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 paper examines and builds on an earlier contribution to this journal focusing on private supplementary tutoring -- widely known as shadow education -- in Francophone West and Central Africa. Drawing on wider literature about research methods in this domain, it examines the basis for the numerical estimates presented in the original article…

This study examined the predictive power of students' demographic characteristics, reading attitudes, school characteristics, and teacher-informed reading activities on three metacognitive reading skills: understanding and remembering, summarizing, and assessing credibility and their influence on 15-year-old students' reading scores. The dataset…

Interest in understanding creativity through Programme for International Student Assessment (PISA) data is on the rise, yet researchers face methodological challenges in synthesizing findings across various constructs, measures, and datasets. Meta-analysis--a valuable methodology for synthesizing quantitative data--remains underutilized in…

Increased use of computer-based assessments has facilitated data collection processes that capture both response product data (i.e., correct and incorrect) and response process data (e.g., time-stamped action sequences). Evidence suggests a strong relationship between respondents' correct/incorrect responses and their problem-solving proficiency…

The importance of family background in determining a student's academic achievement has long been acknowledged by researchers. Nonetheless, the effect of schooling on this relationship has also been widely investigated. Some studies have shown that family background plays a far stronger role while the effect of schooling is minimal; others have…

The OECD's PISA program assesses 15-year-old students globally in key competencies every 3 years, providing influential data on education quality and spurring policy debates. In the latest cycle, the innovation domain focused on creative thinking, assessing over 140,000 students across 60+ countries, in the largest study of adolescent creativity…

State education agencies are sitting on rich repositories of quantitative and qualitative assessment data. This document is designed to provide a conceptual framework and implementation guidance that can help agency leadership leverage and interrogate student performance data in systematic ways for reporting, outreach, and planning purposes. The…

Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…

The Program for International Student Assessment Young Adult Follow-up Study (PISA YAFS) is a follow-up study with students who participated in PISA 2012 in the United States. The study is designed to measure how performance on PISA 2012 relates to subsequent measures of outcomes and skills of young adults on an online assessment, Education and…

The advancement of technology has led to a growing interest in assessing scientific inquiry within digital platforms. This shift towards dynamic and interactive inquiry assessments enables researchers to investigate not only the accuracy of student responses ("product data") but also their steps and actions leading to those responses…

The process of quantification is a powerful development shaping many domains of life today. In the area of education, for example, performance measurement, testing and ranking have become common tools of governance. Quantification is not a neutral way of describing society, but a process of valorisation. It has three sociologically relevant…

The purpose of this study is to examine the effect of missing data imputation methods, namely regression imputation (RI), multiple imputation (MI) and k-nearest neighbor (kNN) on differential item functioning (DIF). In this regard, the datasets used in the research were created by deleting some of the data via the missing completely at random…

Background: In recent years, there has been generalized concern in all countries about increasing the younger population's level of financial literacy. However, there is still little evidence on the key factors explaining financial literacy, as the existing literature is inconclusive about this issue. This paper focuses on exploring whether…

There has been a growing research interest in the identification and management of disengaged test taking, which poses a validity threat that is particularly prevalent with low-stakes tests. This study investigated effort-moderated (E-M) scoring, in which item responses classified as rapid guesses are identified and excluded from scoring. Using…