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Misko, Josie – National Centre for Vocational Education Research (NCVER), 2015
The opening-up of the market for education and training, including vocational education and training (VET), has increased the importance of regulation and quality assurance mechanisms in ensuring the integrity of qualifications. This report investigates approaches to the regulation and quality assurance of vocational education and training in a…
Descriptors: Foreign Countries, Vocational Education, Comparative Education, Quality Assurance
Gershenson, Seth – W. E. Upjohn Institute for Employment Research, 2015
The 2001 No Child Left Behind Act (NCLB) increased accountability pressure in U.S. public schools by threatening to impose sanctions on Title 1 schools that failed to make adequate yearly progress (AYP) in consecutive years. Difference-in-difference estimates of the effect of failing AYP in the first year of NCLB on teacher effort in the…
Descriptors: Accountability, Educational Legislation, Federal Legislation, Teacher Attendance
Beckmann, Jennifer; Weber, Peter – International Association for Development of the Information Society, 2015
The paper introduces a virtual collaborative learning setting called "Net Economy," which we established as part of an international learning network of currently seven universities. Using the Community of Inquiry framework as guidance and Canonical Action Research (CAR) as the chosen research design, the discussion forum of the online…
Descriptors: Electronic Learning, Cooperative Learning, College Students, Foreign Countries
US Department of Education, 2015
The Common Education Data Standards (CEDS) common data vocabulary supports the collection and use of information about virtual and blended learning. The data element "Virtual Indicator", introduced in version 3 of CEDS, supports a range of virtual learning-related use cases. The Virtual Indicator element may be related to a Course…
Descriptors: Blended Learning, Educational Technology, Technology Uses in Education, Elementary Secondary Education
Sparks, Sarah D. – Education Week, 2011
The new and rapidly growing field of educational data mining is using the chaff from data collected through normal school activities to explore learning in more detail than ever, and researchers say the day when educators can make use of Amazon.com-like feedback on student learning behaviors may be closer than most people think. Educational data…
Descriptors: Data Analysis, Educational Indicators, Databases, Technology Uses in Education
Griffith, Robin; Groulx, Judy – Journal of Research in Education, 2014
The Profile for Teacher Decision Making Survey was developed to capture inservice teachers' beliefs and practices related to instructional decision making. Eighty-seven inservice teachers enrolled in various Master's degree programs responded to the survey. Results indicate that most teachers, regardless of grade level or content area taught…
Descriptors: Profiles, Decision Making, Reading Instruction, Best Practices
Mulongo, Godfrey – World Journal of Education, 2014
This review essay looks at three publications that discuss the contentious issue of evaluating education quality (Note 1) by learner outcomes as a proxy indicator (Note 2). The essay explores the debates, gaps and proposes recommendations in the context of Education For All (EFA) (Note 3). The three articles reviewed are Harvey Goldstein's (2004)…
Descriptors: International Assessment, Educational Quality, Quality Assurance, Outcomes of Education
Hawley, Carolyn E.; McMahon, Brian T.; Cardoso, Elizabeth D.; Fogg, Neeta P.; Harrington, Paul E.; Barbir, Lara A. – Rehabilitation Research, Policy, and Education, 2014
Purpose: To examine the recent labor market indicators of science, technology, engineering, and mathematics (STEM) versus non-STEM college graduates with disabilities. Method: The sample included bachelor of science (B.S.)/B.S.-level college graduates including 1,567,527 with a disability and 32,512,446 without a disability. Data were derived from…
Descriptors: STEM Education, College Graduates, Labor Market, Educational Indicators
Savas, Behsat; Gurel, Ramazan – Educational Research and Reviews, 2014
The aim of this study is to determine the variables affecting the success of students. This research, which was conducted through the relational screening model, has a sampling of students who were selected from a middle city in Turkey. The schools are classified into three as low, medium and high. A total of 3491 students are selected by using…
Descriptors: Predictor Variables, Success, Foreign Countries, Educational Indicators
Paufler, Noelle A.; Amrein-Beardsley, Audrey – American Educational Research Journal, 2014
Value-added models (VAMs) are used to measure changes in student achievement on large-scaled standardized test scores from year to year. When aggregated, VAM estimates are used to measure teacher effectiveness and hold teachers accountable for the value they purportedly add to or detract from student learning and achievement. In this study,…
Descriptors: Elementary School Students, Student Placement, Models, Educational Policy
Sae-Khow, Jirasak – Turkish Online Journal of Educational Technology - TOJET, 2014
This study was the development of e-learning indicators used as an e-learning benchmarking model for higher education institutes. Specifically, it aimed to: 1) synthesize the e-learning indicators; 2) examine content validity by specialists; and 3) explore appropriateness of the e-learning indicators. Review of related literature included…
Descriptors: Higher Education, Benchmarking, Educational Indicators, Models
Starr, Joshua P.; Spellings, Margaret – Education Next, 2014
More than 40 states plan to assess student performance with new tests tied to the Common Core State Standards. In summer 2013, results from Common Core-aligned tests in New York showed a steep decline in outcomes. Common Core advocates hailed the scores as an honest accounting of school and student performance, while others worried that they…
Descriptors: High Stakes Tests, State Standards, Academic Standards, Scores
Hale, Jimmie Edwin – ProQuest LLC, 2014
This study explained Academic Progress Rate (APR) levels and differences in APR (DAPR) with team and institutional variables. Team variables included team gender, sport profile, and squad size. Institutional variables included individual variables aggregated to the institutional level. The data analyzed in this study was derived from the National…
Descriptors: Longitudinal Studies, Academic Achievement, Educational Indicators, College Athletics
Malone, Nolan; Mark, Lauren; Narayan, Krishna – Regional Educational Laboratory Pacific, 2014
This guide offers educators, program managers, administrators, and researchers a resource for building capacity for monitoring program outcomes. It provides concise definitions of program monitoring components and a framework for assessing program progress. Examples demonstrate the relationships among program components: outcomes, indicators,…
Descriptors: Capacity Building, Program Evaluation, Program Effectiveness, Outcomes of Education
Light, Heather – ProQuest LLC, 2014
All states test students at specified times as required by the No Child Left Behind Act, but the results of these tests indicate that many students do not meet adequate yearly progress (AYP). This problem was evident in a school district in Missouri in which 3rd-grade students in 2 of the 3 elementary schools did not meet AYP on the communication…
Descriptors: Response to Intervention, Academic Achievement, Educational Indicators, Federal Programs

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