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Sarah Klevan; Melanie Leung-Gagné; Tomoko M. Nakajima – Learning Policy Institute, 2024
Across the United States, there is an increased interest in improving school climate, reflecting a deepening understanding of the foundational role that school climate can play in supporting students' well-being, learning, and development. School climate is constructed from norms, expectations, and interpersonal relationships that come together to…
Descriptors: Educational Environment, Middle Schools, School Districts, Data Use
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Duncan Culbreth; Rebekah Davis; Cigdem Meral; Florence Martin; Weichao Wang; Sejal Foxx – TechTrends: Linking Research and Practice to Improve Learning, 2025
Monitoring applications (MAs) use digital and online tools to collect and track data on student behavior, and they have become increasingly popular among schools. Empirical research on these complex surveillance platforms is scant, and little is known about the efficacy or impact that they have on students. This study used a multi-method…
Descriptors: High School Students, COVID-19, Pandemics, Progress Monitoring
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Jin, Hui; Hokayem, Hayat; Cisterna, Dante – Research in Science & Technological Education, 2023
Background: New technology and increased collaboration have revolutionized how scientists work with data. This creates a need to identify new aspects of working with scientific data that are important for K-12 students to learn. Purpose: To address this need, we conducted a study with practicing scientists and K-12 science teachers. The purpose of…
Descriptors: Scientists, Science Teachers, Elementary School Teachers, Secondary School Teachers
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Ahn, June; Nguyen, Ha; Campos, Fabio – Contemporary Issues in Technology and Teacher Education (CITE Journal), 2021
In the United States, teachers are expected to analyze data to inform instruction and improve student learning. Despite investments in data tools, researchers find that teachers often interact with data visualizations in limited ways. Researchers have called for data interpretation training for preservice teachers to increase teachers'…
Descriptors: Visual Aids, Professional Autonomy, Data Interpretation, Data Use
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Confrey, Jere; Shah, Meetal – ZDM: Mathematics Education, 2021
This study investigated the process of instructional change required to translate data on student progress along learning trajectories (LTs) into relevant instructional modifications. Researchers conducted a professional development session on ratio LTs, which included analyzing 3 years of district-level data from Math-Mapper 6-8, a digital…
Descriptors: Instructional Improvement, Mathematics Instruction, Data Use, Decision Making
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Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…
Descriptors: Intervention, Outcomes of Education, Randomized Controlled Trials, Data Use
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Kahn, Jennifer; Jiang, Shiyan – Learning, Media and Technology, 2021
We present a micro-analysis of youth interactions with large complex, socioeconomic datasets and data visualization tools. Middle and high school youth used georeferenced data and data visualization tools to assemble models that present their family migration histories in relation to larger socioeconomic trends in a summer program. Using…
Descriptors: Visualization, Data Use, Data Interpretation, Decision Making
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
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Oslund, Eric L.; Elleman, Amy M.; Wallace, Kelli – Journal of Learning Disabilities, 2021
In tiered instructional systems (Response to Intervention [RTI]/Multitier System of Supports [MTSS]) that rely on ongoing assessment of students at risk of experiencing academic difficulties, the ability to make informed decisions using student data is critical for student learning. Prior research has demonstrated that, on average, teachers have…
Descriptors: Data Use, Decision Making, Data Interpretation, Professional Development
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Chikwe, Moses; Cooper, Robert – Journal of Educational Leadership and Policy Studies, 2020
This qualitative phenomenological study explored how 19 school leaders in seven California comprehensive high schools were making sense of data and using data to transform their schools by closing achievement gap for historically underrepresented students. Data is a powerful tool in the hands of school leaders to transform patterns of inequality…
Descriptors: School Administration, Social Justice, Equal Education, Data Use
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Kjelvik, Melissa K.; Schultheis, Elizabeth H. – CBE - Life Sciences Education, 2019
Data are becoming increasingly important in science and society, and thus data literacy is a vital asset to students as they prepare for careers in and outside science, technology, engineering, and mathematics and go on to lead productive lives. In this paper, we discuss why the strongest learning experiences surrounding data literacy may arise…
Descriptors: Data Use, Scientific Research, Information Literacy, STEM Education
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Oren Pizmony-Levy; James Harvey; William H. Schmidt; Richard Noonan; Laura Engel; Michael J. Feuer; Henry Braun; Carla Santorno; Iris C. Rotberg; Paul Ash; Madhabi Chatterji; Judith Torney-Purta – Quality Assurance in Education: An International Perspective, 2014
Purpose: This paper presents a moderated discussion on popular misconceptions, benefits and limitations of International Large-Scale Assessment (ILSA) programs, clarifying how ILSA results could be more appropriately interpreted and used in public policy contexts in the USA and elsewhere in the world. Design/methodology/approach: To bring key…
Descriptors: Misconceptions, International Assessment, Evaluation Methods, Measurement