Game-based learning (GBL) is increasingly recognized as an effective tool for teaching diverse skills, particularly in science education, due to its interactive, engaging, and motivational qualities, along with timely assessments and intelligent feedback. However, more empirical studies are needed to facilitate its wider application in school…

This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…

Background: We examined prevalence, incidence, and trajectory of obesity from kindergarten through grade 8 in one of the first states to implement annual surveillance. Methods: Participants included 16,414 children enrolled in kindergarten in Arkansas in 2004 with complete body mass index (BMI) measurements in kindergarten and eighth grade.…

Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…

Studies of student risk of school dropout have shown that present predictors of at-risk status do not accurately identify a large percentage of students who eventually drop out. Through the analysis of the entire Grade 1-12 longitudinal cohort-based grading histories of the class of 2006 for two school districts in the United States, the author…

Spurred by the "No Child Left Behind Act" of 2001, virtually every educational reform program now includes an accountability component that requires sound data collection and reporting (NCLB, 2002, section 101). Drawing from empirically based and theoretical literature in the field, this dissertation examines Adequate Yearly Progress…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…