The "Every Student Succeeds Act" requires that student's test scores be disaggregated by racial characteristics. Nevertheless, the author's recent study suggests that K-12 school principals may not intentionally think about race when they collect, interpret, analyze, and make decisions about data. By not disaggregating data by race,…

Few studies have explored approaches to teaching qualitative data analysis software (QDAS). As more researchers rely on self-teaching, more research into best practices for developing QDAS expertise is warranted. In this paper, we report our experience using the Five-Level QDA® method to guide the design of an introductory ATLAS.ti workshop. By…

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 article, we review the recent automated text methods relevant to educational…

The primary objective of the Remote Mentoring of Undergraduate Research Students (ReMentURS) workshop series is to design a remotely available professional development training that will provide rigorous research concept and skills introduction to incoming undergraduate research students. This pilot run eight-week remote learning workshop series…

Recent calls to reform undergraduate biology education, including Vision and Change in Undergraduate Biology Education, have led biology departments to examine their curriculum to determine the extent to which it aligns with Vision and Change content and competency recommendations. The recently released BioSkills Guide translates the broad Vision…

Geographic technologies and perspectives are important for understanding health issues because places and locations influence human health and diseases. Despite the increasing use of a geographic information system (GIS) in health research, and the explosion of new and emerging technologies, little is known about their potential as educational…

In this dissertation, I empirically investigate the changes in the market structure after new entrants, and how these changes affect the welfare of market participants. In Chapter 1, using records for public and charter schools in New York City, I empirically show that public schools adjusted after charter schools entered the neighborhood. I…

This 2015 document was developed to help technical assistance (TA) providers and state staff define and limit the scope of data analysis for program improvement efforts, including the State Systemic Improvement Plan (SSIP); develop a plan for data analysis; document alternative hypotheses and additional analyses as they are generated; and…

This article describes (1) the survey methodological and statistical characteristics of the nonrandomized method for surveying sensitive questions for both cross-sectional and panel survey data and (2) the way to use the incompletely observed variable obtained from this survey method in logistic regression and in loglinear and log-multiplicative…

We argue that the development of statistical literacy is greatly supported by engaging students in carrying out statistical investigations. We describe the use of driving questions and interesting contexts to motivate two statistical investigations. The PPDAC cycle is use as an organizing framework to support the process statistical investigation.

Recently, several authors have attempted to make the literature review process more transparent by providing a step-by-step guide to conducting literature reviews. However, although these works are very informative, none of them delineate how to display information extracted from literature reviews in a reader-friendly and visually appealing…

Educational data science is an emerging transdisciplinary field formed from an amalgamation of data science and elements of biological, psychological and neuroscientific knowledge about learning, or learning science. This article conceptualises educational data science as a biopolitical strategy focused on the evaluation and management of the…

Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…

Many interventions are characterized by repeated observations on the same individuals (e.g., baseline, mid-intervention, two to three post-intervention observations), which offer the opportunity to consider differences in how individuals vary over time. Effective interventions may not be limited to changing means, but instead may also include…

The purpose of this research is to examine the research that has been done on MOOCs by applying data mining and analytic approaches and to depict the current state of MOOC research. The text mining revealed four broad themes: (I) MOOCs as a mainstreaming learning model in HE, (II) motivation and engagement issues in MOOCs, (III) assessment issues…