I design human-centered digital experiences that simplify complex user workflows. As Lead UX/UI Engineer for Tails of Joy, I led the end-to-end UX research and web application design to facilitate virtual emotional support animal (ESA) therapy for K-8 students. By transforming qualitative research into an intuitive booking, volunteering, and donation platform, I delivered an accessible digital space to alleviate student anxiety and foster classroom wellness.
Role
Samira (UX Research Lead & Co-UI Engineer) | Jenny (Interaction Design Lead)
Timeline:
2021
Platforms
Responsive Web (Desktop & Mobile)
Focus
EdTech UX Research, Virtual Pet Therapy, Booking Architecture & Conversion
Tools & Research Methodologies: Axure, Miro, UserZoom, Figma, Keynote, Adobe Photoshop, Adobe Illustrator, Google Forms, Trello, Qualitative Student/Parent Interviews, Affinity Mapping, Persona Creation, User Flow Architecture, Information Architecture (Site Mapping), Usability Testing (Round 1 & 2), Low/Mid-Fidelity Wireframing
To address the nuanced emotional needs of remote K-8 students, I executed a structured 5-stage design methodology—moving systematically from empathetic discovery and qualitative research to high-fidelity delivery and iterative testing.
Research: Surveys, student interviews, and academic secondary research.
Analyze: Synthesizing data via affinity mapping, persona creation, and user flows.
Prototype: Mid-fidelity Axure interactive models for task validation.
Design: Responsive web UI execution and style tile creation.
Deliver: Usability testing, iteration, and design-to-dev handoff.
Conducting research with K-8 students required a delicate, child-centric approach. I conducted 6 direct interviews with students alongside parent observations, ensuring a relaxed environment. Grounded in academic case studies from Stanford University and Australian remote schools, this research validated how virtual pet interactions lower emotional guards.
"Establishing comfort is critical when interviewing children. Smiling, speaking slowly, and engaging parents first allowed kids to naturally share their feelings about classroom stress, reading focus, and favorite pets."
After gathering qualitative feedback from student interviews and parent surveys, I mapped the raw data into an Affinity Diagram in Miro. This process synthesized dozens of individual observations into core thematic clusters—revealing key emotional triggers, mental models, and feature expectations.
Anxiety & Focus Support: Students noted that reading to non-judgmental pets reduces stress, builds confidence, and aids concentration.
Social Connectivity: Animals served as a natural bridge to ease social anxiety and loneliness stemming from remote learning.
Transparent Animal Bios: Users expressed a strong desire to see detailed pet biographies, health standards, and treatment details before booking.
Flexible Engagement Options: High interest in selecting pet sizes, species filters, and exploring virtual "mystery animals" via live video sessions.
To identify market gaps and product opportunities, I evaluated 4 established emotional animal therapy providers (Pet Partners, UW Pet Therapy, Sirius Healing, Meghan Whitlock). I audited their onboarding flows, contact accessibility, image galleries, and hero section navigation.
Lack of Direct Onboarding: Existing competitors failed to offer streamlined digital onboarding or direct online booking pathways.
Absence of Specific Animal Bios: Platforms lacked individual pet profiles and health details to build user trust prior to scheduling.
Market Opportunity: Positioned Tails of Joy as the primary high-impact, user-expected solution featuring clear animal galleries and friction-free booking.
Based on research insights and affinity clustering, I finalized the primary educator persona—capturing the core goals and frustrations of managing distracted, anxious students in remote learning environments.
Goals: Transform student mood, alleviate classroom anxiety, and build a safe decompression routine.
Frustrations: Nervousness in students, lack of student engagement, and fragmented booking tools.
To ensure frictionless navigation for parents and educators, I structured 4 primary user flows—enabling smooth execution for booking appointments, exploring animal profiles, making donations, and signing up to volunteer.
Before building interactive prototypes, I sketched initial layout ideas to map core functionality. I then converted these sketches into mid-fidelity wireframes using Axure, focusing on structural clarity for booking forms, animal galleries, and donation pages.
Simplified Booking Sequence: Structuring the multi-step form to reduce drop-off.
Structured Animal Cards: Ensuring clear CTA buttons for viewing bios and scheduling.
Clear Value Incentives: Organizing the donation page layout to communicate impact clearly.
I conducted two rounds of usability testing (4 in-person sessions and 4 online UserZoom trials) to evaluate navigation efficiency and task success rates across booking, searching, and donating workflows.
Navigation Confusion: Users struggled with the term "Explore" in the top bar; updated to "Our Animals" for immediate clarity.
Donation Incentive Gap: The original donation page lacked organization; added visual reward tiers ($1 = 1 Star) and clear impact messaging.
Step 1 Ambiguity: In the booking flow, users were unsure whether images were clickable buttons; refined component states to guide action.
Transforming tested wireframes into an accessible web platform, I designed structured Product Details Pages (PDP) and a streamlined 3-step appointment flow to minimize drop-off for parents and teachers.
Recognizing that over 60% of parents access school communication platforms via mobile devices, I architected a touch-friendly, mobile-responsive layout for quick session bookings, donation management, and volunteer forms on the go.
Empathetic Research Foundation: Conducting child-centric interviews required building trust first, providing deep insights into post-pandemic student anxiety.
Frictionless Booking Pipeline: Transforming complex multi-step forms into a clear 3-step sequence directly reduced user drop-off during usability testing.
Multi-Device Accessibility: Designing responsive mobile interfaces ensured seamless scheduling access for busy parents and school educators.
AI Smart Matching Assistant: Implementing a conversational AI wizard to match students with therapy pets based on energy levels and anxiety triggers.
Predictive Scheduling Engine: Utilizing machine learning to suggest optimal decompression session times within school calendars.
Automated Feedback Sentiment Analysis: Leveraging NLP to analyze post-session teacher notes and automatically track emotional progress over time.