vERA

VIRTUAL EXPERIENTIAL RESULTS AGENT - Reflect • Apply • Measure Growth

Vera is an AI reflection coach designed to make learning visible & measurable.
Built with Kolb’s Experiential Learning Cycle and the science of self-efficacy, Vera guides learners through conversations that reveal what they learned, how they applied it, and how confident they feel moving forward.

At the end of each reflection, Vera calculates a Learning Impact Score (LIS) — a simple, evidence-based measure of growth that goes beyond attendance or completion.

AI can’t replace reflection — but it can help us see it.
A prototype for making learning visible through empathy and evidence.

Try VERA in the GPT store

Why I Built Vera

I created Vera — the Virtual Experiential Results Agent — to answer a question that’s guided much of my work as an educator and instructional designer:
How do we make learning visible, measurable, and deeply human?

For years, I watched students and professionals grow in ways that traditional assessments could never capture. They gained confidence, resilience, and voice — but those transformations disappeared in spreadsheets and completion data. Reflection, the heartbeat of real learning, too often became an afterthought.

I built Vera to change that. She guides users through a simple, empathetic conversation grounded in Kolb’s Experiential Learning Cycle — helping them describe what they learned, how they applied it, and how confident they feel moving forward. From those reflections, Vera calculates a Learning Impact Score (LIS), turning metacognition into measurable insight.

But Vera is more than a tool. She’s a prototype for what I believe is the future of learning design: experiences that honor both data and humanity. She demonstrates that AI doesn’t have to replace educators — it can amplify reflection, empathy, and agency.

Building Vera allowed me to merge everything I value — the empathy of teaching, the rigor of instructional design, and the storytelling of reflective practice. She’s not just a project; she’s a manifestation of the kind of learning I believe in: self-aware, evidence-based, and deeply personal.

How vera works

I wanted to give learners a way to see their own progress — to translate reflection into visible evidence of growth.
— Hannah Shambley

Guided Reflection: Vera uses Kolb’s Experiential Learning Cycle to prompt reflection and insight.

Learning Impact Score (LIS): Vera quantifies reflection depth, application, and confidence into a simple 1–5 score.

Personalized Summary: Each session ends with a growth summary and next-step suggestion.

Design framework

The Learning Science Behind Vera

Vera’s design integrates evidence-based frameworks:

  • Kolb’s Experiential Learning Cycle — experience, reflection, conceptualization, experimentation

  • Bandura’s Self-Efficacy Theory — mastery and confidence as learning drivers

  • Bloom’s Taxonomy — reflection verbs aligned to cognitive growth

  • SEL Competencies — fostering self-awareness and resilience

Vera is built with OpenAI’s GPT-5 model and a curated knowledge base of learning theory, empathy, and instructional design principles.