The issue of model uncertainty has been gaining interest in education and the social sciences community over the years, and the dominant methods for handling model uncertainty are based on Bayesian inference, particularly, Bayesian model averaging. However, Bayesian model averaging assumes that the true data-generating model is within the…

Science, Technology, Engineering, and Math (STEM) skills are increasingly required of students to be successful in higher education and the workforce. Therefore, modeling assessment outcomes accurately, often using more types of student data to get a complete picture of student learning, is increasingly relevant. The Program for International…

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…

For assessment scales applied to different groups (e.g., students from different states; patients in different countries), multigroup differential item functioning (MG-DIF) needs to be evaluated in order to ensure that respondents with the same trait level but from different groups have equal response probabilities on a particular item. The…

The waning interest of students in science became a global concern. The purpose of this research was to translate, adapt, and validate the My Attitude toward Science [MATS] questionnaire instrument, which was used to measure students' attitudes toward science in the Indonesian context. We also investigated the items that contributed to gender and…

In this study, we take a critical look at the degree to which the measurement of bullying and sense of belonging at school is invariant across groups of students defined by immigrant status. Our study focuses on the invariance of these constructs as measured on a recent PISA administration and includes a discussion of two statistical methods for…

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…

The importance of enhancing social and emotional skills in educational settings has gained prominence, with many countries and organizations embracing the Social and Emotional Learning (SEL) framework to equip individuals with the tools needed for shaping a self-identity, emotional regulation, goal achievement, empathy, nurturing relationships,…