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Showing 1 to 15 of 41 results Save | Export
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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
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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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Braun, Henry – International Journal of Educational Methodology, 2021
This article introduces the concept of the carrying capacity of data (CCD), defined as an integrated, evaluative judgment of the credibility of specific data-based inferences, informed by quantitative and qualitative analyses, leavened by experience. The sequential process of evaluating the CCD is represented schematically by a framework that can…
Descriptors: Data Use, Social Sciences, Data Analysis, Data Interpretation
Meng-Ting Lo – ProQuest LLC, 2020
Multilevel modeling is commonly used with clustered data, and much emphasis has been placed specifically on the multilevel linear model (MLM). When modeling clustered ordinal data, a multilevel ordinal model with cumulative logit link assuming proportional odds (i.e., multilevel cumulative logit model) is typically used. Depending on the research…
Descriptors: Data Analysis, Models, Best Practices, Data Interpretation
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Cintron, Dakota W.; Montrosse-Moorhead, Bianca – American Journal of Evaluation, 2022
Despite the rising popularity of big data, there is speculation that evaluators have been slow adopters of these new statistical approaches. Several possible reasons have been offered for why this is the case: ethical concerns, institutional capacity, and evaluator capacity and values. In this method note, we address one of these barriers and aim…
Descriptors: Evaluation Research, Evaluation Problems, Evaluation Methods, Models
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Ferguson, Sarah L.; Moore, E. Whitney G.; Hull, Darrell M. – International Journal of Behavioral Development, 2020
The present guide provides a practical guide to conducting latent profile analysis (LPA) in the Mplus software system. This guide is intended for researchers familiar with some latent variable modeling but not LPA specifically. A general procedure for conducting LPA is provided in six steps: (a) data inspection, (b) iterative evaluation of models,…
Descriptors: Statistical Analysis, Computer Software, Data Analysis, Goodness of Fit
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Achilleas Mandrikas; Constantina Stefanidou; Constantine Skordoulis – Journal of STEM Education: Innovations and Research, 2024
A STEM education program entitled "Come rain or shine" implemented in a primary rural school in southern Greece as part of the "Diffusion of STEM (DI-STEM)" project and the results of its implementation are presented in this paper. The educational program deepened in weather education and intended to develop eight scientific…
Descriptors: Foreign Countries, STEM Education, Elementary Education, Program Implementation
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Seymoens, Tom; Van Audenhove, Leo; Van den Broeck, Wendy; Mariën, Ilse – Journal of Media Literacy Education, 2020
This paper presents "the DataBuzz Project." "DataBuzz" is a high-tech, mobile educational lab, which is housed in a 13-meter electric bus. Its specific goal is to increase the data literacy of different segments of society in the Brussels region through inclusive and participatory games and workshops. In this paper, we will…
Descriptors: Data Analysis, Literacy, Program Descriptions, Laboratories
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Wise, Alyssa Friend; Shaffer, David Williamson – Journal of Learning Analytics, 2015
It is an exhilarating and important time for conducting research on learning, with unprecedented quantities of data available. There is a danger, however, in thinking that with enough data, the numbers speak for themselves. In fact, with larger amounts of data, theory plays an ever-more critical role in analysis. In this introduction to the…
Descriptors: Learning Theories, Predictor Variables, Data, Data Analysis
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Elouazizi, Noureddine – Journal of Learning Analytics, 2014
This paper identifies some of the main challenges of data governance modelling in the context of learning analytics for higher education institutions, and discusses the critical factors for designing data governance models for learning analytics. It identifies three fundamental common challenges that cut across any learning analytics data…
Descriptors: Data, Governance, Data Analysis, Influences
Brookhart, Susan M. – ASCD, 2015
In this book, best-selling author Susan M. Brookhart helps teachers and administrators understand the critical elements and nuances of assessment data and how that information can best be used to inform improvement efforts in the school or district. Readers will learn: (1) What different kinds of data can--and cannot--tell us about student…
Descriptors: Data, Decision Making, Student Evaluation, Data Analysis
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Andrade, Alejandro; Delandshere, Ginette; Danish, Joshua A. – Journal of Learning Analytics, 2016
One of the challenges many learning scientists face is the laborious task of coding large amounts of video data and consistently identifying social actions, which is time consuming and difficult to accomplish in a systematic and consistent manner. It is easier to catalog observable behaviours (e.g., body motions or gaze) without explicitly…
Descriptors: Student Behavior, Data Analysis, Models, Video Technology
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Podeschi, R. J. – Information Systems Education Journal, 2015
This paper reports on the use of QlikView business intelligence software for use in a Business Intelligence (BI) course within an undergraduate information systems program. The course provides students with concepts related to data warehousing, data mining, visualizations, and software tools to provide business intelligence solutions for decision…
Descriptors: Experiential Learning, Business, Intelligence, Computer Software
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Figueiredo, Zenólia Christina Campos; Figueira, Janaína Esfalsini; Della Fonte, Sandra Soares; Caparróz, Francisco Eduardo – Sport, Education and Society, 2016
This study examines physical education (PE) curriculum development in an elementary school. Our goal was to understand the daily construction of a curriculum. We sought to analyse the theoretical and methodological framework and documents that a PE teacher uses each day while putting a curriculum into practice (lived curriculum). The data…
Descriptors: Physical Education, Foreign Countries, Curriculum Development, Elementary Schools
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Galyardt, April; Goldin, Ilya – Journal of Educational Data Mining, 2015
In educational technology and learning sciences, there are multiple uses for a predictive model of whether a student will perform a task correctly or not. For example, an intelligent tutoring system may use such a model to estimate whether or not a student has mastered a skill. We analyze the significance of data recency in making such…
Descriptors: Achievement Rating, Performance Based Assessment, Bayesian Statistics, Data Analysis
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