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Bret Bailey – ProQuest LLC, 2024
The purpose of this quantitative study was to provide school district leaders and policymakers information of the impact grade configuration had on academic performance using math and ELA ILEARN scores over a three-year period. The study included data from 585 schools that were classified into four groups: Elementary Setting, Intermediate Setting,…
Descriptors: Academic Achievement, Grade 6, Data, Mathematics
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Erik Eliassen; Ragnhild Eek Brandlistuen; Mari Vaage Wang – European Early Childhood Education Research Journal, 2024
Many studies have linked quality in early childhood education and care [ECEC] to school performance, but the mechanisms of how ECEC process quality affects children in ways that lead to improved school performance is unclear. In this study on 7431 children in Norway, we test the hypothesis that the relation between process quality in ECEC and…
Descriptors: Early Childhood Education, Academic Achievement, Foreign Countries, Interpersonal Competence
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Beverly Cheri Neal – International Journal of Educational Administration and Policy Studies, 2024
The purpose of the study was to better understand the extent to which middle school principals' transformational leadership styles affect teachers' data-informed instruction, the influence of teachers' data-informed instruction on middle school student achievement, and the extent to which transformational leaders affect student achievement through…
Descriptors: Transformational Leadership, Data Use, Teaching Methods, Academic Achievement
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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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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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Changhee Lee; Eric M. Camburn; James Sebastian – School Effectiveness and School Improvement, 2025
This study examines what forms of data school leaders use, how they matter for students' learning, and which school contexts matter for such leadership practices to succeed. Utilizing hierarchical linear modeling, we analyzed survey responses from 1,381 school leaders and administrative data from 269 Florida schools. We find that although school…
Descriptors: Data Use, Decision Making, Principals, Administrator Attitudes
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Nuttaporn Lawthong; Warunee Lapanachokdee; Vorachet Saejea; Purin Thepsathit – International Journal of Educational Management, 2025
Purpose: Drawing from the equitable education fund (EEF) launching 6Qs innovation in the teacher school quality program (TSQP) for small and medium schools, this research aims to analyze the effect size of the ordinary national educational test (O-NET) scores between TSQP schools that implement 6Qs innovation and non-TSQP schools and explain the…
Descriptors: Educational Innovation, Academic Achievement, Foreign Countries, Effect Size
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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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Cumming, Joy; Goldstein, Harvey; Hand, Kirstine – Educational Assessment, Evaluation and Accountability, 2020
In Australia, under the National Assessment Plan, educational accountability testing in literacy and numeracy (NAPLAN) is undertaken with all students in Years 3, 5, 7 and 9 to monitor student achievement and inform policy. However, the extent to which these data have been analysed to report student progress is limited. This article reports a…
Descriptors: Accountability, Data Use, Indigenous Populations, Foreign Countries
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Karimov, Ayaz; Saarela, Mirka; Kärkkäinen, Tommi – International Educational Data Mining Society, 2023
Within the last decade, different educational data mining techniques, particularly quantitative methods such as clustering, and regression analysis are widely used to analyze the data from educational games. In this research, we implemented a quantitative data mining technique (clustering) to further investigate students' feedback. Students played…
Descriptors: Student Attitudes, Feedback (Response), Educational Games, Information Retrieval
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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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