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No Child Left Behind Act 20011
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Showing 1 to 15 of 20 results Save | Export
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Bird, Erin Bridges; Ballard, Heidi L.; Harte, Margaret – Instructional Science: An International Journal of the Learning Sciences, 2023
Youth-focused Community and Citizen Science (CCS) projects are contexts in which youth can contribute to the entire "data lifecycle"--from data-collection to decision-making with their scientific findings. But data alone does not contain the answers for what action to take and how. Using the educational context of an afterschool CCS bird…
Descriptors: Data Use, Decision Making, Elementary School Students, Educational Change
Oslington, Gabrielle Ruth; Mulligan, Joanne; Van Bergen, Penny – Mathematics Education Research Group of Australasia, 2021
This longitudinal study aimed to determine changes in students' predictive reasoning across one year. Forty-four Australian students predicted future temperatures from a table of maximum monthly temperatures, explained their predictive strategies, and represented the data at two time points: Grade 3 and 4. Responses were analysed using a…
Descriptors: Foreign Countries, Thinking Skills, Prediction, Grade 3
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Keuning, Trynke; van Geel, Marieke; Visscher, Adrie; Fox, Jean-Paul – Journal of Educational Measurement, 2019
Data-based decision making (DBDM) is presumed to improve student performance in elementary schools in all subjects. The majority of studies in which DBDM effects have been evaluated have focused on mathematics. A hierarchical multiple single-subject design was used to measure effects of a 2-year training, in which entire school teams learned how…
Descriptors: Data, Decision Making, Elementary School Students, Mathematics Instruction
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Krumm, Andrew E.; Boyce, Jared; Everson, Howard T. – Journal of Learning Analytics, 2021
This paper describes a collaboration organized around exchanging data between two technological systems to support teachers' instructional decision-making. The goals of the collaboration among researchers, technology developers, and practitioners were not only to support teachers' instructional decision-making but also to document the challenges…
Descriptors: Cooperation, Data Use, Decision Making, Technology Uses in Education
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Jiang, Yang; Gong, Tao; Saldivia, Luis E.; Cayton-Hodges, Gabrielle; Agard, Christopher – Large-scale Assessments in Education, 2021
In 2017, the mathematics assessments that are part of the National Assessment of Educational Progress (NAEP) program underwent a transformation shifting the administration from paper-and-pencil formats to digitally-based assessments (DBA). This shift introduced new interactive item types that bring rich process data and tremendous opportunities to…
Descriptors: Data Use, Learning Analytics, Test Items, Measurement
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Soland, James; Thum, Yeow Meng – Journal of Research on Educational Effectiveness, 2022
Sources of longitudinal achievement data are increasing thanks partially to the expansion of available interim assessments. These tests are often used to monitor the progress of students, classrooms, and schools within and across school years. Yet, few statistical models equipped to approximate the distinctly seasonal patterns in the data exist,…
Descriptors: Academic Achievement, Longitudinal Studies, Data Use, Computation
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Hershkovitz, Arnon – Technology, Instruction, Cognition and Learning, 2015
Still lacking in the mainstream data-driven approaches to studying educational settings is the very basic, most popular educational setting -- that is, the classroom. Capturing data that describes learning in the classroom is the focus of the current issue. The articles in this issue present a large variety of data sources, data collection tools…
Descriptors: Data, Data Use, Instructional Improvement, Data Collection
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Regan, Kelley; Evmenova, Anya S.; Mergen, Reagan L.; Verbiest, Courtney; Hutchison, Amy; Murnan, Reagan; Field, Sara; Gafurov, Boris – Learning Disabilities Research & Practice, 2023
Rubrics can be used to give students targeted feedback on their writing and, therefore, teachers should be able to use them as a type of formative assessment to guide writing instruction. This article describes an exploratory study of how three teachers provided instruction for fourth, fifth, and seventh graders with learning disabilities and…
Descriptors: Grade 4, Grade 5, Grade 7, Elementary School Students
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Gleason, Philip; Crissey, Sarah; Chojnacki, Greg; Zukiewicz, Marykate; Silva, Tim; Costelloe, Sarah; O'Reilly, Fran – National Center for Education Evaluation and Regional Assistance, 2019
Most districts help teachers use data to improve student learning, often supporting this effort with federal funds. But many teachers feel unprepared to use student data to inform their instruction -- referred to as data-driven instruction (DDI) -- and there is little evidence of whether it improves student achievement. This report assesses an…
Descriptors: Data Use, Instruction, Academic Achievement, Professional Development
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Gleason, Philip; Crissey, Sarah; Chojnacki, Greg; Zukiewicz, Marykate; Silva, Tim; Costelloe, Sarah; O'Reilly, Fran – National Center for Education Evaluation and Regional Assistance, 2019
As part of their improvement efforts, schools have increasingly turned to the use of data to improve instruction. This is due in part to the increasing availability of student assessment data throughout the school year. The strategy of using assessment and other data to inform teachers' instruction is often called data-driven instruction (DDI).…
Descriptors: Data Use, Instruction, Academic Achievement, Professional Development
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Gleason, Philip; Crissey, Sarah; Chojnacki, Greg; Zukiewicz, Marykate; Silva, Tim; Costelloe, Sarah; O'Reilly, Fran – National Center for Education Evaluation and Regional Assistance, 2019
The three appendices in this publication accompany the full report, "Evaluation of Support for Using Student Data to Inform Teachers' Instruction. NCEE 2019-4008" (ED598641). They include: (1) Supplemental Information on Study Design, Data, and Methods; (2) Supplemental Findings on Implementation of the Data-Driven Instruction…
Descriptors: Data Use, Instruction, Academic Achievement, Professional Development
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Peters, Martin T.; Förster, Natalie; Hebbecker, Karin; Forthmann, Boris; Souvignier, Elmar – Journal of Learning Disabilities, 2021
In most general education classrooms in Germany, students with and without special educational needs are taught together. To support teachers in adapting instruction to these heterogeneous classrooms, we have developed learning progress assessment (LPA) and reading instructional materials, the "Reading Sportsman" (RS), in line with the…
Descriptors: Data Use, Decision Making, Reading Fluency, Reading Comprehension
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Foster, Elizabeth – Learning Professional, 2019
A recent qualitative study by a team of researchers looked into how grade-level teams of teachers are thinking about causes and strategies based on looking at student performance data. What is interesting in these findings is how infrequently teachers attribute student results to instruction -- just 15% of the time. Teachers in this study were…
Descriptors: Teacher Attitudes, Academic Achievement, Teacher Student Relationship, Data Use
Noble, Amanda – ProQuest LLC, 2019
An achievement gap is defined as a significant difference in academic performance between two groups. Massachusetts Comprehensive Assessment System (MCAS) data indicate that, in Crestland Public School District (pseudonym), there is a clear achievement gap in mathematics between students with disabilities and those without disabilities,…
Descriptors: Achievement Gap, Mathematics Achievement, Students with Disabilities, Elementary School Students
Raudonyte, Ieva – UNESCO International Institute for Educational Planning, 2021
Although the number of countries conducting large-scale assessments has increased significantly over the past two decades, this has not necessarily led to the effective use of learning assessment data in policy-making and planning. To better understand the reasons for this, the UNESCO International Institute for Educational Planning (IIEP)…
Descriptors: Foreign Countries, Measurement, Data Use, Educational Planning
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