FLUX-ID™

The Framework for Intelligent, Empathic Design

(Frame → Lab → Unitize → eXecute → Integrate → Deepen)
A modern, AI-infused instructional design and project operating system for snackable, social, sticky learning.

FLUX-ID™: The Future Fluent Framework for Ethical, Adaptive, and Empathic Design

Created by Carolyn DeClue, FLUX-ID™ (Future Fluent Learning eXperience and Instructional Design) is a next-generation framework that reimagines how humans and technology learn, work, and evolve together. Built at the intersection of instructional design, project management, and emotional intelligence, FLUX-ID™ fuses AI’s analytical precision with empathy’s human wisdom. Its architecture operates as a double-helix, two interwoven threads of Artificial Intelligence (AI) and Emotional Intelligence (EQ), that guide every phase of design, from idea to implementation.

At its core, FLUX-ID™ transforms traditional learning and project systems into living ecosystems. Each of its six adaptive phases—Frame, Lab, Unitize, Execute, Integrate, and Deepen—ensures that progress remains intelligent and humane. Designed to address the challenges of modern learners and organizations, it enables teams to design faster without losing reflection, automate smarter without losing compassion, and measure success not just in efficiency, but in trust, inclusion, and long-term impact.

In a world racing toward automation, FLUX-ID™ stands for something profoundly simple yet essential: technology should learn to care. It’s not just a framework. It’s a philosophy for a new era of learning and leadership, where intelligence is ethical, systems are self-aware, and design is human again.

Principles

  • Problem-first (Merrill): Every learning object begins with a real-world scenario or task. No “content orphans” that can’t be applied.

  • Short + Social: Default to 30 seconds–2 minutes “swipe-size” units with a built-in social action (post, duet, stitch, comment, poll). Learning feels like scrolling hacks, not homework.

  • Retrieval & Loop over Rewatch: Every unit ends with recall or application. Videos play on loop by default (social media style) to support learners who need multiple passes for comprehension.

  • Feedback Fast: Learners receive feedback in under 24 hours — AI-first for speed and scalability, human-layered where nuance matters.

  • AI Everywhere: AI is co-designer, content generator, tutor, assessor, orchestrator, and analyst. It works behind the scenes and in front of learners seamlessly.

  • Evidence In → Evidence Out: Every unit maps to clear, observable transfer tasks directly tied to job or field performance.

  • Accessibility & Multimodal by Default: Text, audio, captions, alt-text, motion-friendly, and inclusive design aren’t extras — they’re baked in from the start.

The FLUX-ID™ Macro Cycle (project operating system)

F — Frame (Strategic Analysis, fast)

  • Goal: Align on outcomes, constraints, risks, and success metrics.

  • Inputs: Stakeholder intent, target roles, key tasks, performance gaps.

  • Activities (ADDIE-Analysis + Agile Inception):

    • AI co-analysis of docs/interviews → draft task model & learner archetypes.

    • Risk map + “will not do” list (scope kill-switch).

    • Success North Star: 2–3 real transfer tasks; 3–5 outcome KPIs.

  • Artifacts: Task map, audience snapshots, KPI tree, draft measurement plan.

  • AI Roles: Transcript summarizer, gap miner, benchmark scanner.

L — Lab (Rapid Design & Prototyping)

  • Goal: Prototype the experience loop before scaling content.

  • Activities (SAM/Agile + Gagné + Merrill):

    • Pick one flagship scenario; sketch the learning beat map:

      • Hook (Gagné 1) → Why now (2) → Prior activation (3)
        → Demo (4) → Guided try (5–6) → Immediate feedback (7)
        → Performance check (8) → Transfer cue (9)

    • Test with 5 learners in 48–72 hrs; iterate twice.

  • Artifacts: Beat map, clickable prototype, feedback matrix.

  • AI Roles: Script drafter, tone shaper, demo generator, micro-usability tester.

U — Unitize (Microlearning Architecture)

  • Goal: Break into snackable, loopable units with recall & application built-in.

  • Activities:

    • Chunk into 30 sec–2 min units; each unit = 1 scenario + 1 action + 1 recall.

    • Map retrieval & spacing plan (day 0, 2, 7, 21, 45).

    • Design social prompts (comment, stitch, challenge).

    • Align objectives with Bloom as a tool (verb checks, assessment fit).

  • Artifacts: Unit backlog, spacing calendar, social action map.

  • AI Roles: Chunking assistant, question generator, distractor sanity checks.

X — Execute (Sprint Build & Release)

  • Goal: Build, QA, and ship in 1–2 week sprints.

  • Activities (Agile/Scrum):

    • Sprint plan by value slices (end-to-end usable paths).

    • Content build → accessibility pass → pilot release → telemetry on.

    • Definition of Done: Accessible, measured, includes recall + transfer task.

  • Artifacts: Sprint board, release notes, telemetry dashboards.

  • AI Roles: Content draft → human refine, captioning, alt-text, QA, bias checks.

I — Integrate (Transfer to Workplace)

  • Goal: Make learning show up where work happens.

  • Activities:

    • Publish just-in-time job aids (cards, checklists, snippets).

    • Workflow embeds: LMS + chat + project tools (Teams/Slack).

    • Performance alignment: Rubrics mirror real outputs; micro-coaching kits for managers.

  • Artifacts: Job aids, quick-apply templates, manager prompts.

  • AI Roles: Contextual recommender, on-demand coach.

D — Deepen (Retention & Continuous Improvement)

  • Goal: Cement knowledge, extend skills, evolve the product.

  • Activities:

    • Spaced retrieval nudges across channels.

    • Adaptive practice: AI scales difficulty, flags misconceptions.

    • Evidence review: Compare transfer tasks vs. KPI movement.

    • Quarterly kill/keep/iterate decisions; retire stale content ruthlessly.

  • Artifacts: Retention curves, misconception heatmaps, iteration roadmap.

  • AI Roles: Nudge scheduler, mastery estimator, anomaly detector.

The Micro Pattern (per unit): S.N.A.P.

  • Spark (Hook + Why it matters now) — 15–40s

  • Navigate (Demo or example-in-context) — 30–60s

  • Act (Guided try or mini-challenge) — 30–60s

  • Pull (Retrieval + Transfer cue + Social action) — 20–40s

Mapping the classics:

  • Gagné: Spark (1–3), Navigate (4), Act (5–7), Pull (8–9).

  • Merrill: Problem/demonstration/application/integration map directly.

  • Bloom: A verb/assessment check tool, not the skeleton.

AI Thread (woven end-to-end)

  • Co-Designer: Drafts scripts, scenarios, examples, and checks Bloom verbs.

  • Tutor/Coach: Inline hints, Socratic prompts, adaptive difficulty.

  • Orchestrator: Schedules spacing, recommends next unit, pushes nudges.

  • Assessor: Generates items, calibrates, analyzes misconceptions.

  • QA & Compliance: Accessibility lints, bias sweeps, content integrity checks.

  • Analyst: Dashboards for recall rates, transfer task quality, and KPIs.

Measurement

  • Learning KPIs: Retrieval success at D0/D2/D7/D21/D45; misconception rates; time-to-first-success.

  • Behavior KPIs: Use of job aids in the wild; “show-your-work” posts; manager-observed change.

  • Outcome KPIs: Cycle time ↓, errors ↓, satisfaction ↑, compliance incidents ↓, sales/throughput ↑.

  • Product KPIs: Completion heatmap, content kill rate, sprint release velocity.

Quick Templates

  • SNAP Script card: Spark | Navigate | Act | Pull | Accessibility notes.

  • Spacing Plan: D0, D2, D7, D21, D45 with channels & items.

  • Transfer Task Rubric (3–5 criteria): accuracy, completeness, time, judgment, communication.