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Feedback is an AI-powered platform designed to help workplace supervisors give more effective feedback to interns during work placements.
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Problem (what was solved)

The "Feedback" addresses the problem of workplace supervisors in Work‑Integrated Learning giving feedback that is rushed, unclear, and often not developmentally useful, due to time constraints, role ambiguity, limited pedagogical training, and the emotional difficulty of delivering corrective feedback. This leads to students receiving feedback that is generic, compliance‑oriented, and hard to act on.

The "Feedback" addresses the problem of workplace supervisors in Work‑Integrated Learning giving feedback that is rushed, unclear, and often not developmentally useful, due to time constraints, role ambiguity, limited pedagogical training, and the emotional difficulty of delivering corrective feedback. This leads to students receiving feedback that is generic, compliance‑oriented, and hard to act on.

process (what was done and why)

We used a hybrid Design Thinking + Lean UX approach: starting with a structured literature‑driven discovery and affinity mapping to deeply understand supervisor‑side constraints, then translating those insights into explicit functional and non‑functional requirements. From there we iterated through low‑, mid‑ and high‑fidelity Figma prototypes, using heuristic evaluation and expert/stakeholder feedback as our validation loop. This combination let us ground the product in established WIL and feedback‑literacy research while still moving quickly and refining the interaction model through successive design cycles.

We used a hybrid Design Thinking + Lean UX approach: starting with a structured literature‑driven discovery and affinity mapping to deeply understand supervisor‑side constraints, then translating those insights into explicit functional and non‑functional requirements. From there we iterated through low‑, mid‑ and high‑fidelity Figma prototypes, using heuristic evaluation and expert/stakeholder feedback as our validation loop. This combination let us ground the product in established WIL and feedback‑literacy research while still moving quickly and refining the interaction model through successive design cycles.

Design rationale (why the solution looks the way it does)

Focused the product narrowly on feedback and communication rather than a full LMS; embedded pedagogical scaffolding directly into supervisor workflows via goal‑setting modals, contextual Notes, and inline AI suggestions; positioned AI as an optional co‑pilot that enhances tone, clarity, and developmental focus without overriding human judgement; and added a Supervisor Contributions Dashboard to surface mentors’ effort and create tangible value for supervisors as well as students.

Focused the product narrowly on feedback and communication rather than a full LMS; embedded pedagogical scaffolding directly into supervisor workflows via goal‑setting modals, contextual Notes, and inline AI suggestions; positioned AI as an optional co‑pilot that enhances tone, clarity, and developmental focus without overriding human judgement; and added a Supervisor Contributions Dashboard to surface mentors’ effort and create tangible value for supervisors as well as students.

Watch the prototype and user flows

The video below is a walkthrough of the project, covering the problem framing, research insights, key screens, and end‑to‑end supervisor flows. Fast‑forward to [0:45 secs] to see the dashboard, Smart Feedback, Notes, and Messages flows in action.

The video below is a walkthrough of the project, covering the problem framing, research insights, key screens, and end‑to‑end supervisor flows. Fast‑forward to [0:45 secs] to see the dashboard, Smart Feedback, Notes, and Messages flows in action.

User Flows Across Core Features

Smart Feedback

A submission‑based view where supervisors read student work and write feedback side‑by‑side. Before writing, they set a feedback goal, and inline AI suggestions help make comments clearer and more constructive.

Smart Feedback

A submission‑based view where supervisors read student work and write feedback side‑by‑side. Before writing, they set a feedback goal, and inline AI suggestions help make comments clearer and more constructive.

Smart Messages

An email‑style space for performance and behavioural messages that aren’t tied to a single submission. While composing, supervisors can pull in relevant notes and use AI suggestions to make messages specific, balanced, and professional.

Notes

A private notes space for each intern, where supervisors log quick observations over time. These tagged notes give richer context for future feedback and power more personalised AI suggestions.

Supervisor Contributions Dashboard & Report

A lightweight analytics view that turns day‑to‑day mentoring into visible impact. It tracks key supervision metrics and generates an editable “Your Impact This Quarter” report supervisors can use in reviews and appraisals.

Design system
Design system
Marketing materials & Collateral
Marketing materials & Collateral

Biz Car

A5 - Flyer

A3 - Poster

Branding : Logo explorations
Branding : Logo explorations

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INSPIRED BY SWISS DESIGN
BUILT BY ME

THANK YOU

TOP

LINKEDIN
X(TWITTER)

0493940597

CONNECT.THEJAS@GMAIL.COM

I WOULD LIKE TO ACKNOWLEDGE THE GADIGAL OF THE EORA NATION, THE TRADITIONAL CUSTODIANS OF THIS LAND AND PAY MY RESPECTS TO THE ELDERS BOTH PAST AND PRESENT