Interactive Visualizations for Knowledge Building Communities

Lydia Cao, Marlene Scardamalia, Emily Liu


Knowledge Building Space Navigator (KBSN) is an AI-powered visualization tool designed to help research communities collaboratively explore, reflect on, and advance collective knowledge. The design is theoretically based on a camera-ready paper for the ISLS 2025 conference. My role focused on translating these complex concepts into a usable, explorable product.

My Role

Translating complex knowledge-building concepts into actionable product experiences.

This case study highlights my approach to turning high-level theoretical ideas into intuitive interaction models. I worked closely with researchers to understand the essence of the concepts (e.g., semantic density, cross-topic connections, potential collaboration networks), then mapped those into interactive visual components such as topic evolution flows, zoomable semantic maps, and researcher network views. My contribution lies in balancing mutiple version of conceptual fidelity with UX clarity, ensuring the tool remains rigorous for academic use while being accessible and actionable for users.

Problem framing

Demo video