The societal demand for graduates with expertise in Science, Technology, Engineering, and Mathematics (STEM) stands in contrast with prevalent issues of diminished interest among high school students in STEM subjects and low completion rates in STEM academic programs. In the Flemish educational context, heterogeneity in STEM preparedness of…

This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…

Test development is a complicated process that demands examining various factors, one of them being writing items of varying difficulty. It is important to use items of a different range of difficulty to ensure that the test results accurately indicate the test-taker's abilities. Therefore, the factors affecting item difficulty should be defined,…

Introduction: We report predictive validity of the newly defined Student Risk Screening Scale -- Internalizing and Externalizing (SRSS-IE 9, with 9 items) when used for the first time by middle and high school teachers from 43 schools. Methods: The sample included 11,773 middle school-aged students representing four geographic regions, and 7,244…

Educational leaders through the United States have prioritized developing integrated tiered systems to assist educators in meeting students' academic, behavioral, and social and emotional well-being learning needs in an integrated fashion (McIntosh & Goodman, 2016). This is an important shift away from traditional reactive models towards…