses to go away

Perhaps the most uncomfortable aspect of the debate is that it continues to return to wellbeing. The reforms were intended to make inspection less damaging. The Big Listen specifically identified the need for greater empathy, stronger inspector training and a more collaborative approach. Yet the latest feedback suggests many leaders remain unconvinced.

The issue extends beyond individual inspections. Leadership capacity is finite. When accountability systems consume excessive amounts of time and emotional energy, they can unintentionally weaken the very schools they are designed to strengthen. Ofsted argue it is not meant to be like that, leaders should just be continuing their day-to-day work, nothing extra, nothing special. It’s not like that.

No profession should accept severe psychological harm as the unavoidable cost of accountability. That does not mean lowering standards. It means recognising that sustainable improvement depends on healthy people leading healthy organisations.

Looking beyond grades

Other parts of the UK already offer alternative approaches. Estyn in Wales uses narrative reporting rather than summary grades. Northern Ireland’s inspectorate follows a similar model. These systems focus more heavily on strengths, development needs and professional improvement. They are not perfect. No accountability model is.

However, they prompt an important question. If teachers routinely provide pupils with detailed feedback rather than relying solely on grades, why should school accountability operate differently? A narrative report can still be rigorous. It can still identify weaknesses. It can still demand improvement. What it may avoid is reducing a complex organisation to a collection of labels.

The question that still needs answering

The lasting challenge for Ofsted is not whether it listened. The Big Listen clearly demonstrated that concerns were heard. Significant changes followed. The real question is whether the reforms addressed the causes of dissatisfaction or merely the symptoms.

Many school leaders wanted lower stakes, greater trust and a culture built on improvement rather than compliance. Ofsted concluded that parents wanted clearer information and more detailed reporting. Both perspectives can be valid. The difficulty is that they lead to different solutions.

As the debate continues, perhaps the most useful question is not how inspections should be graded, structured or colour-coded. Instead, it is this:

What kind of accountability system genuinely helps schools become better places for the children and communities they serve?

Until the profession and policymakers can agree on the answer, the conversation about Ofsted is unlikely to disappear anytime soon.

Want to know more? Catch us on ‘At the chalk face’ where we go into more detail.

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Should I make my own resources?

5 October 2026

A trainee teacher recently asked a thoughtful question during a training session, “Should I be making my own resources?” It is a question that many teachers ask whether they are new to the profession or experienced and preparing for a new curriculum. The answer is rarely binary.

Why this question matters

Teaching has always been demanding. New teachers quickly discover that lesson planning, behaviour management, assessment, pastoral responsibilities and professional development compete for attention every day. It can often make you feel inadequate.

Sam Gibbs, Curriculum and development lead at Greater Manchester Education Trust captures this well:

“If the job feels difficult, this shouldn’t be taken as evidence that you’re terrible at teaching. That difficulty doesn’t ever really go away, which should be reassuring, because I think teaching is about embracing complexity and difficulty and finding your way through it.”

Teaching is a profession built on continuous improvement. There is always another lesson to refine, another explanation to strengthen and another approach to try. The challenge is not eliminating this complexity but managing it wisely. Remembering that what matters most is helping pupils learn.

The case for creating your own resources

Designing resources remains an important professional skill. When teachers create or adapt materials, they think carefully about sequencing and the needs of a particular class. The process encourages deeper subject knowledge and a stronger understanding of curriculum design. It also allows learning to be tailored to local contexts, current events and student interests.

Creating resources can be particularly valuable early in a teaching career. Building lessons from the ground up helps teachers understand how learning develops over time. It encourages reflection on why activities work, or don’t, and how each supports progress.

However, there is a cost. Developing high-quality resources takes considerable time. Many teachers discover that lessons are never truly finished. Small improvements become constant revisions, and a scheme of learning can absorb far more evenings, weekends and holidays than intended.

The benefits of off-the-shelf resources

Commercial resources exist because they solve a genuine problem. A high-quality resource can save hours of preparation time. Subject specialists, experienced teachers, designers and curriculum experts often contribute to published materials, producing resources that are often both visually appealing and more importantly, carefully structured.

Departments also benefit from consistency. Shared resources help ensure that classes receive comparable experiences and that curriculum coverage remains coherent across year groups. For teachers working outside their specialism, published materials can be particularly valuable. Few teachers would willingly spend hours designing lessons in an unfamiliar area when expert resources already exist.

Good resources also expose teachers to new ideas. An activity, explanation or sequence that works well elsewhere can spark improvements in your own classroom practice. The challenge is recognising that attractive resources do not automatically lead to effective learning. Some packages appear impressive but offer little pedagogical value beneath the design. Others may work well in one context but require significant adaptation in another.

Why extremes rarely work

Debates about resources often become unnecessarily polarised. One view suggests that teachers should create everything themselves because nobody understands their pupils better. Another assumes that purchasing a complete package removes the need for planning.

Neither position reflects reality. Teachers who create everything themselves risk spending enormous amounts of time reinventing materials that already exist. The pursuit of perfection can become endless, with resources continuously revised in search of marginal gains.

At the opposite extreme, teaching directly from a purchased resource without prior thought doesn’t always produce the best outcomes. Not because the resource itself is poor, but because implementation and delivery are equally important. Every class is different and even the time of day can make a big difference. Excellent resources still benefit from adaptation.

Planning matters more than ownership

A useful question is, “How well does this resource support learning, the approach and the outcomes I’m aiming to achieve?”

Students rarely care whether a slideshow, worksheet or activity originated from a classroom teacher, a publisher or a colleague. What matters is whether the material is clear, engaging and appropriate for the task.

A carefully selected resource that has been adapted thoughtfully often provides greater value than a completely original resource produced under severe time pressure. Many experienced teachers develop a practical workflow. They begin with a strong existing resource, then modify examples, add context, adjust explanations and build in scaffolding or differentiation. The result retains the efficiency of an off-the-shelf product while meeting the needs of a specific class.

In this sense, adaptation may be the most important skill of all.

Where AI fits into the picture

Artificial intelligence has added a new dimension to the discussion. AI lesson builders can generate presentations, worksheets and activities within minutes. The speed is impressive, but speed alone does not guarantee quality. Many AI-generated lessons look convincing at first glance. Closer inspection often reveals serious weaknesses. Explanations may not hit the mark, activities may lack practical classroom realism, and presentation choices may do little to support learning.

The issue is not that AI produces poor ideas. In fact, AI can be extremely useful for brainstorming activities, identifying misconceptions, suggesting examples, refactoring and developing ideas or acting as a critical friend during planning.

The real value comes from dialogue and reflection. Used well, AI can challenge assumptions and subject knowledge. Offer alternatives and help teachers think more deeply about lesson design. Used poorly, it can encourage teachers to accept generic materials without sufficient professional judgement. AI works best as an assistant rather than a replacement for expertise.

Collaboration is the hidden advantage

One of the most effective ways to improve resources is to stop working in isolation. Departmental collaboration and local networking allow teachers to share successful activities, test ideas and refine approaches collectively. Resources become stronger when colleagues contribute different perspectives and challenge each other’s assumptions.

No single teacher produces the perfect lesson. Collaboration allows resources to evolve through discussion, adaptation and classroom experience. For trainee teachers in particular, this should be reassuring. Creating resources does not mean starting with a blank page. Existing departmental materials, mentor feedback and shared planning all provide valuable foundations. Teaching is a collaborative profession. Resource development should reflect that reality.

A balanced conclusion

The question is not whether teachers should make their own resources or buy them. The better question is which resources are worth creating, which are worth purchasing and which are worth adapting.

Buy resources when they save substantial time, provide specialist expertise, have unique activities, fit a pedagogy you want to adopt or support consistency across a department. Create or heavily adapt resources when local context and differentiation require it.

Most importantly, avoid confusing workload with effectiveness. Spending every weekend creating lessons from scratch does not automatically make someone a better teacher. Strong planning remains essential, but sustainable planning is even more important. The goal is to deliver excellent learning experiences in the classroom while maintaining the capacity to do that well, day after day, year after year.

The strongest resource is rarely one that is entirely homemade or entirely purchased. More often, it is a well-chosen foundation shaped by professional judgement and thoughtful adaptation.

Want to know more? Check out our ‘At the chalk face’ video HERE.

A strong foundation for your classroom

Did you know we’ve created a whole range of Computer Science resources designed to make life easier for teachers? We’ve built them with real classrooms in mind, drawing on our own teaching experience to create clear, engaging and practical resources that are ready to use and easy to adapt.

From fully editable lessons and structured schemes of learning to engaging activities, extension tasks and resources to support different learners, our aim is simple: to save you time while helping you deliver great Computer Science lessons.

So, if you’re a trainee teacher starting out, an experienced teacher looking to reduce your workload, or a non-specialist looking for some extra support, you don’t have to start from a blank page.

Take a look at the Craig’n’Dave resources and see how they could work for you: Explore our resources 

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How does age verification technology work?

28 September 2026

From ticking a box to AI-powered age checks

We’ve all seen it: you visit a website, it asks whether you’re over 18, and you confidently click “yes”. But these days, simply taking someone’s word for it isn’t always enough.
As online age restrictions become more important, age verification technology is becoming increasingly sophisticated. From databases and identity documents to artificial intelligence and facial recognition, there are several ways technology can determine whether someone is old enough to access online content.

Database checks: searching for your digital footprint

One of the simplest approaches is a database age check. You provide details such as your name, address or date of birth, and the system cross-references them against sources such as electoral registers, credit reference agencies or mobile phone records.
Rather than proving exactly who you are, the technology is essentially checking whether your details match a real person who meets the required age.
It can work well, but only if there is enough accurate information available. If you’ve recently moved house or have a limited digital footprint, things can become more complicated.

Document verification and OCR

Another method is document verification. You may be asked to upload a passport or driving licence, which software then analyses for security features, layouts and machine-readable information.
Optical character recognition (OCR) can extract information such as your date of birth, while liveness detection can help establish that you’re a real person rather than someone simply holding up a photograph.
This technology is already widely used by banks and other organisations for online identity checks.

Can AI really guess your age?

One of the more controversial methods is facial age estimation. A camera captures your face and a neural network estimates your age based on patterns learned from large datasets.
However, factors such as lighting, camera quality, facial hair, makeup and other characteristics can affect the result. This raises important questions about accuracy, bias and privacy.

The benefits and the concerns

For websites, automated age verification offers speed and scale. Systems can process huge numbers of users without requiring people to manually check identification.
But there are trade-offs, including false positives, data privacy and security concerns. Asking users to provide documents or facial information also raises questions about how much personal data should be required to access online content.
Age verification technology may be getting smarter, but it highlights an important computer science question: just because technology can verify something, does that mean we should always use it?

Want to see age verification technology in action? Watch our Lesson Hacker video to explore how these systems work and the computer science behind them.


Discover more computer science videos, resources and teaching materials at Craig’n’Dave.org 

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UTF-8 is witchcraft, right?

How computers learned to speak every language

22 September 2026

Ever wondered how your computer can happily store a simple English letter, an emoji, a pound sign and characters from ancient languages – all without everything descending into complete chaos?
It might feel like witchcraft, but there’s some seriously clever computer science behind it.

It all started with ASCII

Back in the day, computers used ASCII (American Standard Code for Information Interchange). ASCII used 7 bits to represent 128 different characters, including English letters, numbers, punctuation and control codes.
Simple, right?
The problem came when people wanted to use characters that weren’t included in the original ASCII character set. Try typing an é, a £ symbol or characters from another language and things quickly became complicated. Various versions of “extended ASCII” appeared, but the same byte could represent different characters on different systems.
Cue: computer chaos.

Enter Unicode

The solution was Unicode, which aimed to give every character a unique number, known as a code point.
For example, the letter A is U+0041, while the pound symbol is U+00A3. Emojis and characters from languages around the world have their own code points too.
Unicode solved the problem of giving characters a consistent identity.

But there was still one important question: How do we actually store those code points as bytes?

UTF-8 does the clever bit

That’s where UTF-8 comes in. UTF-8 is a variable-length character encoding. A character can use between one and four bytes, depending on which character it is.
The really clever part is its backwards compatibility with ASCII. Characters in the original ASCII range (0–127) still use exactly one byte, just as they always did.

Characters outside that range use multiple bytes, with specific bit patterns indicating how many bytes belong to the character. This allows computers to recognise whether a byte starts a new character or continues an existing one.
It sounds complicated, but the result is beautifully efficient.

So, is UTF-8 actually witchcraft?

Thankfully, no.
UTF-8 is simply an incredibly elegant piece of computer science. It manages to remain compact for English text, support languages and symbols from around the world, handle emojis and remain compatible with decades of existing technology.

Not bad for a system that, at first glance, looks like someone made a deal with a very organised demon.

Want to see UTF-8 in action? Watch the full video to explore how character encoding really works.

And for more Computer Science resources, videos and teaching materials, visit the Craig’n’Dave website and discover more ways to bring Computer Science to life.

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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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Will Quantum Computers Break Encryption?

7 September 2026

The Truth Behind the Hype

Quantum computers are all over the headlines, and one question keeps cybersecurity experts (and curious Reddit users) awake at night: will they break encryption? Let’s unpack this complex topic in a way that’s informative, a little fun, and very relevant for computer science enthusiasts.

What Makes Quantum Computers Different?

A standard computer thinks in bits – ones and zeroes, on or off. Quantum computers, however, use qubits, which can exist as one, zero, and everything in between simultaneously. This phenomenon, called superposition, allows quantum computers to explore multiple possibilities at once. Imagine trying every combination of a password simultaneously – it’s like a student’s excuse for not doing homework, but way more powerful.

Shor’s Algorithm: Why Experts Worry

The panic around quantum computing often centres on Shor’s Algorithm. This quantum method can factor extremely large numbers at lightning speed. Most modern encryption, such as RSA, relies on the difficulty of breaking these numbers into prime factors – essentially trying to un-mix a smoothie. With Shor’s Algorithm, those numbers could be split back into their ingredients in seconds. If a sufficiently powerful quantum computer existed, today’s encryption could be compromised.

The Reality Check: We’re Not There Yet

Here’s the reassuring bit: current quantum computers have only a few hundred noisy qubits prone to mistakes, like a Year 10 coding project. To break modern encryption, we’d need millions of perfectly stable qubits with near-perfect error correction. This is decades away, requires extreme cooling near absolute zero, and a level of engineering that makes the Large Hadron Collider look like a Lego set.

Post-Quantum Encryption: Staying Ahead of the Curve

By the time quantum computers are powerful enough to threaten encryption, post-quantum encryption will likely be in place. These new cryptographic methods are designed to withstand quantum attacks, keeping your data safe. In short, quantum computing is exciting but not yet a cyber apocalypse.
Until then, your passwords are safe, unless you’re still using “password123”. In that case, your cat on the keyboard is a bigger threat.

Want to learn more about quantum computing and cyber security? Watch the full Lesson Hacker video on our YouTube channel.

For more tech tips, computer science insights, and classroom-friendly explanations, visit our Craig’n’Dave website and explore our resources.

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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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Digital ID cards: The future of work or a privacy nightmare?

Digital ID cards might sound like something straight out of 1984, but they’re very much part of the UK’s current political conversation. In this blog, we unpack the big debate featured in our latest Craig ’n’ Dave video — from the promise of smarter identity checks to the fear of slipping into a surveillance society.

What are digital ID cards?

Prime Minister Keir Starmer had proposed introducing digital ID cards across the UK. Instead of a physical card, your identity would live in a gov.uk Wallet app on your smartphone — proving who you are and your right to work or access services.
The idea stems from concerns about illegal working and the UK’s fragmented systems. Supporters claim it’s a modern solution to outdated processes. Critics say it’s political theatre.
Think of it as a “VIP badge”, but instead of wearing it on your shirt, it’s tucked inside your phone. Sleek in concept — but potentially powerful in ways that have raised eyebrows.

The benefits: efficiency, integration, and ease of use

On paper, digital IDs look like a tech upgrade we never asked for but could definitely use. They promise:

  • Faster access to services
  • Less paperwork
  • One digital place for everything — tax returns, healthcare, age checks, passport verification

For anyone who’s battled the NHS login system or spent weeks proving their identity (guilty), this sounds like a dream. No more scavenger hunts for forgotten documents. No more overstuffed wallets. Just a smartphone and a secure login.

The big concerns: privacy, surveillance & cyber threats

Here’s where the plot thickens.
A key criticism is the fear of creating a “checkpoint society”, where identity checks become the norm everywhere you go. Nobody wants to ping facial recognition just to buy a train ticket or open a bank account.

Then there’s cybersecurity. Recent high-profile hacks at major UK companies like M&S and Jaguar Land Rover remind us that no system is untouchable. If huge corporations can fall victim to digital breaches, how safe will a centralised identity system really be?
And with government contracts often awarded to the lowest bidder, can we genuinely trust that the system will be as secure as it needs to be?

How does this link to the Online Safety Act?

The Online Safety Act aims to make digital spaces safer — and a national digital ID system could help combat fraud, bots, and anonymous abuse.
But there’s a fine line between protection and restriction. Some worry this combination could lead to tighter control, restricted freedoms, or a feeling of digital censorship — the ice-cream-brain-freeze version of tech regulation.

Public pushback and political turbulence

Over 760,000 people have signed a petition opposing the plans. Critics argue it’s a quick fix for deeper issues, comparing it to “tidying your room by shoving everything under the bed”.
The idea sounds simple. The execution? Potentially as complicated as building HS2… digitally.

So, is this the future or a digital disaster?

Digital ID cards sit at the crossroads of innovation and intrusion. They could revolutionise how we prove our identity — or open the door to bigger problems around privacy and surveillance.
The key question now is whether the UK can strike a balance between security, efficiency, and civil liberties. Only time (and probably several government pilots) will tell.

Want to know more? Watch the full Lesson Hacker video on our YouTube channel.


For more tech tips, computer science insights, and classroom-friendly explanations, visit our Craig’n’Dave website and explore our resources.

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Why does your phone get dimmer in the sun?

28 August 2026

Have you ever been outside on a bright, sunny day, trying to check your phone, only to find the screen suddenly going dim? It feels completely backwards—you want more brightness, and your phone seems to be taking a nap instead. But there’s actually a clever reason behind this “moody” behaviour.

Heat: Your phone’s biggest nemesis

Your phone’s screen isn’t just a simple piece of glass with light behind it. It’s an intricate electrical sandwich. Crank up the brightness, and you’re pushing more current through the display, generating extra heat. Now, add direct sunlight literally cooking your device, and suddenly your sleek smartphone is teetering on the edge of becoming a pocket panini press.

To prevent overheating, phones have built-in self-preservation systems. The operating system constantly monitors internal temperature and, when things get too toasty, it dials down the brightness. This helps protect not only the screen but also the internal chips and battery. Think of it like an athlete in the sun—if they’re overheating, they slow down to stay safe rather than sprint into trouble.

OLED screens and burn-in

If your phone has an OLED screen, there’s another reason for dimming. Running OLEDs at maximum brightness for extended periods can cause burn-in, where ghostly outlines of your last app linger on the screen. By dimming, your phone is actively protecting the pixels and prolonging the life of your display.

Extreme measures

In really hot conditions, dimming is just the start. Your phone might throttle performance, slow down charging, or even display a “temperature warning” before shutting off entirely. It’s all about keeping your device safe.

How to keep your phone cool

So, what can you do? The simplest solution is shade. Avoid using high-performance apps or games while in direct sunlight, and give your phone time to cool down. Much like you on holiday, your phone doesn’t tan well!

Understanding why your phone dims in the sun not only satisfies curiosity but also helps you take better care of your device.

Want to know more? Watch the full Lesson Hacker video on our YouTube channel.


For more tech tips, computer science insights, and classroom-friendly explanations, visit our Craig’n’Dave website and explore our resources.

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Do we really use database normalisation in the real world?

26 August 2026

If you learned databases at school, you might remember normalisation as a rigid set of rules: First Normal Form, Second Normal Form, Third Normal Form—like Pokémon evolutions, but with fewer Pikachu moments.

The goal is simple: split your data into smaller, related tables to avoid duplication and inconsistency.

What is database normalisation?

In theory, normalisation keeps your data clean. Update a record in one place, and everything stays consistent. No messy anomalies, no duplicated information floating around. For transactional systems like banking, this is critical.

Imagine if your account balance was stored in three different tables—eventually, you’d lose track of where that tenner went!

The trade-off: Speed vs. accuracy

Here’s the catch: normalisation is excellent for correctness but not for speed. Highly normalised databases rely on JOINs to piece data back together. And JOINs? They’re like that colleague who hits “reply-all” on every email—technically correct, but painfully slow.

Analytical systems, reporting platforms, and social media often bend these rules. Take Twitter as an example. A fully normalised feed would query every account you follow to fetch their latest tweets on the fly. Sounds neat, right? But it would be catastrophically slow.

Instead, Twitter denormalises: each tweet is inserted directly into a large table for your timeline, ready to display instantly. Sure, it uses more storage, but your feed loads lightning fast.

Normalisation in the real world

So, do we actually use normalisation? Absolutely—but selectively. It’s not some sacred law etched in stone; it’s a toolkit. Most production databases are a pragmatic mix: normalised enough to maintain consistency, denormalised where speed and scalability demand it.

After all, a perfectly elegant database schema won’t help if your app takes ten minutes to load a cat meme.

Understanding this balance is crucial for computer science students, developers, and anyone working with data at scale. Knowing when and where to apply normalisation can make all the difference between a slow, cumbersome system and a sleek, responsive one.

Want to know more? Watch the Full Lesson Hacker video on our YouTube channel for a detailed, visual breakdown.


For more tech tips, computer science insights, and classroom-friendly explanations, visit our Craig’n’Dave website and explore our resources.

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Why do batteries get worse over time?

The science behind your fading charge

24 August 2026

Understanding battery degradation: How lithium-ion batteries age

If you’ve ever noticed your phone or laptop battery holding less charge than it used to, you’re not imagining it. Lithium-ion batteries, the powerhouse behind most modern devices, gradually lose capacity over time. But why does this happen? Let’s break it down.

Batteries are like sponges for electricity

Inside a lithium-ion battery, there’s an anode, a cathode, and an electrolyte in between. When you charge your device, lithium ions move into the anode. When you use it, those ions migrate to the cathode, creating a flow of electrons that powers your tech. Think of it like a sponge being soaked and squeezed repeatedly. Over time, the materials inside the battery become stressed. Tiny cracks form, parts of the electrode lose contact, and some lithium gets trapped in chemical reactions, leaving it permanently unavailable. The result? A battery that just can’t hold as much charge as it once did.

Heat and the SEI layer—battery villains

Heat is a major factor in battery ageing. Charging quickly or leaving your device in direct sunlight makes the battery hotter, accelerating chemical reactions and structural changes. On top of that, the electrode surface gradually develops a thin layer called the SEI (solid electrolyte interphase), similar to plaque on teeth. Each charge cycle thickens this layer, making it harder for ions to move efficiently and further reducing battery performance.

Practical tips for extending battery life

Manufacturers often suggest keeping batteries between 20% and 80% charge, avoiding deep discharges, and steering clear of high-temperature charging. While this isn’t always practical, gentle care goes a long way. Keep your devices cool, avoid extreme charging habits, and remember: all batteries age. The good news? Unlike us, batteries can be replaced.

Curious to see exactly how batteries degrade and why heat is the hidden villain?

Watch the full Lesson Hacker video on our YouTube channel.


For more tech tips, computer science insights, and classroom-friendly explanations, visit our Craig’n’Dave website and explore our resources.

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Why does a weak signal drain your phone battery so fast?

21 August 2026

Your phone’s desperate drama

Ever noticed your phone battery disappearing faster than snacks at a party when the signal is weak? It’s not just bad luck, your handset is basically having a panic attack. The moment it senses a slipping signal, it starts shouting at every mobile tower in range: “ARE YOU STILL THERE?!” The weaker the signal, the louder your phone screams, blasting its transmitter at full power to cling onto any connection. And all that shouting? That’s your battery paying the price.

The endless cycle of screaming and searching

It doesn’t stop there. Your phone keeps shouting while frantically scanning for other towers, like someone running around a city with a megaphone while checking every street corner for friends. This repeated effort burns energy. Electrons in this case and leaves your battery drained faster than you’d expect.

Even if your phone does manage to reach a tower, weak signals can garble data. Phones send information in small chunks called packets. When packets get lost, the tower politely asks your phone to repeat itself. So your handset retransmits the same data again and again, like posting the same meme multiple times because no one liked it the first two.

Why your phone gets hot

All that frantic communication makes your handset heat up. Your phone’s radio chips are working overtime, like a runner sprinting uphill while juggling eggs. The worse the signal, the harder your phone has to work, leading to increased battery consumption and heat. Ironically, streaming a 4K video over a full 5G connection uses less battery than trying to check a couple of emails with a single lonely bar of signal.

Keep your battery alive

Next time your phone feels like it’s roasting your palm in the middle of nowhere, don’t blame the battery—it’s just doing its best to keep the conversation alive. Understanding how signal strength impacts battery life can help you manage your usage and expectations, especially when you’re off the beaten track

Want to know more? Check out our Lesson Hacker’s YouTube video. 

For more Lesson Hacker Videos, check out the Craig’n’Dave YouTube playlist HERE.
Be sure to visit our website for more insights into the world of technology and the best teaching resources for computer science and business studies.
Stay informed, stay curious!

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Why September nerves can be a good thing.

21 August 2026

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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What is refactoring?

And why every programmer secretly loves it

19 August 2026

Refactoring: spring cleaning for your code

Refactoring is the art of improving your code without changing what it actually does. Think of it as tidying up your room – you’re not buying new furniture, just rearranging things so you can move around without tripping over yesterday’s “temporary” fixes. The end result? Cleaner, easier-to-read code that’s simpler to maintain and far less likely to give future you a headache.

Here’s the funny thing: you won’t find “refactor your code” written into your GCSE or A level computer science syllabus. Your assignments usually stop at “make it work and submit it before midnight.” But in the real world? Refactoring is a developer’s dream. It’s their version of a spa day. Many professional programmers love taking messy, old code and transforming it into something elegant – even if they pretend it’s all about “optimising architecture.”

Why refactoring matters

Over time, all code starts to decay. Those little shortcuts, quick fixes, and “I’ll sort it later” moments build up into what’s known as technical debt. The bigger your project gets, the more this debt grows – until it starts slowing everything down or breaking things entirely.
Refactoring tackles that build-up. It turns your tangled ball of code spaghetti back into neat, structured linguine – still the same code, just beautifully organised.

More than pressing a button

Sure, your IDE might have a handy “Refactor” button, but real refactoring goes far beyond renaming variables. It’s about rethinking the structure of your program: breaking down giant functions, reorganising classes, and deleting ancient comments that should’ve been gone years ago.
AI tools can even help with refactoring nowadays, but here’s the catch – you still need the programming knowledge to spot when the AI’s “fix” is actually nonsense.

The bottom line

Refactoring is about making internal improvements to your code – cleaner, more efficient, and more aligned with its purpose. It’s the quiet, behind-the-scenes work that makes great programmers stand out.

Want to dive deeper into how to improve your coding skills?

Watch the full Lesson Hacker video on our YouTube channel to see refactoring in action.

And for more resources, lessons, and insights for computer science teachers and students, visit craigndave.org.

 

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