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Rebeka Man – ProQuest LLC, 2024
In today's era of large-scale data, academic institutions, businesses, and government agencies are increasingly faced with heterogeneous datasets. Consequently, there is a growing need to develop effective methods for extracting meaningful insights from this type of data. Quantile, expectile, and expected shortfall regression methods offer useful…
Descriptors: Data, Data Analysis, Data Use, Higher Education
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Ayhan Duygulu; Sibel Dogan; Sevgi Yildiz – Journal of Theoretical Educational Science, 2025
The purpose of this study is to develop a valid and reliable scale to determine and evaluate the different dimensions of data literacy at school. The study is a quantitative descriptive survey model. The sampling for exploratory factor analysis was formed of 307 and confirmatory factor analysis 338 teachers and school administrators who are on…
Descriptors: Data, Literacy, Test Construction, Measures (Individuals)
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Evenstein Sigalov, Shani; Nachmias, Rafi – Education and Information Technologies, 2023
Wikidata is a free, multilingual, open knowledge-base that stores structured, linked data. It has grown rapidly and as of December 2022 contains over 100 million items and millions of statements, making it the largest semantic knowledge-base in existence. Changing the interaction between people and knowledge, Wikidata offers various learning…
Descriptors: Collaborative Writing, Electronic Publishing, Data, Data Use
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Bowers, Alex J.; Choi, Yeonsoo – Educational Researcher, 2023
Despite increasing calls to build equitable data infrastructures, the education field has yet to have a shared guideline around equitable education data management and stewardship. To address this gap, we propose one framework from the data governance literature: the FAIR (Findable, Accessible, Interoperable, Reusable) data management principles…
Descriptors: Data, Governance, Information Management, Guidelines
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Christine M. White; Stephanie A. Estrera; Christopher Schatschneider; Sara A. Hart – Grantee Submission, 2024
Researchers in the education sciences, like those in other disciplines, are increasingly encountering requirements and incentives to make the data supporting empirical research available to others. However, the process of preparing and sharing research data can be daunting. The present article aims to support researchers who are beginning to think…
Descriptors: Data, Educational Research, Information Dissemination, Incentives
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Lei Zhang – Discover Education, 2025
This systematic review presents the first synthesis of the scientific literature on estimating school and teacher/class effects on student academic performance using random-effects (RE) models with three or more levels. The review delves into the theoretical framework underpinning the estimation of educational effects, the associated statistical…
Descriptors: Academic Achievement, Teacher Effectiveness, School Effectiveness, Content Analysis
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Oleksandra Poquet – British Journal of Educational Technology, 2024
The paper argues that learning analytics as a research field can benefit from a theory-informed shared language to describe sensemaking of learning and teaching data. To make the case for such shared language, first, I critically review prominent sensemaking theories to then demonstrate how studies in learning analytics do not use coherent…
Descriptors: Learning Analytics, Data, Affordances, Theories
Nancy Smith; Claus von Zastrow – Education Commission of the States, 2022
When the COVID-19 pandemic drove schools online in March 2020, state education leaders were left without access to data needed to understand how best to support students. The pandemic revealed the strengths and limitations of state education data systems while inspiring new strategies for collecting, reporting and using data. In 2021, DataSmith…
Descriptors: State Departments of Education, Data, Data Collection, Pandemics
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Wilkerson, Michelle Hoda; Polman, Joseph L. – Journal of the Learning Sciences, 2020
The emerging field of Data Science has had a large impact on science and society. This has led to over a decade of calls to establish a corresponding field of Data Science Education. There is still a need, however, to more deeply conceptualize what a field of Data Science Education might entail in terms of scope, responsibility, and execution.…
Descriptors: Data, Information Science Education, Learning, Data Collection
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Decuypere, Mathias – Journal of New Approaches in Educational Research, 2021
This paper offers a methodological framework to research data practices in education critically. Data practices are understood in the generic sense of the word here, i.e., as the actions, performances, and the resulting consequences, of introducing data-producing technologies in everyday educational situations. The paper first distinguishes…
Descriptors: Data, Data Use, Topology, Research Methodology
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Paul Donner – Research Evaluation, 2024
This study introduces an approach to estimate the uncertainty in bibliometric indicator values that is caused by data errors. This approach utilizes Bayesian regression models, estimated from empirical data samples, which are used to predict error-free data. Through direct Monte Carlo simulation--drawing many replicates of predicted data from the…
Descriptors: Data, Accuracy, Bibliometrics, Educational Indicators
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Quadir, Benazir; Chen, Nian-Shing; Isaias, Pedro – Interactive Learning Environments, 2022
The purpose of this study is to review journal papers on educational big data research published from 2010 to 2018. A total of 143 papers were selected. The papers were characterized based on three dimensions: (a) educational goals; (b) educational problems addressed; and (c) big data analytical techniques used. A qualitative content analysis…
Descriptors: Data, Educational Research, Educational Objectives, Data Analysis
Peterson, Elizabeth Sarah – ProQuest LLC, 2023
Moving Beyond the Ordinal Methodological Controversy: A Systematic Review (Manuscript 1): Ordinal outcome data is a common byproduct of education research. Yet more than seventy-five years after the development of Stevens' original measurement framework, the permissibility of select analytic techniques to ordinal outcome data remains a topic of…
Descriptors: Data, Educational Research, Statistical Analysis, Social Sciences
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Aiken, John M.; Lewandowski, H. J. – Physical Review Physics Education Research, 2021
We present a model for sharing quantitative data in the field of physics education research and use it to present a newly available dataset as an example. This model is in line with calls from across physics and science more generally to democratize data and results through open access. The model includes suggestions for data collection, creation…
Descriptors: Physics, Educational Research, Data, Shared Resources and Services
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Williams, Tamara; Cheng, Xiaoyue; Majumder, Mahbubul; Hastings, Matt; Suh, Hongwook; Dash, Kunal; Yeo, Jian Ju – School Community Journal, 2020
Big data is a unique field of study which requires specialized analytics. The field of education has a lot of data: individual student test scores, attendance, behavior, and demographic data are just some of the regularly collected information year after year. Individual student data across an entire state over several years quickly becomes big…
Descriptors: Data, Elementary Secondary Education, Data Analysis, Cooperation
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