Collecting data for an individual participant data meta-analysis (IPDMA) project can be time consuming and resource intensive and could still have insufficient power to answer the question of interest. Therefore, researchers should consider the power of their planned IPDMA before collecting IPD. Here we propose a method to estimate the power of a…

The COVID-19 pandemic caused tremendous upheaval in schooling. In addition to devasting effects on students, these disruptions had consequences for researchers conducting studies on education programs and policies. Given the likelihood of future large-scale disruptions, it is important for researchers to plan resilient studies and think critically…

Simple matrix sampling planned missing (SMS PD) design, introduce missing data patterns that lead to covariances between variables that are not jointly observed, and create difficulties for analyses other than mean and variance estimations. Based on prior research, we adopted a new multigroup confirmatory factor analysis (CFA) approach to handle…

The purpose of this study was to investigate the effectiveness of four different models (bifactor, CTC(M-1), CTCU and unidimensional) as to optimal model selection when the wording effect associated with negatively worded items was present. A Monte Carlo simulation study was conducted to compare model-data fit and accuracy in parameter estimates…

The COVID-19 pandemic caused tremendous upheaval in schooling. In addition to its devasting effects on students' academic development, the disruptions to schooling had important consequences for researchers conducting effectiveness studies on educational programs during this era. Given the likelihood of future large-scale disruptions, it is…

Digital learning platforms (DLPs) can transform educational research by serving as infrastructure that bridges the gap between practice and research. This white paper examines the progress of DLPs in SEERNet, a multi-year initiative funded by the Institute of Education Sciences (IES), which aims to advance research infrastructure. Through…

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…

This study aims to investigate the trustworthiness of empirical research published in distance education (DE) journals, an area that has yet to be systematically explored. The review covers 238 empirical studies which were based on primary data and published in 2021 in eight DE journals listed in Social Science Citation Index (SSCI) or Emerging…

As the field of K-12 data science education continues to take form, humanistic approaches to teaching and learning about data are needed. Data feminism is an approach that draws on feminist scholarship and action to humanize data and contend with the relationships between data and power. In this review paper, we draw on principles from data…

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…

This case study is based on a program evaluation of a professional certificate program that trains early childhood care and education providers to build and support young children's emotional literacy. The research project described in the case study will address approaches to methodological combination, justifying research design and changes to…

Single-case design (SCD) methodology, in which data are displayed in a line graph, can be helpful in determining intervention effectiveness in research and practice. Using visual inspection of graphed data, researchers and practitioners can explore the existence of a functional relationship between implementation of the intervention and a…

Single-case designs are a class of repeated measures experiments used to evaluate the effects of interventions for small or specialized populations, such as individuals with low-incidence disabilities. There has been growing interest in systematic reviews and syntheses of evidence from single-case designs, but there remains a need to further…

Single-case data are frequently used in school psychology. In research, single-case designs allow experimenters to provide rigorous demonstrations of treatment effects on a smaller scale and with more precise measurement than traditional group experimental design. In practice, single-case data are used to evaluate the effects of school-based…