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Strategy · RISE Scenario Development Competition 2026

Purpose, roadmap & the end product

The clips we have been building are not the entry. They are the reference implementation that de-risks it. This page says what the video is for, what we ship and when — and puts the one expensive decision in front of you.

Content is 60% of the marks Design gates production Platform live ~5 Oct Deadline 30 Oct, 12:00nn
1 · Purpose

The video is the scenario artefact — not marketing, not a film

The competition asks students to author a branching scenario with two decision levels, and specifies that video clips are required at the branch points — to visualise the scenario "and the moments before each branch point". So each clip has exactly one job:

Put the learner inside the situation, and leave them at the moment where they must decide.

That framing sets the bar, because of how the rubric is weighted:

Content = organisation 10 · design of choices 20 · explanation 20 · language 10. Overall = understanding developed 10 + topic relevancy 10.

The design of choices alone is worth as much as the entire visual presentation. A beautiful clip bolted onto a weak decision tree loses to a plain clip on a sharp one. So the video's target is believable and clear — not photoreal — and its budget should be capped accordingly.

The video must

  • Create the decision moment — a real context, a real deadline, a real person pushing back.
  • Show consequences through dialogue and emotion, not "telling feedback".
  • Earn the Graphic Design 20% — legible captions, consistent identity, a professional finish.
  • Keep every option defensible — ambiguity, no cartoon villain.

The video must not

  • Tell the learner what to think.
  • Show a bare correct / incorrect stamp.
  • Spend its effort on rendering quality the rubric does not reward.
  • Become a film: the entry needs three short clips, not a production.
2 · What we ship

Three separate surfaces

A · the artefact

Our competition entry

A no-login folder: MP4 clips for the intro and both branch moments (<60 s each), a PDF/Word design + rationale, and the mandatory AI-usage declaration. Up to 4 competences, at least 2 domains.

B · the product

The helper platform

Where a student goes from an idea → framework-guided domain & competence choice → branching structure → storyboard → export, with a rubric checklist. Launches ~5 Oct.

C · the teaching material

The samples we've been making

These are the reference implementation: they prove the pipeline, and they become the platform's demo content. They are not the entry yet.

3 · Roadmap

Milestones to 30 October

  1. 9–11 SepM0 · Capability provenRules, rubric and framework verified. Style samples render end-to-end. Voices fixed. Figures now interact believably.
  2. 12–15 SepM1 · Route + look lockedYou sign off style and tech stack in the decision dashboard.
  3. 16–30 SepM2 · Scenario designedTwo levels, 3–4 options each, debriefs, framework map. This is the 60%.
  4. 23 Sep–5 OctM3 · Platform liveA student can go idea → framework → branching → storyboard → export.
  5. 28 Sep–15 OctM4 · Clips producedThree clips under 60 s, captions, consistent identity, GenAI declared.
  6. 22–26 OctM5 · QA'd against the rubricScored by someone who is not the author.
  7. 27 OctM6 · SubmittedBuffer before the 30 Oct, 12:00nn GMT+8 deadline.

The sequencing rule

Design gates production. Do not render a clip before the decisions it frames are final — every design change costs a re-render. On the 3D route that cost is ~12–13 minutes per minute of video.

Why the order looks like this

  • M2 before M4 — the rubric pays for choice design, not footage.
  • M3 in parallel — the platform is a separate build with its own deadline (first week of Oct), so it must not sit behind the entry.
  • M5 as a hard gate — a fresh pair of eyes against the rubric catches the gaps that authors cannot see.
4 · The one expensive decision

How do we produce the clips?

The trade is believability versus cost per revision — and the rubric caps how much believability is worth. Click a route.

A · 3D VRM avatars

Believability good · cost per revision high (~4 fps software render; 90 s ≈ 12–13 min)

What we built

B · Stylised 2D motion graphics

Believability medium (deliberately stylised) · cost per revision low (seconds)

Recommended for the entry

C · Live action

Believability highest · cheap to re-cut, expensive to re-shoot; consent & casting

Strong option if a cast exists

D · Hybrid (real footage/photos + graphics + voice)

Believability high · cost per revision low; needs editing skill

Recommended for the entry
Pick a route to see the trade-off.
Our recommendation: B or D for the entry — a stylised, instantly legible treatment clears the "believable + clear" bar at a fraction of the cost, and every design iteration is cheap. Keep A (the 3D avatars) as the platform's showcase and as our "we can do the hard thing" demo, which is where it earns its keep. Unless the team deliberately wants to win on Graphic Design polish — in which case A or C are defensible, but should be committed to now, not in October.
5 · What changed this week

Your note turned out to be three defects

"Two girls with their arms up and waving are not engaged in authentic interaction." Two of the three causes were invisible until we measured the rig — we cannot see the render, so we calibrate numerically.

DefectHow it was foundStatus
Both avatars used the same model (tinted copies)By inspectionfixed two distinct CC0 avatars — a female student and a male lecturer
Both avatars were facing away from the cameraMeasured from the toe bones (toes point forward): the 180° VRM-0 orientation flip was being overwritten by the staging yawfixed every frame verified facing the camera
"Arms down" was inverted, and the non-gesturing arm was left in the bind T-poseMeasured by reading the hand world position back while sweeping the arm rotationfixed both arms posed every frame; all four hands rest low
Listener nearly frozen; gestures were emblems, not conversationalStaging research (turn-taking, backchannels, gesture taxonomy)fixed backchannel nods, brow raise, tilt; speaker glances away and returns

Guard scripts now exist so these cannot silently regress: verify_pose.py, verify_interaction.py, calibrate_arms.py, check_facing.py, probe.py.

Research: the biggest lever is the listener

Bavelas, Coates & Johnson (2000): listeners are co-narrators — a dead listener degrades the speaker's own performance. More impactful than any render upgrade. Also: a wave is a speech-independent emblem (it means hello), not a conversational gesture — which is exactly how it read.

Cheap upgrades still on the table

  • rhubarb-lip-sync (MIT, verified running on this M2) — audio-accurate mouth shapes instead of a viseme flap.
  • Mixamo clips retargeted at runtime via vrm-mixamo-retargeter (MIT) — genuine idle / talk / listen cycles.
  • Not available: every photoreal talking-head model (Wav2Lip, SadTalker, MuseTalk, LivePortrait, EchoMimic) is CUDA-first and outputs 2D face video rather than rig data — the wrong tool even if it ran.
6 · Decisions

What we need from you

#DecisionOur recommendation
1Which production route — 3D, 2D graphics, live action, or hybrid?B or D for the entry; keep the 3D avatars as the platform showcase.
2Which theme for the scenario?Academic integrity under pressure — highest recognition for students, maps cleanly to several competences.
3Who is on the 4-person team, and who owns the design (the 60%)?Assign a named design owner now — it is the highest-weighted work and it gates production.
4Does the platform MVP generate clips, or stop at storyboard + export?Stop at storyboard + export for the 5 Oct launch; clip generation is a heavy second phase.
5Is the platform part of our entry story, or a separate side project?Separate. Keep the entry clean and scoreable; use it to showcase the platform.

Full reasoning: projects/Scenario/roadmap.md. Supporting research: interaction-research.md, interaction-tools.md, sources.md, plan.md.