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Should AI have morals?

What happens when artificial intelligence starts flattering us instead of challenging us?

13 January 2026

Artificial intelligence is evolving fast — but as it gets friendlier, should we be worried it’s losing its grip on the truth?

We’re exploring a hot topic in both computer science and ethics: Should AI be built with morals, or is it enough for it to make you feel good?

Spoiler alert — if your chatbot applauds your worst ideas, it might be time for a software update.

Let’s start with ChatGPT, specifically the GPT-4o update. This version of OpenAI’s popular AI assistant had one job: make users happy. It did this so well, it started agreeing with everything. People shared examples of it praising clearly harmful behaviour, reinforcing conspiracy theories, and even applauding dodgy life choices. Why? Because its success was measured on positive user feedback — essentially, how many people responded with smiley face emojis.

The result? A hype man in silicon form. Warm and fuzzy? Yes. Useful? Not so much.

Eventually, OpenAI admitted it had gone too far and rolled back the overly agreeable behaviour. But the episode raised big questions about the purpose of AI. Should it be emotionally supportive at all costs, or should it sometimes challenge us?

Then there’s Grok — Elon Musk’s “anti-woke”, “truth-seeking” AI launched via X (formerly Twitter). Despite the branding, Grok began doing something unexpected: it corrected false claims, backed up scientific consensus, and even fact-checked Musk himself. It wasn’t trying to be political — just accurate. But that honesty proved controversial, especially for users who expected Grok to reinforce their existing views. Apparently, it’s all fun and games until the AI doesn’t flatter your worldview.

So, what do we actually want from AI? Is it more important that it makes us feel good — or helps us be better?

On one hand, supportive AIs can offer comfort and validation. But when they reinforce false beliefs or encourage risky decisions, the consequences can be serious. On the other hand, AIs that challenge misinformation and offer correction might feel uncomfortable in the moment — but they can help us grow. Just like that one teacher who was a little harsh with the red pen, but made you a stronger thinker.

This is about more than software — it’s about trust, responsibility, and the future of technology in society. Because if we build AI to agree with us no matter what, we’re not building intelligence. We’re building digital yes-men. And they might just smile and nod while we walk ourselves off a cliff.

So, where do you stand?

Should AI be polite and supportive — or truthful, even if it stings?

Watch the full video here to explore the debate in full.

For more Lesson Hacker Videos, check out the Craig’n’Dave YouTube playlist HERE.

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What is vibe coding? Is it the future of programming?

Welcome to the “tell, don’t type” era of coding

12 January 2026

If “vibe coding” sounds like something you’d do while lounging in a beanbag with lo-fi beats and herbal tea, you’re not alone. But despite its chilled-out name, vibe coding is a seriously powerful development method—and it’s changing the way we write software.

At its core, vibe coding means using plain English to tell an AI what you want your program to do. Instead of hammering out every loop, condition, and semicolon, you type something like: “Make a form that submits user data to the backend and shows a thank-you message.” The AI interprets your request and generates the code for you—sometimes even with documentation.

This magic happens thanks to large language models like GPT, which have been trained on vast amounts of code. They break your prompt into tokens, map those to patterns they’ve seen before, and predict the most likely next tokens to generate full functions, boilerplate files, and more. Think autocomplete on steroids.

What’s more, modern AI tools like Copilot, Cursor, and Replit are context-aware. They don’t just spit out code snippets—they understand your project structure, track variables across files, and can even refactor code you’ve long forgotten you wrote.

Of course, vibe coding isn’t flawless. The AI can “hallucinate” functions that don’t exist, or write code that looks great… until it crashes. It’s like having a super-keen intern: quick, clever, but occasionally wildly overconfident.

Still, for speeding up development, brainstorming solutions, or simply avoiding another late-night regex breakdown, vibe coding is a game-changer. You bring the ideas. The AI brings the syntax.

Watch our Lesson Hacker video here to explore more.

For more Lesson Hacker videos, check out the Craig’n’Dave YouTube playlist HERE.

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What does a GPU actually do?

The crayon-filled truth about graphics processing.

9 January 2026

Why your graphics card is more of an art class than a supercomputer

If you’ve ever wondered what a GPU really does, you’re not alone. Graphics Processing Units often sound like the mysterious cousins of CPUs, quietly making magic happen behind the scenes of your favourite games and videos. But here’s a fun way to think about it: imagine a colouring book the size of the Eiffel Tower… and a looming deadline.

A CPU would take one look, grab a single crayon, and carefully colour inside the lines—inch by inch. Methodical, yes. Efficient? Not quite.

CPUs are brilliant at complex, sequential tasks, like running your operating system or checking your emails. They’re your digital Swiss Army knives. But they weren’t built for speed painting.

Enter the GPU: not one person with a crayon, but a room full of toddlers—each with a crayon in hand. Shout “RED!” and suddenly hundreds of tiny hands go wild scribbling. It might not all be tidy, but the job gets done at lightning speed. That’s parallel processing in action.

GPUs are crammed with hundreds (sometimes thousands) of tiny, specialised cores designed to handle the same task simultaneously. They’re ideal for things like shading millions of pixels, calculating real-time lighting effects, or rendering dragons in ultra-high resolution at 60 frames per second.

While your CPU can do a little of everything, a GPU goes all-in on one job: graphics. It doesn’t bother with emails or spreadsheets—it’s far too busy making your game worlds look stunning (or quietly mining crypto, if you’re into that).

So next time you’re blown away by slick visuals, thank the GPU. And if something crashes? Don’t blame the hardware. Maybe just check the crayon count.

Watch our Lesson Hacker video to explore more.

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Should beginners use AI to code?

8 January 2026

Here’s why the answer isn’t so simple. AI can be an amazing tool for coders—but should absolute beginners rely on it?

So, you’ve just dipped your toes into the world of coding—still coming to terms with variables, loops, and the existential dread of debugging. Then someone tells you, “Just use AI, it’ll write the code for you!” Sounds tempting, right?

But here’s why that shiny tool might be more lightsaber than lifesaver.

Imagine giving a Jedi weapon to someone who’s only just mastered the art of stick-fighting. That’s what it’s like handing over AI code generation tools to a beginner. Yes, it’s powerful. Yes, it sounds impressive. But if you don’t yet understand the basics, there’s a real risk of slicing through your logic and confidence.

This isn’t to say you should avoid AI altogether. In fact, it can be an incredible tutor—if you use it the right way. Ask it questions. Explore its answers. Use it to understand concepts like callbacks (which, let’s be honest, sound more like something your ex never gave you). But don’t fall into the trap of copying and pasting code like you’re following a recipe from the internet—because while it might work, you won’t truly know how or why.

AI should be your sidekick, not your saviour.

It’s brilliant when you need a quick fix or to meet a tight deadline. But if your goal is to learn how to code—really learn—then you need to do the thinking. The debugging. The failing and fixing.

Because one day, you’ll face AI-generated code that doesn’t work. And if you’ve skipped the hard stuff, you’ll be stuck—realising, with horror, that the problem isn’t the code. It’s you.

Watch our Lesson Hacker video here to explore more.

For more Lesson Hacker videos, check out the Craig’n’Dave YouTube playlist HERE.

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The biggest curriculum shake-up in a decade – Part 3

Understanding the new Progress 8 and Attainment 8 model: What it means for computing teachers

28 November 2025

In part three of our curriculum and assessment review breakdown, we’re turning our attention to something every secondary teacher needs to understand: the changes to Progress 8 and Attainment 8 — and how these shifts affect curriculum planning, subject value, and, importantly, computing.

If you’ve missed parts one and two, don’t panic, you can find them here –

Curriculum and Assessment Review – PART 1

Curriculum and Assessment Review – PART 2

And the full downloadable CAR report breakdown is available HERE – Curriculum and Assessment Review Summary

Where we are now: The current model in brief

For years, schools have been judged on a system built around eight subject “buckets”, with English and maths double-weighted, three EBacc subjects required, and the final slots filled by students’ strongest remaining grades. It’s a model most of us know inside-out, even if it’s felt increasingly restrictive — especially for creative subjects.

With the EBacc now officially scrapped for being too narrow and no longer fit for purpose, the Department for Education (DfE) is reshaping the performance framework. And while the changes may look subtle at first glance, the implications are anything but.

What’s new: Science, breadth, and category slots

The new model keeps English and maths double-weighted but introduces two science slots (including computer science), followed by a broader “breadth” section composed of four buckets. Crucially:

Buckets 5 and 6 must each be filled by a GCSE from two different categories:
A – Humanities, B – Creative, C – Languages.
Buckets 7 and 8 then take the student’s next two highest grades from any subject.

The DfE is also consulting on a possible Category D (Science/Computing), which could give computing more flexibility — but it isn’t guaranteed.

But what about computing? Does this help us?

Here’s the honest answer: maybe… but maybe not.

Without a Category D, computer science risks being squeezed out of the early buckets entirely. Most students will naturally fill the science slots with combined science or triple science results — leaving computing to fight it out in buckets 7 and 8.

With a Category D, computing has a better shot of contributing to performance measures, making it easier for departments to justify staffing, timetable time, and KS3 curriculum depth. But even then, competition with biology, chemistry, and physics remains fierce.

And that’s the heart of the issue: the new model doesn’t fully resolve the long-standing challenge of establishing computing as a core, protected curriculum area.

The new Progress 8 and Attainment 8 framework offers more breadth, more space for creative subjects, and a genuine attempt to modernise. But for computing, the impact is still uncertain — and for many departments, the battle for recognition continues.

Watch the full video for deeper insight

Catch the full Chalk Face discussion here and watch us unpack all the changes.

Download our FREE summary of the CAR report – Curriculum and Assessment Review Summary

Explore more resources, updates, and teacher support at craigndave.org

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The biggest curriculum shake-up in a decade – PART 2

What the CAR review means for teachers

21 November 2025

Welcome back to the next instalment of our deep-dive into the Curriculum and Assessment Review (CAR). Part one explored broad curriculum design and assessment reform; part two gets straight to the good stuff: What the upcoming changes actually mean for computing teachers.

This new review is a hefty read. Fortunately, this series breaks it all down so you don’t have to! Here’s what matters most for computing.

Computing time is shrinking – and that’s a problem

One of the standout concerns raised in the CAR is the reduction in curriculum time:

Key Stage 3 has dropped from 4% to 3%.
Key Stage 4 has dropped from 5% to 2%.

Schools increasingly push computing into carousels, shortened timetables, or — at Key Stage 4 — only offer it to GCSE Computer Science students. Shockingly, only 10% of schools surveyed teach computing to all KS4 students, despite it being a foundation subject.

The review makes it crystal clear: every pupil should study computing until age 16, just like PE, RS and citizenship.

GCSE Computer Science is being replaced

This news has caused quite a stir: the current GCSE Computer Science will be replaced by a broader, more balanced GCSE in Computing.

But why?

The existing qualification is “too narrow and specialised”.
Students score lower in Computer Science than in almost all other subjects.
The gender gap hasn’t improved despite years of initiatives.

The good news: the government has confirmed that core computer science principles — including programming and algorithms — will remain. They just won’t stand alone as a full qualification anymore.

Expect a GCSE that blends computer science, IT, digital literacy, real-world applications, and modern computing concepts.

Computing won’t sit alone anymore – subjects will intertwine

The new curriculum will be the most holistic version yet. Skills will overlap between subjects, and computing will act as an engine powering others, such as maths, DT, geography, and citizenship.

The programme of study will be machine-readable and interactive, showing explicit links across subjects. Think Google Earth in geography, algorithms discussed in English when analysing bias, or spreadsheet skills needed for financial literacy.

Digital literacy and AI: Now national priorities

Two major themes run across the whole review:

Digital literacy

Defined by the government as the knowledge, behaviours, and confidence needed to use technology safely and critically. This includes:

online safety
digital footprints
cyber security
fake news and bias
navigating modern interfaces
basic operational skills, many pupils no longer have

Schools must offer explicit digital education across all key stages.

AI literacy

AI will feature throughout the curriculum, but computing is its “home”. Students will learn:

how AI works
its limitations
ethical implications
how to use and question it

Given that students already use AI outside school, this is a long-overdue update.

So what next?

The CAR review sets the stage for the biggest shift in computing education in a decade. From a rebalanced curriculum to the arrival of a new GCSE, the coming years will reshape what — and how — we teach.

For now, the key message is simple: computing is becoming broader, more relevant, and more cross-curricular than ever before.

Download our Curriculum and Assessment Review summary HERE- Curriculum and Assessment Review Summary.

📺 Watch our breakdown here as we talk through the key findings in our signature chalk face style.

🌐 Explore more resources, guides and updates on the Craig’n’Dave website — your home for high-quality computing education support.

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The biggest curriculum shake-up in a decade

What it means for computing teachers

14 November 2025

From GCSE computing to AI qualifications: unpacking the curriculum and assessment review.

If you’ve been anywhere near education news lately, you’ll know that the Curriculum and Assessment Review (CAR) has landed — all 180 pages of it (plus a hefty 61-page government response for good measure). It’s the most significant look at the education system from ages 5 to 18 in over a decade. And if that sounds like a lot to digest, don’t worry — we have done the reading so you don’t have to.

Let’s check out what this means for computing teachers, students, and schools across the UK and break down the key takeaways.

GCSE Computing replaces GCSE Computer Science

One of the biggest announcements is the shift from GCSE Computer Science to GCSE Computing. At first glance, it’s just a word change — but it’s much more than that. The new qualification aims to better reflect the breadth of the digital world by combining computer science, IT, and digital literacy.

That means programming and algorithms will still be at the heart of the course, but there’ll be a stronger emphasis on digital skills and critical application — preparing students for a world where tech is integral to every industry.

A new qualification in AI and data science?

There’s also talk of a new Level 3 qualification in Data Science and AI. While it’s not confirmed whether this will be an A-level or T-level, it signals an exciting potential pathway for students keen to explore cutting-edge technology in more depth.

Academies to follow the national curriculum

Another big change: academies will be required to teach the national curriculum. This levels the playing field so every student receives the same core education — including computing — no matter where they are in the country.

NEA changes and assessment reform

Non-examined assessments (NEAs) will only continue where they’re essential. For computing, that means no return of coursework-style assessments at GCSE, though there’s still debate around whether they’ll remain at A level. The government has also made it clear that externally marked exams remain the fairest and most reliable assessment method, particularly in the age of AI.

A new era for digital literacy

Digital literacy will take on a far greater role, not just in computing, but across the entire curriculum. Expect more clarity on what “digital literacy” actually means, and a renewed focus on preparing students for life and work in a tech-driven world.

The changes will roll out gradually — with new programmes of study expected by 2028 and the first teaching of new GCSEs in 2029.

But one thing’s clear: this shake-up is set to reshape computing education for the next generation.

A modern holistic curriculum

This will be the most modern and holistic National curriculum to date. No subject sits in a vacuum, and this is no more true than in Computing, where so much of what we do is transferable to other subjects. It is clear for example, that some subjects, digital methods now influence the content and how it is taught.

Where it does, the government will include a requirement for the relevant digital content in those subjects’ programmes of study and will ensure that it aligns with the computing curriculum, to reduce the risk of duplication.

Broader still, the National curriculum revised programmes of study will prioritise core concepts in each subject and make sure they are coherent within and across subjects.

To enable this, the new National Curriculum will be an online, machine-readable and interactive. It will visually represent the links within and between subject areas and gives connections to prior learning, helping teachers to contextualise learning across traditional subject boundaries.

🎥 Want to hear Craig and Dave’s full breakdown?
Watch the video now for their insights, discussion, and a free downloadable summary of the CAR report – Curriculum and Assessment Review Summary

💻 Explore more resources, updates, and teacher support at craigndave.org

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Is reading necessary?

6 September 2025

Why reading belongs in the Computer Science classroom

In a recent article, an English teacher shared how short, focused reading sessions—just five to seven minutes long—can reignite a love of reading in disengaged students. Inspired by research from Stanford University, Erin Miller trialled one-to-one reading interventions with her Key Stage 3 students and saw a noticeable shift in their attitudes toward reading. The simplicity of the approach is striking: minimal interruption, targeted support, and a consistent routine. But what does this have to do with computer science?

Quite a lot, actually.

Reading for pleasure: more than just literacy

It’s tempting to think that once students can read well enough to access the curriculum, the job is done. But reading for pleasure goes far beyond basic literacy. It’s a gateway to:

Vocabulary growth: Words like concatenate, iterate, and recursion are common in programming but rare in everyday speech. Students who read widely are more likely to encounter and internalise these terms, making it easier to grasp abstract computing concepts.
Improved comprehension: Understanding problem statements or even debugging messages requires stronger reading skills.
Higher academic performance: OECD’s PISA studies consistently show that students who read for pleasure outperform their peers—not just in literacy, but in maths and science too.
Cultural capital: Reading builds background knowledge, not only providing an opportunity to cement the curriculum in the real world but also helping students engage more meaningfully with others and with the world around them.
Is reading just for English teachers?

Absolutely not. Just as every teacher has a role in developing digital citizens for our subject, every teacher—including in Computing—should be helping students become more literate. Whether it’s understanding ethical dilemmas in AI, exploring the history of computing, or simply following a tutorial, reading is foundational.

Fitting it in: A curriculum challenge

Yes, the curriculum is crowded. But reading doesn’t have to be a separate activity. It can be woven into existing routines:

Replace a retrieval task with a short reading and reflection.
Make a main task require students to read a paragraph before the activity can be undertaken. This might sound old-school, but it helps.
Encourage students to read computing-related texts and share insights with peers.

One practical idea is to use Alan Harrison’s How to Learn Computer Science at A level. Ask students to read a chapter and prepare to discuss something they found interesting. This not only builds subject knowledge but also fosters scholarly habits.

For students with low literacy, reading can feel like a barrier rather than a gateway. So how do we support them without defaulting to overly simplified texts or assistive tools that risk becoming crutches? Scaffold don’t simplify. Pre-teach vocabulary, introducing key terms before reading. In computer science, words like algorithm or binary can be unpacked with visuals first. Chunk the text by using short, manageable passages.

Does AI Make Reading Redundant?

It’s true that AI can summarise texts instantly. But that’s not the point. Reading is about growth. AI can’t replicate the personal development that comes from wrestling with a challenging idea or discovering a new perspective. While tracking independent reading is harder in the age of AI, the benefits—confidence, curiosity, and competence—are worth the effort.

Building Habits That Last

Drawing on James Clear’s work on habit formation, we can help students make reading a regular part of their lives. Techniques like habit stacking (e.g., reading as part of homework) can make reading more automatic and enjoyable. This is where Craig’n’Dave resources help. Not only do students watch a video for homework, but the take-notes icon in the GCSE videos gives them a cue to read and write down what they see.

Ultimately, reading isn’t a luxury, it’s a necessity. If you read more widely around a subject it is a vehicle for synthesising many abstract concepts taught in isolation in class, making it one of the most powerful tools we can give our students.

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Why don’t computers use a different base for numbers?

The simple reason why binary beats all other number bases

30 April 2025

Why not Base-4?

At first glance, it seems logical to ask: Why don’t computers use Base-4 instead of Base-2? After all, wouldn’t using more numbers give us more power? While it might sound appealing, the reality comes down to the fundamental way electronics work—and why binary remains unbeatable.

Electronics love simplicity

Computers are built on circuits that recognise two states: “off” and “on”. These states are easy, reliable, and practical for electronics to detect. Base-4, on the other hand, would mean handling four distinct states—imagine “off,” “partly on,” and “fully on.” Cool in theory, but impractical in reality. Building hardware to detect such levels would not only be expensive but also error-prone. Think of it like trying to get a light switch to dim to exactly 37%—possible, but far from practical.

A costly rewrite of history

Binary’s dominance dates back to the early days of computing, when switches were literal levers toggling between two positions. Switching to Base-4 today would require a complete overhaul of modern technology. Every programme would need rewriting, every processor redesigning, and every programmer retraining. The cost? More than even the world’s wealthiest could cover.

Base-3 computers: A brief history

Interestingly, a ternary (Base-3) computer was once a serious contender in the 1950s. Yet, despite its potential, binary won out for its simplicity, reliability, and efficiency. The entire computing industry has been built on this foundation, and for good reason: sometimes less really is more.

The unbeatable efficiency of binary

While other number bases could theoretically work, binary remains the gold standard. Its simplicity makes it easy to implement, cost-effective, and highly reliable. If it ain’t broke, don’t fix it—or add unnecessary complexity.

Want to dive deeper? Watch our full Craig’n’Dave Lesson Hacker video.

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Getting maximum value from Smart Revise with Year 11

15 April 2025

Exams are only a few months away and what your students do now is going to make the biggest impact to their results in August. It almost doesn’t matter what their work ethic has been like up until now, there is still time for all students to achieve their potential if they engage in regular active revision using the best techniques from today.

Once you have delivered all the course content switch the topic filters to “Student controlled” in Smart Revise. Make sure you have Quiz, Terms reflective, Terms interactive and Advance modes enabled in the class settings. This will allow the students to take charge of what to revise, when and how.

Top tips for students

Use the Summary report to know the topics that are your strengths and weaknesses.

Click on a Quiz pie chart in the summary report to do multiple-choice questions only on weaker topics.

Look at the Top 10 revision references at the bottom of the summary report.
These are your specific weaknesses across the whole course. You can watch the Craig’n’Dave videos if that helps but beware of passive revision.

Click on a Terms pie chart in the summary report and filter the cards you want to focus on: sad, neutral, happy, unanswered. Reflective is a passive reflection. Interactive is more challenging but is essential. You should be able to define terms at this stage of the course. Use reflective as a reminder and interactive when you are revising.

Click on an Advance pie chart in the summary report to see exam-style questions. Use the next button to find a question you want to attempt. Start with the low mark questions first and work up. Pretend you are in a real exam. Set an alarm on your phone for the number of marks the question is worth and spend that amount of time answering the question.

Use the built-in mark schemes to mark your answer and be realistic. It doesn’t matter if you get low marks when you are practicing.

If you don’t get full marks, note the question number. Have another go at the same question a few days later to see if you can improve your answer. Use the “last answer” button to see your most recent answer.

Start with low mark questions, but don’t avoid the high mark Advance questions forever. You will get lots of 1–6-mark questions in your exam and one 8-mark question in each paper.

Just because you know something this week doesn’t mean you will remember it next week so don’t neglect the topics you have mostly green on the pie charts in the summary report. Checking you still have the understanding is important.

Start Terms – Leitner mode is good for daily reminders of terminology once you have mostly green or yellow pie charts in most of the topics on your summary report. Remember to set the topic filters to the whole course before using Leitner mode.

Beyond Smart Revise

Although Smart Revise is great, it is important to provide students with real past papers so they can practice writing on lines with a pen too! Some papers will be publicly available on exam board websites, but others will require logging in to their portals to be downloaded.

We often assume students will just “know” how to revise without being explicitly taught how to. This is a mistake. Show students the technique of mind mapping and build a mind map for a topic with them, maybe using the Terms in Smart Revise for reference. Smart Revise compliments this tried and tested approach, it does not replace it.

One technique we developed with our students is the “what why web” (see what we did there) which is a scaffolded approach to making a mind map. Write the concept in the middle and then on a second branch state what words are associated with the concept, and on a third branch state why it is necessary, any implications and examples.

For example, the concept of registers for OCR J277 might look like this:

As Dunlosky showed, the worst revision students can do is reading their notes, looking over classwork and watching videos because these are passive techniques. Knowledge organisers and revision guides are useful, but they should only be used as a reference guide to check understanding, in themselves they are not revision.

By the way, put those highlighter pens away because research has shown that highlighting notes is worthless!

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Smart Revise: The ultimate tool for effective exam success

12 November 2024

Smart Revise is a continual revision tool with quizzes, exam-style questions, and personalised feedback to boost exam performance and reduce teacher workload.

Smart Revise: Raising attainment and reducing workloads.

So, What is Smart Revise?

Smart Revise, created by Craig ‘n’ Dave, is transforming how students and teachers approach revision. Rather than cramming at the last minute, it promotes continual practice throughout the course, helping students to master subjects like Computer Science and Business Studies gradually. The platform is designed to make revision less stressful and more effective by aligning practice questions with the research.

But what exactly makes Smart Revise such a game-changer? Let’s dive into how both students and teachers can benefit from this innovative tool.

How teachers can use Smart Revise to boost classroom success

For teachers, Smart Revise is not just a revision tool, it’s a workload reducer. Teachers often spend hours preparing mock exams, quizzes, and practice materials. Smart Revise does that for you. With its extensive question bank, all designed by experienced examiners, the platform allows teachers to set quizzes, homework, and mock exams in a matter of clicks.

The platform provides personalised and diagnostic feedback through its advanced reporting tools, allowing teachers to easily track student progress and pinpoint areas needing intervention. Plus, it supports various assessment techniques like self-marking, peer marking, and even AI marking, ensuring that students get the feedback they need with minimal teacher effort.

Teachers can also use Smart Revise to promote active learning during lessons. Features such as “Tasks” allow teachers to assign extended questions that mirror exam conditions, enabling students to practice longer-answer formats.

How students can use Smart Revise to ace exams

For students, Smart Revise offers a structured approach to revision that builds confidence. One of the platform’s standout features is its quiz functionality, designed for daily use. These quizzes help students retain knowledge by revisiting past topics in an engaging, low-pressure way. And for those struggling with exam techniques, the platform includes model answers and self-assessment tools so students can refine their responses based on real exam mark schemes

Another helpful feature is the flashcards, which reinforce essential terms and definitions, helping students retain information over the long term. With Smart Revise, students can practice at their own pace, mixing up topics and question types to keep things fresh and engaging.

The result? Improved exam performance and reduced last-minute stress

Ready to revise smarter?

Smart Revise has already proven its worth in classrooms across the UK, helping students improve their grades while lightening the load for teachers. It makes revision more effective and reduces your workload.

If you’re looking for a smarter way to revise or teach, why not try Smart Revise!

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Should AI have morals?

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