How Do Other Students Perform in Your Modules?

It's a reasonable question. You're choosing between three optional modules. You'd like to know how students in your department typically perform in each one. So you look at the module handbook, the VLE, past exam papers. None of them tell you what you actually want to know.

What proportion of students got a First in this module last year? What's the average mark? Is this a module where nearly everyone clusters around 58%, or one where the top quarter tends to reach 70 and above?

That data exists. Universities collect it. They just don't publish it.

Why this information isn't publicly available

Universities track grade distributions at the module level as a matter of routine. Examination boards see this data. Quality assurance processes review it. The information is used internally to flag modules where results look anomalous — either suspiciously high or unexpectedly low.

But this data isn't published in module handbooks, course catalogues, or student-facing systems. The reasons are partly practical (it would take effort to format and maintain for public consumption) and partly political (publishing it might invite uncomfortable questions about why some modules consistently return low grades, or why First rates vary so dramatically between departments).

The result is a structural information gap. Students making important academic choices — choices that meaningfully affect their final degree classification — are doing so without access to information that their university holds and routinely uses.

This is the problem GradeHack was built to fix.

What Freedom of Information requests reveal

The Freedom of Information Act 2000 gives anyone the right to request data held by public bodies — including UK universities. Module-level grade distributions fall within scope.

When a university receives a well-constructed FOI request for module grade distributions, it typically provides a table showing, for each module, how many students fell into each grade band over one or more academic years.

The data reveals things module handbooks don't:

First rates vary dramatically between modules in the same department. In the same subject, across the same year group, some modules return Firsts to 40% or more of students. Others return Firsts to fewer than 10%. The variation is not random — it reflects marking culture, assessment style, and examiner behaviour. Students who could see this would make different choices.

Pass rates are not uniformly high. Some modules have fail rates above 10%. Others fail fewer than 1% of students. The risk profile of different optional modules is meaningful — particularly for students whose classification is borderline.

Grade distributions differ from what you might guess from the title. A module with "Advanced" in the title isn't necessarily harder-marking than a survey module. A dissertation module doesn't necessarily have a higher First rate than a taught module. The name tells you almost nothing about the distribution.

For more on what FOI data has revealed about marking patterns across UK universities, see what FOI data reveals about UK marking.

How the data is structured

When GradeHack receives FOI data from a university, it typically contains:

• Module code and name
• Academic year (usually the most recent 3–5 years)
• Number of students assessed
• Number or proportion falling into each grade band (First, 2:1, 2:2, Third, Fail)

We receive this in various formats — spreadsheets, PDFs, plain text. We standardise it and, for modules with cohorts above our suppression threshold (10 students minimum), make banded signals available on the platform.

We don't publish raw percentages for modules where cohorts are small. A 25% First rate in a 4-student cohort is one person — that's too granular to be meaningful or fair. Our public signals use bands: high First rate, mid First rate, low First rate. Exact figures are available in the platform for modules with adequate cohort sizes.

What this means for your module choices

The question "how do other students do in this module?" is the right question. It's the one piece of information that most reliably predicts your likely outcome, conditional on your own performance patterns.

If you consistently score around 65% in your assessments and you're choosing between:

• Module A (mean mark band: high 2:1, First rate: mid)
• Module B (mean mark band: low 2:1, First rate: low)

...then Module A is likely a better fit for your grade profile. Not a certainty. But a better-informed decision.

This is why module choice affects your degree class more than most students account for. And why access to grade distribution data changes the decision calculus.

How to access grade distribution data

You have a few options:

Ask older students. The informal information network — asking third-years in your department about module difficulty and marking — is how this has always worked. It's hit and miss, subject to bias, and limited by how many people you know.

File your own FOI request. You can submit a request directly to your university via WhatDoTheyKnow. It takes time (20 working days is the statutory response deadline, though many take longer), and you'll need to know what to ask for. But the data comes back to you directly.

Use GradeHack. We file FOI requests systematically, process and standardise the data, and make it searchable by university, degree programme, and module. Rather than waiting 4–8 weeks for a single university's data, you can search across the universities and programmes we've already collected.

We're currently building out the dataset, with Exeter data from the 2018 pilot already ingested and further universities coming in as FOI responses land.

Join the waitlist to access module-level grade distributions — the data that should have been available to students all along.