How to Compare University Modules Before You Pick

Most students compare modules on vibes: what a friend said, how the module handbook reads, whether the lecturer seems nice. None of that tells you anything about how the module actually marks.

Comparing modules properly means putting them side by side on the things that actually move your degree classification.

The four axes that matter

When you're comparing two or more optional modules, ignore the marketing copy in the handbook and compare on these:

1. Grade distribution. What's the historical first-rate? What's the mean mark band? This is the single biggest predictor of outcome, and it's the one axis most students skip entirely because they've never seen the data. See module grade data at UK universities for where to find it.

2. Assessment format. Coursework-heavy modules and exam-heavy modules produce different distributions and reward different skills. If you're strong at sustained written work but weak under exam pressure, that's a real input, not a preference.

3. Workload. Credit-weighted modules should, in theory, carry proportionate workload — in practice they don't always. Ask current students, not just the handbook.

4. Relevance. To your degree classification goal, and separately, to where you want to end up after graduation. These sometimes pull in different directions — see which modules look good on a CV if career relevance is your priority.

A side-by-side comparison table

Here's the shape of a genuine module comparison, using banded descriptors (never raw percentages — see our privacy threshold):

Module	First-rate band	Assessment mix	Cohort size
Module A	High	100% coursework	Large
Module B	Mid	50/50 exam-coursework	Medium
Module C	Low	100% exam	Small

Laid out like this, the decision stops being a guess. Module A carries the lowest downside risk if your goal is protecting your average; Module C is the highest-variance choice — it could pay off, but the data says it's less likely to.

Where to actually get the comparison data

This is the part almost every student skips, not because they don't want the data but because they don't know it exists. Universities hold module-level grade statistics from every exam board, but they don't publish comparisons — they don't even publish the underlying numbers in most cases. See university module statistics UK for what's actually recorded and why it stays buried.

GradeHack's FOI-sourced dataset exists specifically to make this comparison possible without you having to file dozens of requests yourself. Access the data to compare modules in your subject before your selection deadline.

Don't compare on reputation alone

"Everyone says Module X is easy" is a fine starting hypothesis, but it's anecdote, not evidence. Cohort sizes are often small enough that a handful of loud opinions distort the perceived reputation of a module entirely. Cross-check reputation against actual distribution data before you commit — particularly for second-year module choices, where the stakes for your final classification start compounding.

Compare properly once, and you won't need to guess again for the rest of your degree.