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Brannegan, Andrew; Takahashi, Sola – Learning Professional, 2023
Educators have long been awash in a sea of standardized test score data, with the understanding that their engagement with these data will lead to improvement in teaching and learning. But, in practice, these data have often been too infrequent, too lagging, and too distant from day-to-day practice to inform actionable next steps. To improve…
Descriptors: Standardized Tests, Data Use, Educational Improvement, Data Analysis
Adolfsson, Carl-Henrik; Håkansson, Jan – Leadership and Policy in Schools, 2023
From a new institutional theoretical perspective, this article explores school actors' sense-making linked to data-based decision making (DBDM) policy in general and processes of data analysis in particular. The study revealed how actors' interpretation of and response to DBDM pointed to strong and weak couplings between and within the local…
Descriptors: Data Analysis, Educational Improvement, Decision Making, Data Interpretation
Buckner, Elizabeth; Shephard, Daniel; Smiley, Anne – Journal on Education in Emergencies, 2022
Recognizing the lack of knowledge about how to improve data systems for education in emergencies (EiE), we examine in this article how EiE professionals use data and what makes data "useful" to them. Drawing from 48 semistructured interviews from a purposive sample of professionals working in the EiE field across the humanitarian,…
Descriptors: Data Use, Emergency Programs, Professional Personnel, Attitudes
Yu-Jie Wang; Chang-Lei Gao; Xin-Dong Ye – Education and Information Technologies, 2024
The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…
Descriptors: Precision Teaching, Data Use, Intervention, Educational Improvement
Schildkamp, Kim; Datnow, Amanda – Leadership and Policy in Schools, 2022
Because learning from failures is just as important as learning from successes, we used qualitative case study data gathered in the Netherlands and the United States to examine instances in which data teams struggle to contribute to school improvement. Similar factors in both the Dutch and U.S. case hindered the work of the data teams, such as…
Descriptors: Foreign Countries, Educational Improvement, Data Use, Failure
Morris, Kelsey; Lewis, Timothy; Mitchell, Barb – Center on Positive Behavioral Interventions and Supports, 2022
This brief provides district PBIS [positive behavioral interventions and supports] leadership teams a framework to examine school-level fidelity and self-assessment data to guide resource, professional development, and technical assistance decision making.
Descriptors: School Districts, Data Use, Data Analysis, Fidelity
Courtney, Matthew B. – International Journal of Education Policy and Leadership, 2021
Exploratory data analysis (EDA) is an iterative, open-ended data analysis procedure that allows practitioners to examine data without pre-conceived notions to advise improvement processes and make informed decisions. Education is a data-rich field that is primed for a transition into a deeper, more purposeful use of data. This article introduces…
Descriptors: Data Analysis, Data Use, Decision Making, Educational Improvement
Marie Elizabeth Palano – ProQuest LLC, 2020
This study examines administrator perceptions of Pennsylvania's state assessment data. This study had three main purposes. The first purpose was to investigate the value and utility of state assessment data to inform decision making and the possibility of improving student achievement through the routine use of state assessment data. The second…
Descriptors: Administrator Attitudes, Data Use, Data Analysis, Academic Achievement
Knight, Jim – ASCD, 2021
Even under ideal conditions, teaching is tough work. Facing unrelenting pressure from administrators and parents and caught in a race against time to improve student outcomes, educators can easily become discouraged (or worse, burn out completely) without a robust coaching system in place to support them. For more than 20 years, perfecting such a…
Descriptors: Coaching (Performance), Academic Achievement, Success, Teaching Methods
Dobrenen, Diana D. – ProQuest LLC, 2019
Institutions of higher education are required by U.S. accrediting bodies to articulate their conceptual framework and develop a viable program improvement plan through a continuous reflective process of progressive problem solving that enables data-driven decision-making practices. To meet or exceed national accreditation standards for leadership,…
Descriptors: Improvement Programs, Program Evaluation, Higher Education, Educational Improvement
Marjorie Cohen; Steve Klein; Cherise Moore – Career and Technical Education Research Network, 2020
By partnering with researchers, state CTE administrators have the opportunity to better understand CTE programming and practices across their states. This is the fourth in a series of six practitioner training modules developed as part of the Career & Technical Education (CTE) Research Network Lead. Designed for CTE practitioners and state…
Descriptors: Vocational Education, Educational Research, Research Utilization, Data Use
Yoo, Paul Youngmin; Whitaker, Anamarie A.; McCombs, Jennifer Sloan – RAND Corporation, 2019
Expanded learning intermediaries are nonprofit organizations dedicated to making after-school and summer programs better and more accessible for children and youth. They do this by coordinating efforts and resources in a given community, knitting programs together into a cohesive system, helping individual programs function at a high level, and…
Descriptors: Nonprofit Organizations, After School Programs, Summer Programs, Data Collection
Linda McKee, Editor; Sylvia Read, Editor; Debbie Rickey, Editor – Myers Education Press, 2024
"Using Data for Continuous Improvement in Educator Preparation" provides case studies that illuminate and contextualize the ways in which educator preparation programs determine the data they need to improve, collect data, analyze data, share data with stakeholders, and close the loop by making focused improvements based on the data.…
Descriptors: Data Use, Educational Improvement, Teacher Education Programs, Data Collection
Stevenson, Bradley – National Technical Assistance Center on Transition, 2016
Data-based decision making refers to collecting, analyzing, and reporting data to drive school improvement. This can apply to any level of the school from individual students to the entire system. When applied to the field of secondary transition, it refers to using data to drive decisions to improve the in-school and post-school success of…
Descriptors: Data Analysis, Data Use, Decision Making, Educational Improvement
Data Quality Campaign, 2021
The 2020 election brought about legislative change across the country. New and veteran policymakers need information about the schools in their state. What programs are the most cost effective and work best for students? How can states attract and retain great teachers? What information do parents need to ensure that their kids are on track to…
Descriptors: Educational Policy, Policy Formation, Data Collection, Data Analysis
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