Interview scorecard template

Immersive Learning Experience Designer interview scorecard

Pre-screening scorecard for Immersive Learning Experience Designer candidates.

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design visual communicationinstructional designunityxapi scormxr learning
Complete evaluation framework

What to assess and how to score it

Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.

01
Evaluation factor

Portfolio

35% weight

Review shipped immersive modules: VR onboarding sims, AR job aids, 360 video scenarios. Ask for headset build links, learner counts, and completion or assessment data per module.

Evidence to listen for

  • Work exists and can be looked at, not just described
  • States what they made versus what the team or a template made
  • Shows range rather than one repeated style
  • Can walk through a piece from brief to final

Five-point scoring guide

1
Poor

No portfolio, or work that is unattributable or clearly templated.

2
Needs Improvement

Thin portfolio; unclear what they personally made.

3
Satisfactory

Real work with adequate range; contribution mostly clear.

4
Very Good

Strong varied portfolio with clear personal ownership.

5
Excellent

Shows two or three live XR modules with named clients, learner volumes, and pre/post assessment or time-to-competency numbers.

02
Evaluation factor

Craft and rationale

25% weight

Probe the design craft: storyboarding in Twine or Miro, branching scenario logic, Unity or Unreal authoring, Articulate or 8th Wall builds, and why they chose immersion over video.

Evidence to listen for

  • Explains why a layout, type choice, or colour decision serves the brief
  • Knows typography and hierarchy as craft, not decoration
  • Works to a brand system without either breaking it or hiding behind it
  • Names the tools they are genuinely fast in

Five-point scoring guide

1
Poor

Cannot explain any decision; work is arbitrary.

2
Needs Improvement

Talks in taste terms only; no link between choice and brief.

3
Satisfactory

Sound craft with some ability to justify decisions.

4
Very Good

Articulate about why each choice serves the brief.

5
Excellent

Explains interaction affordances, comfort and locomotion choices, and cognitive load reasoning tied to a specific learning objective.

03
Evaluation factor

Feedback and iteration

25% weight

Ask how playtesting shaped a build: headset usability sessions, SME review cycles, xAPI or SCORM data showing where learners stalled, and what got cut.

Evidence to listen for

  • Takes critique without treating it as an attack
  • Distinguishes a subjective preference from a real problem, and says so politely
  • Iterates fast rather than defending version one
  • Delivers files correctly and on time

Five-point scoring guide

1
Poor

Defensive about critique; will not revise.

2
Needs Improvement

Accepts feedback passively; iterations do not improve the work.

3
Satisfactory

Revises willingly; struggles to push back on weak feedback.

4
Very Good

Iterates quickly and can argue for the work when the feedback is wrong.

5
Excellent

Names a mechanic they removed after observing learners fail it, citing session recordings or xAPI drop-off evidence.

04
Evaluation factor

Working with the brief

15% weight

Test intake discipline: how they run SME interviews, write measurable objectives, scope to device constraints (Quest standalone versus tethered), and handle fixed budgets or LMS limits.

Evidence to listen for

  • Asks about audience and goal before opening the design tool
  • Works with marketing, product, or clients rather than in isolation
  • Flags an impossible brief early
  • Hands over files and assets others can actually use

Five-point scoring guide

1
Poor

Designs in isolation; ignores the brief's purpose.

2
Needs Improvement

Starts designing before understanding the goal.

3
Satisfactory

Asks the right questions when prompted.

4
Very Good

Interrogates the brief up front and hands over cleanly.

5
Excellent

Converts vague training requests into objectives, device targets, and asset scope, pushing back with evidence when immersion adds no value.

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