Your curriculum,against the live labour market.

For each programme, we build a labour-market skill profile from tens of thousands of live job postings, and a curriculum skill profile from your course-level learning outcomes. Both are expressed in ESCO L3 — Europe's standard skill vocabulary — so they can be put side by side. The gap between them, with statistical uncertainty quantified, is what drives every recommendation.

1. 01ESCO L3 shared vocabularyEurope's official Skills, Competences and Occupations taxonomy at its third hierarchical level (~3,000 skills, ~3,000 occupations). Used on both sides of the comparison, so curriculum and labour-market evidence are commensurable by construction.
2. 02Career clustersGranular ESCO occupations grouped into coherent career paths a programme's graduates could realistically pursue. Clusters are not predefined — they are configured per programme during onboarding, in a workshop with the university, so they reflect the destinations this faculty actually wants its graduates to compete for. They then form the unit of comparison for every metric below.
3. 03RCA Revealed Comparative AdvantagePer-skill, per-job-ad RCA computed across the full Junior/Mid market, then averaged within each cluster — following Dawson, Williams & Rizoiu (2020), Eq. 3. This surfaces the skills distinctive to a cluster relative to the wider labour market, not the skills that are simply frequent everywhere.
4. 04ECTS-weighted curriculum aggregationProgramme-level skill importance is the credit-weighted sum of course-level skills, modelled in layers — core, specialisation tracks, electives — so the analysis reflects how a real cohort moves through the programme, not just the catalogue.
5. 05Frequency floorsTwo filters keep estimates stable: a skill must appear in ≥ 5 ads market-wide (so the RCA denominator is well-defined), and ≥ 5 ads within a cluster (so cluster-level importance isn't driven by a handful of postings).
6. 06Metric 1 · Weighted mean gapWhat it is. A single-number summary of how well a programme matches a cluster's demand.How it is calculated. For each demanded skill we compute the gap (cluster demand − curriculum provision, both max-normalised within the cluster's skill set), then take the average weighted by the cluster's importance for that skill.What it tells you. A large positive value means the programme is systematically under-providing what the cluster most needs; close to zero means the emphasis is broadly balanced against this destination.
7. 07Metric 2 · Importance-weighted coverageWhat it is. The share of the cluster's demand the programme touches at all.How it is calculated. Sum of cluster importances over skills the curriculum actually teaches, divided by sum of cluster importances over all demanded skills — a value between 0 and 1.What it tells you. High coverage means the programme at least mentions most of what matters for this destination; low coverage points to whole skill areas the programme doesn't address, and is the strongest signal that new content is needed.
8. 08Metric 3 · Spearman ρ rank correlationWhat it is. Whether the curriculum and the cluster put the same skills at the top.How it is calculated. Both sides are ranked across the cluster's demanded skills; Spearman's ρ is the rank correlation between those two rankings.What it tells you. High ρ means emphasis is in the right order even if absolute levels differ; low or negative ρ means the programme teaches the demanded skills, but with the wrong relative weight — a signal to reweight existing courses rather than add new ones.