How Teachers Detect AI in GCSE Combined Science Write-Ups

Detecting AI in GCSE Combined Science practical write-ups has become part of the marking routine for many science teachers. The required practicals — from investigating osmosis in potato chips to measuring the resistance of a wire — produce method, results, and conclusion sections that students increasingly draft with the help of tools like ChatGPT and Claude. When a write-up reads more like a textbook than a fourteen-year-old who was in your lab last Tuesday, you need a fair, consistent way to check.

This guide looks at how teachers use AI likelihood scores to review Combined Science write-ups, where the false positives tend to hide, and how to keep professional judgment at the centre of any decision.

Why Science Write-Ups Are a Special Case

Practical write-ups have a structure that AI models reproduce very well. There is a standard shape — aim, hypothesis, variables, method, results table, analysis, conclusion, evaluation — and a bank of expected scientific vocabulary. An AI model can generate a competent-looking write-up for a required practical in seconds, complete with the language of "independent variable", "anomalous results", and "valid conclusion".

That same predictability makes science write-ups genuinely hard to judge by eye. A conscientious student who has revised the method thoroughly can legitimately produce writing that reads formally and uses precise terminology. So the signals that might look suspicious in a creative English piece — polished phrasing, textbook structure — are often exactly what you are teaching students to produce in science. This is precisely why a probabilistic tool is more useful here than gut feeling alone.

How AI Detection Actually Works

AI detection is probabilistic, not a verdict. GradeOrbit's built-in detection tool analyses a piece of work and returns a likelihood score from 0 to 100%, representing how consistent the writing is with AI-generated text. It is not a lie detector and it does not "prove" anything. A 90% score is a strong signal worth investigating; it is not, on its own, an allegation of malpractice.

For a Combined Science write-up, the score is most useful when you read it section by section in your head. A student's own method — copied from the board or their exercise book — may score very differently from their conclusion or evaluation, where independent reasoning is expected. A write-up where the routine sections look human but the analysis suddenly reads like a revision guide is worth a closer look. Our guide on how AI detection likelihood scores work explains the reasoning behind the number in more detail.

Where False Positives Hide in Science

Science write-ups produce more false positives than almost any other subject, and it pays to know why before you act on a score.

• Standard method wording. If your class copied a method from the same worksheet, thirty students will submit near-identical, formal text. That formality can push scores up without any AI involvement.
• Taught sentence stems. Writing frames like "The results show that... because..." are structures you actively teach. Rewarded phrasing can read as machine-like.
• EAL students. Students writing in an additional language often lean on memorised scientific phrasing, which can raise a score unfairly.

This is why a high score is a prompt to look, not a conclusion. Compare the write-up against the student's classwork, their exercise book, and what you saw them do in the lab. A student who can explain their own conclusion when you ask them about it is telling you far more than any percentage can.

Handling a High Score Fairly

When a Combined Science write-up returns a high likelihood score, treat it as the start of a professional conversation, not the end of one. Look at whether the science is actually correct — AI-generated write-ups often contain plausible-sounding but wrong reasoning, such as confusing correlation with a valid conclusion, or citing a control variable that was never mentioned in your lesson. Ask the student to talk you through their method and what their results mean. Genuine understanding is quickly obvious.

Keep a short, factual record of what you found and what you decided. For more on managing this conversation, see our guide on how teachers handle a high AI likelihood score fairly, which sets out a calm, evidence-based approach that protects both the student and your professional standing.

Keeping Detection Private and Anonymous

GradeOrbit is built privacy-first for solo and team teachers. Before you upload a scanned or typed write-up, you can use the built-in redaction tool to draw black boxes over any identifying details — names, candidate numbers — so work is processed anonymously as Student 1, Student 2, and so on. Uploaded student work is never saved to a database on the solo and team plans; it is used to produce the score and feedback, then discarded.

Try GradeOrbit's AI Detection Tool

GradeOrbit gives UK science teachers a fair, probabilistic starting point for checking GCSE Combined Science practical write-ups — a 0 to 100% likelihood score you interpret with your own knowledge of the class, the practical, and the student in front of you. It never replaces your judgment; it gives you evidence to apply it consistently.

Sign up to GradeOrbit and try the built-in AI detection tool on your next set of science write-ups.