The use of multistage adaptive testing (MST) has gradually increased in large-scale testing programs as MST achieves a balanced compromise between linear test design and item-level adaptive testing. MST works on the premise that each examinee gives their best effort when attempting the items, and their responses truly reflect what they know or can…

Understanding the intraindividual relation between an individual's speed and ability in testing scenarios is essential to assure a fair assessment. Different approaches exist for estimating this relationship, that either rely on specific study designs or on specific assumptions. This paper aims to add to the toolbox of approaches for estimating…

PISA aims to serve as a "global yardstick" for educational success, as measured by student performance. For comparisons to be meaningful across countries or over time, PISA samples must be representative of the population of 15-year-old students in each country. Exclusions and non-response can undermine this representativeness and…

In this research, multistage adaptive tests (MST) were compared according to sample size, panel pattern and module length for top-down and bottom-up test assembly methods. Within the scope of the research, data from PISA 2015 were used and simulation studies were conducted according to the parameters estimated from these data. Analysis results for…

The PISA assessment 2022 of creative thinking was a moonshot effort that introduced significant advancements over existing creativity tests, including a broad range of domains (written, visual, social, and scientific), implementation in many languages, and sophisticated scoring methods. PISA 2022 demonstrated the general feasibility of assessing…

Common indicator-based approaches to identifying careless and insufficient effort responding (C/IER) in survey data scan response vectors or timing data for aberrances, such as patterns signaling straight lining, multivariate outliers, or signals that respondents rushed through the administered items. Each of these approaches is susceptible to…

International large-scale assessments provide cross-national data on students' cognitive and non-cognitive characteristics. A critical methodological issue that often arises in comparing data from cross-national studies is ensuring measurement invariance, indicating that the construct under investigation is the same across the compared groups.…

The increasing use of low-stakes international assessments highlights the importance of test-taking efforts. Previous studies have used self-reported and response time-based measures to examine this effort. Although differences between these measures have been suggested, their association with performances and potential gender gaps remains…

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…

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

This study aimed to compare key predictors of academic resilience in the distinctive socio-cultural contexts of South Korea and the United States, employing a machine-learning-based random forest technique. Using PISA 2018 data, we focused on students in the bottom 25% of family socioeconomic status, totaling 1,654 in South Korea and 1,175 in the…