Francis David
Learning Design Architect
AI-Prompting VILT SB Creation
Project Overview
Designing a governed AI workflow to support instructional design production at scale.
Designing the Framework
This framework was designed to support instructional designers in creating consistent, facilitation-ready VILT storyboards.
It embeds instructional principles, governance rules and delivery constraints directly into the AI prompting structure to support clarity, quality and scale.
This project focused on designing a governed AI prompting framework to support the production of delivery-ready Virtual Instructor-Led Training (VILT) storyboards. The framework helps instructional designers convert approved source content into clear, facilitation-ready narration and aligned visual guidance while maintaining instructional integrity.
Client Context
In large-scale VILT programs, storyboard creation is often time-intensive and inconsistent, relying heavily on individual designer interpretation. Variations in narration quality, visual alignment, and instructional sequencing can affect facilitation readiness and learner experience. This work addressed the need for a structured, repeatable approach to storyboard creation that supports speed and consistency without compromising instructional quality.
What this framework is (and isn’t)
- It is a production support framework for instructional designers, not a content generator.
- It embeds instructional design principles, governance rules, and delivery constraints directly into AI prompts.
Design Approach
I designed this framework by treating the AI prompt itself as an instructional design scaffold rather than a content generator. The structure intentionally constrains AI output to approved instructional inputs, ensuring alignment with learning objectives, syllabus requirements, and source content authority.
The prompt guides designers through a spoken-first design process, emphasizing clarity, pacing, and live delivery considerations. Instructor narration is shaped for teleprompter use, while visual guidance is designed to support—not compete with—spoken instruction.
Instructional design principles such as cognitive load management, sequencing, and learner focus are embedded directly into the prompt structure. This allows AI to accelerate production while preserving professional judgment and design discipline.
Key Components
Governed AI prompting framework for VILT storyboard creation
Learning-objective-aligned narration scaffolding
Spoken-first instructor narration guidelines
Visual guidance aligned to dual-channel learning principles
Validation checklist for facilitation and delivery readiness
Role & Contribution
I designed the overall prompting framework, instructional constraints, and validation logic. This included defining governance rules, shaping narration and visual standards, and ensuring the workflow reflected real-world instructional design and facilitation needs.
Outcome
The framework supports faster, more consistent VILT storyboard production while maintaining instructional fidelity and delivery quality. It demonstrates how AI can be integrated responsibly into instructional design workflows—as a production support tool that enhances efficiency without replacing instructional expertise.
Reflection
This work represents a shift from using AI as a content generator to using it as a structured design accelerator. By embedding instructional intent directly into the prompt, the framework reinforces clarity, consistency, and quality at scale.
Description
Personal Portfolio
5 december, 2025