Ashley Miller, PMHNP-BCInstructional designer · system builder

Complex work.
Clear learning.

Built fast. Reviewed like it matters.

I’m a psychiatric nurse practitioner and instructional designer. I research deeply, design whole learning journeys, build in Articulate, and use AI to speed production without letting it make the final call.

Storyline + Rise · scenarios · video · facilitator materials · LMS QA
Available for remote contract and project work
Source → learning experience → delivery
MOUD & Harm ReductionOriginal lesson film
Original participant page introduces readiness for change with a CHANGE illustration and private reflection prompts.
Participant workbook / original page
7review gates before release.
AI moves the work. Human judgment owns it.
My starting point

AI can move the work faster.
It does not get to lower the standard.

Source-bound.
Human-reviewed.
Built to transfer.
01 / Featured learning journey

One topic.
A complete system.

An interactive course, original video, participant practice and a facilitator route, all carrying the same learning purpose.

Still from the companion recovery film, showing a conversation in a correctional setting.
01 / Learn

Interactive
course

Teaching, media, decisions and practice organized into one learner path.

Open opioid course ↗
02 / Apply

Participant
workbook

Private reflection and usable prompts, with room to write rather than just read.

View 4-page excerpt ↗
03 / Reinforce

Facilitator
guide

The same learner pages translated into session flow, prompts and facilitation boundaries.

View 2-page excerpt ↗

Original Opioids & Your Brain workbook and guide excerpts. Film stills come from the related MOUD & Harm Reduction lesson. The Articulate course opens separately.

i.Teach a useful decision.

Move beyond terminology into noticing a trigger, choosing a response and planning a next step.

ii.Keep the learner human.

Use an adult voice and private reflection without demanding personal disclosure.

iii.Design for transfer.

Carry the same idea through independent learning, participant practice and a guided group.

Build walkthrough

What I was solving, what I built and what I left out.

Performance problem
Learners needed to recognize risk and choose a usable next step, not just remember definitions.
Design choice
A connected journey: short teaching, an original lesson film, private workbook practice and a matched facilitator route.
AI contribution
Bounded support for structure, alternatives and production checks inside a source-controlled review process.
What I rejected
Generic recall questions, unsupported claims, overly clinical language and activities that asked for disclosure without improving performance.

Program-level engagement evidence is reported below with its denominator and limits. I do not attach a broad metric to a single course unless the data supports that connection.

02 / Range of work

Different learners.
The same discipline.

Every project starts with the performance problem and ends with a delivery route people can actually use.

Reentry to Recovery · 3 years

Reentry, GED and workforce learning

Designed correctional and reentry education in Canva and Articulate across GED preparation, workforce integration, personal finance, parenting, recovery and practical life skills.

  • Bite-sized learning for limited-literacy contexts
  • Courses, worksheets, quizzes, surveys and certificate tracks
  • Facility delivery through video, PDF, URLs and LMS tools
System evidenceProgress tracking, certificates, assignments, reporting and facility-specific content routes.
Visit the public program ↗
Off the Record · program architecture

A learning and support ecosystem for public safety

Lead program design for a confidential, peer-driven wellness network serving corrections, law enforcement, military and other public-safety professionals.

  • Research translated into facilitator-led experiences
  • Facilitator training, on-demand resources and short-form learning
  • Privacy-aware LMS and aggregate outcomes strategy
My roleCo-founder and Chief Program Officer: program design, behavioral-health oversight and outcomes strategy.
See how OTR works ↗
Sanitorial · reusable product line

One learning system, multiple work environments

Built a repeatable sanitation-training framework that adapts shared standards to the decisions people make in different facilities.

  • Five published Articulate courses verified in the source library
  • Senior care, janitorial, food service, corrections and childcare tracks
  • One additional pet-care AI outline in development
Design moveReuse the research, assessment pattern and visual system while changing the scenarios and job context.

High-level inventory only. Proprietary course content and editable sources are not exposed here.

Interactive microlearning prototype

A click should change the thinking.

This small scenario demonstrates how I design feedback around a performance decision. It is built in HTML for this portfolio; production Storyline builds use variables, triggers, feedback states and completion gates.

Persona-ledLow stakesFeedback + retryKeyboard accessible
Product workflow / 01Maya has six minutes before her next customer call.

She completed the product course, but still needs help to finish the most common workflow. What should the learning team change first?

03 / The production system

Research first.
AI in the middle.
Judgment at every gate.

I do not hand an empty prompt to a model and hope it makes a course. I build the source environment, the design logic and the review system first.

01ResearchCurrent, authoritative sources
02Source mapClaims, limits and unknowns
03Performance mapLearner, workflow and outcome
04Design packageFlow, storyboard and media
05BuildStoryline, Rise and materials
06ReviewAgents, human SME and peer input
07QA + LMSBehavior, access and reporting
A / Research guardrails

The source pack comes before the prompt.

  • Prefer current sources from the past five years when the topic changes quickly.
  • Use primary, scholarly or authoritative guidance appropriate to the claim.
  • Keep a source hierarchy, claim log and explicit list of unknowns.
  • Separate fact, professional judgment, illustration and open question.
  • Define safety, scope, audience and excluded claims before drafting.
B / How AI fits

One source of truth. Several useful specialists.

I load the approved source pack, guardrails, voice rules and build schema into a Claude Project. I prompt Claude to shape the production package and the prompts used by supporting tools. ChatGPT specialists and Articulate AI help with bounded tasks. I accept, reject and revise the work before it moves forward.

What I reject: unsupported claims, polished-but-empty explanations, childish language, generic interactions, invented citations and anything that breaks the approved scope.

Claude Project
context + orchestration
→Articulate + specialist agents
bounded production
→Ashley
judgment + revision
C / Review bench

Agents disagree before the learner sees it.

Source fidelityInstructional designHuman languageClinical or domain safetyAccessibilityStoryline + LMS QA

When specialist judgment is needed, a qualified clinician or subject expert reviews the content. I call that peer review in the practical team sense, not academic journal peer review.

D / Human-language system

Plain does not mean childish.

My language guides use an adult, dignity-preserving baseline that can reach roughly a fifth-grade reading level when the audience needs it. The rules change with the learner, setting and emotional load.

Instead of

“Utilize adaptive coping mechanisms to regulate distress.”

Use

“Notice what is happening in your body. Choose one thing that helps you get steady enough for the next step.”

Reusable system

Built once, improved every cycle.

Prompt librariesDesign patternsStoryboard templatesHuman-language guidesSource registersQA checklistsVersion historyCompletion tests

The first benchmark: a 30-minute course rebuilt in one week while the reusable process itself was being created. Future-cycle savings are being measured rather than assumed.

Custom Storyline workflow

When the tool does not expose the door, I build a better handoff.

I developed a proprietary Storyline build workflow for situations where direct plugin access was not available. It converts an approved source package into a build-ready specification covering branches, variables, feedback states, trigger logic, accessibility, completion behavior and LMS acceptance tests.

The public version stays intentionally high level. It shows the architecture without exposing client material, source files or private prompts.

01 · Interaction mapDecision, consequence, feedback and retry
02 · State modelVariables, layers, triggers and revisit behavior
03 · Completion gateRequired action, not merely a visited slide
04 · Acceptance testsWrong paths, keyboard, mobile, resume and LMS reporting
04 / Learning systems & program architecture

The course is one part.
The system makes it usable.

Content architecture, delivery choices, access, learning paths and the information staff need to support the learner.

I think about the person using the material and the team responsible for delivering it.

My work extends into LMS planning and configuration: how content is organized, how learners reach it, how staff assign it, and how completion and updates are handled. Each delivery route has different requirements.

01Source control

Define scope, learner, owner and content boundaries.

02Journey map

Organize decisions and practice into a coherent sequence.

03Native build

Adapt media, interactions and checks to the platform.

04Learner access

Support the platform’s approved access route.

05Review & iterate

Use behavior, feedback and QA findings to guide updates.

Native-platform courses are designed for that environment rather than treated as generic files dropped into a catalog.

Conceptual delivery models for this portfolio. Not a production infrastructure diagram, security certification or claim that every integration is live. Private architecture, credentials and learner records are not included.

05 / Evidence with context

Useful numbers.
Honest boundaries.

I separate production evidence, engagement signals and actual outcomes. A large number without a denominator or a clear source is not a result.

81%

Completion in a defined sample

364 completions from 449 course starts across 18 Mind Rehab titles in an Edovo sample.

Scope and limits

Course-level ratio, not unique learners, not a clinical outcome and not evidence of causation. The widely distributed free Sleep course is excluded. The reporting date range and underlying export were not supplied with this portfolio build.

3 yrs

Reentry instructional design

Reentry to Recovery work across reentry, GED, workforce and life-skills education using Canva, Articulate and correctional delivery workflows.

User-supplied professional history; presented as experience, not a claim that Ashley created the entire catalog.
1 wk

Build plus process creation

A 30-minute course was rebuilt in one week while the reusable production and review workflow was being developed.

Self-reported internal build benchmark. Future-cycle time reduction is not claimed until it is measured.
5 + 1

Reusable Articulate product line

Five published Sanitorial courses verified in the source library, with one additional AI outline in development.

Inventory evidence only. Completion, transferability and learner outcomes are separate questions.
Ashley Miller, PMHNP-BC
The person behind the work

Ashley Miller, MSN, PMHNP-BC

Psychiatric nurse practitioner
Instructional designer · program builder

I want the learning to feel like someone understands the person on the other side of the screen.

My correctional psychiatric practice gives me a close view of the distance between knowing a concept and being able to use it in a difficult moment.

I bring that perspective to instructional design: deep research, adult language, useful decisions, a clear production system and delivery that survives contact with the real world.

My work includes Mind Rehab, Off the Record, three years of instructional design with Reentry to Recovery, and the Sanitorial learning product line.

Learning architectureJourneys, scenarios and performance outcomes
AI-assisted productionClaude Projects, ChatGPT agents and Articulate AI
AuthoringRise 360, Storyline 360 and Canva
Facilitated learningLive sessions, workbooks and facilitator guides
Learning systemsLMS structure, pathways, SCORM and QA
Content stewardshipSource maps, review gates and version history
Research deeply. Build clearly. Review honestly.

Let’s make the learning
worth someone’s time.

Original program page

Selected original source page.

MOUD & Harm Reduction: 60-second opening excerpt

First 60 seconds of the source lesson film. Original audio and on-screen captions are retained. A portfolio excerpt, not the complete lesson.

Open the 60-second excerpt ↗