Classification of Natural Language Descriptions for BKT in Minecraft | AIED2022

This video is a brief poster presentation for AIED2022. I would like to thank the National Science Foundation, the University of Illinois, AIED, and my collaborators: Frank Stinar, Haejin Lee, Jeff Ginger, and Chad Lane.

For our project we used machine learning to provide Bayesian Knowledge Tracing (BKT) for open-learner models and correctness feedback. This work is part of the What-if Hypothetical Implementations in Minecraft (WHIMC) server that is currently being used in the US and the Philippines. WHIMC is a National Science Foundation-funded research project and interdisciplinary collaboration between several organizations dedicated to cutting-edge and impactful informal learning.

The goal of WHIMC is to develop computer simulations that engage, excite, and generate interest and engagement in STEM. WHIMC leverages Minecraft Java Edition as a learning environment for learners to interactively explore the scientific consequences of alternative versions of Earth via “what if?” questions, such as “What if the earth had no moon?” or “What if the earth were twice its current size?” as well as other emerging astronomy inquires, like “What would it take to terraform mars?” or “How do we mine asteroids?” Kids get to explore these as aspiring scientists and engineers on an interactive server that changes to match their interests.

More info about WHIMC - https://whimcproject.web.illinois.edu
Video by Sam Hum - https://www.linkedin.com/in/samhum/

Видео Classification of Natural Language Descriptions for BKT in Minecraft | AIED2022 канала Sam Hum