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Jessica Arnold; Julie Webb – WestEd, 2024
While there are many different types of education data, policymakers and education leaders often place heavy emphasis on data from large-scale quantitative measures, such as annual state assessments. But data from these sources alone do not provide a complete picture of learning and are often not well suited to informing improvements at the local…
Descriptors: Data Use, Measurement, Educational Improvement, Outcomes of Education
Walston, Jill; Conley, Marshal – Regional Educational Laboratory Southwest, 2022
This toolkit is designed to guide educators in developing and improving practical measurement instruments for use in networked improvement communities (NICs) and other education contexts in which principles of continuous improvement are applied. Continuous improvement includes distinct repeating processes: understanding the problem, identifying…
Descriptors: Measurement Techniques, Measurement, Educational Improvement, Communities of Practice
Ian Hardy – Professional Development in Education, 2024
Schooling in Australia has become subject to increased processes of data-based governance. This article draws upon the insights of an experienced teacher, 'Meriam', who, having taught more than 34-years over almost a 50-year span, reflected upon the nature of such changes. Utilising theorising in relation to datafication processes and…
Descriptors: Foreign Countries, Experienced Teachers, Teacher Attitudes, Educational Change
Kino Zhao – ProQuest LLC, 2021
This dissertation is composed of projects on three aspects of gathering and learning from data in the social sciences: drawing representative samples, taking valid measurement, and making warranted inductive inferences. Chapter one studies the challenge of drawing representative human samples. It is well documented that most samples used by…
Descriptors: Social Sciences, Data Collection, Data Use, Educational Research
Juan D’Brot; W. Chris Brandt – Region 5 Comprehensive Center, 2024
In today's educational landscape, state and local educational agencies (SEAs and LEAs) often experience challenges connecting large-scale accountability data with actual school improvement initiatives. These challenges tend to be rooted in incoherent design and use of data systems for continuous improvement. As we aim to support SEAs in…
Descriptors: Educational Improvement, Data Collection, State Departments of Education, School Districts
Prinsloo, Paul – British Journal of Educational Technology, 2019
Data--their collection, analysis and use--have always been part of education, used to inform policy, strategy, operations, resource allocation, and, in the past, teaching and learning. Recently, with the emergence of learning analytics, the collection, measurement, analysis and use of student data have become an increasingly important research…
Descriptors: Learning Analytics, Data Collection, Data Analysis, Measurement
Williamson, Ben – Journal of Education Policy, 2021
Psychology and economics are powerful sources of expert knowledge in contemporary governance. Social and emotional learning (SEL) is becoming a priority in education policy in many parts of the world. Based on the enumeration of students' 'noncognitive' skills, SEL consists of a 'psycho-economic' combination of psychometrics with economic…
Descriptors: Social Emotional Learning, Data Collection, Data Use, Educational Policy
Madsen, Miriam – Journal of Education Policy, 2021
The increased use of quantitative education data is often regarded by scholars as evidence of the emergence of 'governing by numbers'. These scholars ascribe major stakeholders such as the OECD and nation states agency as they produce, distribute and consume data, and respond to these with policy and management initiatives. This paper argues that…
Descriptors: Measurement, Evaluation Methods, Qualitative Research, Data Analysis
Hewitt, Rachel – Higher Education Policy Institute, 2019
In this new Policy Note, Rachel Hewitt, HEPI's Director of Policy and Advocacy, highlights the need to distinguish between mental health and well-being and calls for more comprehensive data to be made available on the well-being of all those work and study at universities. Key points: (1) The conflation of mental health and well-being is not…
Descriptors: Well Being, Higher Education, Mental Health, Data Collection
Huie, Stephanie Bond; Troutman, David R. – Institute for Higher Education Policy, 2019
Accurate, timely data on student outcomes and post-graduate earnings is a critical piece of any state effort to close equity gaps in college access and success, boost attainment statewide, and strategically align education and workforce goals. Unfortunately, in the absence of a federal student-level data network, states and other key stakeholders…
Descriptors: Universities, Government School Relationship, Partnerships in Education, Data Collection
Dalporto, Hannah – MDRC, 2019
Career and technical education (CTE) programs (programs that teach students specific workplace skills aligned with the labor market) may track data for lots of different reasons: to comply with funding requirements, to manage their services and continually improve, to measure their progress toward their goals, and to evaluate whether they are…
Descriptors: Vocational Education, Data Use, Program Development, Data Collection
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use

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