DataBites and Knowledge Net

Investigating how informal interactions with AI-focused museum exhibits affects participants’ interest in and understanding of AI.

learning creativity

DataBites – hands-on activity about AI decision-making using patterns.

Knowledge Net – introduces semantic networks and AI organization of ideas.

Project Overview

👫 Who?
  • Designed for middle school students visiting a museum.
    • Assuming little to no knowledge on technical concepts.
  • Collaboratively designed by undergraduate, graduate, and PhD researchers at Northwestern University.
💡 What?
  • Two interactive prototypes:
    • DataBites: Allows visitors to create datasets, teaching them how AI uses patterns to make decisions.
    • Knowledge Net: Introduces the concept of semantic networks, visualizing how AI systems connect and organize information.
  • I led the signage and content design, crafting clear, engaging, and accessible messaging to guide visitor understanding and support the overall learning goals of the exhibits. This involves designing:
    • Informational posters
    • Bubble prompts to encourage engagement and discussion

Informational posters

Example Image

Guides parents and curious adults, highlighting what children are learning and offering ways to extend safe, engaging AI conversations beyond the museum.

Activity Bubble Prompt Example:

Bubble prompts

Example Image

Wall-mounted quick engagement prompts

Discussion Bubble Prompt Example:

🕰 When?

January 2024

Joined the Creative Interfaces Research and Design Studio

June 2024

First pop-up installation at MSI

May 2025

Completed second interation of the exhibits

Ongoing

User testing & feedback loops

📍 Where?
  • Designed at Northwestern University.
  • Intended for exhibit at the Museum of Science and Industry (Chicago).
  • Tested both on campus and at the museum.
❓ Why?
  • To demystify AI concepts for a general audience.
  • To foster critical thinking about how AI systems work — and don’t work — in real-world contexts.
  • To create inclusive and engaging STEM education experiences for all types of learners.

Learning Takeaways

  • I learned how to design content that breaks down complex AI ideas into engaging, age-appropriate experiences for diverse learners.

  • I discovered the value of speaking up and sharing my perspective, even as a junior team member without a traditional tech background.

  • I developed the skill of prioritizing feedback, learning that thoughtful revisions matter more than trying to incorporate every suggestion.

Next

Food-ordering app tackling food accessibility challenges through UX Design Course.