NYU BetterNotes
Team project
Nanxi Qu — Project Management Lead | Prototype Developer | Research & Media Ideation
NYU BetterNotes is an AI-supported learning-design concept that connects note-taking with active review, moving beyond lecture transcription toward active processing. I led project management and developed the prototype with a team that translated research and media ideation into a web experience for structured notes, focused study, and reflection.
My contribution
- Led project management across research, design, and development phases.
- Developed the web prototype across dashboard, notes, study, and analytics.
- Contributed to research and media ideation on transformation, review, and reflection.
- Translated the team’s learning strategy into note-taking and review flows.
- Identified first-use confusion as a priority for learner-centered iteration.
Static prototype captures from the team’s published documentation. All on-screen statistics are illustrative prototype values, not measured learning outcomes. Select a screen to enlarge it.
- 01Learning challengeFrom recording information to working with it.
- 02ResearchLearning behaviors shaped the brief.
- 03Learning strategyThe Active Learning Loop.
- 04Prototype & iterationMaking the strategy tangible.
- 05ReflectionWhat I would carry forward.
Recording more is not the same as learning more.
The design challenge was to support what students do with their notes—not simply make notes easier to produce.
Our team focused on NYU students, especially undergraduates. The research described a familiar gap: students take notes, yet often return to passive rereading rather than actively reorganizing, recalling, or connecting ideas. We framed the opportunity as a learning behavior problem, not a feature checklist.
Let learning needs define the product.
The team combined a survey, interviews, and a literature review to understand note-taking and review habits.
From transcription to transformation
Passive recording and rereading appeared in the research. Our response was to explore prompts and tools that ask students to process ideas, not only save them.
Flexibility over one “best” method
Different learners need different structures. Template and page-style choices preserve flexibility rather than prescribing one universal note-taking format.
Reflection needs a visible place
Mixed confidence and difficulty reviewing suggested a need for metacognition. Study patterns and reflection became part of the design direction.
Build an Active Learning Loop.
Media ideation connected note transformation with retrieval practice, then extended the direction toward connections and reflection.
- Structure
Choose a note format that fits the material.
- Transform
Reorganize information and work with key ideas.
- Retrieve
Use review and flashcards to revisit knowledge actively.
- Reflect & connect
Notice study patterns and consider connections across subjects.
Strategy diagram synthesized for this case study from the team’s Media & Ideation and learning-design rationale.
The four ideation directions were active note transformation, retrieval practice and spaced review, cross-subject connections, and a metacognitive weekly note profile. They formed a learning strategy; the prototype made selected parts tangible rather than demonstrating every proposed idea as a finished feature.
Translate the strategy into an experience.
The web prototype connects an Academic Dashboard, My Notes editor, Study Mode, and Learning Analytics.
Make the important parts stand out.
Familiar editing tools let students structure notes, distinguish concepts, and mark what matters. In this example, multi-color highlights separate three ideas, while text color emphasizes a section label. Font, size, and heading controls offer other ways to organize a note.
My Notes · Flexible Editing
Adjust Text Size
Adjust text size for comfortable reading and clear emphasis.
Structure Your Notes
Organize ideas with titles, headings, and body text.
Format with Purpose
Use block quotes and inline code, or clear formatting to reset your text.
Support that stays beside your notes.
Three tools in the right sidebar help students refine their notes, keep key terms accessible, and return to important concepts without leaving their writing workspace.
Refine Your Notes
Get AI-generated feedback on clarity, structure, and completeness, alongside learning strategies, practical tips, and suggestions for improving your notes.
Keep Key Terms Within Reach
The system identifies important terms in your notes and collects them in an academic glossary. Add your own terms and annotations to build a reference you can return to while studying.
Revisit What Matters
Use system-generated key concepts and review prompts to revisit the content of your notes and guide your next study session.
Prototype screenshots show example AI-generated responses. Select a screen to examine the highlighted sidebar.
Prompts ask students to identify the most important concept, explain it to a classmate, and connect it to a real-world application. Alongside summaries, flashcards, and concept extraction, these prompts make the intended shift from collecting information to processing it visible.
Prepare, then focus.
Before writing, students choose a Cornell, Outline, or Blank template and a page style on the dashboard. The choice makes note structure intentional without prescribing one format.
Study Mode then creates a separate space for concentration, away from editing tools.
The gap between intention and first use.
In my reflection, I noted that features we found intuitive could confuse first-time users. That observation changed how I evaluated the prototype: a feature’s presence is not enough; students need to understand how it supports their learning.
A next iteration should observe how learners choose a template, move from writing into active review, and interpret study feedback. These are questions to investigate, not evidence of completed usability improvements or learning gains.
One workspace. Two appearances.
Four recorded views of the prototype’s light and dark appearances.
Design the learning behavior, not just the interface.
Three lessons I carry into future learning experiences.
Every feature needs a learning purpose.
I began by asking whether features worked. Research and media ideation taught me to ask what behavior each feature should change—and whether that behavior belonged in the learning strategy.
Watch learners, not our assumptions.
First-time confusion exposed the distance between design intention and use. Learner-centered iteration means observing that gap rather than imagining students will follow the path we expect.
Manage the work as a connected system.
Leading across phases made the relationship between research, ideation, and development concrete. The value of ADDIE and design thinking became clearer when new insights required us to revisit earlier decisions.
Sources & scope
This team-project account draws on the published research synthesis, Media & Ideation, design rationale, Final Product, and my reflection. Images reproduce published static captures; the live AI Studio app was not exercised for this case study. Evaluation planning is not treated as evidence of learning impact, and the documentation’s mock evaluation results are not presented as measured outcomes.