CoLearn — Helping Educators Connect with the People They Need Most

Concept Strategy, Prototyping, User Insight

Jan–Jun 2025

Project Overview

CoLearn is a platform concept developed in partnership with the Educators Alliance at the UC San Diego Design Lab. The team explored how to help educators overcome isolation and connect with peers who share their goals, challenges, and teaching philosophies.


My Role: Research lead, synthesis, prototyping (functional), concept direction, early product strategy
Tools: Figma, Miro, User Interviews, Survey Testing

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1. Background

Despite attending workshops, events, and conferences, teachers reported feeling isolated and unsupported in bringing new ideas into their classrooms. They wanted:

  • relationships built on shared goals

  • mentorship rooted in lived experience

  • a place to exchange practical ideas without noise


This became the foundation for CoLearn.

  1. The Problem

Educators are eager to innovate, but existing networks don’t help them form meaningful, sustained peer connections.


Key insights from 17+ interviews and conference observations:

  • “I want someone slightly more seasoned who hasn’t burned out — someone I can learn from.”

  • Teachers lack trusted spaces to collaborate.

  • Students feel their education doesn’t prepare them for real-world skills.

  • Systemic constraints leave educators without support for creative teaching.

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  1. My Role

I contributed across four core areas:


a) Research & Synthesis (Primary Lead)

  • Led educator interviews and synthesized insights across a complex stakeholder ecosystem.

  • Identified connection patterns, emotional needs, and breakdowns in current support systems.

  • Created artifacts (affinity maps, journey flows, empathy summaries) that shaped team direction.


b) Concept Development

  • Helped the team define CoLearn’s core value: relationship-first connections.

  • Pushed for an AI-assisted matching direction, clarifying how onboarding data could enable future personalization.

  • Identified positioning in the market and explored potential monetization models.


c) Functional Prototyping

  • Designed and built the functional onboarding prototype in Figma — not visually styled, but fully interactive.

  • This prototype captured user goals, teaching interests, and pain points through an 20-question flow that was later refined.

  • Served as the foundation for testing hypothetical AI-matching behavior.


d) User Testing

  • Distributed and tested the onboarding prototype with 7 educators across the U.S.

  • Gathered qualitative feedback and identified:

    • need to clarify mentorship vs. peer-to-peer matching

    • value of shared challenges in fostering trust

    • barriers older educators face with mobile-first tools


These insights reshaped the platform’s direction toward collaboration over mentorship.

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  1. Research Process

Methods

  • 17 educator/stakeholder interviews

  • CAYS Conference observations

  • Onboarding prototype test with 7 educators

  • Competitive landscape + market positioning analysis


Key Themes

  • Isolation + desire for sustained peer support

  • Teachers want “safe,” low-friction ways to meet others like them

  • Students crave relevant, real-world learning

  • Systemic constraints block innovation — making bottom-up support essential

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  1. Prototyping

I developed the first operational version of CoLearn’s onboarding flow — focused on:

  • capturing teaching goals

  • identifying emotional drivers (burnout, isolation, inspiration)

  • surfacing collaboration needs

  • collecting structured & unstructured data for theoretical AI matching


This prototype created the data model the AI concept would later rely on.

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  1. Testing & Iteration

From 7 user testing sessions:


What resonated:

  • CoLearn helps teachers find new ideas faster

  • Shared challenges build trust

  • A dedicated space “felt like a support system”


Changes made:

  • Wording updates to remove hierarchy assumptions

  • Streamlined onboarding steps (refined questions to 11)

  • Reframed platform from “mentorship” to “peer collaboration”

  • Validated value of AI-intentional matching (in theory)

  1. Final Concept

CoLearn is a simple, supportive platform with three core pillars:


1. Onboarding Survey

Captures role, interests, teaching challenges, and collaboration goals.


2. Intentional Matching

Hypothetical AI uses structured tags + open responses to pair educators based on:

  • shared values

  • complementary experience

  • similar challenges


3. Connection Tools

Lightweight conversation starters, connection cards, and messaging help educators build momentum without overwhelm.

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  1. Impact

This project strengthened my ability to:

  • design for complex social systems

  • synthesize conflicting stakeholder needs

  • translate research into functional product flows

  • test concepts with real users

  • articulate product strategy grounded in educator realities

What I Learned

“Designing for educators taught me that innovation is relational. Tools matter, but trust matters more — and systems only change when people feel supported enough to try something new.”

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