What UK Students Say About Costs and Value for Money: NSS Feedback Analysis (5,994 Comments, 2018–2025)

Students’ comments on costs and value are overwhelmingly negative across the dataset. Tone is strongly unfavourable overall (sentiment index −46.7), with full-time and younger students notably more critical than part-time and mature students. Views are negative across broad subject areas, with the least negative tones in combined/general, psychology, engineering, and medicine/dentistry. Apprenticeships look far less negative, though numbers are very small.

Key findings

  • 5,994 comments analysed across UK programmes (2018–2025); overall sentiment is negative (index -46.7)
  • The category is dominated by negative sentiment: 88.3% of comments are negative, only 9.3% positive.
  • Mode and age matter. Full-time students (78.7% of comments) are much more negative (index −50.4) than part-time (−33.8).

What are students saying in this category?

  • The category is dominated by negative sentiment: 88.3% of comments are negative, only 9.3% positive.
  • Mode and age matter. Full-time students (78.7% of comments) are much more negative (index −50.4) than part-time (−33.8). Younger respondents are also more negative (−50.2) than mature (−39.1).
  • By subject (CAH1), negativity is broad-based. The most negative tones appear in historical/philosophical/religious studies (−52.9), creative arts (−50.4) and social sciences (−51.4). Combined/general studies (−37.8), psychology (−41.5), engineering (−41.1) and medicine/dentistry (−39.6) are less negative but still below neutral.
  • Differences by sex and disability status are small (indices around −46 to −48). Ethnicity shows variation: Mixed ethnicity is more negative (−52.8) while Black students are less negative (−31.8), though all groups remain net negative.
  • Apprenticeships show near-neutral tone (−1.2) but with only 13 comments; treat cautiously.

Breakdown and benchmarks

By mode of study

Mode n Share % Positive % Negative % Sentiment idx
Full-time 4716 78.7 7.1 90.6 −50.4
Part-time 1176 19.6 16.8 80.4 −33.8
Apprenticeship 13 0.2 46.2 53.8 −1.2
Unspecified 80 1.3 22.5 76.3 −31.7

Broad subject area (CAH1) — top 8 by volume (excluding “unknown”)

Broad subject (CAH1) n Share % Sentiment idx
Social sciences (CAH15) 557 9.3 −51.4
Business and management (CAH17) 458 7.6 −49.0
Subjects allied to medicine (CAH02) 418 7.0 −43.8
Design, and creative and performing arts (CAH25) 408 6.8 −50.4
Historical, philosophical and religious studies (CAH20) 331 5.5 −52.9
Psychology (CAH04) 277 4.6 −41.5
Computing (CAH11) 276 4.6 −45.0
Combined and general studies (CAH23) 274 4.6 −37.8

Notes on numbers: Sentiment indices run from −100 to +100. Very small groups (e.g., Apprenticeship, n=13) can fluctuate substantially; interpret with caution.

What this means in practice

  1. Make costs visible and predictable
  • Publish a simple “total cost of study” view per programme: what fees cover, typical extra costs, when they occur, and what’s optional.
  • Adopt a “no surprises” cost policy with minimum notice periods for any additional spend.
  1. Reduce out-of-pocket spend at known pressure points
  • Prioritise areas with the most negative tone (e.g., creative arts, social sciences, historical/philosophical subjects) for cost audits of materials, trips, specialist spaces and licences.
  • Expand equipment/kit loans, print/material allowances, and software access to reduce personal purchases.
  1. Target the groups with the lowest value perceptions
  • For full-time and younger students, front-load information on included provisions, travel/placement reimbursements, and hardship routes; schedule support before cost-heavy weeks.
  • Use short pulse checks after high-cost activities and close the loop quickly.
  1. Tighten support and reimbursement operations
  • Standardise cost guidance in module handbooks and the VLE; keep a single source of truth.
  • Set service targets for reimbursements and track turnaround time publicly.
  1. Learn from pockets of better tone
  • Where programmes achieve less negative perceptions (e.g., combined/general, psychology, engineering, medicine/dentistry), capture and share practices that minimise student spend or clarify value.

How Student Voice Analytics helps you

  • Pinpoint where value-for-money concerns are sharpest by mode, age, subject (CAH), ethnicity, disability and sex, and monitor movement over time.
  • Drill from institutional to school/department cohorts; produce concise anonymised summaries for programme teams and finance/operations.
  • Provide like-for-like comparisons across CAH codes and demographics, and segment by campus/site or cohort.
  • Export-ready tables and narratives for quick briefing and action tracking.

Data at a glance (2018–2025)

  • Volume: 5,994 comments; 100.0% sentiment coverage (≈1.6% of all comments).
  • Overall mood: 9.3% Positive, 88.3% Negative, 2.4% Neutral (sentiment index −46.7).
  • Composition: 78.7% Full-time; 19.6% Part-time. 70.1% Young; 28.5% Mature.

How to use this data

This page presents sector-level student feedback analysis for the Costs and Value for Money category (Others), with demographic and subject-area benchmarks you can reference directly in institutional documents.

Use this for

  • Annual Programme Review (APR) — reference the segment benchmarks to contextualise your programme's feedback patterns against the sector.
  • TEF and quality enhancement — cite the demographic breakdowns and subject-area sentiment as evidence of awareness of differential student experience.
  • Equality, diversity and inclusion (EDI) — use the ethnicity, disability and age segment data to evidence where feedback experience differs by student group.
  • Staff-Student Liaison Committees (SSLCs) — share the key findings and subject-area table as discussion starters with student representatives.
  • Action planning — use the "What this means in practice" recommendations as a starting point for targeted interventions.

Common subject areas linked to this theme (on our blog)

Most-read posts in this category

Recommended next steps

  1. Quantify: how often does this theme appear (and where)?
  2. Segment: by discipline (CAH/HECoS), level, mode, and cohort where appropriate.
  3. Benchmark: compare like-for-like to avoid cohort-mix artefacts.
  4. Act: define 1–3 changes, then track whether the theme shifts next cycle.

Cite this page

Student Voice AI (2025). "Costs and Value for Money: NSS student feedback analysis (2018–2025)." Student Voice AI. https://www.studentvoice.ai/category/costs-and-value-for-money/

Subject specific insights on "costs and value for money"

The Student Voice Weekly

Research, regulation, and insight on student voice. Every Friday.

© Student Voice Systems Limited, All rights reserved.