Course Description Quality Assessment
Course: Creating Educational MicroSims with Generative AI Assessment Date: 2025-11-25 Skill Version: Learning Graph Generator v0.02
Elements Found
| Element | Status | Notes |
|---|---|---|
| Title | ✓ Present | "Creating Educational MicroSims with Generative AI" |
| Target Audience | ✓ Present | Teachers, Educators, and Instructional Designers |
| Prerequisites | ✓ Present | Basic programming knowledge (variables, control flow, loops) |
| Course Length | ✓ Present | 14-week undergraduate course, 3 credits |
| Main Topics | ✓ Present | 20+ distinct topic areas covered |
| Topics Excluded | Partial | Privacy/security mentioned as out-of-scope |
| Learning Outcomes Header | ✓ Present | "Upon successful completion..." format used |
| Remember Level Outcomes | ✓ Present | 4 specific outcomes |
| Understand Level Outcomes | ✓ Present | 5 specific outcomes |
| Apply Level Outcomes | ✓ Present | 5 specific outcomes |
| Analyze Level Outcomes | ✓ Present | 5 specific outcomes |
| Evaluate Level Outcomes | ✓ Present | 5 specific outcomes |
| Create Level Outcomes | ✓ Present | 5 specific outcomes including capstone |
| Descriptive Context | ✓ Present | Strong pedagogical framing |
Topic Areas Identified
The course description covers these major topic areas:
- p5.js Fundamentals - setup(), draw(), global variables, canvas
- Generative AI Tools - ChatGPT, Claude, LLMs for code generation
- Bloom's 2001 Taxonomy - Six cognitive levels for learning objectives
- MicroSim Types - p5.js, Mermaid.js, Chart.js, maps, timelines, networks
- MicroSim Architecture - Drawing region, control region, standard layout
- Responsive Design - Container width adaptation, relative positioning
- Metadata Standards - Dublin Core, JSON schemas, quality scores
- Accessibility - describe() function, screen reader support
- User Interface Design - Sliders, buttons, interactive controls
- Packaging Standards - index.md, main.html, style.css, script.js
- Pedagogical Theory - Cognitive load, UDL, scaffolding, PRIMM
- Prompt Engineering - Effective prompts, iterative refinement, skills
- Testing and Quality - 100-point quality rubric
- Integration - iframe embedding, MkDocs, HTML slides
- Professional Topics - Licensing, collaboration, user testing, equity
Estimated Concept Count
Based on the breadth and depth of topics covered:
- Foundation concepts: ~25 (programming basics, p5.js fundamentals)
- Core MicroSim concepts: ~40 (types, architecture, layout)
- AI/Genertic AI concepts: ~30 (prompting, refinement, tools)
- Pedagogical concepts: ~35 (Bloom's, cognitive load, UDL, assessment)
- Technical concepts: ~35 (responsive design, accessibility, metadata)
- Professional concepts: ~20 (licensing, testing, collaboration)
- Advanced/Capstone concepts: ~15 (portfolio, original design)
Total estimated: ~200 concepts (excellent alignment with target)
Comparison with Similar Courses
This course description is more comprehensive than typical:
- Instructional Design courses: Usually 80-120 concepts
- Web Development courses: Usually 100-150 concepts
- AI/ML introductory courses: Usually 120-180 concepts
This course combines elements from all three domains, making 200 concepts appropriate.
Strengths
- Excellent Bloom's Taxonomy alignment - Learning objectives explicitly organized by all six cognitive levels
- Comprehensive topic coverage - Addresses both technical and pedagogical aspects
- Clear learning outcomes - 29 specific, measurable outcomes
- Strong capstone integration - Create-level outcomes include portfolio and original design
- Practical focus - Specific tools and technologies named
- Accessibility consideration - Explicitly addresses inclusive design
Areas for Potential Improvement
- Topics Excluded - Could explicitly list topics NOT covered (e.g., "This course does not cover: server-side programming, database integration, mobile app development")
- Assessment rubrics - While quality scoring is mentioned, detailed rubrics could be expanded
Quality Score Calculation
| Element | Max Points | Score |
|---|---|---|
| Title | 5 | 5 |
| Target Audience | 5 | 5 |
| Prerequisites | 5 | 5 |
| Main Topics Covered | 10 | 10 |
| Topics Excluded | 5 | 3 |
| Learning Outcomes Header | 5 | 5 |
| Remember Level | 10 | 10 |
| Understand Level | 10 | 10 |
| Apply Level | 10 | 10 |
| Analyze Level | 10 | 10 |
| Evaluate Level | 10 | 10 |
| Create Level | 10 | 10 |
| Descriptive Context | 5 | 5 |
| TOTAL | 100 | 98 |
Assessment Result
Quality Score: 98/100
This course description is excellent and well above the 70-point threshold required for learning graph generation. The description provides sufficient detail to generate 200 high-quality concepts with meaningful dependencies.
Recommendation
✅ PROCEED with learning graph generation.
The course description is comprehensive, well-structured, and provides excellent coverage of both technical and pedagogical domains. The explicit Bloom's Taxonomy organization of learning objectives will facilitate accurate dependency mapping.