Sunday, 20 September 2026

What Should a Student Do When They Are Predicted a D but Need a B?

 


What Should a Student Do When They Are Predicted a D but Need a B?

The route from a D to a B usually begins by finding out where the marks are actually disappearing.

Being predicted a D when you need a B can feel alarming.

Perhaps the B is needed for a university course. Perhaps it is part of a sixth-form requirement, an apprenticeship application or simply the grade a student believes they ought to be capable of achieving.

The understandable reaction is often:

"I need to revise much harder."

That may be true.

But it is not usually the best place to start.

If a student is currently performing at D grade, the first question should not be:

"How many more hours can I revise?"

It should be:

"Why am I currently losing enough marks to get a D?"

That distinction matters.

A student may be losing marks because they do not understand several major topics.

But they may also be losing marks because they:

  • misread questions;

  • forget definitions;

  • cannot recall key formulae;

  • abandon difficult questions too quickly;

  • make basic algebraic mistakes;

  • fail to show working;

  • run out of time;

  • write too little;

  • write a great deal without answering the question;

  • know the subject but cannot apply it to unfamiliar situations.

These are very different problems.

And they require very different solutions.

A Predicted Grade Is a Starting Point, Not a Diagnosis

A predicted grade tells us roughly where a student is performing.

It does not tell us why.

Two students might both receive a D in an examination while having completely different difficulties.

One might know most of the course reasonably well but lose enormous numbers of marks through poor examination technique.

Another might be excellent on half the syllabus but have serious gaps in the other half.

A third might understand material when it is explained but be unable to recall it independently a week later.

A fourth might know a surprising amount but work so slowly that they never reach the final quarter of the paper.

Writing D at the top of each of those students' papers tells me almost nothing about what I should teach them next.

That is why one of the first things I want to see when helping a student improve is not simply the grade.

I want to see the paper.

Where did the marks go?

That is much more useful.

Stop Thinking About Grades for a Moment

This sounds slightly strange when the entire objective is to improve a grade, but sometimes we need to stop thinking about grades and start thinking about marks.

Imagine that a particular examination requires approximately 50 marks for a D and approximately 70 marks for a B.

The exact boundaries will vary from year to year, of course, but the principle remains the same.

The problem is no longer:

"How do I turn a D-grade student into a B-grade student?"

It becomes:

"Where can we find another 20 marks?"

That is a much more useful question.

Perhaps five marks are being lost through weak definitions.

Perhaps another five disappear because the student does not show enough working in calculations.

Perhaps six could be recovered from two topics they have never properly understood.

Perhaps another four are disappearing because questions are being misread.

Suddenly the apparently enormous D-to-B leap begins to look like a collection of smaller, more manageable problems.

That is how I prefer to approach grade improvement.

Begin With a Proper Diagnostic Assessment

One of the least efficient things a struggling student can do is revise everything equally.

If you have ten weeks available, spending ten weeks going through the entire textbook from page one is unlikely to be the best strategy.

Some topics will already be secure.

Some will need a little polishing.

Others may represent major weaknesses.

The first job is therefore to construct a weak-topic map.

I often think of topics as falling into four broad groups.

Secure:
The student can answer straightforward and unfamiliar questions reliably.

Nearly secure:
The student understands the topic but makes occasional mistakes or struggles with harder applications.

Weak:
The student recognises the topic but cannot answer questions independently.

Missing:
The student has little usable understanding of the topic at all.

That map is far more valuable than simply saying:

"I'm not very good at Physics."

Or:

"I find Maths difficult."

Those statements are too vague to act upon.

Instead, we might discover:

"I am confident with simultaneous equations and quadratics, but I struggle with trigonometric graphs, vectors and probability."

Now we have something we can work with.

Not All Weak Topics Are Equally Important

Once weaknesses have been identified, they need to be prioritised.

Students sometimes make the mistake of spending enormous amounts of time on the hardest topic in the syllabus simply because it frightens them.

That may not be the best use of limited revision time.

Suppose a student could spend three hours mastering a topic that might contribute two marks to an examination.

Meanwhile, there are three moderately difficult topics worth perhaps six or eight marks each that could be improved relatively quickly.

The second option is probably the better investment.

That does not mean avoiding difficult material permanently.

It means thinking strategically.

When the target is moving from D towards B, I am often interested first in what I call recoverable marks.

These are marks the student could realistically begin collecting with focused work.

They may come from:

  • common question types;

  • key definitions;

  • standard calculations;

  • frequently assessed processes;

  • graphs;

  • data interpretation;

  • straightforward application questions;

  • required terminology;

  • showing complete working.

A student does not necessarily need to become brilliant at everything before their grade begins to rise.

They need to become more reliable at collecting marks.

The Most Important Question: Knowledge or Application?

This is one of the biggest distinctions I make when working with students.

Does the student not know the material, or do they know it but fail to use it successfully in examination questions?

Consider an A-level Biology student.

They may be able to describe the process of natural selection perfectly when asked directly.

But present the idea through an unfamiliar example involving antibiotic resistance, pesticide resistance or changing environmental conditions and suddenly the answer becomes confused.

The problem is not simply missing knowledge.

It is application.

The same happens in Mathematics.

A student may be perfectly capable of differentiating:

y = 3x^3 + 4x^2 - 7x + 2

But give them a problem asking them to determine the maximum volume of a container, and suddenly they cannot see that differentiation is required.

Again, the problem is not necessarily technique.

It is recognising the technique inside an unfamiliar problem.

Physics produces the same difficulty.

A student may know:

v = u + at

but still struggle because they cannot decide whether that equation is appropriate for the situation described.

That is why simply reading notes repeatedly can give students a dangerously misleading impression of progress.

Recognition is not the same as recall.

Recall is not the same as application.

And application is what many examination questions actually test.

Use Examination Papers as Diagnostic Tools, Not Just Tests

Past papers are often treated as something students should save until immediately before the examination.

I think that wastes one of their most useful functions.

Past questions are diagnostic instruments.

They show us exactly what happens when knowledge has to be turned into marks.

Suppose a student attempts 20 questions.

Rather than simply adding up the score, I want to know why each lost mark disappeared.

Was it:

K — Knowledge missing?

U — Understanding weak?

A — Application problem?

R — Question misread?

M — Mathematical error?

T — Terminology inaccurate?

E — Examination technique?

C — Careless mistake?

After several papers, patterns begin to emerge.

That can be extraordinarily revealing.

A student convinced that they "don't know anything" may discover that knowledge is not actually their main problem.

Perhaps most of the lost marks are caused by interpretation and technique.

Equally, a student who believes they merely make "silly mistakes" may discover that there are genuine gaps in understanding that need addressing.

The evidence matters.

Do Not Confuse Revision With Learning

This distinction is particularly important for a student trying to make a significant grade improvement.

Highlighting notes is revision.

Reading a textbook is revision.

Watching a video can be revision.

But none of those activities guarantees learning.

The test is what happens when the support disappears.

Close the book.

Remove the video.

Turn the notes face down.

Now explain the idea.

Answer the question.

Draw the diagram.

Complete the calculation.

Define the term.

If you cannot do it without looking, it is not yet secure.

One practical technique I use with students is very simple.

After we have worked through a question together, I change the numbers or alter the context and ask them to do another one independently.

That immediately tells me whether they have understood the method or merely followed my explanation.

Fix Foundations Before Chasing the Hardest Questions

Students aiming for higher grades understandably want to practise high-grade questions.

That is useful — once the foundations are sufficiently reliable.

But trying to solve extremely difficult problems while routinely dropping straightforward marks can be counterproductive.

A student may spend 20 minutes wrestling with a challenging six-mark question while elsewhere in the paper they have lost:

one mark for a missing unit;

one mark for an incorrect definition;

two marks for not showing working;

one mark through a sign error;

one mark because they forgot to answer part (b).

That is six marks lost without encountering anything intellectually difficult.

This is why improving grades sometimes involves surprisingly unglamorous work.

We make basic procedures reliable.

We practise definitions.

We learn to identify what a question is asking.

We show working.

We check units.

We answer every part.

We learn when to move on.

Those habits accumulate marks.

Examination Technique Can Be Worth an Entire Grade Boundary

Students sometimes regard examination technique as something superficial.

It is not.

An examination is a particular form of communication.

The student has to demonstrate their knowledge in a way that allows an examiner to award marks.

A student might possess good subject knowledge and still underperform because they have not learned how to communicate it effectively under examination conditions.

For example, command words matter.

State does not require an essay.

Explain usually requires a chain of reasoning.

Calculate requires working.

Compare usually requires referring to both things being compared.

Evaluate normally requires a judgement supported by evidence.

Teaching students to respond properly to those instructions is not teaching them to "play the exam system".

It is teaching them to answer the question they have actually been asked.

Look at How Much Is Being Written — and Whether It Earns Marks

In essay-based subjects, one problem I frequently see is students equating quantity with quality.

They write extensively.

But the answer may contain repetition, description without analysis or material that does not address the question.

Writing another page does not necessarily earn another mark.

At the opposite extreme, some students know considerably more than their answer reveals because they write far too little.

The aim is not simply to write more or less.

It is to increase mark density.

How much of what is written is actually doing something useful?

A strong paragraph should have a purpose.

A calculation should have a logical progression.

A scientific explanation should connect cause and effect.

Again, the question becomes:

Where are the marks disappearing?

Create a Marks-Recovery Plan

Once the problems have been diagnosed, improvement becomes much more systematic.

Imagine a student needs approximately another 20 marks.

We might create a plan such as:

+5 marks: strengthen two weak high-frequency topics.

+4 marks: improve definitions and technical vocabulary.

+3 marks: show complete mathematical working.

+3 marks: improve data and graph interpretation.

+3 marks: reduce question-reading errors.

+2 marks: improve time management so the final questions are attempted.

Of course, nobody can guarantee those precise gains.

But thinking this way changes the psychology of the problem.

We are no longer waiting for the student somehow to "become a B-grade student".

We are systematically looking for marks.

Improvement Usually Comes in Steps

Parents and students understandably want to see quick evidence that tuition or revision is working.

But educational progress is rarely a smooth upward line.

A student might score:

54%

then 57%,

then 55%,

then 61%,

then 63%.

The temporary drop from 57% to 55% does not necessarily mean anything has gone wrong.

The second paper may simply have tested different material.

What matters is the trend and, even more importantly, the changing nature of the mistakes.

I am particularly interested when mistakes move from:

"I had no idea how to start this."

to:

"I knew how to do it but made an algebra mistake."

That may still result in a lost mark.

But educationally, it represents considerable progress.

The next stage is making the technique reliable.

Why Confidence Often Improves After Performance

We frequently hear that students need more confidence.

That is true.

But telling someone to "be more confident" is rarely useful.

Confidence often develops from evidence.

A student who repeatedly could not answer a particular type of question begins to solve it successfully.

Then they solve another.

Then they recognise it in a past paper.

Then they solve it under timed conditions.

Eventually the student begins to think:

"I can actually do this."

That confidence is valuable because it has been earned.

The student no longer needs to persuade themselves that they might succeed.

They have evidence that they can.

How Long Does It Take to Move From a D to a B?

There is no responsible answer that applies to everyone.

It depends on why the student currently has a D.

If a capable student has poor examination technique and several repairable gaps, improvement can sometimes happen relatively quickly.

If the student has substantial weaknesses stretching back several years, more rebuilding may be needed.

Other factors matter too:

  • how much time remains before the examination;

  • how regularly the student works;

  • whether homework is completed;

  • whether earlier knowledge is secure;

  • how demanding the target examination is;

  • how effectively independent study time is used.

The important point is to start early enough to allow a cycle of:

diagnose -> teach -> practise -> test -> analyse -> improve

and then repeat it.

That cycle is much more powerful than:

read everything -> panic -> do one past paper -> discover problems three days before the examination.

A Miraculous Revision Weekend Is Not a Strategy

Every year students hope that one heroic weekend of revision will transform months of inconsistent learning.

Occasionally someone does make remarkable short-term progress.

But it is not a sensible plan.

Moving from D to B normally comes from dozens of small improvements.

Learning three definitions today.

Fixing a misunderstanding tomorrow.

Completing ten algebra questions on Thursday.

Correcting them on Friday.

Attempting an examination question on Saturday.

Returning to it again the following week.

None of these activities appears dramatic.

Collectively, they can completely change an examination result.

What I Look for When Teaching a Student Who Needs to Improve

When I work with a student in this situation, I am not simply thinking:

"What topic shall we cover today?"

I am asking:

What is preventing this student from collecting marks?

Sometimes that means reteaching a topic from first principles.

Sometimes it means challenging the student with harder questions.

Sometimes we discover that they know far more than their school assessment suggests.

Sometimes we discover foundational weaknesses that need rebuilding.

Sometimes the biggest improvement comes from teaching them to slow down and read the question.

At other times, the student needs the opposite: they must learn when to stop struggling with one question and move on.

Effective tuition is therefore not just extra teaching time.

It should be diagnostic.

The lesson should respond to what the student actually needs.

Parents Can Help — Without Becoming the Teacher

Parents often ask what they can do.

One of the most useful things is to encourage consistency rather than panic.

Instead of asking:

"Have you revised?"

it may be more useful to ask:

"What did you practise today?"

Or:

"What can you do now that you couldn't do last week?"

Or:

"Which topic are you going to improve next?"

Those questions focus attention on progress and actions rather than simply hours spent at a desk.

A student who says they revised for three hours may have achieved very little.

A student who spent 40 focused minutes correcting a genuine weakness may have achieved far more.

From D to B Means Becoming More Reliable

There is one final point that is easy to miss.

Students sometimes imagine that a B-grade student knows completely different material from a D-grade student.

Sometimes they do.

But often the difference is reliability.

The stronger student:

gets more of the straightforward questions right;

makes fewer avoidable mistakes;

recognises familiar methods more quickly;

uses terminology more accurately;

shows enough working;

manages time more effectively;

and collects marks consistently across the paper.

That is encouraging because reliability can be trained.

The Real Question Is Not "Can I Get a B?"

A student predicted a D may look at a B and see an enormous gap.

I prefer to break that gap apart.

Which topics are weak?

Which mistakes repeat?

Which examination skills are missing?

Which marks are realistically recoverable?

What should we fix first?

What can the student practise independently?

How will we know whether it has worked?

Those are answerable questions.

And once those questions begin to be answered, something important happens.

The grade becomes less mysterious.

The student is no longer simply hoping for a B.

They are building one mark by mark.

The route from a D to a B rarely begins with working twice as many hours. It begins by discovering where the marks are disappearing — and then systematically getting them back.

Philip M Russell Ltd — Private Tuition, Hemel Hempstead and Online

#PrivateTuition #GCSE #ALevel #ExamPreparation #Revision #StudySkills #ExamTechnique #MathsTuition #ScienceTuition #StudentSuccess #Education #Tutoring

Saturday, 19 September 2026

My Music Rest Has Disappeared — Turning the Pergamon into a Digital Music Library

 


My Music Rest Has Disappeared — Turning the Pergamon into a Digital Music Library

The biggest change I made to my organ wasn't musical at all — I removed the music rest.

When most people look at a large electronic organ such as my Wersi OAX Pergamon, their attention naturally goes to the keyboards, pedals, stops, controls and sounds.

That is understandable. After all, those are the things that actually make the music.

But one of the most useful changes I have made to my own Pergamon has nothing directly to do with the sound of the instrument.

I have effectively removed the conventional music-rest arrangement and replaced it with a large computer screen.

Instead of reaching for folders filled with printed music, loose sheets and photocopies, I can now call up much of my music electronically.

For me, this is not technology for the sake of technology. It is an example of something I enjoy doing in many areas: looking at the way something has traditionally been done, identifying the parts that cause inconvenience, and asking whether there might be a better solution.

In this case, the question was very simple:

Why should an instrument capable of producing extraordinarily sophisticated digital sound still depend entirely on pieces of paper sitting on a wooden or plastic music rest?

The Traditional Music Rest Has Worked for Centuries

There is, of course, nothing inherently wrong with printed music.

It works.

You put the music on the stand, open the book at the correct page and start playing.

There are no operating systems to update, no cables to connect and no possibility of the screen suddenly deciding that it would rather do something else.

Printed music has another enormous advantage: familiarity.

Musicians have been reading from paper for generations. You can make a pencil mark beside a difficult passage, circle a fingering, add a registration note or put a great large warning mark beside the bar where you repeatedly make the same mistake.

A well-used piece of music almost becomes part of the history of learning the piece.

So my aim was never to prove that digital music is universally better than paper.

It was to see whether digital technology could remove some of the frustrations that increasingly appear when a collection of music grows.

The Problem Starts When the Music Collection Gets Bigger

One piece of music is easy to manage.

Ten pieces are not difficult either.

But over many years it is very easy to accumulate hundreds — potentially thousands — of pieces.

There may be:

  • individual sheets;

  • music books;

  • photocopies;

  • downloaded PDFs;

  • arrangements in different keys;

  • different editions of the same piece;

  • music for organ;

  • music for piano;

  • orchestral scores;

  • theatre-organ arrangements;

  • church music;

  • popular music;

  • teaching material;

  • pieces being learned;

  • pieces already mastered;

  • and pieces that I might want to play again one day.

Eventually the problem is not owning the music.

The problem is finding it.

That is where a digital library begins to become very attractive.

Hundreds of Pieces Can Be Available Almost Instantly

With music stored electronically, the physical size of the collection stops being particularly important.

A folder containing 500 PDF scores takes up practically no more physical space beside the organ than a folder containing five.

More importantly, those scores can be organised and searched.

Instead of thinking:

"I know I have that arrangement somewhere..."

I can search for the title, composer or filename and bring it onto the screen.

That completely changes the experience of casually choosing something to play.

Suppose I suddenly decide I would like to play a particular film theme, hymn, theatre-organ piece or classical work.

With a paper library, I might have to leave the instrument, find the correct shelf, search through several books and perhaps discover that the music I want is somewhere else entirely.

With the digital system, the search can take seconds.

That encourages experimentation because there is much less friction between thinking of a piece and actually playing it.

A Large Screen Makes an Enormous Difference

Simply replacing paper with a small tablet is not necessarily an improvement.

Music notation contains a great deal of information.

There are notes, accidentals, dynamics, articulation markings, fingering, pedal markings, chord symbols, registration changes and sometimes several staves to follow simultaneously.

That is why I wanted a large screen rather than simply balancing a small tablet where the music rest used to be.

The larger display allows the notation to remain comfortably readable.

And unlike a printed book, a digital score can be enlarged.

That is particularly useful with music that has:

  • been scanned from an older source;

  • originally been printed in a small format;

  • complicated notation;

  • several staves;

  • detailed registration instructions;

  • or awkwardly crowded pages.

A difficult passage can potentially be enlarged temporarily and examined much more closely.

For anyone whose eyesight is not quite what it was decades ago, that alone can be a substantial advantage.

The Page Is No Longer Necessarily Fixed

Printed music has one rather obvious limitation.

The size of the notation was decided when the page was printed.

Digital music does not have to work like that.

Depending upon the software being used, it may be possible to:

  • zoom into the page;

  • display a complete page;

  • display two pages side by side;

  • crop unnecessary margins;

  • rotate a page;

  • change the screen brightness;

  • or move rapidly between different sections.

That flexibility can be surprisingly useful.

For example, when learning a difficult section I may care far more about clearly seeing four particular bars than seeing the whole page.

Once the section becomes familiar, I can return to a normal view.

Digital presentation therefore has the potential to change depending upon what I am actually trying to achieve.

No More Loose Sheets

Anyone who has used photocopied or downloaded music will know the problem.

One piece might consist of six separate sheets.

Those sheets then have to be placed in order, kept together and somehow prevented from sliding, falling or becoming mixed with something else.

And, naturally, the sheet you actually need is often the one that has disappeared.

Digital files remove that particular problem completely.

Page 5 cannot accidentally migrate into a different folder.

A gust of wind cannot send page 3 across the room.

And the piece does not suddenly become unplayable because someone has moved one sheet to another pile.

There is something wonderfully satisfying about pressing a few controls and having the complete score appear exactly where it should be.

Organisation Becomes Far More Powerful

A digital music collection does not have to be organised in only one way.

That is another important difference.

A physical book has to sit on one shelf.

A digital file can effectively belong to several categories.

I might organise music by:

  • composer;

  • musical style;

  • difficulty;

  • instrument;

  • performance;

  • practice;

  • church music;

  • theatre organ;

  • classical music;

  • film music;

  • Christmas;

  • teaching;

  • or simply favourites.

I can also use filenames intelligently.

A consistent naming system makes an enormous difference once a digital library becomes large.

For example, rather than keeping files with names such as:

scan000347.pdf

it is much more useful to have something such as:

Bach - Jesu Joy of Mans Desiring.pdf

The technology is only useful if the information itself is organised properly.

This is something I encounter in many areas of computing: storing information is easy; being able to retrieve it efficiently is the real challenge.

Annotated PDFs Bring Back Some of the Advantages of Pencil

One criticism of electronic music is perfectly reasonable:

"I like writing on my score."

So do I.

But electronic documents do not necessarily mean giving up annotation.

Many PDF systems allow notes, highlighting, symbols and handwritten markings to be added electronically.

That could include:

  • fingering;

  • registration changes;

  • reminders about tempo;

  • notes about articulation;

  • rehearsal markings;

  • difficult bars;

  • pedal instructions;

  • or reminders to change a sound or accompaniment setting.

In some respects this can be more flexible than pencil.

A digital annotation can be moved, changed or removed without gradually turning the page into an indecipherable collection of old markings.

It also raises another useful possibility.

You could keep an untouched original score and a separate working copy containing your personal markings.

More Than Just the Score Can Sit Beside the Organ

This is where the system starts becoming more interesting than simply replacing a sheet of paper.

A computer display is not restricted to displaying notation.

Suppose I am learning a piece.

Alongside the music I could potentially have immediate access to:

  • a professional recording;

  • a backing track;

  • a MIDI file;

  • a rehearsal recording;

  • notes about registration;

  • information about the composer;

  • alternative arrangements;

  • lyrics;

  • performance notes;

  • or even a video of somebody else playing the piece.

That can turn the organ console into much more of a complete learning environment.

For example, if I am unsure about the intended phrasing in a passage, I can listen to a reference performance.

If I am experimenting with registration, I can record different versions and compare them.

If I am working on a piece for video production, I might also have the accompanying film material available nearby.

The distinction between music stand, computer, recording system and creative workstation begins to disappear.

Electronic Page Turning Could Solve One of Music's Oldest Problems

(The same page turner I use but on the white OAX 800)

There is one problem that musicians have been battling since long before computers existed.

Turning the page.

You reach the bottom of the page.

Both hands are busy.

Your feet may also be busy.

And somehow the page needs to move.

Organists are particularly familiar with this problem because both hands and both feet can be occupied simultaneously.

Electronic music opens the possibility of using:

  • a foot pedal;

  • a programmable button;

  • a touchscreen control;

  • a wireless controller;

  • or another switching system

to turn pages electronically.

The ideal system would allow the page to change without interrupting the performance at all.

I think this is one of those areas where digital technology is not merely copying paper.

It can genuinely improve upon it.

There Are Disadvantages

It would be very easy to write an article such as this and claim that digital music is obviously the future and everyone should throw away their music books.

I do not believe that.

Digital systems introduce their own problems.

Computers Can Go Wrong

Paper music has an outstanding reliability record.

It does not crash.

It does not install an update immediately before you want to play.

It does not forget which monitor it is supposed to be using.

A digital system therefore needs to be reliable, particularly if it is going to be used for performance rather than simply practice.

Screens Need Power

A printed score keeps working during a power cut.

Admittedly, my Pergamon itself becomes a little less useful if the electricity disappears, but the principle still matters for portable digital music systems.

File Organisation Requires Discipline

A thousand badly named PDF files are not a library.

They are a digital cupboard full of paper.

Files need sensible names, folders and backups.

Scans Vary in Quality

Older music may have been scanned poorly.

Pages might be crooked, dark, incomplete or difficult to read.

Some material is much more pleasant to use as the original printed edition.

Copyright Still Matters

The fact that music can be copied electronically does not mean that everything may legally be copied, shared or distributed.

Digital storage does not remove normal copyright responsibilities.

And Paper Still Feels Different

There is also something that is much harder to quantify.

A good music book is pleasant to use.

You can physically see how far you are through a piece.

You can flick rapidly backwards and forwards.

You develop a memory of where something sits on the page.

An old score can also contain a history.

There may be pencil marks made while learning it twenty years ago.

A particular book may remind you of a teacher, an examination, a concert or another period of your life.

Digital files are enormously convenient.

But convenience is not the only thing that matters.

I certainly do not intend to dispose of my printed music collection.

Instead, I see the digital system as another way of accessing it.

It Is Really an Example of Problem-Solving

The part of this project that interests me most is not actually the screen.

It is the thinking behind it.

I had a conventional arrangement.

I identified several inconveniences:

  • limited space;

  • increasing amounts of music;

  • small notation;

  • awkward page turning;

  • loose sheets;

  • and difficulty finding things quickly.

Then I asked what existing technology might do better.

That is the sort of experimentation I enjoy.

It is the same approach I use in photography, video production, science teaching, electronics and computing.

You do not necessarily need to accept equipment exactly as it arrives from the manufacturer.

Sometimes a piece of equipment becomes much more useful when it is adapted to the way you actually work.

Technology Should Disappear Into the Creative Process

The best technology is often the technology you eventually stop noticing.

If I have to spend ten minutes fighting with the computer every time I want to play something, then my digital music library has failed.

The objective is exactly the opposite.

I want to sit at the Pergamon, choose a piece, bring it onto the screen and start making music.

The screen should not become the centre of attention.

The organ should not become the centre of attention either.

Ultimately, the music is what matters.

That is an important principle as more technology enters music creation.

We now have extraordinary electronic instruments, virtual synthesisers, DAWs, digital scores, software instruments, recording systems and increasingly AI-assisted tools.

All of them can be useful.

But they are tools.

The purpose is not to operate impressive technology.

The purpose is to make something worth listening to.

The Biggest Change Wasn't Musical

Replacing the traditional music rest on my Wersi Pergamon with a large digital display may appear to be a fairly simple alteration.

But it has changed the way I think about my music collection.

Instead of music being something stored in books and folders elsewhere in the room, it can become an immediately accessible digital library sitting directly in front of the instrument.

Thousands of pages can occupy virtually no physical space.

Notation can be enlarged.

Scores can be searched.

PDFs can be annotated.

Recordings and backing tracks can sit alongside them.

Pages may eventually be turned without removing a hand from the keyboard.

And yet the old printed score remains valuable.

For me, that is the important conclusion.

The aim is not to replace traditional music simply because technology exists. It is to use technology where it genuinely makes playing, learning and creating music easier.

My music rest may have disappeared.

The music most certainly has not.

Friday, 18 September 2026

Can AI Help Create Better Photography, Video and Music — Without Replacing the Creative Process?

 

Can AI Help Create Better Photography, Video and Music — Without Replacing the Creative Process?

AI can accelerate creative work — but somebody still has to know what “good” looks and sounds like.

Artificial intelligence is rapidly finding its way into photography, video production, music, graphic design and almost every other creative field.

That inevitably leads to a rather dramatic question:

Will AI replace the photographer, filmmaker, editor, musician or producer?

I think that is the wrong question.

A much more useful question is:

Can AI help a creative person produce better work, more efficiently, without allowing the technology to take over the creative process?

My answer is very definitely yes.

I use technology extensively in creative work, but I have never regarded the technology itself as the creativity.

A camera does not decide what is worth photographing.

A microphone does not decide what emotion a performance should convey.

An editing system does not decide which moment in an interview tells the story.

And an AI system does not automatically know whether an idea is interesting, appropriate, original or simply rather dull.

AI can be an extraordinarily useful assistant.

But somebody still has to make the decisions.

Creativity Has Always Used Tools

It is worth remembering that creative work has never been separated from technology.

Photographers embraced autofocus, automatic exposure, image stabilisation and digital processing.

Video production moved from physical film cutting to non-linear digital editing.

Musicians moved from purely acoustic instruments to synthesisers, digital recording, MIDI, sampling and virtual instruments.

Graphic designers moved from drawing boards and Letraset to software.

Every major technological change produced some concern that the craft was disappearing.

Usually, something rather different happened.

The repetitive or technically awkward parts became easier, while the expectations placed upon the creator became higher.

AI may simply be another stage in that process.

The important distinction is between using AI to support creativity and asking AI to substitute for creativity.

Those are not the same thing.

Photography: AI Before the Shutter Is Pressed

People often associate AI photography with generating artificial pictures.

That is only one small part of what it can do.

AI can be useful long before a photograph is taken.

Imagine that a business asks me to photograph a new product.

Before setting up the camera, I might use AI to explore questions such as:

  • What sort of visual style would suit this product?

  • Should the photographs look technical, luxurious, friendly, traditional or modern?

  • What props might support the story without distracting from the product?

  • What backgrounds could work?

  • What sequence of images would be useful for a website and social media campaign?

  • What detail shots might a customer want to see?

That can turn a vague request such as:

“Can you photograph our new product?”

into a much more useful creative plan.

The AI has not taken the photograph.

It has helped organise the thinking behind it.

From Idea to Shot List

This becomes particularly useful when a photographic session has to produce many different assets.

Suppose we need:

a clean product photograph;

a close-up showing craftsmanship;

a photograph of the product being used;

a vertical image for social media;

a wide image suitable for a website banner;

and perhaps some behind-the-scenes photographs.

Rather than discovering halfway through the session that we have forgotten something, AI can help produce a checklist or shot list beforehand.

That is a productivity gain.

It is not a replacement for photographic judgement.

Once I am standing behind the camera, I still need to decide:

Where should the light come from?

How hard or soft should it be?

What focal length should I use?

What should be sharp?

What should be blurred?

Is the composition balanced?

Does the image actually communicate what the customer wants?

AI may have helped create the plan.

The photographer still has to create the photograph.

AI Cannot See the Scene Quite Like the Photographer Can

This is where human judgement becomes very important.

A photograph may be technically excellent and still fail.

Perhaps the lighting is too clinical for a warm, personal brand.

Perhaps the background colour clashes subtly with the product.

Perhaps the photograph is perfectly sharp but somehow lifeless.

Perhaps somebody's expression changed for a fraction of a second and that is the frame that suddenly feels natural.

Creative work contains enormous numbers of these small decisions.

Experienced photographers often make them instinctively.

We move a light slightly.

We lower the camera.

We wait half a second longer.

We change the focal length.

We remove something distracting from the background.

We ask someone to turn their head slightly.

None of these decisions seems dramatic.

Together, however, they can transform the image.

That is what I mean when I say somebody still needs to know what “good” looks like.

AI as a Photographic Editing Assistant

AI can also be extremely useful after the photograph has been taken.

Modern editing tools can assist with tasks such as selecting subjects, masking areas of an image, reducing noise, sharpening, identifying unwanted distractions and speeding up repetitive adjustments.

That can save considerable time.

But there is an important difference between asking:

“Can this image be improved?”

and:

“Can we make this image into something that never really happened?”

Both may have legitimate uses, but they are different creative activities.

For commercial photography, documentary work, scientific photography or event photography, authenticity may be extremely important.

Removing a temporary dust spot from a product photograph might be entirely reasonable.

Changing the product itself could be misleading.

Removing an unwanted sensor blemish from a landscape is one thing.

Adding a dramatic mountain range that was never there is something quite different.

AI therefore makes judgement more important, not less.

Video: AI Can Help Before Filming Starts

Video production is an area where AI can be particularly useful because even a short film involves many stages.

There may be:

research;

story development;

scripting;

interview questions;

shot planning;

filming;

sound recording;

transcription;

editing;

titles;

captions;

music;

and finally different versions for different platforms.

AI can help with almost all of those stages.

But again, helping is not the same as directing.

Turning an Idea Into a Structure

Suppose a small business wants a two-minute promotional film.

They know what their company does, but when asked what the film should say, the answer might initially be:

“Just show people what we do.”

That is understandable, but it is not yet a film.

AI can help explore possible structures.

For example:

Open with the customer's problem.

Introduce the company.

Show the process.

Include a customer testimonial.

Show the finished result.

Finish with a clear call to action.

Now we have something that can be discussed.

I may reject half of it.

I may rearrange the order.

I may decide that the company history is actually the strongest story.

That does not mean the AI failed.

It did its job by giving me something to react to.

This is one of the ways I find AI particularly valuable creatively.

A blank page is difficult to criticise. A draft is easy to improve.

Better Interview Questions

AI can also help prepare interviews.

Consider the difference between asking:

“Did you enjoy working with the company?”

and:

“Can you describe what problem you had before you contacted the company, and what changed afterwards?”

The first question may produce:

“Yes.”

The second may produce an entire story.

AI can help generate possible questions, but the person conducting the interview still needs to listen.

Quite often, the best question is not on the prepared list at all.

It is the follow-up question prompted by something the interviewee has just said.

That requires attention, curiosity and judgement.

The technology cannot replace genuine human conversation.

Creating a Useful Shot List

Video production also benefits enormously from good planning.

Imagine filming somebody making a bespoke object.

It might be useful to capture:

the wide workshop view;

hands performing the work;

close-ups of tools;

the raw materials;

the maker concentrating;

small details of the process;

the finished product;

and perhaps the customer's reaction.

AI can help remind us of these possibilities.

But while filming, something unexpected may happen.

Perhaps light suddenly falls beautifully across the workbench.

Perhaps the maker pauses to examine a detail.

Perhaps an apparently insignificant action turns out to be the perfect transition shot.

A rigid automated system might miss that.

A filmmaker notices it.

Transcription May Be One of AI's Most Useful Video Tools

One of the less glamorous applications of AI may also be one of the most useful.

Transcription.

An interview lasting forty minutes may contain only ninety seconds that ultimately appears in the finished film.

Searching through the footage manually can take considerable time.

An automatically generated transcript allows the editor to search the conversation as text.

If the customer remembers that somebody spoke about “how the company started”, it becomes much easier to find that section.

The transcript can also help create subtitles and captions.

This does not replace editing.

It removes some of the administrative work around editing.

And that distinction is important.

The Edit Is Where the Story Is Often Discovered

Film editing is not simply joining clips together.

It is storytelling.

Two editors given exactly the same material can create very different films.

One might make the story energetic.

Another might make it emotional.

Another might make it humorous.

Another might make it reflective.

AI may suggest edits, locate pauses, identify speakers or help find footage.

But the editor still has to decide:

Should we hold this shot for another second?

Should the music begin here?

Should we hear the person's voice before we see them?

Is this pause awkward or powerful?

Does the audience need another explanation?

Would removing this sentence make the story clearer?

That is creative judgement.

And it can be surprisingly difficult to automate because there may not be one objectively correct answer.

AI and Music: A Particularly Interesting Relationship

Music raises perhaps even more interesting questions.

AI can already generate musical ideas, suggest chord sequences, explore arrangements, produce rhythmic patterns and assist with many technical parts of audio production.

That can be extremely useful.

But music is not simply a mathematically correct sequence of notes.

Anyone who has played an instrument will recognise this immediately.

Two people can play exactly the same notes and produce completely different performances.

Timing matters.

Phrasing matters.

Dynamics matter.

Articulation matters.

Registration matters.

Balance matters.

And sometimes tiny imperfections make a performance feel human.

AI may provide a musical starting point.

The musician still decides what the music is trying to say.

Using AI as a Musical Sketchbook

I think one of the healthiest ways to regard AI in music is as a sketchbook.

Suppose I have a melody and want to explore several approaches.

It might help generate ideas for:

a gentle accompaniment;

a dramatic orchestral interpretation;

a jazz-influenced version;

a theatre-organ style treatment;

or a modern electronic arrangement.

Those suggestions can provide inspiration.

But I may then decide:

“That harmony is too predictable.”

“The accompaniment is far too busy.”

“This needs more space.”

“The melody should move to another instrument.”

“The introduction gives away too much too soon.”

These are musical decisions.

In other words, AI can produce possibilities.

The musician selects, modifies, combines and often rejects them.

The Danger of Accepting the First Answer

There is a potential problem with all AI-assisted creativity.

It can make producing something acceptable extremely easy.

That is not necessarily the same as producing something good.

Ask for a promotional script and you may receive a perfectly respectable script.

Ask for a photographic concept and you may receive a perfectly respectable concept.

Ask for a music idea and you may receive something perfectly respectable.

And that is where creative complacency can begin.

If everything is accepted exactly as generated, creative work can start to feel generic.

The language becomes familiar.

The visual ideas become predictable.

The musical structures sound conventional.

The result may be competent without being memorable.

The solution is not to abandon AI.

It is to become more demanding.

Instead of asking:

“Is this good enough?”

ask:

“Is this actually interesting?”

AI Is Particularly Good at Giving Us Something to Challenge

This is one of the ways I most value it.

Suppose I ask for ten ideas and dislike nine.

That may still have been useful.

Perhaps the tenth idea works.

Perhaps the ideas show me what I definitely do not want.

Perhaps two mediocre ideas can be combined into a much better one.

Creativity has always worked like this.

We sketch.

We experiment.

We discard.

We try again.

AI simply allows some of that exploration to happen faster.

Captions, Titles and Social Media

Another very practical use is turning a completed creative project into material that people will actually discover.

A photographer may create excellent images.

A videographer may create an excellent film.

A musician may produce an excellent recording.

None of that guarantees that anybody will see it.

AI can help turn the finished work into:

social media captions;

video descriptions;

alternative titles;

short introductory posts;

website copy;

hashtags;

thumbnail ideas;

and different versions for different audiences.

Again, the creator should review them.

A social media post may be grammatically perfect while completely failing to sound like the person or company publishing it.

Tone matters.

Personality matters.

Experience matters.

That final human edit is often what changes generic content into communication.

What AI Is Good At

The pattern that emerges is interesting.

AI is particularly useful when we need to:

generate possibilities;

organise information;

summarise material;

restructure ideas;

find variations;

produce first drafts;

handle repetitive tasks;

or speed up searching.

Those are substantial advantages.

They can give a creative professional more time to concentrate on the decisions that matter.

What Humans Are Still Very Good At

Humans remain remarkably good at things that are difficult to define precisely.

We notice that something feels wrong.

We recognise authenticity.

We respond emotionally.

We understand context.

We notice an unexpected opportunity.

We can deliberately break a rule.

Most importantly, we can ask:

What am I actually trying to communicate?

That question sits at the heart of photography, filmmaking and music.

AI Does Not Remove the Need to Learn the Craft

There is another reason I think creative skills remain important.

If you do not understand lighting, how do you know whether an AI lighting suggestion is sensible?

If you do not understand composition, how do you recognise a weak composition?

If you do not understand sound recording, how do you know that the microphone arrangement is inappropriate?

If you do not understand music, how do you recognise poor harmony or an unsuitable arrangement?

If you do not understand storytelling, how do you recognise a boring script?

AI can produce answers extraordinarily quickly.

That makes the ability to evaluate those answers more valuable.

Perhaps one of the most important skills of the AI era will therefore be something very traditional:

knowing your subject.

The Same Principle Applies to Equipment

There is an interesting parallel here with cameras, microphones, lighting and editing systems.

Owning an expensive camera does not make someone a photographer.

Owning a sophisticated editing system does not make someone a filmmaker.

Owning a powerful musical instrument does not make someone a musician.

And having access to an advanced AI system does not automatically make someone creative.

These are tools.

Excellent tools, in many cases.

But tools nevertheless.

The creative result comes from how they are used.

My Preferred Approach: Human First, AI Assisted

For me, the most useful workflow is not:

AI creates — human accepts.

It is closer to:

Human defines the objective.

AI helps explore possibilities.

Human evaluates them.

The real creative work is produced.

AI assists with some technical and repetitive tasks.

Human makes the final decisions.

That keeps the technology in a useful role.

It becomes an accelerator rather than the driver.

A Customer Does Not Really Want AI — They Want a Result

This is especially important in commercial creative work.

Most customers are not really interested in whether AI helped produce a shot list.

They care whether the photographs look good.

They care whether the film tells their story.

They care whether the sound is clear.

They care whether their product looks attractive.

They care whether the final video holds someone's attention.

They care whether the finished piece communicates what their business actually does.

The technology behind the process matters because it can help us work more effectively.

But it should rarely become the whole story.

Better Tools Should Allow Better Creative Decisions

That, ultimately, is where I think AI becomes genuinely exciting.

If AI saves twenty minutes transcribing an interview, that gives me twenty more minutes to refine the edit.

If it helps organise a complicated shot list, I am less likely to miss an important photograph.

If it suggests several approaches to a script, I can spend more time improving the strongest one.

If it helps explore musical arrangements, I can concentrate on the interpretation.

Used intelligently, AI does not necessarily make creative work less human.

It may give us more time for the human part.

Conclusion — Somebody Still Has to Know What Good Looks and Sounds Like

Artificial intelligence is going to become increasingly integrated into photography, filmmaking, music and design.

I do not think the most productive response is either to reject it or to hand everything over to it.

The interesting middle ground is to use it intelligently.

Let AI deal with some of the blank pages.

Let it suggest alternatives.

Let it organise information.

Let it transcribe.

Let it speed up repetitive processes.

Let it help us experiment.

But keep the judgement.

Keep the curiosity.

Keep the experience.

Keep the ability to recognise the unexpected moment that is better than anything originally planned.

Above all, keep asking whether the finished work actually achieves what it was intended to achieve.

Because the most sophisticated AI system in the world can generate an enormous number of possibilities.

Somebody still has to know which one is good.