Jake
26c7307607
Phase 9 of the rebrand cascade. Sweep covers everything the Phase 8
frontend pass deliberately skipped: docs/, root markdown, scripts,
Cargo.toml descriptions, code comments that survived earlier
word-boundary sed, plus a handful of identifiers caught on the final
verify pass.
transcription-app changes:
- README.md, HANDOVER.md, KNOWN-ISSUES.md, run.sh — magnotia/Magnotia
-> lumotia/Lumotia.
- docs/ — sweep across all subdirs except docs/handovers/ (preserved
as immutable audit trail). Includes architecture-map references
to magnotia_core::*, magnotia_storage::*, etc. now pointing at
lumotia_*; dev-setup.md tracing output examples (lumotia_startup
target); brief/ + superpowers/ + issues/ + whisper-ecosystem/ +
audit/.
- Cargo.toml descriptions on 9 crates (core, audio, cloud-providers,
hotkey, llm, mcp, plus referenced others).
- crates/core/src/{error,hardware,recommendation,paths}.rs +
crates/audio/src/wav.rs + crates/llm/src/model_manager.rs +
crates/cloud-providers/src/keystore.rs + crates/mcp/src/lib.rs —
doc comments and a model-manager user-agent string.
- Caught on final pass: BroadcastChannel("magnotia_task_sync") -> ...
("lumotia_task_sync"); magnotia_locale i18n localStorage key
renamed + migration shim added; CSS keyframe names
magnotiaPulse / magnotiaBar / magnotiaFade renamed in the design-
system kit; magnotia_viewer_item / magnotia_viewer_mode handoff
keys renamed in HistoryPage + viewer/+page.svelte; src/assets/
wordmark.svg text.
- src-tauri/src/lib.rs comment cleanup ("magnotia era" was sed'd
to "lumotia era" earlier — restored).
Preserved (intentional):
- crates/core/src/paths.rs — keeps "magnotia" / "Magnotia" / ".magnotia"
legacy detection strings in legacy_and_target_paths() so the
migration shim can still find user data from the magnotia era.
- src/lib/stores/{page,focusTimer}.svelte.ts + src/lib/i18n/index.ts
— migration call sites reference the legacy magnotia keys
deliberately.
- docs/handovers/ — historical audit trail.
cargo build --workspace passes. npm run check: 0 errors / 0 warnings
(3958 files). cargo test --workspace: 339 pass / 0 fail.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
27 lines
3.6 KiB
Markdown
27 lines
3.6 KiB
Markdown
<!-- Source: Lumotia Master Brief — Appendix A5: HITL AI Scaffolding -->
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## A5. HITL AI Scaffolding — Autonomy-Supportive Design
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**Core finding:** AI scaffolding must support autonomy, not replace executive function. Controlling or fully automated approaches undermine the self-regulation skills they aim to support. The distinction is not philosophical but empirical.
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**Self-Determination Theory (SDT) framework for ADHD:**
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- **Champ, Adamou & Tolchard 2022** (*Psychological Review*): Proposed a complete SDT-based framework for ADHD, arguing that autonomy, competence, and relatedness needs explain self-regulation patterns better than deficit models.
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- **Champ et al. 2025** (*JMIR Formative Research*): ADAPT randomised feasibility study with **20 adults from an NHS ADHD clinic**. **91.6% intervention completion**. Clinically significant improvement in psychological distress (p = .01) and significant ADHD symptom reduction (p ≤ .01). Demonstrates that autonomy-supportive scaffolding works in clinical practice.
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**Critical review of existing ADHD tools:**
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- **Spiel et al. 2022** (*ACM CHI '22*): Most ADHD technology is "shaped by research aims which privilege neuro-normative outcomes." Time-management interventions frequently cause stress and frustration. Participatory design with ADHD individuals leads to **fundamentally different design outcomes** (e.g. conceiving time as "stretches of activities" rather than clock-based units). Explicitly documents harm caused by surveillance-like monitoring and intrusive alarms.
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- **Carik et al. 2025** (*ACM GROUP '25*): LLM use across **61 neurodivergent Reddit communities**, identifying 20 use cases. ADHD users primarily sought help with organisation, planning, and prioritising. LLM responses are frequently **"overly neurotypical"** and not calibrated for neurodivergent cognition. Users expressed significant concern about overreliance.
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**Longitudinal case evidence:**
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- **Mittler 2025:** 42-year-old neurodivergent student with severe executive dysfunction. Over 4 semesters using strategically integrated AI tools, GPA rose from **1.85 to 3.35**. Psychological trajectory shifted from anxiety to sophisticated "process awareness" — the student internalised external scaffolds.
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- **Azevedo et al. 2022** (*Frontiers in Psychology*): Decade-long MetaTutor programme, 100+ college students. **Adaptive pedagogical agents that prompt metacognitive strategies** (rather than completing tasks) produced significantly better learning outcomes.
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**Five design principles from the literature:**
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1. **Scaffold, don't automate** — prompt metacognitive strategies rather than completing tasks for the user
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2. **Co-regulate, don't correct** — nudges should be reflective ("What were you working on?") rather than directive ("You should be working on X")
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3. **Adapt to fluctuating states** — detect attention shifts and adjust support intensity dynamically
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4. **Keep the human in the loop** — every AI suggestion requires user confirmation, building executive function rather than atrophying it
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5. **Design with, not for** — participatory design with neurodivergent users produces fundamentally different and better outcomes
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**Implication for Lumotia:** The AI agent must be visible, conversational, and interactive — but must never override user autonomy. Every suggestion requires confirmation. The human-in-the-loop feedback mechanism builds metacognitive awareness over time. Users should eventually internalise Lumotia's scaffolding patterns and need them less — that's a feature, not a failure. LLM prompts must be calibrated for neurodivergent cognition, not neurotypical assumptions.
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