Educational data mining (EDM) has been a rapidly growing research field over the last decade and enabled researchers to discover patterns and trends in education with more sophisticated methods. EDM offers promising solutions to complex educational problems. Given the rapid increase in the availability of big data in education and software…

The purpose of this article is to introduce and review the capability and performance of the Stata item response theory (IRT) package that is available from Stata v.14, 2015. Using a simulated data set and a publicly available item response data set extracted from Programme of International Student Assessment, we review the IRT package from…

In this study, the aim was to construct a significant structural measurement model comparing students' affective characteristics with their mathematic achievement. According to this model, the aim was to test the measurement invariances between gender sub-groups hierarchically. This study was conducted as basic and descriptive research. Secondary…

Methods for detecting differential item functioning (DIF) and item bias are typically used in the process of item analysis when developing new measures; adapting existing measures for different populations, languages, or cultures; or more generally validating test score inferences. In 2007 in "Language Assessment Quarterly," Zumbo…

Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…

This study aims to analyse the relationship between students' mathematics achievement in Programme for International Student Assessment (PISA) 2012 and the instructional climate-related factors in the index of principals' perceptions (learning hindrance, teacher morale and teacher intention). As preliminary analysis procedure, the chi-squared…

When dealing with missing responses, two types of omissions can be discerned: items can be skipped or not reached by the test taker. When the occurrence of these omissions is related to the proficiency process the missingness is nonignorable. The purpose of this article is to present a tree-based IRT framework for modeling responses and omissions…

Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and…

In this paper, we develop an information distortion model (IDM) of social class differences in self-beliefs and values. The IDM combines psychological biases on frame-of-reference effects with sociological foci on ability stratification. This combination is hypothesized to lead to working-class children having more positive math self-beliefs and…

This article focuses on analysing the effect of educational differentiation policies of OECD educational systems on socioeconomically disadvantaged students, based on data from PISA 2009. The analysis is conducted on the basis of a definition of two subgroups of disadvantaged students: those that achieve high scores, and those obtaining scores…

This study uses hierarchical linear modeling to examine the influence of a range of factors on the science performances of Hong Kong students in PISA 2006. Hong Kong has been consistently ranked highly in international science assessments, such as Programme for International Student Assessment and Trends in International Mathematics and Science…

The author sought to investigate the effects of inquiry-based science instruction on science achievement and interest in science of 5,120 adolescents from 85 schools in Qatar. Results of hierarchical linear modeling analyses revealed the substantial positive effects of science teaching and learning with a focus on model or applications and…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…