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…

In a sample of high school students (preliminary study: N = 224; main study: N = 235 and 194 at two time points in the beginning and the end of the school year), we developed and tested a self-report measure of attitudes toward creativity. Exploratory factor analyses identified and replicated one factor of positive attitudes toward…

Noncognitive constructs such as self-efficacy, social awareness, and academic engagement are widely acknowledged as critical components of human capital, but systematic data collection on such skills in school systems is complicated by conceptual ambiguities, measurement challenges and resource constraints. This study addresses this issue by…

The purpose of this paper is to confirm the factor structure, examine the invariance, and investigate the predictive validity using disciplinary data for 5262 high school students who completed the Early Identification System--Student Response (EIS-SR). The development and theory of the EIS-SR is discussed along with prior work. Building off of…

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…

Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…

Compared with admissions test scores, why are high school grades better at predicting college graduation? We argue that success in college requires not only cognitive ability but also self-regulatory competencies that are better indexed by high school grades. In a national sample of 47,303 students who applied to college for the 2009/2010 academic…

Admission criteria can be used to predict Saudi student performance in college, but significant differences across several studies exists. This study explores the predictive power of admission criteria for college assignment using King Saud bin Abdulaziz University for Health Sciences as a model. Scores from high school and standardized tests were…

This study aims to identify which socio-economic status (SES) variables have the best predictive validity for academic achievement, based on the international data sets of the Programme for International Student Assessment (PISA) in 2012, 2009, 2006, and 2003. From among 10 SES measures, two composite variables - Index of economic, social and…

Part II of the Houston Longitudinal Study on the Transition to College and Work (HLS) examined potential indicators of college enrollment school and district staff might use to identify and support students at risk of not attending college. The study used administrative data from the Houston Independent School District (HISD) and tracked two…

This report examined three potential indicators of college enrollment school and district staff might use to identify and support students at risk of not attending college: (1) Chicago: Designed to predict high school graduation; based on earning six course credits--the minimum to advance to the next grade in HISD--and having at most one semester…

These are the appendices for "Transitioning to College and Work. Part 2: A Study of Potential Enrollment Indicators," which examined potential indicators of college enrollment school and district staff might use to identify and support students at risk of not attending college. The study used administrative data from the Houston…

Early warning systems (EWS), in the context of secondary transition, are tools that analyze individual student-level data and estimate each student's risk of dropping out of school or completing school on time. Such tools generally consider three primary types of data--commonly referred to as the A, B, Cs: attendance/absence data,…

The Extended Project Qualification (EPQ) is available for students in Key Stage 5 (KS5), to be taken alongside other qualifications, such as A levels. It differs from most other academic qualifications at KS5 because it is not examined, but instead involves students undertaking an in-depth project in an area of their choosing. Students are…

Previous research has established that SAT scores and high school grade point average (HSGPA) differ in their predictive power and in the size of mean differences across racial/ethnic groups. However, the SAT is scaled nationally across all test takers while HSGPA is scaled locally within a school. In this study, the researchers propose that this…