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…

Measuring the implementation fidelity (IF) or integrity of interventions is crucial, otherwise a positive or negative outcome cannot be interpreted. Direct and indirect methods of IF measurement tend to over-emphasize teacher behaviour. This paper focuses on IF measured by student behaviour collected through computers. Attainment was measured by…

This study examined whether web-based phonological awareness (PA) assessment in early childhood, specifically the year preceding formal schooling, could help educators reliably predict children's risk for reading difficulties in the first year of school. Ninety Australian children participated in several web-based PA tasks with a high priority…

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"…

Compressed time from matriculation to graduation prevalent in executive graduate degree programs means that traditional methods of identifying deficiencies in student writing during the course of study may not provide timely remediation enabling for student success. This study examined a writing-intensive, 10-month executive graduate degree…

This article addresses two unsolved measurement issues in dynamic problem solving (DPS) research: (a) unsystematic construction of DPS tests making a comparison of results obtained in different studies difficult and (b) use of time-intensive single tasks leading to severe reliability problems. To solve these issues, the MicroDYN approach is…

Two methods for estimating the reliability of a computerized adaptive test (CAT) without using item response theory are presented. The data consist of CAT and paper-and-pencil scores from identical or equivalent samples, and scores for all examinees on one or more covariates, using the Armed Services Vocational Aptitude Battery. (TJH)

A tailored testing model employing the beta distribution, whose mean equals the difficulty of an item and whose variance is approximately equal to the sampling variance of the item difficulty, and employing conditional item difficulties, is proposed. (Author)

This paper reports the results of using a three-layer backpropagation artificial neural network to predict item difficulty in a reading comprehension test. Two network structures were developed, one with and one without a sigmoid function in the output processing unit. The data set, which consisted of a table of coded test items and corresponding…

Describes a study to determine whether traditional paper-and-pencil tests or new computer-adaptive tests were better suited for assessing entering students at Santa Fe Community College, Florida. Focuses on teachers' attitudes toward computerized placement tests (CPTs), relationships between CPT scores and course grades, predictive ability of CPT…

The microcomputer has increased interest in performance testing, which samples what a person can do rather than what he or she knows. Conventional psychometric theory is based on knowledge tests, but in performance testing the unit of analysis is a trial, and it is unreasonable to assume that mean performance and interim correlations are…

Introduction: For postgraduate training of doctors there is a need for valid and reliable instruments to assess their daily performance. Various instruments have been suggested, some of which use incognito simulated patients (SPs). These methods are resource intensive. Computerised Case-based testing (CCT) is logistically simpler and may still…