What are students actually saying about Strike Action (NSS 2018–2025)?

Strike Action attracts a clear and consistent signal in student comments: it is overwhelmingly negative across subjects and demographics, and it shows up primarily among full-time, younger undergraduates.

Scope: UK NSS open-text comments for Strike Action across academic years 2018–2025.
Volume: ~6,683 comments (≈1.7% of all 385,317 comments); 100.0% sentiment-classified.
Overall mood: 3.4% Positive, 92.3% Negative, 4.3% Neutral; sentiment index −57.1.

What are students saying in this category?

  • Tone is uniformly negative across the board. Only 3.4% of comments are positive, and the sentiment index sits at −57.1. This pattern holds across the largest cohorts: full-time (95.3% of comments; index −57.1) and younger students (91.8%; index −57.4).
  • By subject (CAH1), the biggest named groups all show similar levels of negativity, typically in the −61 to −52 range. Media/journalism is among the most negative (index −61.6), while business/management (−52.4), biological and sport sciences (−52.8), and psychology (−55.0) are slightly less negative. Very small subjects can deviate (e.g., medicine and dentistry −25.2, n=17).
  • Demographic variation is modest: mature students are somewhat less negative than younger students (−53.4 vs −57.4), males slightly less negative than females (−55.6 vs −57.8), and disabled students slightly more negative than those not disabled (−58.0 vs −56.9). All groups remain strongly negative.

Breakdown by subject (CAH1) — largest named groups

Share = proportion of Strike Action comments.

Subject area (CAH1) Share % Pos % Neg % Neu % Sentiment idx
Social sciences 15.3 3.3 92.2 4.5 −57.0
Historical, philosophical and religious studies 11.0 3.4 92.4 4.2 −57.2
Language and area studies 9.4 2.7 91.7 5.6 −59.1
Law 6.5 3.2 93.1 3.7 −57.2
Psychology 6.2 4.3 91.4 4.3 −55.0
Geography, earth and environmental studies 6.0 2.0 91.8 6.3 −57.0
Business and management 3.7 4.0 89.9 6.1 −52.4
Combined and general studies 2.6 5.1 90.3 4.6 −57.6
Media, journalism and communications 2.5 1.2 95.2 3.6 −61.6
Biological and sport sciences 2.4 2.5 88.2 9.3 −52.8

Notes: All subjects are net negative. Small-volume subjects can show larger swings.

Demographic snapshot (share within Strike Action)

Segment Share % Pos % Neg % Neu % Sentiment idx
Age — Young 91.8 3.3 92.4 4.3 −57.4
Age — Mature 7.0 4.9 91.8 3.2 −53.4
Sex — Female 66.7 3.1 92.9 4.1 −57.8
Sex — Male 31.8 4.0 91.4 4.7 −55.6
Mode — Full-time 95.3 3.4 92.3 4.3 −57.1
Mode — Part-time 3.3 3.2 95.0 1.8 −56.1
Disability — Not disabled 80.5 3.4 92.3 4.3 −56.9
Disability — Disabled 18.3 3.3 92.9 3.8 −58.0
Ethnicity — White 77.5 3.2 92.6 4.2 −57.3
Ethnicity — Asian 6.0 4.5 90.5 5.0 −55.3
Ethnicity — Black 1.4 7.4 84.2 8.4 −49.2
Ethnicity — Not UK domiciled 8.0 3.5 92.2 4.3 −56.9

What this means in practice

With sentiment this negative and broad-based, the operational response matters as much as policy. Prioritise the large cohorts (full-time, young undergraduates) and the biggest subjects by volume.

  1. Communicate with precision
  • Keep a single, always-up-to-date source of truth covering what is affected, what is unchanged, and what mitigation exists.
  • Publish concise weekly (or daily during action) updates: what changed, why, and next steps.
  1. Protect learning and assessment continuity
  • Pre-plan catch-up windows and alternative activities/resources so students know how lost learning will be recovered.
  • Stabilise assessments: clear deadline policies, alternative formats where needed, and explicit marking timelines.
  1. Make mitigation visible and trackable
  • Log lost teaching hours and map them to recovery actions per module/programme.
  • Track and close student-reported issues; share closure rates and time-to-resolution.
  1. Target support by volume
  • Prepare subject-specific mitigation packs for the largest contributing areas (e.g., social sciences; historical/philosophical/religious; languages).
  • Tailor messaging for high-volume demographics (full-time, younger cohorts), while ensuring parity across all groups.

How Student Voice Analytics helps you

  • Quantifies topic and sentiment for Strike Action across cohorts and subjects, with drill-downs from provider to school/department.
  • Surfaces segment-level patterns by CAH code and demographics (age, domicile/ethnicity grouping, mode, disability), enabling targeted mitigation.
  • Produces concise, anonymised summaries to brief programme teams, unions and committees, with export-ready tables for governance papers.

Subject specific insights on "strike action"