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JSTOR

JSTOR

A generative AI-powered research assistant integrated into JSTOR, designed to support students, faculty, and librarians in academic research. The tool provides article summaries, Q&A functions, and contextual insights to help users deepen understanding and accelerate the research process—especially for mobile-first learners.
ROLE

UX Research
UI Designer
Interaction Designer

DOMAINS

Visual Design
Heuristic Evaluation
Usability Testing

TOOLS

Figma
Adobe Illustrator
Adobe Photoshop

TIMELINE

3.5 Months

Problems ✋

The Gap Between AI Tool Design and Real User Behavior

The current JSTOR research tool assumes that users will complete full research workflows on mobile. However, most users—especially students—engage in skimming, quick discovery, and saving for later. This misalignment leads to frustration, abandonment, and underutilization of JSTOR's AI features.

Problem Statement⚡️

How might we align JSTOR’s AI-powered research tool with mobile users’ real behaviors while maintaining trust, accuracy, and depth in academic research?

Goals ✅

Improve the Usability of the AI research tool that will:

Accelerates article discovery through fast, low-friction browsing and summarization tools.
Supports cross-device continuity, enabling users to seamlessly switch between mobile and desktop research.
Builds trust in AI assistance by providing clear, transparent outputs and citations to maintain academic rigor.

{ Final Design & Key Features }

{ Next Steps }

{ Next Steps }

Future Exploration Needed

-Expand usability testing scope with a more diverse user base—including faculty researchers—and explore accessibility improvements based on WCAG guidelines to ensure inclusive design.

Refine cross-device experience

-Prototype full-screen chat and chat sync features to support deeper, uninterrupted research on mobile and desktop

{ Key Learnings }

{ Key Learnings }

Design decisions must be grounded in diverse user perspectives

This project highlighted the importance of including a wide demographic range—students, faculty, and librarians—in user research. Without this, we risk overlooking critical needs and behaviors, especially across different platforms and research habits.

User insights are essential to guide impactful design

We learned that meaningful design decisions rely on strong user feedback. When insights are limited or unclear, it's challenging to confidently prioritize features or resolve usability issues—reinforcing the need for well-structured, intentional research methods.

AI enhances research—but doesn’t replace human judgment

Through this project, we realized that while generative AI can accelerate certain tasks like summarization and discovery, it cannot replace the critical thinking and contextual understanding required in academic research. AI should be treated as a productivity aid, not a shortcut—and users still need time, guidance, and agency in the research process.

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Resume

LinkedIn

xinjianlidesign@gmail.com