Independent project · Learning experience design · Interactive prototype
MentorHub.
Designing for the space between mentoring conversations.
A learner-centered mentoring workspace that turns conversations into shared commitments, makes follow-through visible, and treats progress as something to support with evidence.
Fictional learners and temporary practice data. No login or real student records.
mentorhub / continuity
IllustrativeStart with the learner
Avery Brooks
Career exploration · fictional
01 / Listen
“I'm curious about design careers, but I'm not sure where to start.”
02 / Agree
Find two designers to contact for an informational conversation.
03 / Revisit
The commitment stays connected to the conversation.
Illustration of the design logic—not a screenshot. Open the live demo to interact with the product itself.
MY ROLE
Independent concept designer, learning experience designer, and application builder
DELIVERABLE
Working fictional-data mentoring workflow, responsive interface, and public demonstration
PROJECT STATUS
Public prototype · Real user research and educational validation still needed
01 / The challenge
Recording a meeting is not the same as supporting progress.
My experience in youth mentoring led me to ask how people could carry what matters from one session into the next. Logging contact is useful, but it does not itself preserve the learner's priorities, commitments, or emerging evidence.
MentorHub began as an exploration of support operations. When I returned to the early prototype, I reframed the problem around one purposeful mentoring cycle rather than a broad collection of dashboards.
This is a design hypothesis informed by experience, not a claim that I conducted a formal needs assessment or validated the tool with students.
02 / Product philosophy
Structure should support a relationship, not replace it.
Four educational commitments shaped the interaction, turning an abstract mentoring philosophy into visible product decisions.
01
Learner voice first
Check-ins begin with what matters to the learner, not a predictive label or the mentor's interpretation.
02
Accountable next steps
Every conversation produces an observable next action, a named owner, and a date to revisit the agreement.
03
Evidence before progress
A check-in does not automatically advance a goal. Progress updates need an explicit decision and supporting evidence.
04
Human judgment stays central
The system helps mentors remember, reflect, and follow through rather than replacing a relationship with automated assessment.
03 / Interaction design
One complete mentoring cycle, not another dashboard of activity counts.
A visitor can practice each stage with invented learners and see how decisions travel through the workspace. The interface centers continuity rather than treating check-ins as isolated transactions.
Prepare
Review a fictional learner's interests, current goals and previous commitment.
Design rationale: Continuity begins before the new conversation.
Listen
Record the learner's own perspective, self-reported mood, and the mentor's reflection.
Design rationale: Separate learner voice from interpretation.
Commit
Co-define an action, assign responsibility, and set a review date.
Design rationale: Give the next step an owner and a time to revisit.
Revisit
Complete or reopen the follow-up; return to the learner's recorded history.
Design rationale: Make follow-through part of the workflow.
Explore the actual product
Try the complete loop.
Choose Avery Brooks, load the fictional conversation, agree on an action, complete its follow-up, and open the learner history.
04 / Development history
The redesign began by reconsidering what was worth building.
Origin · 2025
The student-support question
My AmeriCorps mentoring experience prompted questions about how mentors could maintain contact, manage commitments, and reduce the friction between conversations. An early Next.js/Supabase concept explored the problem but remained unfinished.
Revival · 2026
From dashboard to mentoring loop
I revisited the original concept and narrowed the scope to one complete, learner-centered experience. Fictional profiles, reflective check-ins, accountable actions, and connected history replaced speculative product breadth.
Public edition · October 2026
A safer way to demonstrate the work
I separated the portfolio experience from legacy authentication and database routes. The independent static showcase has no accounts, backend APIs, or persistent student records, and was verified with browser tests.
An early concept explored AI-supported student services. The current public demonstration does not include autonomous coaching or predictive learner analytics; it prioritizes a legible, human-directed workflow.
05 / Implementation & evidence
Prove the prototype works. Be precise about what that proves.
I built a responsive Next.js/React interface with fictional learner profiles, guided check-ins, optional evidence-backed goal revisions, and agreed actions that can be completed or reopened.
The public showcase runs as a static Next.js 16 experience, isolated from historical authentication and database routes. There is no student record system, API, or persistent account. Practice notes stay in temporary browser memory and disappear when the page reloads.
Release checks exercise the entire mentoring journey, mobile layouts, staged dialogs, form validation, absent legacy routes, and automated accessibility rules. These are useful engineering signals, not proof that the design improves mentoring or learning outcomes.
06 / Reflection & validation
A working prototype is a beginning, not an educational outcome.
What this work demonstrates
- Turning youth-mentoring experience into a coherent learning-and-product design problem.
- Translating learner agency, feedback, reflection, and follow-through into product interactions.
- Combining instructional design, UX, responsive software and AI-assisted prototyping under intentional human direction.
- Separating an inspectable fictional-data prototype from unfinished legacy infrastructure.
What I would test next
- Observe consenting adult mentors completing realistic tasks with fictional records.
- Assess whether actions, ownership, review dates, and learner voice are easy to find.
- Complete a manual keyboard and screen-reader audit beyond automated scans.
- Test the mentoring value of the workflow before adding accounts, persistence, or AI features.
MentorHub is an independent working prototype—not a commissioned school product, validated intervention, or deployed institutional student-information system. All demo learners and metrics are fictional.