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Jane Buckley; Elyse Postlewaite; Thomas Archibald; Miriam R. Linver; Jennifer Brown Urban – American Journal of Evaluation, 2025
The purpose of this article is to offer both theoretical and practical support to evaluation professionals preparing to facilitate the utilization phase of evaluation with a program or organization team. The Systems Evaluation Protocol for Participatory Data Use (SEPPDU) presented here is rooted in a partnership approach to evaluation and is…
Descriptors: Data Use, Evaluation Utilization, Data Interpretation, Decision Making
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Iva Božovic – Journal of Political Science Education, 2024
This work reports on the implementation of a self-contained data-literacy exercise designed for use in undergraduate classes to help students practice data literacy skills such as interpreting and evaluating evidence and assessing arguments based on data. The exercises use already developed data-visualizations to test and develop students' ability…
Descriptors: Data Use, Teaching Methods, Data, Information Literacy
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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
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Prerna Srigyan; Kim Fortun – Science & Education, 2025
Research in cultural anthropology and the interdisciplinary field of science and technology studies (STS) has demonstrated that environmental disasters are not only techno-scientifically and socio-politically complex but also epistemically complex -- involving perspectival diversity; multiple, often conflicting forms of evidence; data gaps and…
Descriptors: Case Studies, Environmental Education, Natural Disasters, Justice
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Jordan P. Beck; Diane M. Miller – Journal of Chemical Education, 2022
A version of the classic rotationally resolved infrared (IR) spectrum of a diatomic molecule experiment has been developed using the POGIL framework to more fully engage students in the collection, modeling, analysis, and interpretation of the data. An analysis of the experimental protocol reveals that the POGIL approach actively engages students…
Descriptors: Learner Engagement, Chemistry, Science Instruction, Laboratory Experiments
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Iannario, Maria; Tarantola, Claudia – Sociological Methods & Research, 2023
This contribution deals with effect measures for covariates in ordinal data models to address the interpretation of the results on the extreme categories of the scales, evaluate possible response styles, and motivate collapsing of extreme categories. It provides a simpler interpretation of the influence of the covariates on the probability of the…
Descriptors: Data Analysis, Data Interpretation, Probability, Models
E. Nielsen; M. Pelczar – Institute of Museum and Library Services, 2024
This research brief describes recent methodological initiatives with the Public Libraries Survey. It describes how starting with the 2022 data, Institute of Museum and Library Services (IMLS) updated geographic identifiers to better align Census Bureau geography types with the library's legal service area, with the goal of enabling data users to…
Descriptors: Public Libraries, Special Libraries, Museums, Library Role
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Annie Irvine – International Journal of Social Research Methodology, 2024
Engaging with primary researchers during qualitative secondary analysis is a practice much recommended but rarely written about. In this article, I reflect on my experience of crossing an imagined boundary between the discrete textual dataset and its creators, of acknowledging and engaging with those researchers who invested in constructing the…
Descriptors: Researchers, Foreign Countries, Primary Sources, Research Methodology
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McHenry, William K. – Journal of Information Systems Education, 2022
Students now have readily available and powerful tools to access, manipulate, combine, and visualize data. Acquiring data and visual literacy requires more than knowledge of how to use these tools. Students need to engage with assignments that challenge them to make relatively complex visualizations, interpret them, and explain why these…
Descriptors: Visual Aids, Scoring Rubrics, Feedback (Response), Data Interpretation
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Corinne Thatcher Day – Mathematics Teacher: Learning and Teaching PK-12, 2025
Since data collection technologies has become a part of daily life, measurement and data requirements now permeate many state mathematics standards, beginning as early as kindergarten and extending through high school. For example, the Standards for Mathematical Content, recommend that kindergarteners "describe and compare measurable…
Descriptors: Middle School Mathematics, Middle School Students, Middle School Teachers, High School Students
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Dunn, Peter K.; Marshman, Margaret – Australian Mathematics Education Journal, 2021
This is the fourth in a series of statistical articles for mathematics teachers. In this article, the authors discuss topics in General Mathematics in Unit 2 Topic 1 (Univariate data analysis and the statistical investigation process) and topics in Essential Mathematics, Unit 2 Topic 1 (Representing and comparing data).
Descriptors: Mathematics Education, Mathematics Instruction, Data Analysis, Graphs
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David Voas; Laura Watt – Teaching Statistics: An International Journal for Teachers, 2025
Binary logistic regression is one of the most widely used statistical tools. The method uses odds, log odds, and odds ratios, which are difficult to understand and interpret. Understanding of logistic regression tends to fall down in one of three ways: (1) Many students and researchers come to believe that an odds ratio translates directly into…
Descriptors: Statistics, Statistics Education, Regression (Statistics), Misconceptions
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Federica Picasso; Javiera Atenas; Leo Havemann; Anna Serbati – Open Praxis, 2024
The development of critical data and artificial intelligence (AI) literacy has become a key focus in current discussions in Higher Education, thus it is necessary to develop and advance capacity building, reflectiveness and awareness across disciplines to critically address the possibilities and challenges presented by data and AI. In this paper,…
Descriptors: Undergraduate Students, College Faculty, Artificial Intelligence, Data Collection
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Wise, Alyssa Friend – Journal of the Learning Sciences, 2020
This article discusses how each of the papers in this special issue explored some combination of subject, audience, and data scientist perspectives with an eye toward helping students situate their relationship to data. Specifically, within the data scientist perspective, the papers examined a variety of ways in which students can relate to data…
Descriptors: Data, Information Science Education, Multiple Literacies, Relationship
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Rubel, Laurie H.; Nicol, Cynthia; Chronaki, Anna – Educational Studies in Mathematics, 2021
Data visualizations have proliferated throughout the COVID-19 pandemic to communicate information about the crisis and influence policy development and individual decision-making. In invoking exponential growth, mathematical modelling, statistical analysis, and the like, these data visualizations invite opportunities for mathematics teaching and…
Descriptors: Mathematics Education, Data Use, Data Interpretation, Visual Aids
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