Yuanlin Zhang

Professional Title
Associate Professor
Organization/Institution
Texas Tech University (TTU)
About Me (Bio)
Yuanlin Zhang is on the faculty of Computer Science at Texas Tech University. He is mainly interested in Knowledge Representation and Reasoning of Artificial Intelligence (AI) and computing education research. His recent interest is on logic based approach to developing curriculum integrating computing and STEM subjects and its impact on students’ learning. His work has been published in journals and conferences including AI journal, AAAI and IJCAI. He also won some awards including the AI journal classic paper award (2022).
Personal Website
http://redwood.cs.ttu.edu/~yuazhang/
Keywords
Computer Science
Statistics
Disciplinary Content Knowledge
Curriculum

Fostering Virtual Learning of Data Science Foundations with Mathematical Logic for Rural High School Students (Collaborative Research: Xing)

University of Florida (UF)
07/15/2022

This project addresses a major educational barrier, namely that rural students are less likely to choose a major in STEM and have far less access to advanced STEM courses taught by highly qualified teachers. The LogicDataScience (LogicDS) curriculum and virtual delivery are expected to relieve the resource constraints significantly and thus reach rural students. The strategy behind this curriculum development for data science explores the utility of emphasizing how the foundations of data science in computing, mathematics, and statistics are unified by mathematical logic. The project is studying the impacts of the new curriculum on students’ learning of computing, mathematics, and statistics.

Fostering Virtual Learning of Data Science Foundations with Mathematical Logic for Rural High School Students (Collaborative Research: Zhang)

Texas Tech University (TTU)
07/15/2022

This project addresses a major educational barrier, namely that rural students are less likely to choose a major in STEM and have far less access to advanced STEM courses taught by highly qualified teachers. The LogicDataScience (LogicDS) curriculum and virtual delivery are expected to relieve the resource constraints significantly and thus reach rural students. The strategy behind this curriculum development for data science explores the utility of emphasizing how the foundations of data science in computing, mathematics, and statistics are unified by mathematical logic. The project is studying the impacts of the new curriculum on students’ learning of computing, mathematics, and statistics.