Start with the decision your research needs to support and the people affected by it. That gives you a focused first question to test.
AI-Enabled Design Studio / Framing feedbackInteractive portfolio demonstration
AI-Coach Training Artificial Neural Network
Purpose: give instructional teams a consistent way to review AI coach replies. They score each reply, make an approval decision, and create a record for later training and evaluation.
My role: Review workflow, evaluation criteria, and AI behavior requirements.
Portfolio note: This is a wireframe reference to a deployed system. It preserves the review workflow while omitting proprietary content, branding, and production details.
Interactive walkthrough
Human review shapes the record.
Instructional designers rate AI coach replies and decide which records are ready for later training and evaluation.
Review creates training data
One reply. Three decisions.
Choose it, score it, save it.
Choose a reply
Review the reply.
Learner asked“What should I do first when framing the problem?”
Select a reply to begin.
Save when you are ready.
Factual accuracy5/5
Source fidelity5/5
Teaching value4/5
Clarity5/5
Representative backend payload
Displayed intentionally for this portfolio walkthrough. After the review is saved, this record is sent to the ANN training dataset, where it can be curated and prepared for a later training and evaluation cycle.