To conduct a multilevel meta-analysis of multiple single-case experimental design (SCED) studies, the individual participant data (IPD) can be analyzed in one or two stages. In the one-stage approach, a multilevel model is estimated based on the raw data. In the two-stage approach, an effect size is calculated for each participant and these effect…

Many ethical concerns in online big data research stem from a pervasive assumption that data are disembodied and place-less. While some scholars have begun addressing the ethical dilemmas of big data, few offer approaches or tools that fully grapple with the situatedness of online data and its ethical implications. We draw on feminist new…

The aim of this paper is to introduce a software that is appropriate for the generalizability theory for not only balanced but also unbalanced data sets. Because it is possible to have unbalanced data sets while conducting a study, the researchers have devised an easy solution, other than deleting data, to balance the design to cope with this…

Interest in the regression discontinuity (RD) design as an alternative to randomized control trials (RCTs) has grown in recent years. There is little practical guidance, however, on conditions that would lead to a successful RD evaluation or the utility of studies with underpowered RD designs. This article describes the use of RD design to…

This is the decade of data analytics and big data, but not everyone agrees with the definition of big data. Some researchers see it as the future of data analysis, while others consider it as hype and foresee its demise in the near future. No matter how it is defined, big data for the time being is having its glory moment. The most important…

Salivary cortisol is often used as an index of physiological and psychological stress in exercise science and psychoneuroendocrine research. A primary concern when designing research studies examining cortisol stems from the high cost of analysis. Planned missing data designs involve intentionally omitting a random subset of observations from data…

Professors Richard J. Murnane and John B. Willett set out to capitalize on recent developments in education data and methodology by attempting to answer the following questions: How can new methods and data be applied most effectively in educational and social science research? What kinds of research designs are most appropriate? What kinds of…

This conceptual model introduces a process to help school counselors use data to drive decision making and offers examples to implement the process. A step-by-step process is offered to help school counselors and school counselor supervisors address educational issues, close achievement gaps, and demonstrate program effectiveness. To illustrate…

Written for pre- and in-service educators, this "Third Edition" of Craig A. Mertler's "Action Research: Improving Schools and Empowering Educators" introduces the process of conducting one's own classroom- or school-based action research in conjunction with everyday instructional practices and activities. The text provides educators with the…

This study examined the impact of principals' data-driven decision-making practices on student achievement using the theoretical frame of Dervin's sense-making theory. This study is a quantitative cross-sectional research design where principals' perceptions about data were quantitatively captured at a single point in time. The participants for…