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Noonan, James; Schneider, Jack – Phi Delta Kappan, 2022
Parents and the public use accountability data to judge if schools are doing a good or a bad job educating their students. However, using the current data, schools perceived as "good" tend to be in better-resourced districts and enroll higher percentages of wealthy and white students. Schools perceived as "bad" tend to be in…
Descriptors: Educational Quality, Accountability, School Demography, Educational Resources
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Choi, Jungtae; Kim, Kihyun – Prevention Science, 2022
The purpose of this study was to explore and identify patterns of risk predictors of maltreatment recurrence using predictive risk modeling (PRM). This study used the administrative dataset from the National Child Maltreatment Information System recorded by Korean CPS (Child Protective Service) workers. The information, including recurrent…
Descriptors: Foreign Countries, Child Abuse, Social Services, Children
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Dubrow, Joshua K. – International Journal of Social Research Methodology, 2022
The COVID 19 pandemic illuminates the role data has in public policy-making, i.e. datafication of society, and the importance of exploring the local sources of data to reveal errors in what has assuredly been from the beginning an undercount of cases and deaths. I note four interrelated error sources. The first two are common to any quantitative…
Descriptors: Data Use, COVID-19, Pandemics, Data Collection
Region 8 Comprehensive Center, 2022
Most school and district leaders have a wealth of information available to them before, during, and after the hiring process, but they might not analyze it regularly or use it to inform their recruitment and retention plans. However, using data strategically is key to positively impacting teacher recruitment and retention. This brief discusses…
Descriptors: Data Use, Teacher Recruitment, Teacher Persistence, Elementary Secondary Education
Keeanna Jessica Marie Warren – ProQuest LLC, 2022
Teacher turnover continues to be a significant problem in the United States. Teacher turnover is expensive because it costs money to continue recruiting, hiring, and training new teachers to replace those leaving (Carver-Thomas & Darling-Hammond, 2017). Most important though, teacher turnover hurts student achievement and success (Sorensen…
Descriptors: Data Analysis, Prediction, Teacher Persistence, Faculty Mobility
Eric Jordan Mendelson – ProQuest LLC, 2022
Educators and researchers have long contemplated the most effective ways to provide feedback to students, to build sustainable feedback practices, and to establish feedback literacy. While a considerable amount of research, theory, and practical approaches exist to support the effect of formative feedback practices, less research exists on the…
Descriptors: Preservice Teachers, Teacher Attitudes, Feedback (Response), Data Use
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Amelia Parnell – Journal of Postsecondary Student Success, 2022
Data-informed decision-making is no longer an optional or occasional practice, as higher education professionals now routinely respond to calls for accountability by providing data to show how their work impacts students. Institutions are operating with a culture that, at a minimum, includes the use of descriptive and diagnostic analyses to assess…
Descriptors: Student Needs, Data Use, Prediction, Data Analysis
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Melissa A. Gallagher; Jennifer E. Scholla – Mathematics Teacher: Learning and Teaching PK-12, 2025
Adaptive teachers use student data to guide instruction. Learn about using an anecdotal record form to support adaptive teaching. In this article, the authors describe how teachers can use learning trajectories to make adaptive decisions to meet the needs of their students. They provide an example using the U .S. Math Recovery Council's learning…
Descriptors: Mathematics Instruction, Learning Trajectories, Developmentally Appropriate Practices, Student Needs
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Elliott Ostler; Tami Williams; John Schultz – School Leadership Review, 2025
In today's data-driven and data-informed educational landscape, leaders face increasing pressure to make decisions and present results based on what appear to be comprehensive statistical analyses. However, the ethical implications of these responsibilities can be complex, particularly when statistical results carry the potential to be…
Descriptors: Data Analysis, Statistical Analysis, Data Use, Ethics
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Qinyi Liu; Ronas Shakya; Jelena Jovanovic; Mohammad Khalil; Javier Hoz-Ruiz – British Journal of Educational Technology, 2025
High-volume, high-quality and diverse datasets are crucial for advancing research in the education field. However, such datasets often contain sensitive information that poses significant privacy challenges. Traditional anonymisation techniques fail to meet the privacy standards required by regulations like GDPR, prompting the need for more robust…
Descriptors: Privacy, Data, Information Security, Compliance (Legal)
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Elizabeth J. Allan; Kimberly Stewart; David Kerschner – Journal of Student Affairs Research and Practice, 2025
This investigation explored the concept and practice of organizational commitment to hazing prevention in higher education. Using Bolman and Deal's four frames we analyzed qualitative data from written materials and interviews with 16 campus professionals at eight U.S. universities. Findings revealed structural, human resource, political, and…
Descriptors: College Role, Hazing, Prevention, College Administration
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Ulrike Krein – Leadership and Policy in Schools, 2025
In the context of digital transformation processes in schools, the introduction of technology is often discussed in terms of the individualization and optimization of teaching, learning and school management. However, it is often neglected that technologies are preconfigured and provide socio-material offers that invite certain actions and thus…
Descriptors: Educational Technology, Technology Uses in Education, Technology Integration, School Administration
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Robin Clausen – Discover Education, 2025
Early Warning Systems (EWS) are research-based analytics that use statistical models to assess dropout risk. School leaders use this analytic to consolidate data about a student and provide actionable data to craft an intervention. Little is currently known about the processes involved in school implementation or data use. By analyzing Montana EWS…
Descriptors: Dropout Prevention, Data Analysis, Principals, School Counselors
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Mukesh Kumar Rohil; Saksham Mahajan; Trishna Paul – Education and Information Technologies, 2025
Intelligent Tutoring Systems (ITS) and Augmented Reality (AR) have become greatly popular in current scenario, especially for helping students in mastering difficult subjects through a variety of different methods with the implementation of smart algorithms. There are many papers in the current literature that discuss the ITS architecture and the…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Physical Environment, Simulated Environment
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Fang-Ying Yang; Yuan-Li Liu; Shih-Chieh Chien; Yi-Wen Hung – Educational Technology & Society, 2025
In this study, an interactive science learning app on the topic of plate tectonics was developed for tablets to promote argumentative reasoning. The app guided learners through learning stages that required them to propose arguments, identify relevant evidence, acquire background knowledge, and engage in argumentative reasoning in different…
Descriptors: Abstract Reasoning, Persuasive Discourse, Visual Perception, Attention
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