Data visualization is a core tenet of communicating measurement research and outcomes. Measurement professionals utilize data visualization in various phases of research, including exploration and communication. However, data visualization has not received enough attention in the measurement field. While it is true that many measurement graphics…

Building a better data culture can be the path to better results and greater equity in schools. But what do we mean by data? Your students are not just statistics. They aren't simply a set of numbers or faceless dots on a proficiency scale. They are vibrant collections of experiences, thoughts, perspectives, emotions, wants, and dreams. And taken…

This dissertation address two significant challenges in the causal inference workflow for Big Observational Data. The first is designing Big Observational Data with high-dimensional and heterogeneous covariates. The second is performing uncertainty quantification for estimates of causal estimands that are obtained from the application of black box…

The robustness of qualitative comparative analysis (QCA) results features high on the agenda of methodologists and practitioners. This article aims at advancing this debate on several fronts. First, in line with the extant literature, we take a comprehensive view on robustness arguing that decisions on calibration, consistency, and frequency…

Identifying motivation for enrollment in MOOCs has been an important way to predict participant success rates. But themes for motivation have largely centered around themes for enrolling in any MOOC, and not ones specific to the course being studied. In this study, qualitatively coding discussion forums was combined with topic modeling to identify…

Interaction is a much-claimed attribute of focus group research yet is often deficient in analysis when its essence can become lost. In this paper we aim to develop a flexible framework that can be operationalized and replicated when attempting to encourage and capture interaction. Working as outsider researchers with John Lewis & Partners…

The empirical study investigates what log files and process mining can contribute to promoting successful learning. We want to show how monitoring and evaluation of learning processes can be implemented in the educational life by analyzing log files and navigation behavior. Thus, we questioned to what extent log file analyses and process mining…

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…

Environmental education (EE) has received more and more attention worldwide. In Korea, there is a national consensus on the importance of EE; however, it is not as much of a priority as other education subjects or themes, based on annual survey results. This study asks how much value Korean citizens place on EE, revealing its value more…

We provide a novel characterization of augmented balancing weights, also known as automatic debiased machine learning (AutoDML). These popular "doubly robust" or "de-biased machine learning estimators" combine outcome modeling with balancing weights -- weights that achieve covariate balance directly in lieu of estimating and…

Researchers may have at their disposal the raw data of the studies they wish to meta-analyze. The goal of this study is to identify, illustrate, and compare a range of possible analysis options for researchers to whom raw data are available, wanting to fit a structural equation model (SEM) to these data. This study illustrates techniques that…

The significance of ethics in data science research has attracted considerable attention in recent years. While there is widespread agreement on the importance of teaching ethics within computing contexts, there is no clear method for its implementation and assessment. Studies focusing on methods for integrating ethics into data science courses…

Given the increased focus of educational research on what works for whom and under what circumstances over the last decade, educational researchers are increasingly turning toward mixture models to identify heterogeneous subgroups among students. Such data are inherently nested, as students are nested within classrooms and schools. Yet there has…

Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…

Postsecondary Institutions are under pressure to explain their costs. Noninstructional administrative staff represent a significant cost and number of people working in higher education. Postsecondary institutions hire noninstructional staff in response to their specific needs related to educational activity at the institution. Past research on…