The present study compared the diagnostic accuracy of a single computer adaptive test (CAT), Star Reading or Star Math, and a combination of the two in a gated screening framework to predict end-of-year proficiency in reading and math. Participants included 13,009 students in Grades 3-8 who had at least one fall screening score and end-of-year…

Blended learning combines online and traditional classroom instruction, aiming to optimize educational outcomes. Despite its potential, student engagement with online components remains a significant challenge. Gamification has emerged as a popular solution to bolster engagement, though its effectiveness is contested, with research yielding mixed…

Computational Thinking (CT) skill was a part of the global framework of reference on Digital Literacy for Indicator 4.4.2, widely developed in mathematics and science learning. This study aimed to promote an assessment tool using a two-tier Computerized Adaptive Test (CAT). The study used the Design and Development Research (DDR) method with four…

Curriculum-based measurement of reading (CBM-R) is a common assessment educators use to monitor student growth in broad reading skills and evaluate the effectiveness of instructional programs. Computer-adaptive tests (CATs), such as Star Reading, have been cited as a viable option to formatively assess reading growth. We used Bayesian…

Over the past few years, several states have begun to explore or pilot different through-year assessments to serve as replacements to the traditional end-of-year summative assessments that are currently the predominant source of information used by states to meet federal accountability requirements. While there are several different assessment…

Star Math (SM) is a popular computer adaptive test (CAT) schools use to screen students for academic risk. Despite its popularity, few independent investigations of its diagnostic accuracy have been conducted. We evaluated the diagnostic accuracy of SM based upon vendor provided cut-scores (25th and 40th percentiles nationally) in predicting…

Due to low cost monte-carlo (MC) simulations have been extensively conducted in the area of educational measurement. However, the results derived from MC studies may not always be generalizable to operational studies. The purpose of this study was to provide a methodological discussion on the other different types of simulation methods, and run…

We report on an innovative computer-adaptive assessment, the Comprehensive Research-based Early Math Ability Test (CREMAT), using the case of 1st- and 2nd-graders' understanding of geometric measurement. CREMAT was developed with multiple aims in mind, including: (1) be administered with a reasonable number of items, (2) identify the level(s) of…

Background and Context: Valid assessment of understanding of programming concepts in primary school children is essential to implement and improve programming education. Objective: We developed and validated the Computerized Adaptive Programming Concepts Test (CAPCT) with a novel application of Item Response Theory. The CAPCT is a web-based and…

This study explored the validity of growth on two computer adaptive tests, Star Reading and Star Math, in explaining performance on an end-of-year achievement test for a sample of students in Grades 3 through 6. Results from quantile regression analyses indicate that growth on Star Reading explained a statistically significant amount of variance…

Prior research on the Measures of Academic Progress (MAP), a computer-adaptive test distributed by the Northwest Evaluation Association, has primarily focused on the Reading MAP for screening/benchmarking in elementary grades. The purpose of this study was to explore the functional form of growth and the extent to which student variability in…

The purpose of this study is to generate non-verbal items for a visual reasoning test using templated-based automatic item generation (AIG). The fundamental research method involved following the three stages of template-based AIG. An item from the 2016 4th-grade entrance exam of the Science and Art Center (known as BILSEM) was chosen as the…

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…

Low examinee effort is a major threat to valid uses of many test scores. Fortunately, several methods have been developed to detect noneffortful item responses, most of which use response times. To accurately identify noneffortful responses, one must set response time thresholds separating those responses from effortful ones. While other studies…

In large-scale educational assessment data consistent with a simple-structure multidimensional item response theory (MIRT) model, where every item measures only one latent variable, separate unidimensional item response theory (UIRT) models for each latent variable are often calibrated for practical reasons. While this approach can be valid for…