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National Forum on Education Statistics, 2023
This guide is designed for use by school, district, and state education agency staff to improve the effectiveness of efforts to collect and use discipline data, including reporting accurate and timely data to the federal government. It explains the importance of collecting discipline data, identifies key considerations for agencies implementing…
Descriptors: Discipline, Data Collection, Data Analysis, School Districts
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Logan, Tracy – Australian Educational Researcher, 2020
Secondary data analysis in educational research has been an established research method for many years. Yet, few publications outline the "how to" of undertaking the process. This paper presents an analysis framework suitable for undertaking secondary data analysis within the field of education. The framework is a modification and an…
Descriptors: Data Analysis, Educational Research, Databases, Mathematics Education
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Broumi, Said, Ed. – IGI Global, 2023
Fuzzy sets have experienced multiple expansions since their conception to enhance their capacity to convey complex information. Intuitionistic fuzzy sets, image fuzzy sets, q-rung orthopair fuzzy sets, and neutrosophic sets are a few of these extensions. Researchers and academics have acquired a lot of information about their theories and methods…
Descriptors: Theories, Mathematical Logic, Intuition, Decision Making
Perry, Angela – Project on Student Debt, 2019
California has long been a national and global leader in developing and maintaining quality higher education options, as well as in providing financial aid and consumer protections for Californians who access that education. However, although California's colleges and the state government do collect, receive, and report a great deal of data, these…
Descriptors: Education Work Relationship, Access to Information, Wages, Data Collection
Stelina Chatzichristou; Vlasis Korovilos; Jasper van Loo – UNESCO-UNEVOC International Centre for Technical and Vocational Education and Training, 2025
This publication is the fourth in a series of practical Cedefop skills anticipation guides for policymakers, analysts, and expert professionals. The three previous guides presented a rich mosaic of conventional and emerging methods for identifying technological change and its impact on skills. They assessed the merits and challenges of using…
Descriptors: Foreign Countries, Sustainability, Labor Market, Job Skills
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Lester, Jaime; Klein, Carrie; Rangwala, Huzefa; Johri, Aditya – ASHE Higher Education Report, 2017
The purpose of this monograph is to give readers a practical and theoretical foundation in learning analytics in higher education, including an understanding of the challenges and incentives that are present in the institution, in the individual, and in the technologies themselves. Among questions that are explored and answered are: (1) What are…
Descriptors: Educational Research, Data Collection, Data Analysis, Higher Education
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van Halem, Nicolette; Cornelisz, Ilja; Daly, Alan; van Klaveren, Chris – International Journal of Research & Method in Education, 2023
In educational contexts where many domains subject to improvement are interdependent and causal evidence is frequently lacking it is difficult, if not impossible, for policymakers and educational practitioners to decide which domain should be invested in. This paper proposes a new method that uses Conditional Mean Independent Correlations (CMIC)…
Descriptors: Educational Improvement, Evaluation Methods, Decision Making, Growth Models
National Forum on Education Statistics, 2012
Education data are growing in quantity, quality, and value. When appropriately used to guide action, data can be a powerful tool for improving school operations, teaching, and learning. Education stakeholders who possess the knowledge, skills, and abilities to appropriately access, analyze, and interpret data will be able to use data to take…
Descriptors: Educational Indicators, Data Interpretation, Information Utilization, Data Analysis
Means, Barbara; Anderson, Kea – Office of Educational Technology, US Department of Education, 2013
This report describes how big data and an evidence framework can align across five contexts of educational improvement. It explains that before working with big data, there is an important prerequisite: the proposed innovation should align with deeper learning objectives and should incorporate sound learning sciences principles. New curriculum…
Descriptors: Educational Technology, Technology Uses in Education, Educational Resources, Individualized Instruction
Porter, Kristin E.; Balu, Rekha – MDRC, 2016
Education systems are increasingly creating rich, longitudinal data sets with frequent, and even real-time, data updates of many student measures, including daily attendance, homework submissions, and exam scores. These data sets provide an opportunity for district and school staff members to move beyond an indicators-based approach and instead…
Descriptors: Models, Prediction, Statistical Analysis, Elementary Secondary Education
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Huang, Ronghuai, Ed.; Kinshuk, Ed.; Price, Jon K., Ed. – Lecture Notes in Educational Technology, 2016
This book aims to capture the current innovation and emerging trends of digital technologies for learning and education in k-12 sector through a number of invited chapters in key research areas. Emerging Patterns of innovative instruction in different context, Learning design for digital natives, Digital learning resources for personalized…
Descriptors: Elementary Secondary Education, Computer Uses in Education, Instructional Innovation, Instructional Design
Brown-Chidsey, Rachel; Steege, Mark W. – Guilford Publications, 2010
This bestselling work provides practitioners with a complete guide to implementing response to intervention (RTI) in schools. The authors are leading experts who explain the main components of RTI--high-quality instruction, frequent assessment, and data-based decision making--and show how to use it to foster positive academic and behavioral…
Descriptors: Teaching Methods, Intervention, Reprography, Federal Legislation
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Isenberg, Eric J. – Peabody Journal of Education, 2007
This article discusses quantitative research on homeschooling, including the available data, pitfalls of using the data, estimates of the number of homeschooled children, part-time homeschooling, and why families homeschool. I compare research on homeschooling to research on charter schools, voucher programs, and private schools.
Descriptors: Statistical Analysis, Private Schools, Charter Schools, Home Schooling
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Turner, Stephen J.; O'Brien, Gregory – Journal of the American Society for Information Science, 1984
Results of data analysis on 470 journal titles illustrate complexity of the fuzzy set theory modeling process, which consists of three factors--number of missing issues, citations, circulations--and its limitations in making journal binding decisions. Procedures of research, data collection, and data analysis are discussed. Matrices are included.…
Descriptors: Data Analysis, Data Collection, Decision Making, Discriminant Analysis
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McClure, Charles R. – Government Information Quarterly, 1985
Assesses the value of the Government Printing Office's 1983 "Biennial Survey" as a tool to support depository library planning and decision making. The survey data are evaluated in terms of reliability, validity, and utility, and recommendations are offered for improving the design, administration, and analysis of the survey. (CLB)
Descriptors: Data Collection, Data Interpretation, Decision Making, Depository Libraries
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