AI-Powered Course Development Workflows
Designing and implementing AI-driven workflows to streamline course development, standardize outputs, and significantly increase production speed across programs.
Context
- Rapid development of fully online programs across schools
- High volume of courses requiring simultaneous development
- New instructional design team operating without established systems or templates
- Need for consistent quality across courses, faculty and subject matter experts
- Pressure to accelerate timelines without compromising instructional integrity
The Problem
- Course development was time-intensive and highly manual
- Inconsistent outputs across designers and subject matter experts
- Lack of standardized templates for lessons, assessments and rubrics
- Bottlenecks in drafting, review and revision cycles
- Limited scalability for growing program demands
My Role
As Senior Instructional Designer, I led the design and implementation of AI-powered workflows that would:
- Standardize course development outputs across programs
- Reduce time required to draft lessons, assessments and rubrics
- Improve consistency in tone, structure and instructional quality
- Support instructional designers and SMEs with scalable tools
- Accelerate production timelines while maintaining alignment with standards
Approach
1. Workflow Analysis and Opportunity Identification
I carefully mapped the end-to-end course development process and identified high-effort, repeatable tasks suitable for AI augmentation. Then, I prioritized areas with the greatest impact on time, quality and consistency.
2. Designing GPT-Based Templates and Tools
I developed custom GPT workflows to generate lesson structures aligned to institutional templates, assessment prompts and instructions and rubrics directly aligned to module and program outcomes.
I also built specialized GPTs to align course content with institutional style guides and production standards and to check alignment between learning objectives, instructional content and assessments. My GPTs also identified opportunities for authentic learning and assessment design.
3. Multi-Tool Experimentation and Optimization
I consistently tested and evaluated multiple AI platforms, including ChatGPT, Claude, Copilot, NotebookLM and others. I identified strengths and limitations of each tool for instructional design use cases and then selected and refined tools based on effectiveness, reliability and scalability.
4. Standardization of Outputs
I created consistent frameworks for lesson organization, assignment design and rubric structure and evaluation criteria. I also embedded institutional voice, tone, accessibility (UDL/WCAG) and quality standards into AI-generated outputs.
5. Integration into Development Workflows
I embedded AI tools directly into instructional design processes and enabled designers to generate high-quality first drafts rapidly, and to iterate and refine outputs efficiently. I reduced reliance on fully manual drafting while maintaining human oversight.
6. Continuous Improvement and Governance
I maintained and updated a centralized library of custom GPTs used by instructional design teams. I ensured that these tools reflected the most current institutional guidelines, best practices and approved resources. I also designed workflows to discourage or reject outdated or misaligned practices.
Impact
Institutional Impact
- Enabled scalable development of courses across multiple programs
- Supported rapid expansion of fully online offerings
- Established a repeatable, AI-enhanced development model
Operational Impact
- Significantly reduced time required for initial course drafting
- Increased efficiency across instructional design workflows
- Reduced bottlenecks in development and revision cycles
Quality and Consistency Impact
- Standardized structure, tone and instructional approach across courses
- Improved alignment with institutional templates, outcomes and accreditation expectations
- Strengthened quality control through AI-supported alignment checks
Tools & Capabilities Demonstrated
- AI integration in learning design workflows
- Prompt engineering & GPT system design
- Systems design & process optimization
- Instructional design at scale
- Change management & team enablement