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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
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
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
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
Denisa Gándara; Hadis Anahideh; Matthew P. Ison; Lorenzo Picchiarini – Grantee Submission, 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
Tamara L. Shreiner – Teachers College Press, 2024
We are surrounded by data and data visualizations in our everyday lives. To help ensure that students can critically evaluate data--and use it to promote social justice--this book outlines principles and practices for teaching data literacy as part of social studies education. The author shows how social studies content and skills can enhance both…
Descriptors: Social Studies, Multiple Literacies, Teacher Competencies, Elementary Secondary Education
Region 1 Comprehensive Center, 2024
The Maine Department of Education (MDOE) wanted to better understand if their current educator workforce data collection could help them quantify supply and demand for educators in the state. They also wanted to understand if local school administrative units collected data that could inform future efforts to understand educator vacancies to…
Descriptors: School Administration, Teacher Characteristics, Labor Force, Data Collection
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
John Hattie; Douglas Fisher; Nancy Frey; John Taylor Almarode – Corwin, 2024
It may seem obvious, but learning should never be implied or assumed. Learning must be explicit, evaluated and monitored; the impact of teaching on student learning should be visible. But how can we be sure? Armed with years of research that includes more than 2,100 meta-analyses, and 130,000 studies that include more than 300 million…
Descriptors: Evidence Based Practice, Data Collection, Data Use, Educational Quality
Evelyn Goffin; Rianne Janssen; Jan Vanhoof – AERA Online Paper Repository, 2024
We undertook a research project consisting of four interrelated studies, in order to shed light on ways educational professionals make sense and make use of educational data in general and school performance feedback in particular. Theoretical insights illuminate why a sensemaking perspective is an appropriate and valuable lens to study data use.…
Descriptors: Data Use, Educational Research, Data Interpretation, Performance Based Assessment
Data Quality Campaign, 2024
A national poll from the Data Quality Campaign (DQC), conducted by The Harris Poll, surveyed early childhood administrators--educational or child care professionals in program director or general manager roles serving children from birth through age four--to find out how they are collecting, using, and reporting data. Early childhood…
Descriptors: Early Childhood Education, Administrator Attitudes, Data Use, Decision Making
National Forum on Education Statistics, 2023
This forum guide was developed to meet the need for common, widely understood, standardized course codes. The purpose of this guide is to introduce the voluntary School Courses for the Exchange of Data (SCED) classification system, including information on the structure of SCED codes, the process for ensuring that SCED remains up to date and…
Descriptors: Courses, Classification, Coding, Data
Dogan, Emine – Journal of Theoretical Educational Science, 2023
This meta-analysis study aimed to examine the effect of data literacy education, which affects databased decision processes, on data use knowledge and skills of school administrators and teachers. Therefore, theses on data literacy education for school administrators and teachers and relevant studies in peer-reviewed journals were examined through…
Descriptors: Meta Analysis, Data Analysis, Information Literacy, Statistics Education
Chow, Jason C.; Sandbank, Micheal; Hampton, Lauren H. – Journal of Speech, Language, and Hearing Research, 2023
Meta-analyses can be used to comprehensively summarize the state of a given literature base, understand development and relations between constructs, and synthesize intervention effects to identify "what works for whom," all of which can directly inform research, practice, and policy. In this tutorial, we first argue that data reporting…
Descriptors: Data Use, Usability, Meta Analysis, Educational Research

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