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Chenglong Wang – Turkish Online Journal of Educational Technology - TOJET, 2024
The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…
Descriptors: Decision Making, Prediction, Models, Intervention
St. John, Victor; Gabriel, Alexander – National Technical Assistance Center for the Education of Neglected or Delinquent Children and Youth (NDTAC), 2021
The primary purpose of Title 1, Part D programs is to improve the educational outcomes for youth who are categorized as "neglected" (n), "delinquent" (d), or at-risk under the statute. This brief is designed to help State Coordinators, grantees involved in data collection or analyses, and personnel involved in the design of…
Descriptors: Elementary Secondary Education, Federal Legislation, Educational Legislation, At Risk Students
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Attaran, Mohsen; Stark, John; Stotler, Derek – Industry and Higher Education, 2018
Business leaders around the world are using emerging technologies to capitalize on data, to create business value and to compete effectively in a digitally driven world. They rely on data analytics to accelerate time to insight and to gain a better understanding of their customers' needs and wants. However, big data and data analytics solutions in…
Descriptors: Models, Higher Education, Data Collection, Program Implementation
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Filderman, Marissa J.; Austin, Christy R.; Toste, Jessica R. – Intervention in School and Clinic, 2019
The process of implementing intensive reading interventions using data-based decision-making (DBDM) becomes increasingly challenging as students move into the secondary grades and reading tasks correspondingly become more complex. This article provides teachers with guidelines to support effective implementation of DBDM for students with or at…
Descriptors: Data Use, Reading Difficulties, At Risk Students, Secondary School Teachers
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Ruffini, Stephen J.; Miskell, Ryan; Lindsay, Jim; McInerney, Maurice; Waite, Winsome – Regional Educational Laboratory Midwest, 2016
Many schools identified by states as needing improvement through their Elementary and Secondary Education Act waivers have selected Response to Intervention (RTI), a three-tiered instruction program sometimes referred to as tiered levels of instruction, as one of their main strategies for improving school performance and closing achievement gaps.…
Descriptors: Program Implementation, Fidelity, Response to Intervention, Public Schools
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Ruffini, Steffen J.; Lindsay, Jim; Miskell, Ryan; Proger, Amy – Regional Educational Laboratory Midwest, 2016
Regional Educational Laboratory Midwest assisted Milwaukee Public Schools in developing a fidelity monitoring system for measuring schools' progress in implementing Response to Intervention (RTI). The study examined the ratings produced by that system to determine the system's reliability, schools' progress in implementing RTI, and whether ratings…
Descriptors: Program Implementation, Fidelity, Response to Intervention, Public Schools
McIntosh, Kent; Barnes, Aaron; Eliason, Bert; Morris, Kelsey – Technical Assistance Center on Positive Behavioral Interventions and Supports, 2014
The problem of racial and ethnic discipline disproportionality is both long-standing and widespread. Educators must address this issue by identifying rates of discipline disproportionality, taking steps to reduce it, and monitoring the effects of intervention on disproportionality. The purpose of this guide is to provide a reference for…
Descriptors: Positive Behavior Supports, Intervention, Racial Differences, Ethnic Groups
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Brawley, Susan; Stormont, Melissa A. – Journal of Positive Behavior Interventions, 2014
The importance of collecting and using data for educational decision making is clear. However, little information has been gathered about the systematic collection and use of data in early childhood. The purpose of this study was to explore teacher perceptions of data collection practices in early childhood. Participants included 137 early…
Descriptors: Data Collection, Early Childhood Education, Teacher Attitudes, Preschool Teachers
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Prinsloo, Paul; Slade, Sharon – International Review of Research in Open and Distance Learning, 2014
Higher education, and more specifically, distance education, is in the midst of a rapidly changing environment. Higher education institutions increasingly rely on the harvesting and analyses of student data to inform key strategic decisions across a wide range of issues, including marketing, enrolment, curriculum development, the appointment of…
Descriptors: Distance Education, Educational Technology, Colleges, Higher Education
Parker, Tiffany, Ed. – Online Submission, 2015
The NEAIR 2015 Conference Proceedings is a compilation of papers presented at the Burlington, VT, conference. Papers in this document include:(1) Strategies to Analyze Course and Teaching Evaluation Data (Kati Li); (2) Using a Mixed Methods Approach to Assess a Leadership Mentoring Program (Betty Harper); (3) Flagship Institutions and the Struggle…
Descriptors: Conference Papers, Evaluation Methods, Research Methodology, Educational Research
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Siemens, George; Long, Phil – EDUCAUSE Review, 2011
Attempts to imagine the future of education often emphasize new technologies--ubiquitous computing devices, flexible classroom designs, and innovative visual displays. But the most dramatic factor shaping the future of higher education is something that people cannot actually touch or see: "big data and analytics." Learning analytics is still in…
Descriptors: Higher Education, Educational Change, Learning Experience, At Risk Students
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Zweig, Jacqueline; Irwin, Clare W.; Kook, Janna Fuccillo; Cox, Josh – Regional Educational Laboratory Northeast & Islands, 2015
The purpose of this study is to describe what data preschools in a mid-sized city in the Northeast collect, how they use that data, and the challenges they face. The study focuses on three types of data: early learning outcomes, dosage (i.e., the amount of exposure to early childhood education), and classroom quality. The report further…
Descriptors: Preschool Education, Data Collection, Early Childhood Education, Educational Quality
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Zweig, Jacqueline; Irwin, Clare W.; Kook, Janna Fuccillo; Cox, Josh – Regional Educational Laboratory Northeast & Islands, 2015
This "Stated Briefly" report is a companion piece that summarizes the results of another report of the same name. This study explores how seven early childhood education programs in a mid-sized city in the Northeast region are collecting and using data, how they would like to use data, how they could use the data that they have, and the…
Descriptors: Preschool Education, Data Collection, Early Childhood Education, Educational Quality
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Buzhardt, Jay; Greenwood, Charles R.; Walker, Dale; Anderson, Rawni; Howard, Waylon; Carta, Judith J. – NHSA Dialog, 2011
We investigated Early Head Start home visitors' use of evidence-based practices and the efficacy of a web-based system to support these practices. Home visitors learned to use 3 evidence-based practices: (a) frequent assessment of children's early communication for screening and progress monitoring, (b) 2 home-based language-promoting…
Descriptors: Evidence, Early Intervention, Disadvantaged Youth, Home Visits
Workinger, Heather A. – ProQuest LLC, 2011
The purpose of this study was to analyze admissions policies pertaining to the declaration of academic majors for incoming students and structures of academic advising at American universities and how they relate to student outcomes. The student outcomes considered for the study were first to second year retention rates and graduation rates. …
Descriptors: College Admission, Educational Policy, Content Analysis, College Students
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