Date of Graduation
Doctor of Philosophy in Computer Science (PhD)
Computer Science & Computer Engineering
Second Committee Member
Third Committee Member
gesture recognition, Microsoft Xbox, Kinect, programming, visual interface
Computer programming is an integral part of a technology driven society, so there is a tremendous need to teach programming to a wider audience. One of the challenges in meeting this demand for programmers is that most traditional computer programming classes are targeted to university/college students with strong math backgrounds. To expand the computer programming workforce, we need to encourage a wider range of students to learn about programming.
The goal of this research is to design and implement a gesture-driven interface to teach computer programming to young and non-traditional students. We designed our user interface based on the feedback from students attending the College of Engineering summer camps at the University of Arkansas. Our system uses the Microsoft Xbox Kinect to capture the movements of new programmers as they use our system. Our software then tracks and interprets student hand movements in order to recognize specific gestures which correspond to different programming constructs, and uses this information to create and execute programs using the Google Blockly visual programming framework.
We focus on various gesture recognition algorithms to interpret user data as specific gestures, including template matching, sector quantization, and supervised machine learning clustering algorithms.
Streeter, L. (2019). Teaching Introductory Programming Concepts through a Gesture-Based Interface. Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/3240