Integrating Digitised Collections into Teaching
When asked to help a university museum or collection move teaching online (or make an emergency "pivot" permanent), start by mapping three things:
- What exists: inventory of already-digitised objects, images, 3D scans, catalogue records
- What's taught: which courses/modules use (or could use) physical collections
- What changed: what was improvised during a disruption (e.g. Covid-19) that worked well enough to keep
Then produce a short brief with:
- Current digital assets vs. teaching needs (gap analysis)
- 2–3 low-effort ways to embed existing digital content into online/hybrid sessions
- A plan for evaluating whether it worked (student feedback, staff reflection, usage data)
Progress:
- Step 1: Scope the collections and courses involved (object types, subjects, student numbers)
- Step 2: Audit existing digitisation — images, metadata, 3D models, online catalogues, past digital exhibits
- Step 3: Identify teaching formats affected (lectures, object-handling sessions, seminars, assessments)
- Step 4: Map digital assets to specific learning activities (e.g. replace handling session with annotated high-res images + discussion prompts)
- Step 5: Identify gaps — objects/topics with no digital surrogate, and decide whether to digitise, substitute, or redesign the activity
- Step 6: Pilot with one course/module; collect feedback from both students and teaching staff
- Step 7: Document what worked as improvisation vs. what should become standard practice
- Step 8: Write up findings for institutional learning (teaching committee, museum network, publication)
Example 1: Input: A university museum has 3D scans of 200 archaeological objects but no plan to use them beyond a one-off exhibit; a course on material culture lost access to handling sessions during a disruption. Output: A brief proposing embedding the 3D scans into a redesigned seminar: students examine models asynchronously via a shared platform, submit annotated observations, then discuss synchronously online. Includes a note that scan resolution is insufficient for 15% of objects, flagged for future digitisation funding.
Example 2: Input: Five university museums want to compare how they each adapted teaching during a pandemic and decide what to keep. Output: A shared cross-institutional framework (object types digitised, platforms used, course formats affected, staff/student feedback themes) enabling a joint comparative write-up, plus a shortlist of practices common to all five sites worth formalising as "new normal" guidance.
- Treat the emergency pivot as a data source, not just a crisis response — document what was improvised, since it reveals genuine latent demand
- Match digital format to pedagogical purpose: high-res images for visual analysis, 3D models for form/spatial reasoning, catalogue metadata for research skills — don't substitute blindly
- Involve both museum/collections staff and teaching academics from the start; gaps often appear at the handoff between the two
- Collect feedback from students and instructors separately — their priorities differ (engagement vs. logistics/workload)
- Favor cross-institutional comparison (e.g. a network of museums) over single-site conclusions; patterns that hold across contexts are more defensible as "new normal" policy
- Keep a running list of objects/topics where digital surrogates are inadequate — this becomes the digitisation priority list
- Assuming any digitisation is good enough for teaching — low-res or poorly catalogued digital objects frustrate rather than support learning
- Treating online delivery as a permanent downgrade rather than evaluating it on its own pedagogical merits (some things work better online)
- Skipping evaluation because "it worked during the emergency" — emergency tolerance is not the same as sustained satisfaction
- Digitising collections without reference to actual curricula, producing assets no one uses
- Failing to capture institutional knowledge before the staff who improvised the pivot move on