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…

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…

The COVID-19 pandemic has changed the university admissions and proficiency testing landscape. One change has been the meteoric rise in use of the fully automated Duolingo English Test (DET) for university entrance purposes, offering test-takers a cheaper, shorter, accessible alternative. This rapid response study is the first to investigate the…

Typically, only a minority of applicants to health professional training are invited to interview. However, pre-interview measures of cognitive skills predict for national licensure scores (Gauer et al. in "Med Educ Online" 21 2016) and subsequently licensure scores predict for performance in practice (Tamblyn et al. in "JAMA"…

Typically, only a minority of applicants to health professional training are invited to interview. However, pre-interview measures of cognitive skills predict for national licensure scores (Gauer et al. in "Med Educ Online" 21 2016) and subsequently licensure scores predict for performance in practice (Tamblyn et al. in "JAMA"…

Motivated by the multiple-measures clause of recent federal policy regarding student eligibility for alternate assessments based on modified academic achievement standards (AA-MASs), this study examined how scores or combinations of scores from a diverse set of assessments predicted students' end-of-year proficiency status on statewide achievement…

The goals of our study were to determine the predictive value and usability of an audience response system (ARS) as a knowledge assessment tool in an undergraduate medical curriculum. Over a three year period (2006-2008), data were collected from first year didactic blocks in Genetics/Histology and Anatomy/Radiology (n = 42-50 per class). During…

Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international…

This report presents data concerning the validity of a set of experimental computerized and paper-and-pencil tests for measures of on-job performance on global and job elements. It reports on the usefulness of 30 experimental and operational variables for predicting marks on 42 job elements and on a global criterion for Electrician's Mate,…