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…

As data are 'numbers with context' (Cobb & Moore, 1997), contextual knowledge plays a prominent role in dealing with statistics. While insights about a specific context can further the depth of interpreting and evaluating outcomes of data analysis, research shows how it can also hinder relying on data especially if results differ from…

To develop competency in science practices, such as data analysis and interpretation, chemistry learners must develop an understanding of what makes an analysis and interpretation "good" (i.e., the criteria for success). One way that individuals extract the criteria for success in a novel situation is through making social comparisons,…

This paper argues for three aspects of tolerance with respect to QCA research: tolerance with respect to different approaches to QCA; producing QCA research with tolerance (work that is resistant to criticism); and for QCA researchers to be clear about the tolerance of the solutions they present -- especially in terms of calibration and truth…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

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…

This study aims to introduce network meta-analysis (NMA) to provide educational researchers with an extended view of the reviewing educational research. Meta-analytic methods have been widely used in educational research reviews. However, weaknesses have emerged in the multi-group comparison analysis of educational studies where different…

Graphic interpretation is as critical in physics education as problem-solving. However, we know that today's classes focus more on problem-solving. This study uses a survey to determine college students' graphic interpretation skills. The study consists of two phases. The first phase includes the development and statistical analysis of the survey.…

This applied research methods report is a guide for state and local education agency policymakers and their analysts who are interested in studying teacher mobility and retention. This report is the second in a two-part set and builds on the foundational information in report 1. This report presents guidance on how to interpret differences in…

Qualitative comparative analysis (QCA) is gaining ground in evaluation circles, but the number of applications is still limited. In this article, we consider the challenges that can emerge during a QCA evaluation by drawing on our experience of conducting one in the field of development cooperation. For each stage of the evaluation process, we…

It is widely believed that regression models for binary responses are problematic if we want to compare estimated coefficients from models for different groups or with different explanatory variables. This concern has two forms. The first arises if the binary model is treated as an estimate of a model for an unobserved continuous response and the…

K-12 students are expected to acquire competence in data display as part of developing statistical literacy. To support research, assessment design, and instruction, we developed a hypothesized learning progression (LP) using existing empirical literature in the fields of mathematics and statistics education. The data display LP posits a…

Health risks, when presented as ratios (e.g., two out of seven people), are challenging to understand, but visual displays can foster accurate understanding. We conducted three experiments to test how characteristics of numbers (Experiment 1), icon arrays (Experiments 1, 2, and 3), and number lines (Experiments 1 and 3) influenced people's ability…

Data visualization literacy can be defined as "the ability and skill to read and interpret visually represented data in and to extract information from data visualizations" (Lee, et al., 2017, p.552). Within the information science profession, data visualization literacy is an emerging and increasingly important competency within the…