University of Florida
Knowledge tracker system
KNOWLEDGE TRACKER
The Knowledge Tracker project addresses a critical need in modern education by providing students with a powerful tool to log their day-to-day activities and gain valuable insights into their learning journeys. In an era where educational data is crucial, this system offers a user-friendly platform for students to record their activities and visualize them in the context of topics covered each week. Knowledge Tracker not only enhances comprehension but also streamlines the categorization of daily prompts. This innovative project is designed to empower students, making education more transparent, engaging, and impactful, ultimately shaping the future of learning.
ABOUT
The Knowledge Tracker project is a collaborative endeavor developed in partnership with Texas A&M University, aimed at revolutionizing the educational experience. Currently deployed across 15 school districts, this innovative system empowers students to seamlessly log their daily activities and witness them visualized in terms of the topics they’ve covered during the week. By providing a dynamic and intuitive interface for exploring related subtopics, Knowledge Tracker significantly enhances user engagement and comprehension. Knowledge Tracker is poised to transform the way students interact with their learning journeys, making education more transparent and engaging than ever before.
Year
2023
Affiliation
University of Florida
Services
Web Design
Project
Full-Stack Website
Description
The Knowledge Tracker project, developed in collaboration with Texas A&M University and deployed in 15 school districts, enables students to log daily activities and visualize weekly topics. Using advanced NLP and BERT-based topic modeling, it offers transparency in learning patterns, streamlining the assessment of 300+ daily prompts and reshaping education.
I led the GPT 3.5 Turbo API integration, improving accuracy by 30%, and implemented BERT-based modeling. Using Flask, Node.js, and D3.js, I reduced response times by 25% and enhanced user engagement by 50%. My role streamlined the project, showcasing ML and NLP expertise for efficient prompt processing and precise categorization.