This article presents findings on the consequences of matrix sampling of context questionnaires for the generation of plausible values in large-scale assessments. Three studies are conducted. Study 1 uses data from PISA 2012 to examine several different forms of missing data imputation within the chained equations framework: predictive mean…

E. A. Hanushek points out in this commentary that applied researchers in education have only recently begun to appreciate the value of international assessments, even though there are now 50 years of experience with these. Until recently, these assessments have been stand-alone surveys that have not been linked, and analysis has largely focused on…

Semantic priming, the phenomenon that a target is recognized faster if it is preceded by a semantically related prime, is a well-established effect. However, the mechanisms producing semantic priming are subject of debate. Several theories assume that the underlying processes are controllable and tuned to prime utility. In contrast, purely…

Bayesian Knowledge Tracing (BKT) models were in active use in the Intelligent Tutoring Systems (ITS) field for over 20 years. They have been intensively studied, and a number of useful extensions to them were proposed and experimentally tested. Among the most widely researched extensions to BKT models are various types of individualization.…

Large-scale experiments are often expensive and time consuming. Although Massive Online Open Courses (MOOCs) provide a solid and consistent framework for learning analytics, MOOC practitioners are still reluctant to risk resources in experiments. In this study, we suggest a methodology for simulating MOOC students, which allow estimation of…

Curriculum-Based Measurement of Oral Reading (CBM-R) is often used to monitor student progress and guide educational decisions. Ordinary least squares regression (OLSR) is the most widely used method to estimate the slope, or rate of improvement (ROI), even though published research demonstrates OLSR's lack of validity and reliability, and…

Although many studies have found that children with learning disabilities (LD) are less liked by peers than children without LD, the results are not unequivocal. In the present study, we investigated the social status (in terms of likeability and popularity) of children with LD by considering peer academic reputation and peer reputation of teacher…

Educational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students' behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this…

Computer-based scaffolding plays a pivotal role in improving students' higher-order skills in the context of problem-based learning for Science, Technology, Engineering and Mathematics (STEM) education. The effectiveness of computer-based scaffolding has been demonstrated through traditional meta-analyses. However, traditional meta-analyses suffer…

Although ownership is acknowledged to exert a potent influence on various aspects of information processing, the origin of these effects remains largely unknown. Based on the demonstration that self-relevance facilitates perceptual judgments (i.e., the self-prioritization effect), here we explored the possibility that ownership enhances object…

Maori and Pacific students generally do not attain the same levels of tertiary success as New Zealanders of European descent, particularly in science, technology, engineering, and mathematics (STEM) subjects. Te Ropu Awhina (Awhina), an equity initiative at Victoria University of Wellington in New Zealand between 1999 and 2015, aimed to produce…

The aim of this study is to investigate interrelationships between overexcitability and learning patterns from the perspective of personality development according to Dabrowski's theory of positive disintegration. To this end, Bayesian structural equation modeling (BSEM) is applied which allows for the simultaneous inclusion in the measurement…

Competition judges are often selected for their expertise, under the belief that a high level of performance expertise should enable accurate judgments of the competitors. Contrary to this assumption, we find evidence that expertise can reduce judgment accuracy. Adaptation level theory proposes that discriminatory capacity decreases with greater…

Synthesizing results from multiple studies is a daunting task during which researchers must tackle a variety of challenges. The task is even more demanding when studying developmental processes longitudinally and when different instruments are used to measure constructs. Data integration methodology is an emerging field that enables researchers to…

Previous studies on discourse have employed a self-paced sentence-by-sentence paradigm to present text and record reading times. However, presenting discourse this way does not mirror real-world reading conditions; for example, this paradigm prevents regressions to earlier portions of the text. The purpose of the present study is to investigate…