Student Voice Analytics for History of Art Architecture and Design — UK student feedback 2018–2025

Scope. UK NSS open‑text comments for History of Art Architecture and Design (CAH20-01-02) students across academic years 2018–2025.
Volume. ~947 comments; 97.8% successfully categorised to a single primary topic.
Overall mood. Roughly 51.4% Positive, 46.4% Negative, 2.2% Neutral (positive:negative ≈ 1.11:1).

What students are saying

The dominant theme is the quality of the people teaching the course. Comments about Teaching Staff carry the largest share (~10.0%) and a clearly positive tone (sentiment index +48.3), well above the sector benchmark for the same topic. Students also discuss the intellectual shape of the curriculum: Type and breadth of course content (8.3%) and Module choice/variety (8.0%) both over‑index versus sector and are evaluated positively.

Two areas temper that picture. First, sector‑wide events: Strike Action is unusually prominent here (6.3% vs 1.7% sector) and strongly negative in tone, reflecting disruption and uncertainty. Second, several Assessment & Feedback topics attract consistent criticism: Feedback (4.9%, −34.3), Marking criteria (3.9%, −49.4), Dissertation (3.0%, −25.4) and Assessment methods (2.6%, −23.6). These patterns point to clarity and usefulness—what good looks like, how work is judged, and when/where students get actionable guidance.

Around the learning environment, Student life is frequently mentioned (5.0%) but is less positive than the sector on average. Library (4.2%) and Learning resources (2.7%) are talked about more than sector by share but with a cooler tone, suggesting expectations around access, availability or relevance are not always met. Operational delivery topics are a smaller part of the conversation overall, yet when they do appear the tone can dip sharply—especially Communication about course and teaching (1.7%, −63.6) and Scheduling/timetabling (0.6%, −33.0). Placements/fieldwork/trips are rarely mentioned (1.1%) and are notably positive when they are.

Top categories by share (discipline vs sector)

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Teaching Staff	The teaching on my course	10.0	6.7	+3.3	+48.3	+12.7
Type and breadth of course content	Learning opportunities	8.3	6.9	+1.4	+27.4	+4.8
Module choice / variety	Learning opportunities	8.0	4.2	+3.8	+24.3	+6.9
Strike Action	Others	6.3	1.7	+4.5	−66.2	−3.2
Student life	Learning community	5.0	3.2	+1.8	+14.0	−18.1
Feedback	Assessment and feedback	4.9	7.3	−2.4	−34.3	−19.2
Delivery of teaching	The teaching on my course	4.3	5.4	−1.1	+24.0	+15.2
Library	Learning resources	4.2	1.8	+2.4	+5.4	−21.3
Marking criteria	Assessment and feedback	3.9	3.5	+0.3	−49.4	−3.7
Student support	Academic support	3.7	6.2	−2.5	−12.0	−25.2

Most negative categories (share ≥ 2%)

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Strike Action	Others	6.3	1.7	+4.5	−66.2	−3.2
Marking criteria	Assessment and feedback	3.9	3.5	+0.3	−49.4	−3.7
COVID-19	Others	3.1	3.3	−0.2	−40.9	−8.0
Feedback	Assessment and feedback	4.9	7.3	−2.4	−34.3	−19.2
Dissertation	Assessment and feedback	3.0	1.1	+1.9	−25.4	−14.8
Contact time	Learning opportunities	2.7	0.6	+2.1	−25.3	+0.4
Assessment methods	Assessment and feedback	2.6	3.0	−0.4	−23.6	+0.2

Shares are the proportion of all comments whose primary topic is the category. Sentiment index ranges from −100 (more negative than positive) to +100 (more positive than negative).

Most positive categories (share ≥ 2%)

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Personal development	Learning community	2.5	2.5	+0.0	+54.1	−5.7
Teaching Staff	The teaching on my course	10.0	6.7	+3.3	+48.3	+12.7
Type and breadth of course content	Learning opportunities	8.3	6.9	+1.4	+27.4	+4.8
Module choice / variety	Learning opportunities	8.0	4.2	+3.8	+24.3	+6.9
Delivery of teaching	The teaching on my course	4.3	5.4	−1.1	+24.0	+15.2
Student life	Learning community	5.0	3.2	+1.8	+14.0	−18.1
Learning resources	Learning resources	2.7	3.8	−1.1	+6.3	−15.1

What this means in practice

Prioritise assessment clarity. Publish annotated exemplars, tighten marking criteria and rubric language, and set a realistic feedback SLA with progress tracking. For dissertations and larger projects, a short, structured guidance checkpoint mid‑way helps convert feedback into action.
Stabilise the operational rhythm. Use a single, authoritative channel for course communications, summarise changes weekly, and name owners for timetable and module‑level updates. This reduces the sharp sentiment seen around communication and scheduling.
Close the loop on disruption. Where industrial action affects teaching or assessment, signal mitigation plans early, explain trade‑offs plainly, and capture student questions in one place with status updates.
Protect and amplify strengths. Teaching Staff are a clear asset—make space for brief, regular formative moments in taught sessions, and ensure students know how and when to access staff. Where Student life and Library/resources are less positive than sector, refine reading‑list access, high‑demand materials, and clear signposting to support.

Data at a glance (2018–2025)

Top topics by share: Teaching Staff (10.0%), Type and breadth of course content (8.3%), Module choice/variety (8.0%), Strike Action (6.3%), Student life (5.0%), Feedback (4.9%).
Cluster view:
- People & growth cluster (Personal Tutor, Student support, Teaching Staff, Availability of teaching staff, Delivery of teaching, Personal development, Student life): ≈29.7% of all comments; tone broadly positive.
- Delivery & ops cluster (Placements/fieldwork, Scheduling/timetabling, Organisation & management of course, Communication about course and teaching, Remote learning): ≈7.2% of all comments; tone mixed, with communications/scheduling the main drags.
How to read the numbers. Each comment is assigned one primary topic; share is that topic’s proportion of all comments. Sentiment is calculated per sentence and summarised as an index from −100 to +100, then averaged at category level.

How Student Voice Analytics helps you

Student Voice Analytics turns open‑text survey comments into clear, prioritised actions by tracking topics, sentiment and movement by year for every discipline, including History of Art Architecture and Design. It supports whole‑institution overviews as well as fine‑grained department and school analysis, producing concise, anonymised theme summaries and representative comments for programme teams and stakeholders.

Crucially, it enables like‑for‑like sector comparisons across CAH codes and by demographics (e.g., year of study, domicile, mode of study, campus/site, commuter status), so you can evidence change against the right peer group. You can segment by site/provider, cohort and year to target interventions where they will move sentiment most. Export‑ready outputs (web, deck, dashboard) make it straightforward to share priorities and progress across the institution.