NoteLoom — AI Note Taking & Study Tool

An AI-powered web application designed to help students learn more efficiently by reducing cognitive overload. NoteLoom combines intelligent note summarization, flashcard generation, and progress tracking — all in one distraction-free workspace.

Research Foundation

We conducted 7 semi-structured interviews with students aged 18–35, supplemented by contextual observation of note-taking behaviors. Using Crazy 8s ideation, we generated and refined features around three core personas.

Key Design Decisions

• Separated "NoteLoom AI" from standalone feature buttons after testing revealed users couldn't find features nested inside a single AI panel
• Restructured note-title entry field after two rounds of feedback — users confused it with breadcrumb navigation
• Reformatted AI summaries to bullet points after Round 1; users found dense paragraph summaries harder to scan
• Added onboarding skip option after users expressed frustration being forced through setup

Outcomes

Three rounds of usability testing with 11 participants showed steady improvement across every metric. SUS scores rose from 78.5 → 78.3 → 97.5, with all Round 3 participants rating discoverability at the maximum scale.

MindLen — Wellness App

MindLen is a mobile wellness app designed to be a supportive daily companion — helping users understand their emotions, build small consistent habits, and stay connected with their mental well-being. The app uniquely integrates music with emotional reflection.

Key Screens & Features

• Home / Mood Check-In: Daily affirmation card, emoji-based mood selector, and custom emoji creator for nuanced emotional expression
• Meditate: Curated audio sessions (5–20 min) with a built-in player and illustrated meditation avatar
• Journal: Free-form entry with date/title fields, thought prompts, and quick-tap feeling tags
• Progress: Lightweight weekly tracker showing sessions, total minutes, journal entries, and mood history

MedCheck — OTC Medication Safety App

A 5-phase research project investigating the gap between how everyday users interpret risk information on over-the-counter medication labels versus clinically accurate expert models. Culminated in MedCheck — a high-fidelity prototype that reframes medication safety to match how users actually think.

5 Key Findings

• Warnings vs. Side Effects: 4/11 participants showed no distinction — treating both as interchangeable. Clinically, warnings mean "stop use" while side effects mean "expected outcome."
• Medical Terminology Barrier: 7/11 did not recognize MAOI — the most dangerous contraindication on any tested label, confirmed life-threatening by pharmacists.
• Selective Reading Behavior: 8/11 skipped labels entirely for familiar brands, relying on trust rather than clinical re-evaluation.
• Personal Relevance Filtering: 5/11 ignored warnings that didn't feel personally relevant, even conditions that could develop or affect people they care for.
• Dosage Misinterpretation: 4/11 read per-dose count only, ignoring timing intervals; 3/11 found daily limit math confusing — especially when sick.