The main purpose of this study was to demonstrate the uses of regularization, a machine
learning technique, in exploring important predictors for online student success. We …

Background Large-scale international studies offer researchers a rich source of data to
examine the relationship among variables. Machine learning embodies a range of flexible …

This paper investigates a use case of robust anomaly detection applied to the scenario of a
photovoltaic production factory—namely, Enel Green Power's 3SUN solar cell production …

The purpose of this study was to explore variables related to school belonging from a holistic
perspective, including a large number of variables in one model, different to the traditional …

Abstract Background Life's Essential 8 (LE8) is a novel assessment of cardiovascular health
(CVH) by evaluating lifestyle, and reports of the associations between LE8 and urinary …

Promotion of Sports for All (SFA) can contribute to improving health and physical fitness
status, and ultimately national competitiveness. The main purpose of this study is to explore …

As a branch of statistical latent variable modeling, multidimensional item response theory
(MIRT) plays an important role in psychometrics. Multidimensional graded response model …

This study illustrated an exploratory study of LMS log data from undergraduate fully-online
flipped classrooms. A total of 237 students' instructional video watching behaviors were …

Among machine learning methods, penalized regression provides interpretable predictive
models, which increases its importance and usability in educational research in which …

Variable selection is one of the most pervasive problems researchers face, especially with
the increased ease in data collection arising from online data collection strategies. Machine …