AI Implementation
Article
1. Iterative Testing Plan
From the beginning, I viewed the AI Healthcare Resource Center as an evolving product rather than a completed website. My testing plan followed an iterative cycle of design, review, feedback, revision, and refinement after each course milestone.
Each assignment served as an opportunity to test a different aspect of the website:
Phase 1: Evaluate the overall website structure, navigation, and organization.
Phase 2: Review individual pages for clarity, relevance, and alignment with course objectives.
Phase 3: Assess whether the content met the needs of the intended audience (healthcare educators, simulation professionals, and healthcare leaders).
Phase 4: Continue refining content as new assignments were added and the scope of the website expanded.
Future Testing: After the course, I plan to conduct usability testing with colleagues in healthcare simulation, gather feedback from educators and implementation leaders, and incorporate findings as the resource continues to grow.
Rather than conducting a single testing event, I intentionally incorporated continuous improvement throughout the development process.
2. Process and Decision-Making for the Testing Plan
Because the website is intended to become a long-term professional resource, I wanted testing to focus on usability and practical value rather than aesthetics alone.
My testing questions included:
Is the information easy to find?
Is the content understandable for users with varying AI experience?
Does the website solve a real problem?
Are the implementation resources practical and actionable?
Does each page contribute to the overall purpose of the website?
These questions were influenced by principles from Human-Centered Design, which emphasizes designing around user needs, and implementation science, which focuses on creating resources that can realistically be adopted in practice.
As the website evolved, I continuously revisited earlier pages to ensure consistency across content, terminology, and navigation.
3. How Testing Was Conducted
Formal usability testing was outside the scope and timeline of this course; therefore, I relied on several complementary forms of evaluation.
Testing included:
Continuous self-review after each assignment
Feedback received through instructor comments
Informal peer discussions during course activities
AI-assisted review using ChatGPT to evaluate readability, organization, and consistency
NotebookLM to verify that content aligned with assignment requirements and accurately reflected supporting literature
I also revisited pages after adding new content to ensure the overall user experience remained cohesive rather than feeling like a collection of unrelated assignments.
4. Test Results and Feedback
The feedback I received was primarily qualitative.
Positive Findings
The website developed into a cohesive resource rather than a collection of assignments.
Organizing information into themed sections improved navigation.
The implementation science focus differentiated the website from many AI resource websites that primarily emphasize technology.
The combination of blogs, resources, podcasts, and implementation frameworks created multiple ways for users to engage with the material.
Areas Identified for Improvement
Some pages initially contained more text than necessary and benefited from improved visual organization.
Several assignments overlapped in content and required consolidation to eliminate redundancy.
Additional visual elements such as infographics and diagrams would improve readability.
Future versions should include downloadable implementation tools, checklists, and case studies.
Although formal quantitative usability data were not collected, these observations informed subsequent revisions throughout development.
5. Incorporating Feedback
Feedback was incorporated continuously throughout the project.
Examples of revisions included:
Reorganizing the navigation menu into clearer categories.
Refining page titles to better communicate their purpose.
Adding introductory sections that explain why each topic is important.
Converting several assignments into blog posts to improve readability.
Expanding the Implementation Science section after recognizing it as a central theme across multiple assignments.
Improving consistency in formatting, typography, and page layout.
Adding curated references and additional learning resources to support continued exploration.
One of the most significant changes was shifting the website from an assignment repository into a professional resource center. Instead of simply posting coursework, I revised pages to create a cohesive learning experience that could continue to grow beyond the course.
6. Additional Information
One unexpected outcome of this project was that it became closely aligned with my doctoral research interests. As I progressed through the course, I realized the website could serve not only as an educational resource but also as a dissemination platform for future scholarship related to AI implementation in healthcare simulation.
The iterative development process reinforced an important lesson from both Human-Centered Design and implementation science: effective innovation is rarely created in a single iteration. Instead, meaningful solutions emerge through repeated cycles of feedback, reflection, and continuous improvement.
Although this prototype represents the end of the course project, I consider it the beginning of a larger professional initiative. Future iterations will include interactive implementation toolkits, additional educational resources, case studies, podcasts, implementation guides, and findings from my dissertation research, allowing the website to evolve alongside advances in artificial intelligence and healthcare education.