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Agley, Jon; Tidd, David; Jun, Mikyoung; Eldridge, Lori; Xiao, Yunyu; Sussman, Steve; Jayawardene, Wasantha; Agley, Daniel; Gassman, Ruth; Dickinson, Stephanie L. – Educational and Psychological Measurement, 2021
Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…
Descriptors: Data Analysis, Longitudinal Studies, Data Collection, Intervention
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Wardrip, Peter S.; Herman, Phillip – Teacher Development, 2018
Internationally, there has been a policy push for using student data for instruction. Yet, research has noted few examples of actually understanding how this data-use practice takes place. This study presents a case of an instructional data team making sense of student data. The study shares data to show how teachers' process for using data to…
Descriptors: Faculty Development, Educational Improvement, Case Studies, Charter Schools
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Gao, Niu; Semykina, Anastasia – Journal of Research on Educational Effectiveness, 2021
Inappropriate treatment of missing data may introduce bias into the value-added estimation. We consider a commonly used value-added model (VAM), which includes the past student test score as a covariate. We formulate a joint model of student achievement and missing data, in which the probability of observing a test score depends on observing the…
Descriptors: Value Added Models, Elementary School Teachers, Computation, Scores
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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
David Michael Simpson – ProQuest LLC, 2021
The Conover Solution is a nonparametric method used to analyze relative growth in students' achievement on state tests administered on two or more occasions. However, there has been very little research assessing the robustness of this method in the presence of missing data. Using vertically scaled and non-vertically scaled data from the math…
Descriptors: Academic Achievement, Data, Standardized Tests, Grade 4
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Eva Ponte – Center for Educational Policy Studies Journal, 2024
Education is seen as a resource at a global level but is currently considered to be in crisis in many parts of the world. This constitutes a significant drawback in terms of humanity's prosperity and well-being since education is the key not only to an educated workforce but also to humane, collaborative, and caring societies. Even within this dim…
Descriptors: Foreign Countries, Grade 8, Grade 4, Mathematics Education
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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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Baloglu, Nuri – Educational Research and Reviews, 2017
In this study, the effects of family leadership orientation on social entrepreneurship, generativity and academic education success were examined with the views of college students. The study was conducted at a state university in Central Anatolia in Turkey. 402 college students who attending at three different colleges voluntarily participated in…
Descriptors: Leadership, Entrepreneurship, Academic Achievement, College 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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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
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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Meinck, Sabine; Stancel-Piatak, Agnes; Eraydin, Ipek – AERA Online Paper Repository, 2017
The acquisition of early literacy skills prior to school can positively influence later educational outcomes. However, children from culturally and economically disadvantaged backgrounds often lack stimulating educational activities at home. This analysis provides empirical evidence for 31 education systems on the association between parental…
Descriptors: Achievement Tests, Foreign Countries, Reading Achievement, Reading Tests
Raudonyte, Ieva – UNESCO International Institute for Educational Planning, 2021
Large-scale learning assessments can be used to generate performance and contextual data on student learning outcomes. They can be national, regional, or international; school based or household based. The UNESCO International Institute for Educational Planning (IIEP-UNESCO) has conducted a qualitative study to explore both how and why learning…
Descriptors: Foreign Countries, Measurement, Data Use, Educational Planning
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