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Rosa R. Soto Ruidias; Bernardo Pereira Nunes; Ruben Manrique; Sean Siqueira – Journal of Learning Analytics, 2025
Despite the increasing availability of data used to inform educational policies and practices, concerns persist regarding its quality and accessibility. This study surveys quality education data from Brazil, Colombia, and Peru and evaluates their alignment with the FAIR principles and availability to support academic analytics (AA) and learning…
Descriptors: Foreign Countries, Educational Quality, Learning Analytics, Educational Research
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
Julie Fitz; Julie Woods; Naomi Duran; Jennifer McCombs – Learning Policy Institute, 2025
Student participation in summer programming can be an effective way to address students' academic and developmental needs. When well implemented and well attended, summer enrichment programs, academic programs, and employment programs have demonstrated positive outcomes for youth in areas related to program content, including academic achievement…
Descriptors: Summer Programs, Educational Opportunities, Educational Quality, Regional Characteristics
Julie Fitz; Julie Woods; Naomi Duran; Jennifer McCombs – Learning Policy Institute, 2025
As federal funding for summer learning as a pandemic recovery strategy phases out, state governments face decisions about their future role in supporting students' access to quality summer learning opportunities. This brief is based on the full report, "How States Are Expanding Quality Summer Learning Opportunities," and summarizes…
Descriptors: Summer Programs, Educational Opportunities, Educational Quality, Regional Characteristics
Center for IDEA Early Childhood Data Systems (DaSy), 2022
The purpose of the DaSy Data System Framework (referred to as DaSy framework) is to assist Part C (Early Intervention) and Part B (School-Aged) 619 programs in developing and enhancing high-quality state data systems for the collection, analysis, reporting, and use of their Individuals with Disabilities Education Act (IDEA) data. The DaSy…
Descriptors: Educational Legislation, Federal Legislation, Equal Education, Students with Disabilities
Hinds, Teri Lyn; Floyd, Nancy D.; Ueland, Jeffrey S. – New Directions for Institutional Research, 2021
In June 2019, Minnesota State set a critical goal: By 2030, eliminate the educational equity gaps at each of the 30 colleges and 7 universities that comprise the system. To achieve the goal of Equity 2030, and empower actors at every level of Minnesota State, system and campus leaders need to fully embrace data democratization. Without access to…
Descriptors: Equal Education, Higher Education, Educational Quality, State Policy
Marion, Scott – National Center for the Improvement of Educational Assessment, 2020
In March 2020, the coronavirus pandemic and attending shift to remote schooling initiated a dramatic impact on student learning, an impact that state and district leaders feel a sense of urgency to understand and address. These leaders are accustomed using state and district test data to shed light on student achievement and growth. But without…
Descriptors: Educational Opportunities, Equal Education, Data Collection, COVID-19
Schildkamp, Kim – Educational Research, 2019
Background: Data-based decision-making in education often focuses on the use of summative assessment data in order to bring about improvements in student achievement. However, many other sources of evidence are available across a wide range of indicators. There is potential for school leaders, teachers and students to use these diverse sources…
Descriptors: Data Use, School Effectiveness, Educational Improvement, Formative Evaluation
Chelsea Hetherington; Cheryl Eschbach; Courtney Cuthbertson – Journal of Human Sciences & Extension, 2019
Evaluation capacity building (ECB) is an essential element for generating credible and actionable evidence on Extension programs. This paper offers a discussion of ECB efforts in Cooperative Extension and how such efforts enable Extension professionals to collect and use credible and actionable evidence on the quality and impacts of programs.…
Descriptors: Cooperative Education, Extension Education, Capacity Building, Program Evaluation
Portilla, Ximena A.; Mattera, Shira; Wulfsohn, Samantha – MDRC, 2020
Improving the quality of teaching and instruction takes time and planning and may be costly and require intensive work. This is particularly true when trying to make improvements among multiple preschool sites, because preschool systems often lack a cohesive infrastructure for supporting high-quality implementation of curricula and teacher…
Descriptors: Preschool Education, Preschool Curriculum, Curriculum Implementation, Educational Quality
Arnold, Nathan; Voight, Mamie; Morales, Jessica; Dancy. Kim; Coleman, Art – Institute for Higher Education Policy, 2019
As the higher education landscape has expanded beyond issues of access and affordability to include an emphasis on student completion and employment outcomes, accreditors can play a leadership role in advancing this important change. A shift to student success that rightfully centers in part on closing equity gaps between low-income students and…
Descriptors: Educational Improvement, Accreditation (Institutions), Data Use, Academic Achievement
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
Gamse, Beth C.; Spielberger, Julie; Axelrod, Jennifer; Spain, Angeline – Chapin Hall at the University of Chicago, 2019
Afterschool programs can offer enriching opportunities, homework help and a safe environment. To ensure that these programs are cohesive, high-quality and widely available, many cities have designed community-wide systems to coordinate the various afterschool programs offered by different providers. Having a way to collect and share reliable data…
Descriptors: After School Programs, Low Income Students, At Risk Students, Youth Programs
Advance CTE: State Leaders Connecting Learning to Work, 2020
One of the biggest challenges that states and local intermediaries face in setting up and scaling high-quality youth apprenticeships is gathering relevant, accurate and actionable data. High-quality data is an essential ingredient for a strong youth apprenticeship program because it equips state and local leaders to evaluate impact, monitor…
Descriptors: Vocational Education, Youth Programs, Apprenticeships, Data Collection
National Center on Accessible Educational Materials, 2020
When the "AEM Quality Indicators with Critical Components for Higher Education: Institutes of Higher Education" (ED613012) was updated, a series of interviews were conducted with experts in colleges, universities, and related associations with knowledge and experience in system- or campus-wide accessibility. Additionally, a literature…
Descriptors: Higher Education, Instructional Materials, Educational Quality, Accessibility (for Disabled)
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