Beyond Windows and Mac — Why Every Computing Student Should Spend Some Time Using Linux

For many GCSE and A Level Computer Science students, the phrase operating system really means one of two things:

Windows or macOS.

They may know, because the specification tells them, that an operating system manages memory, processes, files, peripherals and the user interface. They may be able to answer an examination question about multitasking or virtual memory.

But there is a considerable difference between learning that an operating system can work in different ways and actually experiencing one that does.

That is why I think one of the most useful things a computing student can do is spend some time with Linux.

Not because everybody should abandon Windows.

Not because Linux is automatically “better”.

And certainly not because using a terminal somehow makes somebody a more serious computer scientist.

The value is much simpler.

Linux makes you realise that many things you thought were fundamental features of a computer are actually just choices made by the designers of the operating system you normally use.

And once students understand that, their view of computing changes.

---

An Operating System Is More Than the Desktop You See

One misconception I frequently encounter is the idea that the graphical desktop is the operating system.

Students see:

• the Start menu;

• the taskbar;

• File Explorer;

• windows;

• icons;

• menus;

• desktop backgrounds.

Because these are the parts of Windows they interact with every day, it is easy to assume that an operating system naturally looks something like Windows.

Linux quickly challenges that assumption.

Strictly speaking, Linux is the kernel, the central part of the operating system that communicates with the hardware and manages resources.

What people commonly call “Linux” is normally a complete Linux distribution containing the kernel together with utilities, libraries, applications, package-management software and usually a graphical desktop environment.

Examples of Linux distributions include:

• Ubuntu;

• Debian;

• Fedora;

• Linux Mint;

• Arch Linux;

• openSUSE;

• Raspberry Pi OS.

Already, that gives students something interesting to think about.

There isn't simply one Linux operating system that looks the same on every machine.

Different distributions can be designed for different purposes.

---

Then You Discover the Desktop Can Change Too

Install Windows and you largely receive Microsoft's Windows interface.

Install macOS and you receive Apple's desktop environment.

Linux can be rather different.

A Linux installation might use GNOME, which presents one style of graphical interface.

Another could use KDE Plasma, which can feel much closer to the traditional desktop environment familiar to Windows users.

Others might use:

• Xfce;

• Cinnamon;

• MATE;

• LXQt.

This is a fascinating discovery for students because the same underlying operating system can be presented through substantially different graphical environments.

It immediately raises a useful computing question:

Where does the operating system finish and the user interface begin?

That is much more interesting than simply memorising:

“The operating system provides a user interface.”

Linux allows students to see that separation in practice.

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Your First Linux Surprise: The Terminal

Then comes the part that can initially look slightly frightening.

The command line.

Open a terminal window and instead of icons and folders you might see something such as:

student@computer:~$

At first it can appear as though computing has suddenly travelled backwards 40 years.

Where have all the windows gone?

Where is File Explorer?

Why would anybody want to type commands when they can click on something?

Spend a little time with it, however, and something interesting happens.

You begin to understand why command-line interfaces have survived.

They are extraordinarily powerful.

---

Your First Few Linux Commands

A beginner does not need hundreds of commands.

Start with a handful.

To find the current directory:

pwd

To display its contents:

ls

To change directory:

cd Documents

To move up one level:

cd ..

To create a directory:

mkdir experiments

To copy a file:

cp results.txt backup.txt

To rename or move one:

mv results.txt oldresults.txt

To display a text file:

cat results.txt

Within quite a short period of time, students are navigating the filesystem without touching the mouse.

And something more important is happening.

They are beginning to understand the filesystem rather than merely operating a graphical representation of it.

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Suddenly File Paths Make More Sense

Students learning programming regularly encounter file paths.

On Windows they might see:

C:\Users\Philip\Documents\program.py

On Linux they might encounter:

/home/philip/Documents/program.py

Linux introduces the idea of the root directory:

/

and beneath it directories such as:

/home
/etc
/bin
/var
/tmp

You certainly don't need a GCSE student to memorise the entire Linux filesystem hierarchy.

What is useful is seeing that there are alternative ways of organising storage.

It also makes absolute and relative paths far less abstract.

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One of Linux's Best Lessons: Permissions

Suppose a student tries to modify a system file and Linux replies:

Permission denied

Initially this can be annoying.

Educationally, it is wonderful.

Who owns this file?

Which user is the program running as?

Who is allowed to read it?

Who is allowed to modify it?

Who is allowed to execute it?

A command such as:

ls -l

might display something resembling:

-rwxr-xr--

Those apparently mysterious characters introduce a very real implementation of:

• read permissions;

• write permissions;

• execute permissions;

• users;

• groups.

Suddenly access rights are no longer just another paragraph in an operating-systems textbook.

They are controlling what you can actually do.

---

Installing Software Works Differently Too

For many students, installing software means:

1. search for a website;

2. download an installer;

3. double-click it;

4. click Next several times;

5. hope you downloaded the genuine version.

Linux distributions commonly use package managers instead.

On a Debian or Ubuntu-based system, for example, software can often be installed using something like:

sudo apt install python3

There is a lot contained in that single command.

The computer:

• contacts configured software repositories;

• identifies the requested package;

• checks dependencies;

• downloads the required files;

• installs them;

• registers the software with the package-management system.

Students can then discover that updating installed packages can also be centrally managed.

This leads to excellent discussions about:

• software repositories;

• dependencies;

• version control;

• trusted sources;

• security updates;

• system administration.

---

Then You Discover Pipes

One of my favourite ideas to show students is the Unix philosophy of combining small tools.

Imagine one command produces some information.

Instead of building an enormous application that does everything, Linux encourages us to take the output of one program and give it to another.

The vertical bar symbol:

|

is called a pipe in this context.

For example:

ls | sort

The first command generates a list.

The second sorts it.

You can begin building increasingly powerful combinations:

ls | sort | head

The concept is remarkably elegant:

take several simple programs and combine them to solve a more complicated problem.

That is a very computer-science way of thinking.

---

Searching Becomes Extremely Powerful

Suppose we have a large text file and want every line containing the word "error".

Instead of opening the document and searching visually, we might use:

grep "error" logfile.txt

Now imagine searching hundreds of log entries.

Or thousands.

Or searching the output from another program.

That is when the command line begins to stop looking old-fashioned and starts looking efficient.

Students begin to appreciate that graphical interfaces and command-line interfaces are not competing generations of computing.

They are tools suited to different tasks.

---

Processes Stop Being an Abstract Diagram

GCSE and A Level students study processes.

They learn that programs executing in memory become processes and that an operating system schedules processor time between them.

Linux gives them opportunities to observe this.

Commands such as:

ps

can display running processes.

Programs such as:

top

allow users to watch processor and memory usage changing in real time.

A student can start a program, observe the process appear, terminate it and watch it disappear.

Now an examination question about process management has a physical experience attached to it.

That matters.

---

Linux Is Particularly Good for Learning Networking

Networking is another subject that can become rather theoretical at school.

Linux provides an extraordinary collection of tools for exploring networks.

Students can investigate concepts using commands such as:

ping

and tools for examining:

• IP addresses;

• routing;

• DNS;

• active connections;

• network interfaces.

For example:

ping bbc.co.uk

does much more educationally than simply demonstrate whether a website responds.

It raises questions.

How did the computer convert the domain name into an IP address?

What route did the packet take?

Why does latency vary?

What happens if a host does not respond?

What exactly is being transmitted?

A networking specification suddenly becomes a network you can interrogate.

---

Linux and Python Work Beautifully Together

Linux is also a natural environment for programming.

Suppose we create a simple Python file:

hello.py

containing:

print("Hello from Linux")

We can run it directly from the terminal:

python3 hello.py

Now consider writing a Python program that:

• reads command-line arguments;

• processes a text file;

• creates a log;

• communicates across a network;

• monitors a sensor;

• controls a Raspberry Pi.

The relationship between software, filesystem and operating system becomes much more visible.

This is especially valuable for students moving beyond very simple programming exercises.

---

From Commands to Shell Scripts

Eventually students discover that if they keep typing the same commands, they can put them into a file and run them automatically.

That introduces shell scripting.

A very simple script might perform several operations sequentially.

Perhaps it:

• creates a backup directory;

• copies important files;

• adds the date to a log;

• reports whether the operation completed successfully.

Now we have moved from merely using the operating system to programming the operating system's environment.

Concepts such as:

• sequence;

• selection;

• variables;

• loops;

• input;

• output;

• automation

suddenly appear somewhere other than Python or another classroom programming language.

That reinforces the underlying principles.

---

Linux Quietly Runs Much of the Computing World

Another reason students should encounter Linux is that desktop market share gives a rather misleading impression of its importance.

Walk around homes and schools and Windows, macOS, Android, iOS and ChromeOS may appear dominant.

Look behind the scenes and Linux becomes extremely important.

Linux-based systems are widely found in:

• web servers;

• cloud computing;

• supercomputers;

• networking equipment;

• embedded systems;

• development environments;

• containers;

• scientific computing;

• Raspberry Pi projects.

Android itself uses the Linux kernel.

So even a student who never intends to replace Windows on their laptop is likely to encounter Linux somewhere if they continue into computing.

---

You Probably Already Own a Linux Computer

There is an especially easy route into all this.

A Raspberry Pi.

Raspberry Pi OS gives students a graphical desktop that feels reassuringly familiar while providing the full Linux terminal underneath.

It is an excellent combination.

Use the desktop to browse the web or edit a Python program.

Open a terminal and investigate:

ls

or:

python3

Then connect an LED, sensor or other device and Linux suddenly becomes part of a physical-computing system.

The computer is no longer simply something that runs applications.

It becomes something you control.

---

You Don't Need to Replace Windows

This is important.

I would not recommend that a student unfamiliar with Linux immediately erase their main computer and install an unfamiliar operating system.

There are much safer ways to experiment.

Option 1 — Use a Raspberry Pi

Probably the most enjoyable educational route.

You have a completely separate Linux computer to experiment with.

If you make a mess of it, you can reinstall the operating system.

That freedom encourages experimentation.

Option 2 — Use a Virtual Machine

Programs such as virtualisation software allow Linux to run as a computer inside your existing computer.

You can experiment without changing your normal Windows installation.

Option 3 — Use a Live USB

Many Linux distributions can run from a USB drive without immediately installing anything on the computer.

Option 4 — Windows Subsystem for Linux

Windows users can also explore many Linux command-line tools through WSL.

For a student primarily interested in programming and command-line skills, this can provide a useful introduction.

---

A Practical Linux Challenge for Computing Students

Rather than simply installing Linux and looking around, I would turn the exercise into a challenge.

See whether you can complete all of these.

Challenge 1

Find your current directory.

Challenge 2

Create a directory called:

linuxchallenge

Challenge 3

Move into that directory.

Challenge 4

Create a text file.

Challenge 5

Copy the file.

Challenge 6

Rename the copy.

Challenge 7

Display the contents of the directory.

Challenge 8

Run a Python program from the command line.

Challenge 9

Find your computer's IP address.

Challenge 10

Use ping to test another computer or suitable internet host.

Challenge 11

Look at running processes.

Challenge 12

Investigate the permissions on one of your files.

A student who completes those twelve tasks has probably learned more about operating systems than somebody who has merely revised several pages of notes describing them.

---

A More Ambitious Project: Build a Tiny Linux Server

For an A Level student, I would go further.

Take a Raspberry Pi or an old suitable computer and turn it into a simple server.

It might host:

• a web page;

• files;

• a small Python web application;

• sensor readings;

• a database;

• a home dashboard.

Now the student has to think about:

• IP addressing;

• users;

• permissions;

• processes;

• services;

• ports;

• files;

• software installation;

• security;

• networking.

Almost an entire section of the Computer Science curriculum begins joining together.

That interconnected understanding is far more valuable than learning each specification point independently.

---

The Mistakes Are Part of the Lesson

Anyone learning Linux will make mistakes.

You will type a command incorrectly.

You will try to access a directory that does not exist.

You will wonder why a file cannot be executed.

You will receive:

Permission denied

You will search the internet for an explanation.

You may spend 20 minutes discovering that Linux filenames are case-sensitive and that:

Program.py

and:

program.py

are not necessarily the same file.

This can occasionally be frustrating.

But it is also how a great deal of genuine computing is learned.

You form a hypothesis.

You try something.

It fails.

You read the error.

You investigate.

You modify your approach.

You try again.

That is computational thinking in a much more authentic environment than simply answering a multiple-choice question about operating systems.

---

Linux Also Teaches an Important Lesson About Choice

There is another reason I like students encountering Linux.

It makes computing feel less fixed.

You can change:

• the desktop;

• the terminal shell;

• the file manager;

• the text editor;

• the programming tools;

• the services running in the background.

You begin to realise that a computer does not have to operate in exactly the way its manufacturer originally presented it.

For somebody interested in Computer Science, that is quite an empowering discovery.

---

But Is Linux Better Than Windows or macOS?

That is probably the wrong question.

Windows has enormous software compatibility and is familiar to vast numbers of users.

macOS provides an extremely polished environment tightly integrated with Apple's hardware and ecosystem.

Linux provides exceptional flexibility, transparency and access to powerful development and administrative tools.

All three have strengths.

The educational value comes from experiencing the differences.

A student who has only ever used one operating system may mistake its conventions for universal computing principles.

A student who has used several begins separating the concept from the implementation.

That is exactly what Computer Science education should encourage.

---

Final Thought — Stop Simply Using the Computer and Start Investigating It

There is a moment when learning computing changes.

At first, the computer is something that provides applications.

You open Word.

You launch a browser.

You run a game.

You write a Python program.

But eventually you start wondering what is underneath all of that.

Where are the files actually stored?

Which processes are running?

Who owns them?

How does the machine know where another computer is?

What happens when software is installed?

How can one program send its output into another?

What exactly is the operating system doing?

Linux provides a wonderful environment in which to start asking those questions.

So my challenge to GCSE and particularly A Level Computer Science students is simple:

Spend a little time outside Windows or macOS.

Install Linux in a virtual machine, try it on a Raspberry Pi, experiment with WSL or boot a suitable live Linux system.

Open the terminal.

Type:

ls

and begin exploring.

You may discover that the most valuable thing Linux gives you is not another operating system.

It is a different way of looking at the computer you thought you already understood.

 

Chemiluminescence — Creating Light From a Chemical Reaction

We are used to making light with electricity, flames or something that is already extremely hot. Chemiluminescence is different. The chemistry itself produces the light.

There are some practical demonstrations that immediately change the atmosphere in a laboratory.

Chemiluminescence is one of them.

Turn down the room lights, start the reaction, and suddenly a solution begins to glow blue. There is no electrical connection to it. There is no bulb hidden underneath it. Nothing is burning.

The light is being produced by a chemical reaction.

That makes chemiluminescence spectacular to watch, but it also makes it an excellent piece of science. Behind that glow are several important ideas: chemical energy, electron excitation, photon emission, reaction rates, catalysts and activation energy.

And, importantly, it gives us something that can be investigated rather than simply admired.

---

What Actually Is Chemiluminescence?

Chemiluminescence is the production of light as a result of a chemical reaction.

Normally, when an exothermic reaction releases chemical energy, much of that energy eventually appears as thermal energy.

We notice the mixture getting warmer.

Chemiluminescent reactions take a rather more interesting route.

Part of the energy released by the reaction is used to produce molecules in an electronically excited state.

Those excited molecules are unstable.

They eventually return to a lower-energy state and release the excess energy as a photon of light.

In simplified form:

chemical reactants -> excited product -> product + light

We can represent the final stage as:

excited molecule -> ground-state molecule + photon

The energy of the photon is related to its frequency:

E = hf

where:

• E is photon energy;
• h is Planck's constant;
• f is frequency.

So the colour we observe is directly connected to the amount of energy being released when the molecule returns to its lower-energy state.

That is a remarkable connection.

A bottle glowing blue in a dark laboratory is ultimately demonstrating quantum behaviour.

---

Light Without Becoming Red Hot

This is perhaps the first surprising feature.

If I want a piece of metal to glow, I normally have to make it extremely hot.

The filament in a traditional incandescent lamp works because electricity heats the filament to a very high temperature.

A flame emits light because energetic particles and hot gases are involved.

Chemiluminescence does not require the material to reach anything approaching those temperatures.

For that reason it is sometimes described as a form of cold light.

That does not necessarily mean absolutely no heat is generated. The chemical reaction can still release thermal energy.

The important point is that the visible light is not being generated simply because the material has become incandescent.

The mechanism is different.

And that immediately raises a good question for students:

If it isn't hot enough to glow, where is the light coming from?

That question takes us straight into energy levels.

---

The Famous Example: Luminol

Probably the best-known chemiluminescent substance is luminol.

Under suitable chemical conditions, luminol undergoes an oxidation reaction that ultimately produces an electronically excited product.

As that product returns to its lower-energy state, blue light is emitted.

It is a wonderfully striking demonstration.

In a sufficiently dark laboratory, the glow can appear almost unreal.

For teaching purposes I prefer to concentrate on the science rather than merely trying to create the brightest possible reaction.

A good chemiluminescence demonstration should lead to questions such as:

• Why is light produced?
• Why is it blue?
• Why does the brightness change?
• Why does the reaction eventually stop?
• What determines how quickly the light fades?
• Can we measure it?

The moment students start asking those questions, the demonstration has become an experiment.

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Why Luminol Appears in Crime Programmes

Luminol is also famous because of forensic science.

The iron associated with haemoglobin in blood can help catalyse the oxidation chemistry involved in the luminol reaction.

Investigators can therefore spray an appropriate luminol reagent over a suspected area in darkness and look for chemiluminescence.

Very small traces of blood may sometimes become visible.

Television crime programmes have understandably made this look enormously dramatic.

But the real chemistry is more interesting than the television version.

A positive glow does not automatically prove:

"There is definitely human blood here."

Other materials can interfere with or catalyse similar reactions.

In forensic science, luminol is therefore useful as a presumptive test, rather than being the final word on what a sample contains.

That distinction is also a useful lesson in experimental science.

A result can provide evidence without providing complete proof.

---

Glow Sticks Are Chemiluminescence Too

Students may have encountered chemiluminescence long before entering a laboratory.

A glow stick is essentially a small chemical reactor.

Inside are substances kept separate until the stick is bent or activated.

Once mixed, a sequence of chemical reactions transfers energy to a fluorescent dye.

The dye becomes electronically excited.

When it relaxes:

excited dye -> dye + light

Different fluorescent dyes can therefore produce different colours.

This makes glow sticks particularly interesting because they show how chemistry can be used to control the colour of emitted light.

And they provide us with an extremely simple investigation.

---

A Very Accessible Experiment: Hot and Cold Glow Sticks

Take identical glow sticks and activate them at approximately the same time.

Keep one at room temperature.

Place another, still sealed, in cold water.

Place another in comfortably warm water.

Do not use very hot water and do not cut the glow sticks open.

Now compare their brightness.

The warm glow stick will normally appear brighter.

The cold one will normally be dimmer.

But wait.

Leave them for longer and another difference becomes apparent.

The warmer glow stick tends to use up its reactants more quickly.

It may initially be bright but fade sooner.

The colder glow stick generally reacts more slowly.

It is dimmer, but the glow can persist for longer.

This is a lovely demonstration of reaction kinetics.

Higher temperature -> faster reaction -> brighter light initially -> shorter useful lifetime.

Lower temperature -> slower reaction -> dimmer light -> longer useful lifetime.

Suddenly the familiar statement that "increasing temperature increases the rate of reaction" becomes something students can actually see.

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From Demonstration to Investigation

The next stage is to stop relying on our eyes.

Can we measure the light?

A light sensor or data logger can transform the experiment.

Place the chemiluminescent source in a darkened enclosure with a light sensor positioned at a fixed distance.

Record light intensity against time.

Instead of simply saying:

"It gets dimmer."

we can produce a graph.

That immediately opens the door to much more interesting questions.

For example:

How quickly does intensity decrease?

Record intensity every few seconds or use continuous data logging.

Plot:

light intensity against time

and compare different conditions.

How does temperature affect maximum brightness?

Repeat the experiment at several controlled temperatures.

How does temperature affect duration?

Define a threshold intensity and measure how long the glow remains above it.

Is the relationship linear?

Probably not.

And that gives students another important lesson.

Natural systems do not have to produce nice straight-line graphs simply because straight lines are convenient to analyse.

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Measuring Chemiluminescence With a Camera

A camera can also be turned into a surprisingly useful scientific instrument.

Keep:

• exposure time constant;
• aperture constant;
• ISO constant;
• camera position fixed;
• background lighting constant.

Photograph the chemiluminescent reaction at regular intervals.

You can then compare image brightness.

Even simple image-analysis software can allow students to extract approximate intensity values from the photographs.

This brings together chemistry, physics and computing.

The result is no longer simply:

"The reaction glowed."

It becomes:

"The recorded light intensity decreased with time, and the rate depended upon temperature."

That is a much stronger scientific statement.

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The Luminol Demonstration in the Laboratory

For a more advanced laboratory demonstration, luminol provides the classic blue chemiluminescence experiment.

Because luminol demonstrations involve oxidising reagents and alkaline conditions, this is something I would carry out using a recognised educational procedure or commercial demonstration system, with appropriate eye protection, gloves and laboratory controls rather than improvising concentrations simply to obtain a stronger glow.

But once the reaction is running, there are several excellent investigations that can be built around it.

Rather than merely turning off the lights and watching, students might investigate:

• light intensity against time;
• the effect of temperature;
• the effect of changing concentrations using an approved procedure;
• the role of a catalyst;
• how long measurable light emission continues;
• the colour or wavelength of the emitted light.

That last possibility takes us into spectroscopy.

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Can We Measure the Colour?

To our eyes, luminol appears blue.

But "blue" is not a particularly scientific measurement.

If suitable equipment is available, the emitted light can be examined using a spectrometer.

Now we can investigate the wavelength distribution of the emitted radiation.

This creates a beautiful connection between chemistry and physics.

The reaction determines the electronic state of the product.

The electronic transition determines the energy released.

The energy determines the photon frequency.

The frequency determines the wavelength.

And the wavelength determines the colour we perceive.

So one glowing solution can connect:

chemical reactions -> molecular energy -> photons -> spectroscopy -> human vision

That is exactly the sort of connection that makes practical science so powerful.

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Chemiluminescence, Fluorescence and Phosphorescence Are Not the Same Thing

These terms are easily confused.

They all involve molecules releasing light, but the source of the excitation is different.

Fluorescence

A molecule absorbs electromagnetic radiation, often ultraviolet light.

It becomes excited and then rapidly emits light.

Turn off the exciting radiation and the fluorescence normally disappears almost immediately.

Phosphorescence

Energy is again absorbed first, but the return to the lower-energy state can be much slower.

The material can therefore continue glowing after the original light source has been removed.

That is why some "glow in the dark" materials remain visible.

Chemiluminescence

The initial energy comes from a chemical reaction.

No external ultraviolet lamp is required to excite the molecules.

The chemistry itself supplies the energy.

That difference is crucial.

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Biology Has Its Own Version: Bioluminescence

Nature discovered the same principle long before chemists did.

Fireflies, some fungi, marine organisms and many deep-sea creatures can produce light through biochemical reactions.

This is called bioluminescence.

Bioluminescence is essentially chemiluminescence occurring within a biological system.

Luciferin molecules undergo enzyme-controlled reactions involving luciferase.

The result is light.

Organisms use it for remarkably different purposes:

• attracting mates;
• communication;
• camouflage;
• attracting prey;
• startling predators;
• signalling.

Think about the evolutionary significance.

In the deep ocean, sunlight may be virtually absent.

An organism capable of producing light has suddenly gained an entirely new method of communication.

Chemistry has become biology.

---

Why Does the Reaction Eventually Go Dark?

This is another deceptively useful question.

Students sometimes think of the glow as if it were a property of the substance.

But chemiluminescence exists only while the necessary chemical reaction continues.

Reactants are being consumed.

Eventually one or more reactants becomes sufficiently depleted that the reaction rate falls.

Fewer excited molecules are being produced each second.

So fewer photons are emitted.

The glow becomes dimmer.

Eventually it disappears.

This reinforces a very basic but important chemical idea:

A reaction cannot continue indefinitely if its reactants are being consumed.

A glow stick is therefore also a tiny practical demonstration of limiting reactants.

---

Brightness and Duration Present an Interesting Trade-Off

This leads to one of my favourite aspects of the glow-stick investigation.

Suppose your goal is simply:

Make the glow stick as bright as possible.

Warm it.

But suppose your goal changes:

Make it remain visible for as long as possible.

Now cooling it may be advantageous.

Neither condition is universally "best".

The best condition depends upon what you are trying to achieve.

That is a very useful scientific and engineering lesson.

Optimization almost always requires deciding what we actually want to optimise.

Maximum brightness?

Maximum duration?

Total light output?

Minimum chemical use?

Performance at a particular temperature?

The science gives us the data.

The engineering problem determines how we use it.

---

A Possible Student Investigation

A very manageable investigation would be:

Question

How does temperature affect the intensity and duration of chemiluminescence?

Use identical sealed glow sticks from the same batch.

Test them under several temperature conditions.

Measure:

• temperature;
• initial light intensity;
• maximum light intensity;
• intensity at regular time intervals;
• time taken to fall below a chosen brightness level.

Then plot graphs of:

light intensity against time

for each temperature.

Students could then discuss:

• reaction rate;
• collision theory;
• energy transfer;
• repeatability;
• control variables;
• uncertainty;
• limitations of the measuring equipment.

Suddenly a relatively inexpensive glow stick has become an experiment touching several areas of GCSE and A-level science.

---

What Would We Need to Control?

This is where the practical becomes particularly valuable.

If we want to compare the results scientifically, we need to think about controls.

Keep constant, as far as possible:

• glow-stick type;
• manufacturing batch;
• activation method;
• time between activation and first measurement;
• distance from sensor;
• sensor orientation;
• ambient lighting;
• temperature throughout the experiment.

That last point is particularly interesting.

Putting a glow stick into water at 10 C does not necessarily mean that the reacting chemicals instantly become 10 C.

There will be a period of thermal equilibration.

That provides another opportunity to discuss the difference between the condition we think we have created and the condition actually experienced by the experimental system.

---

What About Experimental Error?

Imagine two glow sticks apparently behaving differently.

Is that because of temperature?

Perhaps.

But there could also be manufacturing variation.

One stick might contain slightly different quantities of reactants.

They might not have been activated in exactly the same way.

One could be positioned slightly closer to the sensor.

External light might interfere.

That means a better experiment would use repeats.

For each temperature:

repeat the measurement several times

and calculate a mean.

Students can then begin thinking about spread and uncertainty rather than treating every individual measurement as perfectly reliable.

Again, chemiluminescence has become much more than a colourful demonstration.

---

Why I Like Experiments Like This

One reason I enjoy practical science is that a relatively simple observation can lead surprisingly far.

You begin with:

"Look — it glows."

Five minutes later you can be discussing:

• activation energy;
• molecular collisions;
• electron energy levels;
• photons;
• spectroscopy;
• catalysts;
• rate equations;
• forensic science;
• biological evolution;
• experimental uncertainty.

That is what good practical science should do.

The experiment is not an interruption to the theory.

It creates reasons to want to understand the theory.

A student who has watched the brightness of a chemiluminescent reaction change with temperature has a much more concrete reason to care about reaction rates.

A student who has seen blue light appear without a lamp has a reason to ask what a photon actually represents.

Those questions matter.

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The Moment When the Lights Go Out

There is also something valuable about the sheer theatre of chemiluminescence.

Science teaching does not have to be dull in order to be rigorous.

Turn down the laboratory lights.

Start the reaction.

Watch blue light appear where there was darkness.

For a moment, students simply watch.

Then comes the question:

"How is it doing that?"

That is exactly the question we want.

The spectacle gets their attention.

The science keeps it.

---

Conclusion — Sometimes Chemistry Really Does Glow

Chemiluminescence is a wonderful example of why science becomes so much more interesting when we move beyond simply learning definitions.

A chemical reaction releases energy.

Some of that energy creates electronically excited molecules.

Those molecules return to lower-energy states.

Photons are released.

We see light.

But from that simple chain of events we can investigate reaction rates, temperature, catalysts, spectroscopy, forensic chemistry, biochemistry and experimental design.

We can measure the changing brightness.

We can produce graphs.

We can test hypotheses.

And we can ask whether making a reaction brighter necessarily makes it better.

So the next time somebody cracks a glow stick at a party, perhaps look at it slightly differently.

Inside that little plastic tube is a chemical reaction producing excited molecular states and releasing photons into the room.

And if we take it into the laboratory, measure what is happening and start asking questions, that glowing stick becomes a surprisingly sophisticated scientific experiment.

Sometimes the best way to illuminate a scientific idea is quite literally to make the chemistry produce the light.

 

How Do You Discover a Planet You Cannot See?

Detecting Exoplanets by Watching a Star Blink

Astronomy has a rather wonderful problem.

The objects we most want to investigate are often unimaginably far away, extremely faint and sitting beside something enormously brighter.

An exoplanet may be hundreds of light-years from Earth. It does not conveniently appear in a telescope photograph as a neat little sphere next to its star. In many cases, we discover that the planet is there without ever seeing the planet itself.

Instead, we watch the star.

And occasionally, almost imperceptibly, the star becomes slightly dimmer.

That tiny dip in brightness can be enough to reveal an entire world.

This makes exoplanet detection an excellent example of science beyond the normal school syllabus because it combines astronomy, physics, data analysis, graph interpretation and experimental design with one of the most important ideas in science:

You do not always have to see something directly to discover that it exists. You can measure the effect it has on something else.

NASA describes the transit method in essentially these terms: when a planet passes between its star and us, it blocks a small fraction of the star's light. Plotting the measured brightness against time produces a light curve, and a planetary transit appears as a dip in that curve.

And we can reproduce the basic idea on a laboratory bench.

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A Star That Apparently Blinks

Imagine watching a distant star continuously.

For most of the time its measured brightness remains approximately constant.

Then this happens:

Normal brightness -> slight fall -> minimum brightness -> rise -> normal brightness

Nothing necessarily happened to the star itself.

Instead, a planet may have crossed the face of it.

From Earth, we see something rather like a very small eclipse.

The crucial word is small.

A planet is normally considerably smaller than its parent star, so only a fraction of the star's light is removed. Detecting exoplanets therefore depends on making extremely precise measurements and deciding whether a tiny change is genuine or merely noise.

That immediately makes this much more interesting than simply moving a ball in front of a lamp.

The real experiment is about measurement.

Can we detect the change?

Can we distinguish it from random fluctuations?

Can we extract information about our "planet" from the graph?

---

Building a Model Exoplanet System

The simplest version needs surprisingly little equipment.

You need:

• a bright lamp or LED source;
• preferably a translucent diffuser to create a circular illuminated "star";
• several opaque balls or discs of different diameters;
• a light sensor, lux sensor or data logger;
• some way of moving the model planet steadily across the star;
• software capable of recording light intensity against time.

A data logger is particularly useful because it turns the demonstration into something very close to the way astronomical observations are actually treated: a sequence of brightness measurements taken over time.

Why I Would Not Use a Bare LED

There is a useful experimental-design point here.

A bare LED is very nearly a small point source. Put an opaque object directly in front of it and you may simply block most or all of its light.

That is not a very good model of a planet crossing a star.

A better arrangement is to illuminate a circular translucent screen from behind. The whole circle then becomes the visible surface of our model star.

Now a small disc passing across it blocks only part of the illuminated area.

That gives us something much closer to a genuine transit.

---

First Experiment: Find the Planet

Begin with the detector recording a steady brightness.

Do nothing for perhaps five or ten seconds.

Then move the model planet steadily across the illuminated disc.

Continue recording for another five or ten seconds after it has left.

When the data are plotted, students should see something resembling:

Light
intensity

100 |____________             ____________
 98 |            \           /
 96 |             \_________/
 94 |
    +------------------------------------> time

We have created our first transit light curve.

The flat section before the transit represents the normal brightness of the star.

The falling section represents the planet beginning to move across the stellar disc.

The lower section occurs while much of the planet is in front of the star.

The brightness then rises again as the planet moves away.

The planet itself has never been detected by the light sensor.

We detected its shadow.

That is a deceptively profound scientific idea.

---

Can the Light Curve Tell Us How Big the Planet Is?

Now we can start doing some mathematics.

Suppose the star has radius Rs and the planet has radius Rp.

Ignoring complications such as the star being brighter in its centre than around its edge, the approximate fraction of light blocked is:

Transit depth = (Rp / Rs)^2

This occurs because the amount of light blocked depends approximately on the ratio of the areas, not simply the diameters.

Area is proportional to radius squared.

For example, suppose our model star has a diameter of 15 cm and our model planet has a diameter of 3 cm.

The radius ratio is:

3 / 15 = 0.20

So:

Transit depth = 0.20^2

Transit depth = 0.04

The expected brightness decrease is therefore about:

4%

If the normal sensor reading were 1,000 arbitrary units, we might expect it to fall to roughly 960 during the central part of the transit.

Suddenly a small dip on a graph contains physical information about an object we cannot see.

NASA uses exactly this principle with real transit observations: if astronomers know the size of the star, the depth of the transit helps them determine the radius of the planet.

---

Investigation 1: Bigger Planet, Bigger Dip

Now repeat the experiment with different-sized balls or discs.

Perhaps use:

• 1 cm;
• 2 cm;
• 3 cm;
• 4 cm;
• 5 cm.

Keep everything else approximately constant.

Students can record:

Planet diameter	Minimum brightness	Percentage brightness decrease
1 cm
2 cm
3 cm
4 cm
5 cm

They should discover that increasing the planet's diameter does not produce a simply proportional increase in the light lost.

Doubling the radius means approximately four times the area.

That gives a lovely connection between familiar school mathematics and modern observational astronomy.

---

Investigation 2: What Does Orbital Speed Do?

Use the same planet but move it across the star at different speeds.

Importantly, if the planet follows the same path, the depth of the transit should remain broadly similar.

What changes is its duration.

A slowly moving planet produces a wider dip.

A fast-moving planet produces a narrower one.

This introduces another important feature of astronomical light curves:

The shape of a graph can tell us more than the minimum value does.

Astronomers use the timing of transits to learn about planetary systems. Repeated transits reveal a planet's orbital period, while transit duration and shape contribute further information about the system's geometry.

---

Investigation 3: Central or Grazing Transit?

This is one of my favourite variations because it shows why the graph needs interpreting rather than simply reading.

First send the planet straight across the centre of the star.

Then repeat the experiment with the planet just clipping the upper edge.

The second is a grazing transit.

The planet never completely crosses the stellar disc, so it never blocks as much light.

The resulting light curve may therefore be:

• shallower;
• shorter;
• differently shaped.

Now ask:

Did we use a smaller planet?

No.

But if we looked only at the depth of the graph without considering the geometry, we might draw the wrong conclusion.

This is real science.

Measurements are rarely interpreted in isolation. Scientists construct models and ask which combination of variables could have generated the data.

---

Investigation 4: Add Measurement Noise

Real astronomical data do not form beautifully smooth textbook curves.

So perhaps ours should not either.

Try introducing small disturbances.

Move somebody near the apparatus.

Allow a little ambient light into the room.

Introduce a tiny variation in lamp brightness.

Move the detector slightly.

The graph becomes noisier.

Now hide a transit somewhere within the results and ask students to identify it.

This changes the question from:

"Can you see the dip?"

to:

"Are you sufficiently confident that this dip represents a planet?"

That is much closer to the real problem.

NASA's own citizen-science projects invite people to examine actual stellar light curves for the tell-tale patterns of planetary transits.

---

One Dip Is Not Necessarily a Planet

This is an important addition to the experiment.

Suppose our star becomes slightly dimmer once.

Have we discovered a planet?

Not necessarily.

There could be other explanations.

Astronomers therefore look for evidence that supports the planetary interpretation — particularly repeated transits occurring at regular intervals.

If a similar dip appears every 5.2 days, for example, that becomes much more interesting.

The interval gives us the orbital period.

Our laboratory version could mimic this by mounting the planet on a rotating arm so that it repeatedly passes in front of the star.

Students could be given a long data trace containing several transits and asked:

What is the orbital period of this planet?

Measure the time from one transit centre to the next.

If dips occur at:

10 s, 25 s, 40 s, 55 s...

the model orbital period is approximately:

15 seconds

The same reasoning can be applied to astronomical observations collected over days, months or years.

---

Could There Be More Than One Planet?

Now things become considerably more entertaining.

Introduce two different-sized planets travelling with different periods.

One produces a deep dip every 20 seconds.

The other produces a shallower dip every 13 seconds.

Record for long enough and the light curve becomes much more complicated.

Students then have to identify two repeating patterns.

NASA notes that light curves become more complicated when several planets transit the same star, but astronomers can disentangle the different signals.

You have effectively turned a lamp, two balls and a light sensor into a simplified planetary-system discovery problem.

---

From a School Experiment to TESS

This is where I think demonstrations like this become especially valuable.

We have not merely constructed an analogy for something astronomers used to do.

The basic technique remains enormously important.

NASA's TESS — the Transiting Exoplanet Survey Satellite — searches stars for periodic changes in brightness associated with planetary transits. NASA reported in May 2026 that TESS had identified more than 7,900 candidates and 885 confirmed exoplanets at that point.

There is something rather satisfying about showing a student a graph generated using a ball and a light sensor and then explaining:

Space telescopes are looking for essentially the same signature.

The instrumentation is vastly more sophisticated.

The mathematics is much more sophisticated.

The data processing is vastly more sophisticated.

But the underlying observation is recognisable.

Something crossed the star.

The star became dimmer.

Measure that change carefully enough and you may have discovered another world.

---

And a Transit Can Tell Us Even More

The story does not end with finding the planet.

Modern astronomers can study starlight passing through a planet's atmosphere during a transit.

Different gases absorb particular wavelengths of light.

Instead of measuring only:

How much light disappeared?

astronomers can ask:

Which wavelengths disappeared slightly more than others?

That opens the door to studying exoplanet atmospheres.

NASA's James Webb Space Telescope, for example, records extremely detailed transit observations. Its measurements of LHS 475 b included more than a thousand individual brightness measurements over an observation lasting almost three hours.

Our laboratory experiment has therefore taken us from a simple shadow all the way to spectroscopy of the atmospheres of planets orbiting other stars.

---

Can Students Work With Real Data?

Yes — and this would make an excellent extension.

Once students understand the model experiment, show them a genuine exoplanet light curve and ask them to identify:

• normal stellar brightness;
• start of transit;
• minimum brightness;
• end of transit;
• transit depth;
• transit duration;
• uncertainty and scatter.

They can then compare the real curve with the one obtained experimentally.

NASA's Planet Hunters TESS citizen-science project goes a stage further: participants can examine actual TESS light curves looking for possible transits. No specialist astronomy knowledge is required to begin.

NASA also runs Exoplanet Watch, where observers can collect telescope images and turn them into transit light curves using its EXOTIC analysis software.

That creates an extraordinary progression:

Model planet -> model light curve -> real astronomical data -> citizen science.

---

The Experiment Is Really About Evidence

There is a much broader lesson here than exoplanets.

We often teach science using objects that can conveniently be seen.

Here is the cell.

Here is the circuit.

Here is the spring.

Here is the reaction.

But much of science deals with things that cannot be observed directly.

We discovered the internal structure of atoms from scattering.

We infer the presence of dark matter from gravitational effects.

We determine the composition of distant stars from their spectra.

We study Earth's interior using seismic waves.

And we discover planets by watching stars become fractionally dimmer.

The ability to reason from an effect to an unseen cause is one of the most powerful forms of scientific thinking.

---

A Small Shadow From Another World

What I particularly like about the exoplanet transit experiment is that it begins with equipment that looks almost trivial.

A lamp.

A ball.

A sensor.

A graph.

But the question behind it is enormous:

Are there planets orbiting other stars?

For centuries that was largely speculation.

Today we can measure them.

A tiny repeated decrease in a distant star's brightness can tell us that a planet exists, estimate how large it is, determine how frequently it orbits and, with considerably more sophisticated observations, begin investigating its atmosphere.

So perhaps the most important lesson is not really about exoplanets at all.

It is about what scientists mean by evidence.

Sometimes discovery does not begin by seeing the thing you are searching for.

Sometimes it begins by noticing that something else has changed.

And asking why.

---

Practical challenge

Try building your own transit experiment.

Start with one planet and see whether you can produce a convincing light curve.

Then make it progressively harder:

different planet sizes -> different speeds -> grazing transits -> measurement noise -> repeated transits -> two planets

Finally, compare your graph with a genuine exoplanet light curve.

You may be surprised by how recognisable it looks.