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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
Kathleen Lynne Lane; Nathan Allen Lane; Mark Matthew Buckman; Katie Scarlett Lane Pelton; Kandace Fleming; Rebecca E. Swinburne Romine – Behavioral Disorders, 2025
We report the results of a convergent validity study examining the externalizing subscale (SRSS-E5, five items) of the adapted Student Risk Screening Scale for Internalizing and Externalizing (SRSS-IE 9) with the externalizing subscale of the Teacher Report Form (TRF) with two samples of K-12 students. Results of logistic regression and receiver…
Descriptors: Data Analysis, Decision Making, Data Use, Test Validity
Yaosheng Lou; Kimberly F. Colvin – Discover Education, 2025
Predicting student performance has been a critical focus of educational research. With an effective predictive model, schools can identify potentially at-risk students and implement timely interventions to support student success. Recent developments in educational data mining (EDM) have introduced several machine learning techniques that can…
Descriptors: Educational Research, Data Collection, Performance, Prediction
Flanagan, Matthew F.; Kutscher, Elisabeth L. – TEACHING Exceptional Children, 2021
Community-based instruction (CBI) is one type of community experience in which students with disabilities work toward instructional goals while engaged in activities occurring in a natural environment outside of a typical school setting (Hoover, 2016; Rowe et al., 2015). Educators who implement CBI capitalize on their students' time in the…
Descriptors: Community Based Instruction (Disabilities), Progress Monitoring, Students with Disabilities, High School Students
Bartholomew, Scott R.; McGraw, Tim; Fauber, Daphne; Charlesworth, Jon; Weitlauf, John – Technology and Engineering Teacher, 2020
Technological advances, artificial intelligence innovations, and widespread computing have all combined to necessitate a new generation of knowledge workers where data becomes a ubiquitous part of decision making (Sutton, 2006). Teaching today's students through the application of this "new" knowledge to long-established fields…
Descriptors: Sanitation, Water, Agriculture, High School Students
Jiang, Shiyan; Tang, Hengtao; Tatar, Cansu; Rosé, Carolyn P.; Chao, Jie – Learning, Media and Technology, 2023
It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…
Descriptors: Artificial Intelligence, High School Students, Models, Classification
Southall, Adam R. – ProQuest LLC, 2023
The American School Counselor Association (ASCA) calls on school counselors to take part in collaborative work experiences using data to address problems of practice. School counselors experience professional isolation leading to underperformance (Elliot et al., 2004; Stone-Johnson, 2015). School structures that lack collaborative experiences for…
Descriptors: Communities of Practice, School Counselors, Cooperation, Attitudes
Dresback, Michael Kyle – ProQuest LLC, 2023
Accountability has pushed principals to use data to drive and inform decisions in schools to positively impact student achievement. Research has shown that principals are the second most important impact on student achievement, second only to teachers. Principals who can lead change in schools based on data driven response have a positive impact…
Descriptors: Administrator Attitudes, Principals, High Schools, Data Use
St. John, Victor; Gabriel, Alexander – National Technical Assistance Center for the Education of Neglected or Delinquent Children and Youth (NDTAC), 2021
The primary purpose of Title 1, Part D programs is to improve the educational outcomes for youth who are categorized as "neglected" (n), "delinquent" (d), or at-risk under the statute. This brief is designed to help State Coordinators, grantees involved in data collection or analyses, and personnel involved in the design of…
Descriptors: Elementary Secondary Education, Federal Legislation, Educational Legislation, At Risk Students
Data Quality Campaign, 2023
The Data Quality Campaign (DQC) has been reviewing state report cards for the past seven years. They continue to examine the landscape of state report cards because they believe states must increase transparency and build trust by sharing information. But after many years, it was time to look at state report cards with fresh eyes. In addition to…
Descriptors: Parent Attitudes, Data Collection, Information Dissemination, Parents
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
Wesley Jeffrey; Benjamin G. Gibbs – Research in Higher Education, 2024
While a substantial body of work has shown that higher-SES students tend to apply to more selective colleges than their lower-SES counterparts, we know relatively less about "why" students differ in their application behavior. In this study, we draw upon a sociological approach to educational stratification to unpack the SES-based gap in…
Descriptors: College Applicants, Socioeconomic Status, Socioeconomic Influences, College Choice
Data Quality Campaign, 2024
People need access to data to make decisions about post-high school experiences, including postsecondary education. Policymakers need to better understand how financial circumstances relate to college enrollment and completion. And students and their families need information about how much financial aid they may have access to for financing their…
Descriptors: High School Graduates, Post High School Guidance, Student Financial Aid, State Federal Aid
Rany Sam; Khorn Sok; Morin Tieng; Hak Yoeng; Sarith Chiv; Sovannpitou Thay; Saing Saorann – European Journal of Educational Management, 2025
This study examines the characteristics, challenges, and strategies of school leadership in Cambodian high schools, with a focus on leadership in resource-constrained settings. Using a qualitative case study approach, the research investigates how principals in six northwestern provinces implement leadership practices to improve educational…
Descriptors: Foreign Countries, Principals, High Schools, Leadership Styles
Roegman, Rachel; Tan, Kevin; Tanner, Nathan; Yore, Caitlin – Journal of Educational Administration, 2022
Purpose: Drawing on Coburn and Turner's framework for research on data use, this study looks at how contextual factors support interactions around data. In so doing, the authors contribute to the emerging body of literature on administrators supporting high school students' social-emotional learning (SEL). Design/methodology/approach: This…
Descriptors: High School Students, Social Emotional Learning, Data Use, High Schools