Public Malaysian universities are upgrading accessibility but struggle with legacy buildings, budgets and continuous compliance, see the original report from The Star (24 Aug 2025) at www.thestar.com.my/news/nation/2025/08/25/varsities-work-for-inclusive-spaces. In this post for researchers and UX/education teams we show how to run a reproducible qualitative analysis of campus accessibility (interviews, audit notes, policy docs, student feedback) and turn findings into prioritized fixes. Use this practical workflow and see how Evidano (www.evidano.com) speeds auditing, thematic coding, segment comparisons and stakeholder-ready visual outputs.
Fast take: why this matters for researchers
Older campuses (UKM, UPM, USM cited in the source) report steady improvements but persistent gaps: compliance at UPM rose from 50% in 2021 to 69% in 2024, while USM lists discrete counts of OKU-friendly infrastructure (21 parking bays, 50 accessible toilets, 101 ramps, 48 wheelchair lifts). Meeting MS 1184:2014 and doing iterative upgrades is an ongoing research and operational challenge (The Star, 24 Aug 2025: www.thestar.com.my/news/nation/2025/08/25/varsities-work-for-inclusive-spaces).
- Problem: fragmented evidence (audit spreadsheets, interview transcripts, ad-hoc notes).
- Payoff: a 7-step AI-enabled qualitative workflow to map barriers, quantify frequency, compare cohorts and produce prioritized remedial actions.
- Quick win: automate transcription + thematic coding, then export visuals for funding bids and accessibility roadmaps.
Findings snapshot (from the source)
| Item | Figure / Date | Source note |
|---|---|---|
| UPM accessibility compliance | 50% (2021) → 69% (2024) | Annual audits by students/officers (The Star, 24 Aug 2025) |
| USM OKU-friendly facilities (Penang main campus) | 21 parking bays; 50 accessible toilets; 101 ramps; 48 wheelchair lifts | Counts cited by USM deputy VC (The Star, 24 Aug 2025) |
| Policy / standard challenge | MS 1184:2014 | Universities cite ongoing work to meet Malaysian universal design standard |
| Operational constraints | Legacy buildings + limited funds | Quoted across UKM, UPM, USM in the article |
What happened and why it matters
Universities acknowledge responsibility for inclusive campuses but face three recurring constraints: (1) legacy infrastructure built before universal design principles, (2) renovation complexity and high costs, (3) continuous compliance as standards and expectations evolve.
Practically, this produces mixed data: structured audit scores, facility inventories, student/special-needs group feedback, and policy texts. That heterogenous corpus is ideal for qualitative analysis that both surfaces recurring barriers and quantifies them for budgeting and policy-making.
Implications for researchers and UX/education teams
Design & field researchers
Use mixed-source coding to combine audits + student interviews. Prioritize barriers that appear across sources (e.g., inaccessible corridors mentioned in audits and student quotes).
Track frequency and severity separately: frequency = how often a barrier appears; severity = operational impact (e.g., prevents course attendance).
Policy & compliance teams
Translate audit trends (50%→69% compliance example) into targeted capital/maintenance asks. Use time-stamped themes to argue staged upgrades tied to MS 1184:2014.
Document consultation steps (OKU student association input, dedicated committees) as evidence for grants and regulatory reporting.
UX / Digital teams
Don’t forget digital accessibility: UKM’s accessibility menu is a model, map web/portal issues alongside physical audits to produce end-to-end accessibility roadmaps.
Build quick wins (clear signage, emergency lights with sound+visual alerts) from thematic ranking of student requests.
Do more, faster with Evidano
Ingest heterogeneous evidence
Problem: audits in spreadsheets, interviews as audio, policies as PDFs → messy pipeline.
Evidano: ingest spreadsheets, transcripts and PDFs; auto-transcribe interviews (with custom dictionary for local terms/OKU acronyms) and translate where needed.
Consistent thematic coding at scale
Problem: inconsistent manual coding across auditors and years.
Evidano: import or build a codebook, run AI-assisted coding, and surface hierarchical themes → subcodes with frequencies so you can compare 2021 vs 2024 or building A vs B.
Quantify and compare segments
Problem: decision-makers ask “how common is this? ” and “which campus is worst? ”.
Evidano: cross-segment analysis (by campus, faculty, student type) and co-occurrence networks show which barriers cluster with accessibility outcomes.
Stakeholder-ready outputs
Problem: stakeholders need concise evidence for funding and policy.
Evidano: generate exportable visualizations (word clouds, co-occurrence maps, hierarchical code trees) and clickable quote banks for reports and grant applications.
Secure, research-grade data handling
Problem: sensitive student data and ethics obligations.
Evidano: encryption at rest/in transit and data never used to train third-party models, suitable for ethically sensitive, non-diagnostic research.
7-step workflow: from audits to prioritized roadmap
Step 1; Centralize: collect audit spreadsheets, facility inventories, interview audio/transcripts, policy documents into one Evidano project.
Step 2 (Clean & tag: apply metadata (campus, year, facility type, respondent role).
Step 3) Transcribe & translate: auto-transcribe interviews with custom dictionary entries (e.g., OKU, MS 1184) and redact PII where required.
Step 4; Codebook & automated coding: import existing accessibility codebook or bootstrap one from sample transcripts; run AI-assisted coding across the corpus.
Step 5; Cross-segment analysis: run frequency counts and compare cohorts (e.g., students with mobility vs sensory impairments; campus A vs B).
Step 6; Visualize & prioritize: produce co-occurrence networks and a ranked list combining frequency + operational impact to generate a priority matrix.
Step 7; Deliver: export a concise brief (top 5 fixes, estimated cost range, stakeholder quotes) for funders and university leadership.
FAQ: qualitative analysis of campus accessibility
What counts as evidence?
Audit scores, facility inventories, interview transcripts, student complaints, policy texts and digital accessibility logs all count, mix them for stronger triangulation.
How do I compare campuses reliably?
Standardize metadata (same audit rubric, same time window) and use Evidano cross-segment analysis to control for differences in sample or building age.
Is AI transcription safe for sensitive interviews?
Apply PII redaction during transcription, store data encrypted, and use research-only models; Evidano supports custom redaction and ensures data isn’t used to train external models.
Wrapping up & next steps
Universities in the source article (published 24 Aug 2025) show measurable progress but ongoing gaps: these are solvable with targeted, evidence-led programs. Run a reproducible qualitative analysis to convert audits and lived experience into prioritized capital and policy actions.
- Start small: pilot the 7-step workflow on one faculty or campus quadrant.
- Need help ingesting heterogeneous sources and producing stakeholder-ready visuals? Explore a demo at www.evidano.com and see how AI-enabled qualitative research shortens time-to-insight.
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