In recent years, Computerized Multistage Testing (MST), with their versatile benefits, have found themselves a wide application in large scale assessments and have increased their popularity. The fact that forms can be made ready before the exam application, such as a linear test, and that they can be adapted according to the test taker's ability…

Computerized Adaptive Testing (CAT) is a beneficial test technique that decreases the number of items that need to be administered by taking items in accordance with individuals' own ability levels. After the CAT applications were constructed based on the unidimensional Item Response Theory (IRT), Multidimensional CAT (MCAT) applications have…

Examinations form part of the assessment processes that constitute the basis for benchmarking individual educational progress, and must consequently fulfill credibility, reliability, and transparency standards in order to promote learning outcomes and ensure academic integrity. A randomly selected question examination (RSQE) is considered to be an…

The COVID-19 pandemic has had a significant impact on high-stakes testing, including the national benchmark tests in South Africa. Current linear testing formats have been criticized for their limitations, leading to a shift towards Computerized Adaptive Testing [CAT]. Assessments with CAT are more precise and take less time. Evaluation of CAT…

In this article, the beta-binomial model for count data is proposed and demonstrated in terms of its application in the context of oral reading fluency (ORF) assessment, where the number of words read correctly (WRC) is of interest. Existing studies adopted the binomial model for count data in similar assessment scenarios. The beta-binomial model,…

For efficiency, Computerized Adaptive Test (CAT) algorithm selects items with the maximum information, typically with a 50% probability of being answered correctly. However, examinees may not be satisfied if they only correctly answer 50% of the items. Researchers discovered that changing the item selection algorithms to choose easier items (i.e.,…

Recently, adaptive test approaches have become a viable alternative to traditional fixed-item tests. The main advantage of adaptive tests is that they reach desired measurement precision with fewer items. However, fewer items mean that each item has a more significant effect on ability estimation and therefore those tests are open to more…

Questionnaires are by far the most common tool for measuring noncognitive constructs in psychology and educational sciences. Response bias may pose an additional source of variation between respondents that threatens validity of conclusions drawn from questionnaire data. We present a mixture modeling approach that leverages response time data from…

Analyses that reveal how treatment effects vary allow researchers, practitioners, and policymakers to better understand the efficacy of educational interventions. In practice, however, standard statistical methods for addressing Heterogeneous Treatment Effects (HTE) fail to address the HTE that may exist within outcome measures. In this study, we…