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Ph.D Student
[email protected] Ph.D Advisers: Joseph J. LaViola Jr. Pamela Wisniewski |
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My research area is in the intersection between Human Computer Interaction and Artificial Intelligence. I am particularly interested in developing learning systems to improve the human learning experience. I am also interested in modeling and diagnosing user perceptions toward the learning goal. I received BS in Computer Science/ Software Engineering from Beijing University Of Posts and Telecommunication. I got my master in computer science from University of Central Florida. My master thesis was focus on developing an sketch-based demonstration program to help students understand knowledge representations of Boolean algebra.
In my Ph.D, I have been developing a sketch-based math tutoring system to guide students’ understanding toward the analytical geometry domain knowledge. The goal of my Ph.D is to prove its interaction and learnability and their inter-relations. In addition, I am further developing a Bayesian-based adaptation method to diagnose students’ understanding so as to tackle the learning uncertainty.
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AnalyticalInk: An Interactive Learning Environment for Math Word Problem Solving
Bo Kang, Arun Kulshreshth, Joseph LaViola Jr.
IUI '16 Proceedings of the 2016 ACM international conference on Intelligent User Interfaces.
[paper] [slides] [demo] [code] -
Mixed heuristic search for sketch prediction on chemical structure drawing
Bo Kang, Hao Hu, Joseph J LaViola Jr
Proceedings of the 4th Symposium on Sketch-Based Interfaces and Modeling 2014.
[paper] [code and data] -
User perceptions of drawing logic diagrams with pen-centric user interfaces
Bo Kang, Jared N Bott, Joseph J LaViola Jr
Proceedings of Graphics Interface 2013.
[paper] [demo 1, 2, 3 ] -
LogicPad: a pen-based application for visualization and verification of boolean algebra
Bo Kang, Joseph LaViola
IUI '12 Proceedings of the 2012 ACM international conference on Intelligent User Interfaces
[paper] [demo] [code]
The goal of this project is to handle the uncertainty of student understanding toward the analytical geometry domain knowledge. User data are captured from AnalyticalInk, a sketch-based math tutoring system to tutor analytical geometry typical problems. The methodology to use in this project is the inference upon the graphical model + the decision making using the markov decision process.
Simulation Matlab Code: Coming soon
Real Production code: Coming soon
*[Reinventing Explanation]
*[Thing Explainer: Complicated Stuff in Simple Words]
*[Multimodal Science Learning (NLP+Sketch)]
*[Learnable Programming]
*[Python Tutor: Visual Understanding]
*[Slate Math Learning]
*[Building a Modern Computer from First Principles]
*[Science of Problem Solving]
*[The only way to change school]