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Hawkins, Christie; Bailey, Lucy E. – New Directions for Institutional Research, 2020
The increasing volume of information and the intense pace of its circulation are changing the ways universities access, use, analyze, and provide data. Many have championed the use of large-scale databases to track student admissions and retention, faculty productivity, student wellness, and other phenomena that shape our understandings of higher…
Descriptors: Institutional Research, Data Analysis, Data Use, Colleges
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Davis, Susannah C.; Peck, Charles A. – Teachers College Record, 2020
Background/Context: Contemporary accountability policies in teacher education often require that programs systematically use data for program improvement (Council for the Accreditation of Educator Preparation, 2013). However, social science research from multiple fields of human service suggests that the challenges of using data involve much more…
Descriptors: Data Use, Program Improvement, Teacher Education Programs, Educational Policy
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Travis, Tiffini A.; Ramirez, Christian – portal: Libraries and the Academy, 2020
Libraries remain one of the last places on campus where the purging of usage data is encouraged and "tracking" is a dirty word. While some libraries have demonstrated the usefulness of analytics, opponents bring up issues of privacy and debate the feasibility of student-generated library data for planning and assessment. Using a study…
Descriptors: Academic Libraries, Data Collection, Learning Analytics, Ethics
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Dunn, Karee E.; Airola, Denise T.; Hayakawa, Takuya – Current Issues in Education, 2020
In this study, teacher education students' concerns, sense of efficacy, and anxiety related to the future use of data to drive educational decision-making were explored. In alignment with prior research with practicing teachers, this sample of pre-service teachers reported concerns (thoughts, preoccupations, and feelings) that indicate they are…
Descriptors: Preservice Teachers, Self Efficacy, Anxiety, Student Attitudes
Marx, Teri; Peterson, Amy; Arden, Sarah – National Center on Intensive Intervention, 2020
During spring 2020, educators quickly adapted to providing interventions and collecting data virtually despite the challenges of the COVID-19 pandemic. Parents were critical partners in supporting opportunities for students with intensive needs to data-based individualization (DBI) Process practice and receive feedback and sharing what was working…
Descriptors: COVID-19, Pandemics, Individualized Instruction, Data Use
National Governors Association, 2020
On behalf of the National Governors Association (NGA), and with support from the Robert Wood Johnson Foundation (RWJF), the State Health Access Data Assistance Center (SHADAC) has developed this resource, which highlights states that have released data thresholds, sometimes referred to as gating criteria or benchmarks, to guide schools, school…
Descriptors: COVID-19, Pandemics, Elementary Secondary Education, School Closing
Education Commission of the States, 2020
Following a high-quality early care and pre-K experience, the kindergarten-through-third-grade years set the foundation upon which future learning builds; and strengthening this continuum creates opportunities for later success. Key components of a quality experience in K-3 include school readiness and transitions, kindergarten requirements,…
Descriptors: State Policy, Educational Policy, Primary Education, Student Evaluation
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Leu, Katherine – RTI International, 2020
Postsecondary education is awash in data. Postsecondary institutions track data on students' demographics, academic performance, course-taking, and financial aid, and have put these data to use, applying data analytics and data science to issues in college completion. Meanwhile, an extensive amount of higher education data are being collected…
Descriptors: Learning Analytics, Postsecondary Education, Academic Achievement, Graduation Rate
Jacob M. Schauer; Arend M. Kuyper; E. C. Hedberg; Larry V. Hedges – Grantee Submission, 2020
States often turn to a data masking procedure called microsuppression in order to reduce the risk of disclosing student records when sharing data with external researchers. This process removes records deemed to have high risk for disclosure should data be released. However, this process can induce differences between the original data and the…
Descriptors: Student Records, Disclosure, Privacy, State Policy
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Jacob M. Schauer; Arend M. Kuyper; Eric C. Hedberg; Larry V. Hedges – Journal of Research on Educational Effectiveness, 2020
States often turn to a data masking procedure called microsuppression in order to reduce the risk of disclosing student records when sharing data with external researchers. This process removes records deemed to have high risk for disclosure should data be released. However, this process can induce differences between the original data and the…
Descriptors: Student Records, Disclosure, Privacy, State Policy
Velie Sando; Dan Hinderliter, Contributor – Advance CTE: State Leaders Connecting Learning to Work, 2025
"Seeing Green: CTE as a Catalyst for the Green Workforce" is a policy playbook that equips education and workforce leaders with actionable strategies to strengthen pathways into emerging green careers by leveraging the effective structures, mindsets, and collaboration provided through Career Technical Education (CTE). This policy…
Descriptors: Career and Technical Education, Conservation (Environment), Occupations, Labor Force Development
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Schildkamp, Kim; Poortman, Cindy L.; Ebbeler, Johanna; Pieters, Jules M. – Journal of Educational Change, 2019
Data-informed decision making is considered important for school improvement. Working in data teams is a promising strategy for implementing data use in schools. Data teams consist of teachers and school leaders, who collaboratively analyze data to solve educational problems at their school. Studies show that school leaders can enable and hinder…
Descriptors: Data Use, Decision Making, Educational Improvement, Teamwork
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Bergner, Yoav; von Davier, Alina A. – Journal of Educational and Behavioral Statistics, 2019
This article reviews how National Assessment of Educational Progress (NAEP) has come to collect and analyze data about cognitive and behavioral processes (process data) in the transition to digital assessment technologies over the past two decades. An ordered five-level structure is proposed for describing the uses of process data. The levels in…
Descriptors: National Competency Tests, Data Collection, Data Analysis, Cognitive Processes
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Hackmann, Donald G.; Malin, Joel R.; Ahn, Joonkil – Journal of Educational Administration, 2019
Purpose: The purpose of this paper is to examine data use practices within a cross-sector initiative involving high school career academies. It discerns how partners used data to assess the public value of academies and address equity concerns. Design/methodology/approach: A case study methodology was applied to examine cross-sector activities…
Descriptors: Data Use, Career Academies, High Schools, Educational Change
Siddiqi, Javaid; Sims, Patrick C.; Goff, Allison L. – Hunt Institute, 2019
The rise of data collection in the public and private sectors has presented policymakers with an unprecedented opportunity to leverage vast amounts of data to create more efficient systems, improve program performance, and drive equitable outcomes. Empowering policymakers and practitioners with functional access to accurate data has the potential…
Descriptors: Longitudinal Studies, Data Collection, Data Analysis, Data Use
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