Trainee distress and burnout continue to be serious concerns for educational programs in medicine, prompting the implementation of numerous interventions. Although an expansive body of literature suggests that the experience of meaning at work is critical to professional wellbeing, relatively little attention has been paid to how this might be…

Transcription is an integral part of much qualitative data analysis, yet rarely has it received close attention in debates over the use (or non-use) of "computer assisted qualitative data analysis software" (CAQDAS). This article draws upon a mixed-methods study that involved transcribing conversational interviews with carers, third…

Learning to interpret data in context is an important educational outcome. To assess students' attainment of this outcome, it is necessary to examine the interplay between their contextual and statistical reasoning. We describe a research method designed to do so. The method draws upon Toulmin's (1958, 2003) model of argumentation for the first…

In the last few years, Qualitative Comparative Analysis (QCA) has become one of the most important data analysis methods in comparative research. According to the guidelines of this method, there are certain steps that a researcher needs to follow, before causally analyzing the data for necessary and sufficient conditions. One of these steps is…

Over the last decade, there has been a 10-fold increase in the number of published systematic reviews of prevalence. In meta-analyses of prevalence, the summary estimate represents an average prevalence from included studies. This estimate is truly informative only if there is no substantial heterogeneity among the different contexts being pooled.…

This Concise Review is an appraisal of contemporary research on teaching single-case experimental design (SCED) graphical creation published between 2017-2021. Recent work on SCED graphical creation is summarized and areas for future research are highlighted.

Exploratory graph analysis (EGA) is a commonly applied technique intended to help social scientists discover latent variables. Yet, the results can be influenced by the methodological decisions the researcher makes along the way. In this article, we focus on the choice regarding the number of factors to retain: We compare the performance of the…

Much of the special education literature features single-case experimental designs, which traditionally require researchers to determine functional relations among variables through the visual analyses of line graphs. Evidence suggests factors aside from the data influence visual analysis, including line graph construction. Fields including…

Undergraduate economics programs prepare students for future careers by developing competency working with data, or "data literacy." Our research examined the data literacy components of undergraduate economics programs at R1 and R2 universities in the United States (N = 190). We developed a protocol with core data skills and coded…

Although big data applications in education have different usage areas, they can make important contributions to the evaluation of universities and education systems, decision-making and strategy development, and improvement of the education system. In this study, which is considered to contribute to the academicians who will work on big data in…

Although parallel analysis has been found to be an accurate method for determining the number of factors in many conditions with complete data, its application under missing data is limited. The existing literature recommends that, after using an appropriate multiple imputation method, researchers either apply parallel analysis to every imputed…

Data literacy, which is considered among 21st century skills, is becoming increasingly important. In particular, incentives for data-driven decision-making draw attention to data literacy. Data literacy is also critical for teachers who need to use data in educational settings. Therefore, there is a need for data on whether teachers are equipped…

Background: Studies of socio-scientific decision-making in times of crisis are in their infancy. This study investigates how minoritized youth engage and make sense of newly developed COVID-19 vaccines and their intersections with the evolving multi-pandemic. Guided by theories of lively data, data sense and epistemic injustice, we center the…

With the widespread use of visuals in the media and the rapid development of visual technologies, media consumers today increasingly face visual information and visual decision-making. Developing visual literacy is thus crucial to empower people to effectively navigate the visual world. This paper uses two studies to describe the development and…

High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…