HPU PROFESSOR PUBLISHES CHAPTER ON MACHINE LEARNING

HPU Professor and Program Director of Data Science Chong Ho "Alex" Yu, Ph.D., recently co-authored a chapter titled, “Machine Learning for Analyzing the Relationship Between Well-Being, Academic Performance with Large-Scale Assessment Data” in the book Machine Learning in Educational Sciences. Information on the book can be found here.    

The chapter details how educational researchers navigate challenges in analyzing large-scale cross-cultural assessment data. Traditional statistical models struggle with the complexity of such big data, leading to issues like overfitting and instability. To address this, machine learning methods, including neural networks and XGBoost, partition the data into subsets, generating more robust models. The chapter illustrates this approach by analyzing the 2018 PISA data, demonstrating how machine learning enhances the effectiveness of educational research.

Yu is a three-time winner of the SAS faculty scholarship (2016, 2017 SAS Global Forum and 2017 Western Users of SAS Software Conference). In addition, he also won the Distinguished SAS Educator Award in 2021.

He is interested in a range of research areas, such as alternate and emerging research methods (e.g. DSML, exploratory data analysis, data visualization, and item response theory). Yu’s focus also extends to the philosophical aspects of research methodologies, including causal inferences, the nature of latent constructs, and abductive reasoning. Additionally, he explores cross-cultural comparisons in STEM education, involving assessments like PISA, PIAAC, and TIMSS.