Integrating machine learning (ML) methods in educational research has the potential to greatly impact upon research, teaching, learning and assessment by enabling personalised learning, adaptive assessment and providing insights into student performance, progress and learning patterns. To reveal more about this notion, we investigated ML…

Although multiple organizational-level databases are frequently combined into one data set, there is no overview of the matching methods (MMs) that are utilized because the vast majority of studies does not report how this was done. Furthermore, it is unclear what the differences are between the utilized methods, and it is unclear whether research…

Foundations of statistics research aims to establish fundamental principles guiding inference about populations under uncertainty. It is concerned with the process of learning from observations, notions of uncertainty and induction, and satisfying inferential objectives. The growing interest in predictive methods in high-stakes fields like…

Research studies in Educational Data Mining (EDM) often involve several variables related to student learning activities. As such, it may be necessary to run multiple statistical tests simultaneously, thereby leading to the problem of multiple comparisons. The Benjamini-Hochberg (BH) procedure is commonly used in EDM research to address this…

We propose a new method for estimating school-level characteristics from publicly available census data. We use a school's location to impute its catchment area by aggregating the nearest "n" census block groups such that the number of school-aged children in those "n" block groups is just over the number of students enrolled…

The exponential growth of digital libraries and the proliferation of scholarly content in electronic formats have made data mining and information retrieval essential tools for effectively managing, organizing, and disseminating knowledge. This thesis provides a comprehensive analysis of the advancements and challenges in these fields, with a…

This study has three primary objectives. First to provide insight into possibilities for moderation/mediation analysis in education research by discussing analytical methods based on the counterfactual and developed in other disciplines. Second is to highlight specific issues related to mediation and the estimation of effects when the outcome is…

Given the hegemony of developmentalism in early childhood education and care, this article uses a poetic juxtapositional approach to bewilder Piaget's theory of cognitive development. Critical consideration of how the theory of cognitive development has contributed to the imagining of a universal, ahistorical child and childhood(s) are discussed…

Recent advances in computational linguistics and the social sciences have created new opportunities for the education research community to analyze relevant large-scale text data. However, the take-up of these advances in education research is still nascent. In this paper, we review the recent automated text methods relevant to educational…

Critical realism (CR) is a useful philosophical framework for social science; however, little guidance is available on which precise methods -- including methods of data collection, coding, and analysis -- are best suited to applied CR research. This article provides a concrete example of applied qualitative research using CR as a philosophical…

Missing data mechanisms, methods of handling missing data, and the potential impact of missing data on study results are usually not taught until graduate school. However, the appropriate handling of missing data is fundamental to biomedical research and should be introduced earlier on in a student's education. The Summer Institute for Training in…

This dissertation investigates several topics in state merit-based financial aid research. The main research content includes three separate studies, primarily using the administrative datasets from the Missouri Department of Higher Education. The first study is an empirical paper that examines the effects of the Missouri Bright Flight Scholarship…

The problem of mapping items to skills is gaining interest with the emergence of recent techniques that can use data for both defining this mapping, and for refining mappings given by experts. We investigate the problem of refining mapping from an expert by combining the output of different techniques. The combination is based on a partition tree…

The benefits of Big Data Analytics are cited frequently in the literature. However, the difficulties of implementing Big Data Analytics can limit the number of organizational projects. In this study, the authors evaluate business, procedural and technical factors in the implementation of Big Data Analytics, applying a methodology program. Focusing…

The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method. This comparison was made using both an equivalent…