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Dermentzi, Eleni; Zotou, Maria; Tambouris, Efthimios; Tarabanis, Konstantinos – Education and Information Technologies, 2022
With Open Data becoming more popular and more public bodies publishing their datasets, the need for educating prospective graduates on how they can use them has become prominent. This study examines the use of the Problem Based Learning (PBL) method and educational technologies to support the development of Open Data skills in university students.…
Descriptors: Problem Based Learning, Educational Technology, Data, Data Use
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Schneider, Jack; Gottlieb, Derek – Educational Theory, 2021
State and federal policymakers "see" school performance via formal measures -- data collected with attendance sheets and standardized tests. Such an approach, though not without its merits, is extremely limited and inherently exposed to the threat of systematic misperception and unintended consequences, especially as policymakers try to…
Descriptors: Accountability, Education, Governance, Educational Assessment
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Addison Duane; Quinn Hafen; Luca Morales; Tiffany M. Jones; Valerie B. Shapiro – Journal of Educational Change, 2025
School climate surveys are frequently used to collect information about student experiences in school. Less is known about how educators use survey data after survey administration. This paper explores one school district's critical use of evidence to promote equitable change. We conducted eight semi-structured interviews with district and school…
Descriptors: Data Use, Student Attitudes, School Surveys, School Culture
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Menglin Xu; Jessica A. R. Logan – Educational and Psychological Measurement, 2024
Research designs that include planned missing data are gaining popularity in applied education research. These methods have traditionally relied on introducing missingness into data collections using the missing completely at random (MCAR) mechanism. This study assesses whether planned missingness can also be implemented when data are instead…
Descriptors: Research Design, Research Methodology, Monte Carlo Methods, Statistical Analysis
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Yingchen Wang – SAGE Open, 2024
Surveys are typical for student evaluation of teaching (SET). Survey research consistently confirms the negative impacts of careless responses on research validity, including low data quality and invalid research inferences. SET literature seldom addresses if careless responses are present and how to improve. To improve evaluation practices and…
Descriptors: Student Evaluation of Teacher Performance, Responses, Validity, Data Use
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Karly B. Ball; Rachel Elizabeth Traxler – International Journal of Research & Method in Education, 2024
As Twitter's (or X's) influence permeates aspects of education, researchers must consider how to ethically and effectively leverage the unique types of data that this social media platform offers. This paper provides recommended methodological practice considerations for working with qualitative Twitter data toward the advancement of education…
Descriptors: Educational Research, Research Methodology, Social Media, Ethics
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Jyun-Hong Chen; Hsiu-Yi Chao – Journal of Educational and Behavioral Statistics, 2024
To solve the attenuation paradox in computerized adaptive testing (CAT), this study proposes an item selection method, the integer programming approach based on real-time test data (IPRD), to improve test efficiency. The IPRD method turns information regarding the ability distribution of the population from real-time test data into feasible test…
Descriptors: Data Use, Computer Assisted Testing, Adaptive Testing, Design
Candace S. Thompson – ProQuest LLC, 2024
This dissertation discusses the relationship between teacher sensemaking, attributions, and instructional adjustments prompted in response to student performance data. Through this qualitative observation study, this paper explores the varying perspectives of teachers, including their level of assessment literacy, and the dynamics of their…
Descriptors: Decision Making, Attribution Theory, Communities of Practice, Teacher Attitudes
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Jihyun Lee; Dennis Alonzo; Kim Beswick; Jan Michael Vincent Abril; Adrian W. Chew; Cherry Zin Oo – Educational Assessment, Evaluation and Accountability, 2024
The current study presents a systematic review of teachers' data literacy, arising from a synthesis of 83 empirical studies published between 1990 to 2021. Our review identified 95 distinct indicators across five dimensions: (a) knowledge about data, (b) skills in using data, (c) dispositions towards data use, (d) data application for various…
Descriptors: Research Reports, Data Analysis, Teacher Collaboration, Faculty Development
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Sarah Hensley; Janet Fox; Missy Cummins; Meggan Franks; Marianne Bird; Cindy Wells; JoLynn Miller – Journal of Extension, 2024
Cooperative Extension professionals utilize proven qualitative techniques to collect and analyze information to make data-driven decisions that guide program direction and determine impact. While the process may not always look the same, it is indeed essential to ensure findings are credible and reflective of the data. A codebook is a valuable…
Descriptors: Youth Clubs, Nonprofit Organizations, Extension Education, Data Use
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Louise Gwenneth Phillips; M. Obaidul Hamid; Vicente Reyes; Ian Hardy – Educational Review, 2024
We live in a data-driven world. The voluminous scale of data gathered can lead to diminished consciousness of ethics whilst economic interests are prioritised. Across recent decades education has come to be heavily data driven and datafied. We have witnessed the dehumanising and increased labour impacts of school datafication. In search for…
Descriptors: Foreign Countries, Educational Researchers, Data, Data Use
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Denisa Gándara; Hadis Anahideh; Matthew P. Ison; Lorenzo Picchiarini – AERA Open, 2024
Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting, and student-success interventions. Because predictive algorithms rely on historical data, they capture societal injustices, including racism. In this study, we examine…
Descriptors: Algorithms, Social Bias, Minority Groups, Equal Education
Alexandra M. Pierce; Melissa A. Collier-Meek; Thea R. Bucherbeam; Lisa M. H. Sanetti – Communique, 2024
Students cannot experience the full potential benefits of an intervention unless they are receiving the intervention. This is the second installment in a three-part series on intervention fidelity designed to highlight the importance of ensuring classroom supports are implemented as intended. This article provides guidance related to measuring and…
Descriptors: Data Use, Decision Making, Intervention, Fidelity
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Ricardo Matheus; Stuti Saxena; Charalampos Alexopoulos – International Journal of Information and Learning Technology, 2024
Purpose: The purpose of the study is to understand the moderating impact of perceived technological innovativeness (PTI) in terms of gender differences as far as adoption and usage of Open Government Data (OGD) is concerned. Design/methodology/approach: Partial least squares-structural equation modelling (PLS-SEM) methodological approach is used…
Descriptors: Gender Differences, Technological Advancement, Data Use, Foreign Countries
Laura M. Samulski-Peters – ProQuest LLC, 2024
One of the most significant issues in education, as defined by the U.S. Department of Education Office of Accountability (2018), is disproportionality in exclusionary discipline. Disproportionality is defined as the over- and under-representation of racial/ethnic minorities in relation to their overall enrollment (Ahram et al., 2011). Currently,…
Descriptors: Disproportionate Representation, Discipline, Data Use, Minority Group Students
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