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Schweig, Jonathan; McEachin, Andrew; Kuhfeld, Megan; Mariano, Louis T.; Diliberti, Melissa Kay – RAND Corporation, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
Jonathan Schweig; Andrew McEachin; Megan Kuhfeld; Louis T. Mariano; Melissa Kay Diliberti – Grantee Submission, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
Simsek, Mertkan – International Journal of Technology in Education, 2022
Considering the large volume of PISA data, it is expected that data mining will often be assisted in making PISA data more meaningful. Studies show that different dimensions of ICT may reveal different relationships for mathematics achievement. The purpose of this article is to evaluate the success of the decision tree classification algorithms in…
Descriptors: Predictor Variables, Mathematics Achievement, Achievement Tests, Foreign Countries
Klingbeil, David A.; Osman, David J.; Van Norman, Ethan R.; Berry-Corie, Kimberly; Kim, Jessica S.; Schmitt, Madeline C.; Latham, Alexander D. – Reading & Writing Quarterly, 2023
Accurate and efficient universal screening is a foundational component of multi-tiered systems of support for reading. By the time students reach middle school, educators often have extant data available to inform screening decisions. Therefore, the decision to collect additional data to inform screening should be considered carefully. The…
Descriptors: Screening Tests, Reading Tests, Middle School Students, Identification
NWEA, 2020
To help provide context to MAP® Growth™ normative percentiles, this document includes multiple College and Career Readiness (CCR) benchmarks, including those from ACT®, SAT®, and Smarter Balanced Assessment Consortium (Smarter Balanced). The comparative data in the tables presented in this report can be used as data points for instructional…
Descriptors: Data Use, Decision Making, Achievement Tests, College Entrance Examinations
Farley-Ripple, Elizabeth N.; Jennings, Austin S.; Buttram, Joan – AERA Open, 2019
Research consistently has found teachers' use of assessment data for instructional purposes challenging and inconsistent. To support teachers' use of data, we need to develop shared knowledge about how data are and can be used to advance teaching and learning. However, the literature on the specific actions teachers take is inconsistent, creating…
Descriptors: Data Use, Elementary School Teachers, Teacher Educators, Teaching Methods
NWEA, 2017
When Superintendent Dennis Vespe came to Somerdale Park School District, he was very interested in strengthening teachers' capacity to track student growth and progress. To do this, he knew the district needed to enhance its "ability to accurately assess and accurately drive instruction." But years of experience had taught him that new…
Descriptors: School Districts, Achievement Tests, Achievement Gains, Data
dos Santos, Roberta Alvarenga; Paulista, Cássio Rangel; da Hora, Henrique Rego Monteiro – Technology, Knowledge and Learning, 2023
The demand for in-depth studies on educational data presupposes the application of technologies that allow data analysis of vast quantities, and subsequently, drawing relevant information and knowledge. The research objective herein is to employ data mining techniques on PISA databases to identify potential patterns that may explain the…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students
Bertrand, Melanie; Marsh, Julie – Phi Delta Kappan, 2021
Propelled by accountability policies, leaders have touted data-driven decision making as a means to improve K-12 student outcomes and drive equity, as teachers analyze data to change instruction. However, many data-driven decision-making reforms have failed to challenge inequity. Melanie Bertrand and Julie Marsh's study of six middle schools shows…
Descriptors: Data Analysis, Educational Policy, Accountability, Middle School Students
Blagg, Kristin; Lukes, Marguerite – Urban Institute, 2022
More than a quarter of US children have at least one immigrant parent, but researchers and policymakers often do not have adequate data on these children's experiences in school, with far-reaching implications for instruction, student support services, and policy. Proxy factors that are reported by school--such as being designated as an English…
Descriptors: Data Analysis, Immigrants, Educational Policy, Educational Experience
NWEA, 2019
At Tamassee-Salem Elementary School in South Carolina, teacher Anna Durham likes to have data conferences with her third graders. She creates a simple graph of their MAP® Growth™ interim assessment scores with past and current scores, along with a future goal. She believes talking about goals--and how they will get there together--helps to engage…
Descriptors: Case Studies, Decision Making, Scores, Achievement Tests
Amanda Katherine Riske – ProQuest LLC, 2022
This three-article dissertation considers the pedagogical practices for developing statistically literate students and teaching data-driven decision-making with the goal of preparing students for civic engagement and improving student achievement. The first article discusses a critical review of the literature on data-driven decision-making…
Descriptors: Teaching Methods, Data Use, Decision Making, Educational Practices
Roegman, Rachel; Kenney, Rachael; Maeda, Yukiko; Johns, Gary – Educational Policy, 2021
This case study examines how district administrators and high school mathematics and science teachers use data in instructional decision making and what challenges they face in the current accountability context. Findings reveal unique aspects of data use directly related to a high school setting within the context of test-based accountability and…
Descriptors: Case Studies, Educational Policy, Decision Making, High School Students
Gabriel, Florence; Signolet, Jason; Westwell, Martin – International Journal of Research & Method in Education, 2018
Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and…
Descriptors: Artificial Intelligence, Mathematics Instruction, Numeracy, Models
Thinking Heuristically about Student Growth in Austin Independent School District. Publication 17.33
Hutchins, Shaun D.; DeBaylo, Paige Hartman; Williams, Holly – Online Submission, 2018
This report presents a question-driven exploration of growth and achievement data using SAS EVAAS reports. The purpose of this exploration was to bring additional data, information, and ways of thinking about student growth to ongoing district conversations about the measurement of campus-level student growth.
Descriptors: School Districts, Achievement Gains, Achievement Tests, High Schools

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