AI-Assisted Instructional Design Tool — Vision Board

Project Overview

Designing a vision concept for a single, unified AI-assisted instructional design tool that supports instructional designers, QA reviewers, and stakeholders throughout the complete learning development lifecycle.

The vision explores how one shared system can enable teams to design, review, validate, and finalise learning projects collaboratively while maintaining instructional quality and governance.

Designing the Tool Vision

The vision defines a single workspace where all roles involved in instructional design work within the same system on the same project.

Rather than fragmenting work across tools, the concept positions AI as an assistive layer that supports structuring, validation, and quality checks as learning assets move from design through QA and review to final approval.

Client Context

Instructional teams often rely on disconnected tools for design, review, and quality assurance. This leads to versioning issues, repeated rework, and inconsistent application of instructional standards.

The client need is for a unified tool that allows designers, QA, and reviewers to collaborate within a single system, with shared visibility into instructional intent, decisions, and quality checkpoints.

What this tool vision board is (and isn’t)​

  • It is a vision board for a single, end-to-end instructional design tool, not multiple workflows.

  • It supports collaborative project completion across roles.

  • It embeds instructional rules, validation logic, and review checkpoints.

  • It is not an autonomous content-generation platform.

Design Approach​

The vision treats instructional design as a collaborative project lifecycle rather than a sequence of handoffs. Designers, QA reviewers, and approvers interact within the same tool, guided by shared instructional structures and standards.

AI is positioned as a governed support layer that assists with structuring content, checking alignment, and surfacing issues, while all instructional decisions remain visible, reviewable, and human-controlled.

Key Components

  • Single shared workspace for instructional projects

  • Role-based views for designers, QA, and reviewers

  • Governed AI assistance aligned to instructional rules

  • Built-in validation and quality checkpoints

  • Structured review and approval flows

  • Traceability across design and review decisions

Role & Contribution

I designed the overall tool vision, role interactions, and instructional governance logic.

This included defining how different roles collaborate within one system, identifying quality and validation touchpoints, and articulating clear boundaries for responsible AI use.


Outcome

The vision provides a clear conceptual blueprint for a unified instructional design tool that supports collaboration, quality, and scale.

It demonstrates how AI can enhance end-to-end learning development workflows without fragmenting responsibility or compromising instructional rigor.


Reflection

This work reflects a systems-level approach to instructional design tooling. By focusing on collaboration within a single environment, the vision prioritises clarity, accountability, and trust in AI-assisted learning design.