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Ioana-Elena Oana; Carsten Q. Schneider – Sociological Methods & Research, 2024
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…
Descriptors: Robustness (Statistics), Qualitative Research, Comparative Analysis, Decision Making
Casement, Christopher J. – International Journal of Mathematical Education in Science and Technology, 2023
Statistical tables associated with named probability distributions and their families, such as the standard normal, Student's t, and chi-square tables, among others, have been utilized for years and are still widely used today, especially for mathematics and statistics education. While such tables can be found in many statistics textbooks and even…
Descriptors: Tables (Data), Statistics Education, Computer Software, Mathematics Education
Yiwen Wei – Art Education, 2024
Data visualization enables users to transform data into visually compelling graphics that tell a rich story for effective communication (Vora, 2019). Data visualization's visual and artistic nature has also attracted artists and educators, leading them to explore its application in artistic creation and education (e.g., Bertling et al., 2021; Dean…
Descriptors: Art Education, Visual Aids, Data Analysis, Creativity
Thiem, Alrik – Sociological Methods & Research, 2022
Qualitative Comparative Analysis (QCA) is a relatively young method of causal inference that continues to diffuse across the social sciences. However, recent methodological research has found the conservative (QCA-CS) and the intermediate solution type (QCA-IS) of QCA to fail fundamental tests of correctness. Even under conditions otherwise ideal…
Descriptors: Comparative Analysis, Causal Models, Inferences, Risk
Schrauf, Robert W. – Journal of Mixed Methods Research, 2018
Mixed methods, cross-cultural designs are a special case of the more general, mixed methods between-groups designs. The defining feature of mixed methods is the principled integration of qualitative and quantitative approaches, and cross-cultural comparison is premised on the systematic collection and analysis of data from two or more cultural…
Descriptors: Cross Cultural Studies, Mixed Methods Research, Comparative Analysis, Data Collection
Baldwin, Peter; Clauser, Brian E. – Journal of Educational Measurement, 2022
While score comparability across test forms typically relies on common (or randomly equivalent) examinees or items, innovations in item formats, test delivery, and efforts to extend the range of score interpretation may require a special data collection before examinees or items can be used in this way--or may be incompatible with common examinee…
Descriptors: Scoring, Testing, Test Items, Test Format
Dunn, Peter K.; Marshman, Margaret – Australian Mathematics Education Journal, 2020
Peter Dunn and Margaret Marshman present the second of their data files articles in which they discuss the statistical investigation cycle which describes the whole process of conducting a statistical research study. [For "The Data Files: A Series of Articles to Support Mathematics Teachers to Teach Statistics," see EJ1259108.]
Descriptors: Statistics, Data Analysis, Teaching Methods, Problem Solving
Kuha, Jouni; Mills, Colin – Sociological Methods & Research, 2020
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…
Descriptors: Comparative Analysis, Regression (Statistics), Research Problems, Computation
Frericks, Patricia – International Journal of Social Research Methodology, 2022
Social research is rich in methods for analysing societal differences. Yet, although qualitative characteristics are a key component to understanding such differences, the analysis of qualitative data remains a major methodological challenge in most social research, particularly when aiming to compare more than a few cases. The article proposes an…
Descriptors: Social Science Research, Qualitative Research, Data Analysis, Social Differences
Knipe, Sally – Educational Practice and Theory, 2019
The collection of data by government authorities has a complex history. In Australia, this began with the establishment of British government settlements as a way to account for fiscal viability and social prospects. As the colonies became self-governing entities, the collection of social and economic data increased in importance, and included…
Descriptors: Data Collection, Data Analysis, Foreign Countries, Foreign Policy
Chatti, Mohamed Amine; Muslim, Arham – International Review of Research in Open and Distributed Learning, 2019
Personalization is crucial for achieving smart learning environments in different lifelong learning contexts. There is a need to shift from one-size-fits-all systems to personalized learning environments that give control to the learners. Recently, learning analytics (LA) is opening up new opportunities for promoting personalization by providing…
Descriptors: Guidelines, Data Analysis, Learning Experience, Metacognition
Jopke, Nikolaus; Gerrits, Lasse – International Journal of Social Research Methodology, 2019
There is a need to improve the ways in which Qualitative Comparative Analysis (QCA) handles qualitative data. To this end, we propose to include ideas and routines from Grounded Theory (GT) in QCA. We will first argue that there is a natural fit between the two on the ontological level. On the methodological level, we will demonstrate in what ways…
Descriptors: Qualitative Research, Comparative Analysis, Grounded Theory, Sampling
Frischemeier, Daniel; Leavy, Aisling – Teaching Statistics: An International Journal for Teachers, 2020
Posing statistical questions is a fundamental and often overlooked component of statistical inquiry. In this paper, we provide an overview of shared understandings regarding what constitutes a good statistical question. We then describe three approaches--a checklist for improving statistical questions, a three-phase feedback activity, and a…
Descriptors: Statistics, Teaching Methods, Questioning Techniques, Check Lists
Lübke, Karsten; Gehrke, Matthias; Horst, Jörg; Szepannek, Gero – Journal of Statistics Education, 2020
Basic knowledge of ideas of causal inference can help students to think beyond data, that is, to think more clearly about the data generating process. Especially for (maybe big) observational data, qualitative assumptions are important for the conclusions drawn and interpretation of the quantitative results. Concepts of causal inference can also…
Descriptors: Inferences, Simulation, Attribution Theory, Teaching Methods
Hagopian, Louis P. – Journal of Applied Behavior Analysis, 2020
Single-case experimental designs (SCEDs) have proven invaluable in research and practice because they are optimal for asking many experimental questions relevant to the analysis of behavior. The consecutive controlled case series (CCCS) is a type of study in which a SCED is employed in a series of consecutively encountered cases that undergo a…
Descriptors: Case Studies, Data Analysis, Behavior Patterns, Clinical Diagnosis