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Jagline (IUPUI Shuttle) App

Usability Audit & Improvement Roadmap

jagline.png

Project type → Mixed Method ResearchUsability Evaluation

Client → IUPUI & Miller Transportation

Industry → Campus Transportation

Role → UX Research & Strategy

Duration → 5 Weeks

Team → 5 UX Researchers

Overview

IUPUI LOGO.jpeg
BACKGROUND & CONTEXT
Jagline is a free, sustainable shuttle service provided by IUPUI Parking and Transportation to help students—and a handful of off-campus riders—navigate campus and nearby neighborhoods via a mobile app and website. As part of my master’s coursework (Team “Guardians of Jagline”), I led and performed key UX research and evaluation activities over 5 weeks.
PROBLEM
New and international students routinely miss shuttles because the app’s route names, ETAs, and alerts don’t match how they actually navigate campus.
MY ROLE
User Researcher & Evaluator: Planned and executed mixed‑methods study, moderated sessions, analysed data along with 4 peers
Strategist: Converted findings into a severity‑ranked backlog and phased roadmap
TOOLS
Miro · Excel · SPSS 

Research Overview

TARGET AUDIENCE
Students, Faculty & Campus Staff
PARTICIPANT DEMOGRAPHIC
  • 6 Novice Users (Recently moved to Indiana; 1-2 rides)
  • 5 Expert Users (Regular Jagline riders; ≥ 1 month use)
GOALS
  • Measure usability performance against accepted industry benchmarks.
  • Evaluate task‑completion success rates and average time on critical shuttle tasks.
  • Identify friction points, specifically steps in key flows that cause confusion or failure.
  • Generate actionable UX design recommendations ranked by impact and effort.
CRITICAL TASK TESTED
  • Locate the nearest shuttle stop
  • Check real‑time ETA and decide whether to wait or walk
Empty Bus

Methods & Process

Findings & Recommendations

#1 Search was not intuitive to find stops

​72% of participants couldn’t find routes via nearby landmarks, and route names alone proved unintuitive for newcomers.

​"If I want to go to the Kroger nearby, I have to hunt on the map"

Recommendation:

Short Term → Use Google directions API to surface landmark names in search results

​

Long Term → Let users input current & destination locations to auto-recommend nearest stops, plus “approaching stop” alerts

#2 Inaccurate Arrival Times

63% reported ETA inconsistencies: buses shown “arriving” had already left or were stuck, especially problematic in inclement weather

"It says arriving, but the bus just left"

Recommendation:

Short Term → Show bus state (“moving” vs. “stopped”) with timestamp

​

Long Term → Overlay real-time traffic density on routes via Google Location API

#3 No Current‑Location Pin

7 of 11 couldn’t locate themselves on the map, forcing them to cross‑reference Google Maps

“Where am I on this map?”

Recommendation:

Short Term → Sync app versions so all users see a GPS-based location pin

#4 Hidden Alerts & Notifications

Alerts about breakdowns or delays lived behind collapsed routes, leading one user to wait 30 minutes before discovering a “Jagline broken down” notification

“I waited 30 minutes before noticing the delay."

Recommendation:

Add a dedicated “Alerts” panel and push-notification opt-in for tracked Jaglines

Reflections

This project honed my ability to integrate qualitative insights (interview codes, affinity mapping) with quantitative metrics (SUS, task-success CIs) to drive prioritized design recommendations. It reinforced the need for consistency across app versions and the importance of “first-time user” guidance in public-facing transit apps.

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