27 February 2026

Phosphorescence & Fluorescence (and why one “stops showing off” the moment you turn the lights on)

If you’ve ever waved a highlighter under a UV lamp and watched it practically shout neon, you’ve met fluorescence. If you’ve ever charged up a “glow-in-the-dark” sticker, turned the lights off, and it kept glowing like it’s refusing bedtime, you’ve met phosphorescence.

They’re cousins. They both involve electrons being excited and then falling back down, releasing light. The difference is how quickly they stop showing off.

Fluorescence: the instant response

Fluorescence happens when a substance absorbs higher-energy light (often UV) and almost immediately re-emits some of that energy as visible light.

Turn the UV on → it glows.
Turn the UV off → it stops (almost instantly).
Typical timescale: nanoseconds (that’s 0.000000001 s).

What’s happening (simple version):

Light energy bumps an electron to a higher energy level.
It loses a bit of energy as vibration/heat.
It drops back down and emits a photon (light) straight away.

Think of fluorescence as the student who answers immediately with their hand already in the air.

Phosphorescence: the “hang on, I’m still thinking” glow

Phosphorescence also starts with absorption of energy, but the excited electron gets “stuck” in a longer-lived state before it can return to normal.

Shine light → it charges up.
Turn the light off → it keeps glowing for seconds… minutes… sometimes hours.
Typical timescale: milliseconds to hours.

Why the delay?
The electron slips into a state called a triplet state that’s “forbidden” (in quantum rules terms) to drop back down quickly. It’s allowed eventually — just slowly.

Phosphorescence is the student who says, “I’ll email you the answer later,” and actually does.

Quick, safe classroom demos (with explanations)

1) Highlighter fluorescence (cheap, bright, reliable)

You need: UV torch or UV lamp (365–395 nm), yellow highlighter, paper, or a beaker of water.

Method A (paper):

Draw a thick line with a highlighter.
Shine UV on it. Instant glow.

Method B (solution):

Scribble on filter paper, soak in warm water, squeeze/filter into a beaker.
Shine UV: the beaker glows strongly.

Chemistry link: Many highlighters contain fluorescent dyes (often related to pyranine-type dyes). Great intro to absorption/emission and energy loss as heat (Stokes shift).

2) Tonic water fluorescence (the “party trick” that is actually chemistry)

You need: Tonic water, UV lamp, clear glass.

Tonic water contains quinine, which fluoresces blue under UV. It’s a lovely “invisible until UV” example.

Teach it as: “Same liquid, same room… different light source = different observation.” Great for discussing instrumentation and why UV-visible spectroscopy exists.

3) “Glow-in-the-dark” pigment (phosphorescence you can time)

You need: Glow powder/paint (commonly strontium aluminate-based), a bright lamp or UV light, a dark corner, stopwatch.

Charge it under bright light.
Turn lights off.
Time how long the glow remains clearly visible.

Stretch activity: Compare:

charged under normal LED light vs UV
warm vs cool conditions (careful and modest — don’t cook it!)
thin vs thick layer

Chemistry/physics link: Long-lived excited states and slow release of photons. Talk about energy traps/defects in the crystal lattice (age-appropriate version).

4) Glow sticks: chemiluminescence (bonus “third way”)

Glow sticks aren’t fluorescence or phosphorescence — they’re chemiluminescence (chemical energy → light).

Why include them?
Students often mix all “glowing” together. This is a brilliant chance to sort the zoo:

Fluorescence: needs a lamp shining right now
Phosphorescence: charges up then glows later
Chemiluminescence: glows from a chemical reaction

If you want one slide that saves a thousand misconceptions, it’s that.

The exam-friendly explanation (without the quantum headache)

Key comparison table (say it out loud like a spell)

Fluorescence: fast emission, stops when excitation stops
Phosphorescence: slow emission, continues after excitation stops
Both involve: absorption → excited electrons → light emitted on return
Difference comes from: whether the electron can return quickly (allowed) or gets stuck (forbidden/slow)

Vocabulary students should use confidently

Excitation
Emission
Photon
Energy levels
Stokes shift (for brighter groups)
Triplet state (A-level or keen GCSE extension)

Safety and good lab habits (the grown-up bit)

UV light: avoid shining into eyes; don’t encourage students to “test” it on their skin. Use UV safety glasses if you have them.
Keep UV exposure brief and controlled (teacher-held lamp/torch works well).
If using glow powders/paints: avoid dust inhalation; keep it off food/drinks; wash hands.

Wrap-up (with a teacher’s grin)

Fluorescence is the dramatic one: “LOOK AT ME!”
Phosphorescence is the stubborn one: “I’m still glowing, thanks.”
And glow sticks are the chaotic cousin who turns up uninvited and steals the show.

Once students can classify a glow correctly, they’ve basically learnt: energy transfer, electronic structure, and a slice of quantum rules — using a highlighter and a torch. That’s a good day in a school lab.

26 February 2026

The Humble Power Supply

Used every day in schools… and quietly doing electrical wizardry.

If you’ve ever walked into a science lab, a DT room, an ICT suite, or (let’s be honest) a cupboard labelled “DO NOT TOUCH” and found a tangle of mysterious black bricks, you’ve met the humble power supply. It’s the unsung hero of school life: powering microscopes, sensors, laptop trolleys, data loggers, routers, projectors, LED strips, chargers, and that one device nobody remembers owning but everyone is afraid to unplug.

And yet… it’s also a technical marvel. A power supply is basically a small, polite machine whose full-time job is to take whatever electricity it’s given (often rather wild and “mains-y”) and turn it into something calm, safe, and useful for delicate electronics. It does this all day, every day, without applause.

1) The problem: mains electricity is not what your gadgets want

In the UK, mains is about 230 V AC at 50 Hz. That’s brilliant for transmitting power around the country, but it’s not what your Arduino, laptop, or PASCO sensor dreams of at night. Most school kit wants something like 5 V, 9 V, 12 V, 19 V DC, and it wants it stable, smooth, and reliable.

So the power supply acts like a translator:

Mains AC → low voltage DC
“Noisy” → “smooth”
“potentially lethal” → “safe enough to poke into a classroom device without writing a risk assessment the length of War and Peace”

2) The classic approach: transformer power supplies (the chunky ones)

Old-school power supplies often used a transformer. These are the heavier ones that feel like they contain a small neutron star.

A transformer works on electromagnetic induction:

It takes high-voltage AC and steps it down to lower-voltage AC.
It’s robust, simple, and often beautifully over-engineered.

Then the power supply has to convert that AC into DC. That typically means:

Rectification (usually a diode bridge): flips the negative half of the AC wave so it all goes “one way”.
Smoothing (big capacitors): fills in the dips so you don’t get a lumpy output.
Regulation (a regulator circuit): keeps the output steady even if the input or load changes.

The result: usable DC… and a box that could be used as a doorstop in a storm.

3) The modern approach: switch-mode power supplies (the clever ones)

Most of today’s “black bricks” are switch-mode power supplies (SMPS). They’re lighter, smaller, and more efficient — which is why you can have a laptop charger that doesn’t weigh the same as the laptop.

Instead of stepping down 50 Hz AC directly, a switch-mode supply:

Rectifies the mains to DC first.
Chops it at a very high frequency (thousands to millions of times per second).
Uses a much smaller transformer at that high frequency.
Then rectifies and regulates again to get a clean DC output.

That “chopping” is why switch-mode supplies can sometimes cause electrical noise (and why some audio kit gets grumpy when you use a cheap charger).

4) Why schools absolutely depend on them

Schools are basically power-supply ecosystems. Every department has its own habitat:

Science: sensors, microscopes, data loggers, centrifuges, magnetic stirrers
DT: soldering stations, small CNC/laser kit, fans, controllers
ICT: laptop charging, networking kit, servers, monitors
Music: keyboards, amps, interfaces, mixers
Admin: printers, label makers, phones, “conference speaker thingies”

And the secret truth: half the time, the lesson doesn’t fail because the kit is broken… it fails because someone brought the wrong adapter and is now trying to persuade a 12 V device to run on 19 V “because it fits”.

5) The label that saves lives (and lessons)

If you remember one thing, let it be this: read the label.

A power supply label tells you the important stuff:

Output voltage (V): must match what the device wants.
Output current (A or mA): the supply must be able to provide at least what the device needs.
Polarity (centre-positive / centre-negative): crucial for barrel connectors.
AC or DC output: yes, some supplies output AC. Yes, it catches people out.

A common school tragedy:

“It turns on and then goes off.” → current too low, supply overheats or voltage sags.
“It worked once and now smells funny.” → wrong voltage (or wrong polarity).

6) A tiny physics lesson hiding in plain sight

Power supplies are a brilliant real-world link across the curriculum:

Physics: AC vs DC, transformers, diodes, capacitors, power, efficiency
Computing: stable supply rails, noise, data errors, brownouts
Design & Technology: power requirements, safety, connectors, standards
Maths: P = IV, unit conversions, peak vs RMS, energy and efficiency

And they’re also a wonderful reminder that engineering is often about making something complicated look boring.

7) The power supply deserves a bit of respect

We don’t notice power supplies when they work — which is most of the time — but they’re doing constant, precise, high-speed control to protect your devices from spikes, dips, overloads, and the chaos of the mains. They’re not just “chargers”. They’re small power stations with manners.

So next time you see that pile of identical-looking black rectangles in the prep room, take a moment. Somewhere inside each one is a whole chain of clever ideas — quietly turning raw electricity into something your classroom can actually use.

And if you’re the one in charge of the cupboard of adapters… may your labels be clear, your voltages correct, and your spares box forever blessed.

25 February 2026

Maths and Sailing: the Day I Discovered “Tacking” Is Basically Algebra With Wet Shoes

There are two kinds of people in the world: those who think maths is thrilling, and those who think it’s something that happens to other people in exam halls. Then there are sailors… who accidentally do maths all the time, usually while holding a rope and trying not to look panicked.

When you sail on a river (hello, Thames), you quickly realise you can’t just point at where you want to go and go there. The wind has other plans, the stream has very other plans, and the boat has the personality of a stubborn shopping trolley. So you tack — zig-zagging upwind — which is basically a real-life lesson in angles, vectors, and “Why isn’t this working the way it did on the whiteboard?”

1) Angles: “Close-hauled” is a geometry problem

Upwind sailing is all about the angle between the boat and the wind. Too close and the sail flaps like a sad flag. Too far off and you lose ground. That sweet spot? It’s the practical version of “find the optimal angle” — except your calculator is a tell-tale and your teacher is the wind shouting “NO.”

Classroom link: get students drawing angle diagrams with wind direction as a reference line, then ask: Which heading gives the fastest progress toward the buoy? It’s bearings and geometry with purpose.

2) Speed and distance: the river won’t wait for your calculations

Want to know if you’ll reach the mooring before the tide pins you sideways? That’s speed = distance ÷ time — but with a moving conveyor belt underneath you. On the Thames, “I’ll just glide in” turns into “Why am I drifting into Berkshire?”

Classroom link: real data problems: boat speed through water vs speed over ground. Give students two speeds and ask them to work out drift, time to a marker, or whether the boat arrives upstream or embarrassingly downstream.

3) Ratios and forces: the sail is a giant triangular maths lesson

Sail shape (and how tight you pull everything) affects speed. A flatter sail is different to a fuller one — and suddenly you’re in ratios, proportional reasoning, and “adjust this by a bit and the whole system changes.”

Classroom link: show a simple sail triangle and explore how changing one side (sheet tension, boom position) changes the “shape” and performance. You don’t need to go full physics — just proportional thinking and graphs.

4) Turning circles and pivot points: maths you can feel

Powerboaters learn that boats pivot in different places depending on forward or reverse. Dinghies do their own version when tacking and gybing — turn too fast and you stall; too slow and you drift. It’s all about rates of change in the real world.

Classroom link: graph “heading vs time” during a tack and discuss steep vs gentle slopes. Suddenly gradients mean something other than “that line goes up.”

5) Probability: will this tack work… or will I be doing an accidental three-point turn?

Every tack is a mini gamble: wind shift, gust, lull, other boats, and the dreaded “in irons.” That’s probability, decision-making, and risk — plus a splash of psychology.

Classroom link: simple tree diagrams: if wind shifts left/right, what’s the best choice? Add constraints like river width. This becomes a genuine “thinking problem” rather than a worksheet.

Making maths more interesting (without pretending it’s all fun)

The trick isn’t to say “maths is amazing!” while students stare back like you’ve suggested revising for fun. The trick is to give maths a job to do.

Sailing gives you a ready-made world where numbers matter:

If you get the angle wrong, you don’t reach the buoy.
If you misjudge time and drift, you miss the mooring (and your dignity).
If you don’t estimate properly, the river teaches you… repeatedly.

And the best part? Students who think they “aren’t maths people” often are — they just haven’t met maths in a form that moves, splashes, and occasionally shouts “LEEWARD!”

If you want to make maths more interesting, don’t add more gimmicks. Add more reasons. Ideally ones involving boats.

24 February 2026

Measuring the Speed of Sound in Water (without owning a submarine)

Measuring the speed of sound in air is a classic: two microphones, a clap, a ruler, and a small argument about who started the stopwatch too late. Water, however, is a different beast. Sound travels much faster in water than in air, so the time differences you’re trying to measure are tiny. That doesn’t make it impossible — it just means we need methods that don’t rely on someone’s thumb hovering over a phone timer like it’s the Olympic 100 m final.

Below are three practical approaches, from “school-lab achievable” to “this feels like we’re doing proper marine science”.

Method 1: Time-of-flight with two underwater microphones (best and most direct)

Idea

Send a sharp sound pulse through the water. Record when it arrives at two sensors a known distance apart. The speed is:

v = \frac{d}{\Delta t}

Where:

$d$ = distance between sensors (m)
$\Delta t$ = time delay between the two recordings (s)

What you need

A long water tank / trough / (in a pinch) a swimming pool
Two hydrophones (underwater microphones)
- If you don’t have hydrophones, you might hack it with waterproofed microphones in sealed bags, but reliability varies wildly.
Something to record both channels at once:
- A 2-channel audio interface into a laptop works brilliantly
- Some data loggers can do it too
A sharp sound source:
- Two pieces of wood tapped together underwater (clappers)
- An old school bell ( what we used)
- A short ultrasonic “ping” if you have a signal generator + transducer

Procedure

Mount the two hydrophones in line, separated by a measured distance (say 0.50 m to 2.00 m).
Make a sharp sound pulse near one end (closer to hydrophone A).
Record both traces.
Measure the time shift between the first big peak on channel A and channel B.
Calculate $v$ .

Tips to make it work

Use a bigger distance if you can.
Example: if $v \approx 1500\ \text{m s}^{-1}$ , then over 1.0 m the delay is only about 0.00067 s (0.67 ms). That’s measurable… but you need decent sampling.
Set audio sampling to ≥ 44.1 kHz (better: 96 kHz).
Keep sensors at the same depth to reduce odd paths and reflections.
Do it in the middle of the tank, away from walls, or you’ll get echoes bouncing about like a pinball machine.

Typical result

Fresh water at room temperature is usually around 1480–1500 m/s.

Main uncertainties / errors

Reflections from walls and the surface (extra peaks)
Distance measurement (especially if sensors aren’t truly in line)
Temperature (sound speed changes with temperature)

Method 2: Echo (SONAR-style) using a single sensor (simple concept, fiddlier in practice)

Idea

Make a sound pulse and measure the time until the echo returns from a reflecting surface at distance $L$ :

v = \frac{2L}{t}

Because the sound goes there and back.

What you need

A hydrophone (or transducer) and recorder
A flat reflecting target (a metal plate works well)
A way to know $L$ accurately

Procedure

Place the reflector at a known distance $L$ from the sound source/sensor.
Make a sharp pulse.
Measure the time to the echo peak.
Compute $v$ .

Why it’s trickier

Echoes can overlap with the original pulse in small tanks.
Multiple reflections can confuse which peak is “the” echo.
Works better in a long tank or a pool.

Method 3: Resonance in a water-filled tube (clever, but equipment-sensitive)

This is the “do it like the air resonance tube experiment… but underwater” approach.

Idea

Drive sound at a known frequency $f$ and find standing-wave positions in a column of water. Then:

v = f\lambda

If you can measure the wavelength $\lambda$ in water.

Challenge

Generating and detecting clean standing waves in water is harder than in air, and reflections/attenuation can be awkward. This is more of a “physics club project” than a quick GCSE practical — but it’s a brilliant extension activity if you have ultrasonics kit.

What to record in your results table

For time-of-flight (Method 1), a neat table looks like:

Sensor separation $d$ (m)
Time delay $\Delta t$ (s)
Calculated speed $v$ (m/s)
Water temperature (°C)
Notes on reflections / signal quality

Repeat for several distances and average the result.

Safety and sanity notes

Electricity + water: keep interfaces/laptops well away and use long leads.
Don’t smash glass tanks with enthusiastic spoon percussion.
If you use ultrasonics: it’s generally safe at typical lab levels, but don’t drive powerful transducers in a way that heats water or stresses equipment.

A nice “why it’s faster in water” paragraph (for the write-up)

Sound travels faster when particles are more strongly coupled (stiffer medium) and slower when the medium is more compressible. Water is far less compressible than air, so disturbances pass along more quickly — even though water is denser

23 February 2026

A-Level Biology: Is there much life in a river in late February / early March?

If you stand on a bridge in late February and declare, “This river is dead,” the river will respond by doing what rivers do best: quietly getting on with it while you look at the surface like it’s the whole story.

The big difference at this time of year isn’t whether there’s life, but where it’s hiding and how active it can be, which comes down to temperature, flow, light, and habitat.

1) What “late winter” does to river life (in general)

Late Feb/early March in the UK is usually:

Cold water → slower enzyme activity, slower metabolism, less visible animal movement.
Low light / low primary productivity → less algae and plant growth, so less grazing happening in plain sight.
Higher flows after rain (often) → animals shelter in margins, under stones, in weed beds, and in slower back-eddies.

So: fewer “wow” moments at the surface, but plenty happening below it.

2) Chalk stream River Gade: life with the thermostat left on

Chalk streams are groundwater-fed, so they tend to have clear water, stable flows, and relatively stable temperatures (often quoted around ~10 °C for groundwater-fed systems). That stability gives them longer growing seasons and supports lots of specialist invertebrates.

In late winter on a chalk stream like the Gade, you’re often more likely to find:

Active macroinvertebrate larvae/nymphs (mayflies, caddisflies, stoneflies—“riverflies”) tucked into gravel, weed, and margins.
Fish still feeding (not frantic, but not completely “switched off”), helped by that steadier temperature.
Clearer signs of habitat structure (gravels, ranunculus beds later in spring, undercut banks), which matters because habitat complexity = niches.

In other words: the Gade can look “quiet”, but it’s often quietly busy.

3) River Thames at Bourne End: bigger river, bigger hide-and-seek

The Thames at Bourne End is a larger, slower-to-warm (and often more turbid) lowland river reach. In late winter, you can still have huge biomass present, but it’s typically:

Deeper and dispersed (fish shoals holding in steadier water)
More influenced by flow events (spates can shift fine sediment and nudge invertebrates into refuges)
Less visibly “chalk-stream sparkly” because suspended particles reduce light penetration (so you see less plant/algal action until spring picks up)

But don’t confuse “less visible” with “less alive”: Thames catchment monitoring routinely records diverse macroinvertebrate and plant communities across the system, and seasonal sampling shows that invertebrate communities are there year-round.

4) So… which has “more life” in late Feb/early March?

If you mean most visible life on a quick look:

Chalk stream (Gade) often wins: clearer water + stable temperature = more obvious signs (and easier sampling success).

If you mean total biomass and variety of habitats:

Thames can be immense, but you need to sample smartly (margins, slack water, submerged structure) to “see” it.

A nice A-Level way to phrase it:

In late winter, chalk streams often show higher apparent activity and detectability, while large lowland rivers may have equal or greater biomass that is less detectable without targeted sampling.

5) A-Level fieldwork angle: how to test it (properly)

If you want students to compare Gade vs Thames in late winter, make it a mini investigation:

Standardised kick sample (same time, same net mesh, same number of kicks)
Record flow, temperature, dissolved oxygen, turbidity, substrate type, channel width/depth
Identify macroinvertebrates to family level and calculate a biodiversity index (e.g., Simpson’s)
Optional: focus on EPT groups (mayfly/stonefly/caddis) as a rough indicator set.

You’ll usually find the chalk stream produces “nicer” samples for beginners (cleaner, easier to sort), while the Thames rewards patience and better site choice.

6) A seasonal footnote: “Where are the fish?”

A lot of coarse fish spawning is typically spring/summer as temperatures rise, so late Feb/early March is often more about overwintering behaviour than spawning frenzy.

22 February 2026

Understanding Cash Flow (and why profitable businesses still go bust)

A and GCSE Business Studies

Cash flow is the movement of cash into and out of a firm’s bank account.
Profit is when revenue is greater than total costs.

Those two sentences look similar… right up until your “profitable” business can’t pay the rent on Friday.

Think of it like this:

Profit is your score (based on what you’ve earned and what you’ve incurred).
Cash flow is your oxygen (based on what has actually arrived in the bank, and what’s actually left it).

A business can “win on points” (profit) while still running out of oxygen (cash).

Why cash flow and profit don’t match

1) Timing: “Sold” doesn’t mean “paid”

You might invoice a customer today… but they might pay in 30, 60, or 90 days.

So your accounts may show a profitable sale, but your bank account is still doing its best impression of a tumbleweed.

Example:
You sell £10,000 worth of work in January on 60-day terms.
That’s great for profit in January… but the cash might not show up until March.

2) Cash leaves before you’ve “made” the sale

Businesses often pay for stock, wages, and rent before customers pay them.

That gap is where cash flow dramas live.

3) Non-cash costs affect profit (but not cash)

Some costs reduce profit without an immediate cash payment.

Depreciation is the classic: the value of equipment “wearing out” on paper.
The cash left the bank when you bought the kit, not each month afterwards.

So you can have:

Lower profit due to depreciation,
while cash flow that month looks fine.

4) Investment spending hurts cash flow (but not necessarily profit)

Buying a new van, refurbishing the shop, purchasing a 3D printer that you absolutely “need” (honestly)…
That’s a cash outflow now, even though the benefit is spread over years.

5) Loan repayments are cash outflows, but not all are “costs”

Repaying a loan:

Interest counts as a cost (affects profit),
Repaying the capital does not count as a cost, but it does reduce cash.

This catches students out all the time.

A simple cash flow example (the “how are we broke?” moment)

Imagine a small business in January:

Cash in:

Customers pay: £2,000

Cash out:

Rent: £1,200
Wages: £1,500
Stock purchase: £800

Net cash flow = £2,000 − (£1,200 + £1,500 + £800)
Net cash flow = £2,000 − £3,500 = –£1,500

So cash is falling.

But profit for January might look like this:

Sales made (invoiced): £6,000
Costs incurred: £4,000
Profit = £2,000

Profit: +£2,000
Cash flow: –£1,500

That’s how you can be profitable and panicking in the same month.

Why cash flow matters so much in Business Studies (and real life)

Cash flow problems can cause:

Late payments to suppliers (and damaged relationships)
Missed wages (and an instant morale collapse)
Emergency overdrafts (and extra costs)
In extreme cases: business failure, even when the business is “profitable”

In exams, you’ll often link this to:

Working capital (current assets − current liabilities)
Cash flow forecasting
Reasons for using finance (overdrafts, short-term loans)
Managing trade credit (both given and received)

Quick ways businesses improve cash flow

Increase cash inflows

Encourage faster customer payments (shorter credit terms)
Offer small discounts for early payment
Chase late invoices (politely at first… then less politely)
Take deposits or upfront payments

Reduce or delay cash outflows

Negotiate longer payment terms with suppliers
Reduce unnecessary spending
Manage stock levels (too much stock = cash sitting on shelves)
Lease rather than buy expensive assets (sometimes)

Mini “exam-ready” summary

Profit = revenue − total costs (measured over a period, includes non-cash items).
Cash flow = actual cash in − actual cash out (bank balance reality).
A business can be profitable but still fail if it can’t meet short-term payments.

21 February 2026

“Ask an AI to do extended thinking…” — and it tells you what it’s doing?! (Sort of.)

A Level Computing | Philip M Russell Ltd style | UK spelling

You’ve seen it happen:

You ask an AI a tricky question.
You click the button that says something like “extended thinking”.
And then—instead of just blurting out an answer like an overconfident Year 10—you get a response that sounds like the AI is narrating its brain:

“First I’ll break the problem down… then I’ll check edge cases… then I’ll verify…”

It feels like watching a student show their working. Which is oddly comforting.

But here’s the important bit for A Level Computing:

The AI isn’t “showing its thoughts” in the way you think

Most modern AI systems do not reveal their full internal reasoning (often called chain-of-thought). What you’re seeing is usually a summary of the approach: a tidy, human-readable explanation of the steps it took or would take.

That’s not a bad thing. In fact, for learning, it can be brilliant — but you need to understand what you’re getting.

What “extended thinking” usually means (in plain English)

When you request extended thinking, you’re generally asking the model to:

Spend more compute/time on reasoning
Break the task into sub-problems
Self-check for contradictions and missing cases
Explain the method more explicitly than usual

In A Level terms, it’s similar to switching from:

“Give me the answer”
to
“Show me your algorithm, and then run it carefully.”

Why it looks like the AI is narrating its process

Because narration is useful.

A well-structured explanation often includes:

Identifying inputs/outputs (specification thinking)
Planning a method (algorithm design)
Checking constraints (edge cases, assumptions)
Verifying results (testing / validation)

That’s basically the Computational Thinking toolkit:
Decomposition, abstraction, algorithmic thinking, evaluation.

So the AI is doing what your teacher has been nagging you to do all along. (Annoying, isn’t it?)

The catch: “explanations” are not the same as “proof”

Even if the AI gives you a lovely step-by-step explanation, it can still:

use a wrong assumption,
miss a constraint,
produce an answer that sounds correct but isn’t.

So treat it like a very fast study partner who sometimes confidently walks into lampposts.

A Level-friendly rule:

Use the AI’s explanation as a draft algorithm — then test it like you would test your own code.

How to prompt it properly (so it actually helps you learn)

Try these prompt styles:

1) Ask for a plan first (before the final answer)

Prompt:
“Give me a brief plan (like pseudocode / method) before the final answer.”

Why it helps: you can spot dodgy logic early.

2) Force it to state assumptions

Prompt:
“List your assumptions explicitly before solving.”

Why it helps: you can challenge the weak bits.

3) Ask it to check edge cases

Prompt:
“After answering, test your solution against 3 edge cases.”

Why it helps: that’s literally exam evaluation.

4) Ask for a marking-grid style response

Prompt:
“Answer like an A Level student: define terms, show method, give final result, then evaluate limitations.”

Why it helps: it mirrors how marks are awarded.

A quick example: “Explain how you’d search for the fastest route”

Instead of:
“Find the fastest route.”

Try:
“Explain how you’d approach this: identify the graph model, choose an algorithm, and justify it.”

Now you’re doing proper A Level:

Graph representation (nodes/edges/weights)
Algorithm choice (Dijkstra vs A* vs BFS)
Justification (constraints, complexity, correctness)

So… should you trust the “thinking”?

Trust it the way you trust a calculator:

Great for speed
Great for structure
Still your job to check it’s answering the right question

And if it gives you a neat method: brilliant. That’s basically revision.

Just don’t confuse “a convincing explanation” with “guaranteed correct”.