At Atomic Instructional Design, course design is never treated as a checklist of slides, objectives, and assessments. It is a structured journey that moves from purpose to performance.
This road map outlines the process I use to design learning experiences that are clear, engaging, accessible, and built for real-world application. Each step is intentional, from identifying the learner’s needs and defining measurable outcomes to developing story-driven content, building interactive practice, and evaluating impact.
My approach blends instructional design strategy, storytelling, accessibility, and practical development methods to create courses that do more than deliver information. They help learners make decisions, solve problems, and apply what they know when it matters most.
The 2025–26 Compliance Rebuild Plan provides a structured roadmap for redesigning the compliance training suite into a clear, consistent, accessible, and performance-focused learning experience. Using the ADDIE framework, the plan moves through analysis, design, development, implementation, and evaluation to align stakeholders, define standards, build engaging course materials, launch through the LMS, and measure long-term effectiveness. The goal is not simply to update required training, but to create compliance learning that helps employees understand expectations, recognize risk, make informed decisions, and apply what they learn in real workplace situations.
ADDIE Layout Plan:
2025-26 Plan for Compliance rebuild.
A – Analysis (Understanding needs, defining goals, and planning resources)
Phase 1 Strategy and Planning
Define the Vision and the Scope
Clarify the suite’s primary purpose.
Who is the audience? Are there any subgroups?
Outline the number of courses and the estimated length.
Stakeholder Alignment
Kickoff meeting with sponsors, SMEs, and project team.
Define success criteria & KPIs (Key Performance Indicators).
Establish the approval process and communication plan.
High-Level Roadmap
Create a development timeline for the suite.
Assign resources (ID, SMEs, Developers, etc.).
Plan review cycles.
D – Design (Structuring content, creating blueprints, and setting standards)
Phase 2 Design Framework
Instructional Design Blueprint
Select the course model (ADDIE, Agile)
Define visual/branding guidelines for the whole suite for consistency.
Establish interactivity standards and navigation logic.
Content Architecture
Create a Master Content Map to show how courses fit together.
Draft learning objectives for the suite and for each course and module.
Identify shared assets and reusable templates.
Prototype & Standards
Develop a visual and content style guide
Create a course shell in the authoring tool.
Produce a sample module for design approval.
D – Development (Producing materials, building courses, and assembling components)
Phase 3 Content Development
Create Storyboards/Scripts
Create detailed outlines for each course.
Include text, graphics, activities, and assessments.
Media Production
Develop graphics, animations, audio, and video assets.
Apply consistent formatting and branding across all modules.
Build interactive components (quizzes, drag-and-drop, branching)
Course Assembly
Build courses in the selected authoring tool.
Integrate all media, text, and interactions.
Ensure consistent navigation and user experience.
I – Implementation (Delivering the course to learners and ensuring readiness)
Deployment
Publish to the LMS
Configure course settings, metadata, and search tags.
E – Evaluation (Measuring effectiveness and identifying improvements)
Phase 4 Review and Quality Assurance
Alpha Review (Internal)
Instructional review for accuracy, clarity, and alignment with objectives.
Check accessibility and compliance requirements.
Beta Review
Collect feedback from SMEs, sponsors, and pilot users.
Apply revisions as needed
Quality Control
Test course for functionality.
Proofread and finalize all content.
Phase 5 Launch and Sustain
Evaluation and Maintenance
Track KPIs (completion rates, quiz scores, feedback).
Schedule periodic content reviews for accuracy and updates.
This Standard Operating Procedure outlines a structured and responsible approach to using AI throughout the Instructional Systems Design process. It demonstrates how AI can support survey development, evaluation, report writing, learning objective creation, course content development, image generation, and marketing while maintaining the instructional designer’s role as the final reviewer and decision-maker. The SOP emphasizes quality assurance, SME validation, clean data practices, accessibility alignment, and accuracy controls to ensure AI is used as an efficiency tool without replacing human judgment, instructional strategy, or content credibility.
Standard Operating Procedure (SOP)
Use of AI in the Instructional Systems Design (ISD) Process
1. Purpose
This SOP establishes standardized procedures for using AI tools, to support Instructional Systems Design (ISD) activities. The goal is to improve efficiency, maintain quality, and ensure accuracy across deliverables.
2. Scope
This procedure applies to all instructional designers utilizing AI tools to assist with:
Survey development and evaluation
Report writing
Learning objective development
Course content creation
Image generation
Marketing material development
3. Responsibilities
Instructional Designer (ISD):
Provide accurate inputs and documentation
Review and validate all AI-generated outputs
Ensure alignment with learning objectives and SME intent
Subject Matter Expert (SME):
Validate technical accuracy of AI-assisted content
Provide source materials and clarifications
4. Procedure
4.1 Using AI for Survey Development
4.1.1 Survey Creation
Prepare Terminal Objectives (TOs) and Learning Objectives (LOs).
Upload objectives into AI.
Prompt AI to generate a Kirkpatrick-aligned survey:
Specify level (e.g., Level 1, Level 3)
Define number of questions
Identify question types (e.g., multiple choice, open-ended)
Review generated survey for alignment and clarity.
4.2 Using AI for Survey Evaluation
4.2.1 Data Preparation Requirements
Ensure spreadsheet data meets the following standards:
Structure
One row = one record
One column = one variable
Headers in first row only
Formatting
No merged cells
No blank rows or columns
Single dataset per sheet
Data Consistency
Standardized date format (YYYY-MM-DD)
Numeric values without symbols
Consistent categorical values
Data Quality
Remove duplicates
Eliminate ambiguous entries
Handle missing data using consistent values (e.g., NA, NULL)
Data Design
Avoid nested or hierarchical structures
Keep metadata in separate documentation
4.2.2 Evaluation Process
Upload cleaned dataset into AI.
Prompt AI to analyze survey results.
Extract insights for reporting.
Validate findings for accuracy and completeness.
Note: Poor data quality results in unreliable analysis.
4.3 Using AI for Report Writing
Compile evaluated data into a single document.
Prompt AI with:
Report type (e.g., evaluation report)
Target audience
Desired tone (business, conversational, etc.)
Review output for:
Accuracy
Completeness
Alignment with stakeholder expectations
4.4 Writing Terminal and Learning Objectives
Draft initial objectives.
Input draft into AI.
Prompt AI to convert into SMART format.
Review and refine objectives for instructional accuracy.
4.5 Course Development Support
4.5.1 Content Structuring
Upload SME materials into AI.
Prompt AI to:
Create course outline (ILT or WBT)
Review outline before proceeding.
4.5.2 Content Development
Develop course section-by-section using AI assistance.
Prompt AI to:
Convert technical content into conversational format
Validate:
Completeness (AI may omit content)
Accuracy with SME review
4.6 Using AI for Image Generation
4.6.1 Prompt Development Standards
Include the following elements:
Subject clarity
Environment description
Composition and framing
Style and medium
Lighting and mood
Color palette
Narrative/action
Required inclusions/exclusions
Resolution requirements
4.6.2 Best Practices
Run image generation in a single session for consistency
Generate multiple variations
Use silhouettes or abstract visuals when consistency is required
4.7 Marketing Support
Provide course description to AI.
Prompt AI to generate taglines.
Review for:
Audience alignment
Clarity and tone
5. Quality Assurance and Validation
5.1 AI Usage Principles
AI is a drafting tool, not a source of truth
All outputs must be validated
5.2 Validation Process
Generate AI output
Structure and review content
Verify against trusted sources
Cross-check using alternate prompts/tools
Conduct SME or expert review
Finalize deliverable
5.3 Accuracy Controls
Require AI to cite sources when applicable
Identify and verify potential hallucinations:
Unsupported claims
Fabricated data
Vague references
5.4 Data Integrity Requirements
Clean, structured inputs are mandatory
Define accuracy criteria upfront:
Instructional alignment
Compliance (e.g., Section 508, WCAG)
Evaluation standards (e.g., Kirkpatrick Model)
6. Risk Management
AI outputs may omit or misinterpret content
AI lacks consistency in image generation
Human oversight is required for:
Medical, legal, and compliance content
Instructional accuracy
7. Key Takeaways
AI improves efficiency but requires structured inputs
Validation is mandatory at every stage
Clean data directly impacts output quality
Human review ensures reliability and credibility
8. References
Kirkpatrick Evaluation Model
Section 508 Compliance Standards
WCAG Accessibility Guidelines
This Instructional Design Process document outlines a structured approach for determining when training is the right solution and how to move from a performance need to a measurable learning experience. It emphasizes that effective instructional design is more than creating a PowerPoint or delivering information; it begins with identifying the root cause, conducting a needs analysis, defining clear goals and objectives, and selecting the right design framework, such as ADDIE, Dick and Carey, or SAM. This process demonstrates how I approach training as a strategic, learner-centered solution that aligns with organizational goals, supports performance improvement, and creates meaningful outcomes through analysis, design, development, implementation, and evaluation.
Instructional Design Process
Executive Summary
Contents
Training isn't just about creating a slide deck—it's about crafting an experience that ensures people learn, retain, and apply what matters most. The Instructional Design Process is like engineering for learning: a structured approach to break down complex tasks, align them with industry standards, and build solutions that fit real-world needs.
By analyzing the problem, designing focused materials, and iterating for effectiveness, this process transforms abstract goals into measurable results. It's the difference between clicking through slides and truly empowering people to perform better.
When a potential need for training is identified, it is essential to assess whether training is the appropriate solution systematically. The following structured process ensures that training initiatives are targeted, effective, and aligned with organizational goals:
Input Sources:
Training requests may arise from management, employees, compliance requirements, performance reviews, or observed gaps in performance.
Key Questions:
What prompted the need for training?
What are the symptoms (e.g., poor performance, compliance issues, customer complaints)?
Objective: Determine if training is the solution or if other interventions are more appropriate.
Steps:
Stakeholder Interviews: Gather insights from managers, employees, and stakeholders to understand the context.
Performance Analysis: Compare current performance with expected standards.
Root Cause Identification: Use tools such as the 5 Whys or Fishbone Diagram to pinpoint the underlying cause of the performance gap.
Key Questions:
Is the issue caused by a lack of knowledge, skills, or abilities (KSAs)?
Are other factors (e.g., unclear processes, insufficient tools) contributing to the issue?
Objective: Establish clear, measurable goals for the training.
Steps:
Define measurable performance outcomes.
Align training objectives with broader organizational goals.
Key Questions:
What specific skills or behaviors need improvement?
How will success be evaluated?
Objective: Explore non-training solutions if KSAs are not the root cause.
Examples of Alternatives:
Process improvements.
Implementation of new tools or technologies.
Enhanced communication or updated policies.
Key Questions:
Are there more cost-effective solutions than training?
Can the issue be resolved without additional instructional content?
Objective: Finalize the decision based on the needs analysis.
Steps:
Document analysis findings.
Present recommendations to stakeholders.
Outcomes:
If training is needed: Proceed with instructional design.
If training is not needed: Recommend alternative actions.
Objective: Transition into the design phase once training is confirmed as necessary.
Steps:
Assemble a design team, including Subject Matter Experts (SMEs).
Create a project timeline and resource allocation plan.
Conduct detailed task analysis to guide training development.
Once training is deemed necessary, instructional design frameworks such as ADDIE, Dick and Carey, or SAM guide the development process. Each model offers unique benefits based on project needs.
ADDIE (Analysis, Design, Development, Implementation, and Evaluation) is a foundational framework for designing effective learning experiences:
Analysis: Define learning objectives, target audience, and knowledge gaps.
Design: Draft content flow, instructional strategies, and assessment methods.
Development: Create instructional materials based on the design.
Implementation: Deploy the training to the target audience.
Evaluation: Assess the training’s effectiveness and refine it as needed.
This model emphasizes interdependent steps, focusing on alignment between goals, learners, and evaluation:
Identify instructional goals.
Conduct instructional and learner analysis.
Write performance objectives.
Develop assessments and instructional strategies.
Conduct formative and summative evaluations for refinement.
The Successive Approximation Model (SAM) is an agile approach suited for dynamic projects:
Preparation Phase: Define goals and scope.
Iterative Design: Rapid prototyping and collaborative feedback cycles.
Iterative Development: Incremental creation and refinement of content.
The selection of an instructional design model depends on project complexity and organizational needs. Whether following ADDIE, Dick and Carey, or SAM, the goal remains consistent: to create effective, learner-centered training that aligns with business objectives and drives measurable results. Organizations ensure their training initiatives are impactful and successful by systematically assessing training needs and adopting the appropriate design approach.
Traditional approaches to training, such as creating a PowerPoint presentation and delivering it to employees, may seem efficient but often fail to address the root causes of performance issues or meet organizational goals effectively. Here's why the systematic instructional design process stands apart:
PowerPoint presentations often focus on delivering information without addressing whether a lack of knowledge or skills is the real issue. The instructional design process begins with a thorough needs analysis to determine if training is necessary or if other interventions, such as process improvements or resource updates, are more appropriate.
Creating PowerPoints often lacks strategic alignment with business objectives. The instructional design process ensures that every training activity aligns with measurable goals, improving employee performance in ways that directly impact the organization’s success.
PowerPoint presentations typically present content in a one-size-fits-all format, which may not engage or address the needs of diverse learners. Instructional design frameworks (e.g., ADDIE, Dick and Carey, or SAM) tailor content, delivery methods, and assessment strategies to the target audience, ensuring a more engaging and effective learning experience.
While PowerPoints provide a basic framework for presenting information, they lack the depth and interactivity often required for effective learning. Instructional design involves creating robust materials—such as interactive e-learning modules, scenario-based learning, or hands-on activities—that enhance comprehension and retention.
PowerPoints rarely incorporate mechanisms to assess whether learners have achieved the desired outcomes. Instructional design emphasizes the development of performance objectives and aligned assessments to measure success, providing actionable data to improve the training program.
A PowerPoint-based approach often ends with the delivery of the presentation, leaving no room for evaluation or refinement. Instructional design includes formative and summative evaluations to ensure the training is effective, allowing for continuous improvement based on feedback and results.
While PowerPoint presentations can be a useful tool within a training program, they are not a substitute for a structured instructional design process. The systematic approach ensures that training is not only engaging but also effective, targeted, and aligned with organizational objectives. By addressing root causes, customizing content to the audience, and evaluating outcomes, instructional design delivers meaningful results that go far beyond what a standalone PowerPoint can achieve.