What UK Students Say About Strike Action: NSS Feedback Analysis (6,683 Comments, 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.

Key findings

6,683 comments analysed across UK programmes (2018–2025)
Tone is uniformly negative across the board. Only 3.4% of comments are positive, and the sentiment index sits at −57.1.
By subject (CAH1), the biggest named groups all show similar levels of negativity, typically in the −61 to −52 range.

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.

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.

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.

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.

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.

How to use this data

This page presents sector-level student feedback analysis for the Strike Action 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.