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Direct linkMahmoud Abdasalam; Ahmad Alzubi; Kolawole Iyiola – Education and Information Technologies, 2025
This study introduces an optimized ensemble deep neural network (Optimized Ensemble Deep-NN) to enhance the accuracy of predicting student grades. This model solves the problem of different and complicated student performance data by using deep neural networks, ensemble learning, and a number of optimization algorithms, such as Adam, SGD, and RMS…
Descriptors: Grades (Scholastic), Prediction, Accuracy, Artificial Intelligence
Download full textMichael L. Chrzan; Francis A. Pearman; Benjamin W. Domingue – Annenberg Institute for School Reform at Brown University, 2025
The increasing rate of permanent school closures in U.S. public school districts presents unprecedented challenges for administrators and communities alike. This study develops an early-warning indicator model to predict mass closure events -- defined as a district closing at least 10% of its schools -- five years in advance. Leveraging…
Descriptors: Artificial Intelligence, Electronic Learning, School Districts, School Closing
Keith C. Radley; Evan H. Dart – Journal of Behavioral Education, 2025
Recent research has indicated that the manner in which single-case data are typically displayed for visual analysis may influence rater decisions regarding the effect of an intervention. Subsequently, researchers have encouraged adherence to a standard assembly for linear graphs in order to control these effects. Others, however, have encouraged…
Descriptors: Graphs, Research Design, Visual Aids, Data Analysis
Jing Chen; Tianhui Chen – Journal of Computer Assisted Learning, 2025
Background: The creation of Intelligent Supervision Platforms in universities leverages Big Data for robust monitoring and decision-making, which significantly enhances overall efficiency and adaptability in educational environments. Objectives: This research focuses on evaluating how Big Data-driven Intelligent Supervision Platforms in…
Descriptors: Educational Change, Higher Education, Universities, Supervision
Yichun Miriam Liu; Eunice Kim; Greg M. Allenby – Marketing Education Review, 2025
We discuss our experience in teaching data analytics, and in particular prescriptive analytics, to students in business schools using an inter-coherent case study, where a managerial decision is decomposed into a series of research problems with interlocking analyses and the outcome of one analysis is the input of other analysis. Students who…
Descriptors: Business Schools, Computer Software, Marketing, Programming
Juan D’Brot – National Center for the Improvement of Educational Assessment, 2025
Only weeks into its new term, the Trump administration has taken steps to lay off federally funded education research staff, cancel nearly $1 billion in contracts and dismantle the U.S. Department of Education. These moves have upended evaluations of federally funded education programs and threatened access to massive data sets that states,…
Descriptors: Data Use, Decision Making, Capacity Building, Data Analysis
Kathleen Lynne Lane; Katie Scarlett Lane Pelton; Nathan Allen Lane; Mark Matthew Buckman; Wendy Peia Oakes; Kandace Fleming; Rebecca E. Swinburne Romine; Emily D. Cantwell – Behavioral Disorders, 2025
We report findings of this replication study, examining the internalizing subscale (SRSS-I4) of the revised version of the Student Risk Screening Scale for Internalizing and Externalizing behavior (SRSS-IE 9) and the internalizing subscale of the Teacher Report Form (TRF). Using the sample from 13 elementary schools across three U.S. states with…
Descriptors: Data Analysis, Decision Making, Data Use, Measures (Individuals)
Jo Boaler; Cathy Williams – Corwin, 2025
How can we prepare students for a world where data-driven decision-making shapes nearly every aspect of life? "Data Minds: How Today's Teachers Can Prepare Students for Tomorrow's World" helps K-8 educators infuse data literacy into everyday lessons across disciplines, without overwhelming existing curricula. Data literacy is an ability…
Descriptors: Data Use, Decision Making, Information Literacy, Data Analysis
Eric Ortega González; Jairo Jiménez – Educational Philosophy and Theory, 2025
This article examines contemporary educational practices within the rapidly evolving landscape of Artificial Intelligence. We do so by analysing the relationship between artificiality and naturalness in education. Education, often characterized as a human and thus natural-historical phenomenon, now appears increasingly shaped by artificial…
Descriptors: Artificial Intelligence, Educational Practices, Man Machine Systems, Data Analysis
Thomas R. Guskey, Editor; Cassandra Erkens, Contributor; Katie White, Contributor; Mandy Stalets, Contributor; Garnet Hillman, Contributor; Tim Brown, Contributor; Tom Hierck, Contributor; Tom Schimmer, Contributor; Sharon V. Kramer, Contributor; Sarah Schuhl, Contributor; Anthony R. Reibel, Contributor; Joellen Killion, Contributor – Solution Tree, 2025
In "The Teacher as Assessment Leader, Second Edition," editor Thomas R. Guskey and expert contributors offer research-backed strategies for re-envisioning assessment to enhance student learning and teacher instruction. The authors provide actionable steps, practical examples, and strategies for utilizing formative assessments. These…
Descriptors: Teacher Leadership, Formative Evaluation, Data Analysis, Evidence Based Practice
Nicole Barnes; Helenrose Fives; Coby V. Meyers; Tonya R. Moon – Journal of Educational Administration, 2025
Purpose: School principals are increasingly responsible for acting as instructional leaders, but research on data teams typically considers principals as secondary players responsible for ensuring that meetings occur but not necessarily for their quality. We investigated how elementary school principals in one district committed to data use…
Descriptors: Elementary Schools, Rural Areas, School Districts, Principals
Katerina Guba; Angelika Tsivinskaya – Studies in Higher Education, 2025
This paper explores the regulators' perspective and demonstrates how legitimacy deficits of private universities outweigh performance results in decisions regarding university inspections. We examined the period when the regulator had an urgent claim on Russian universities, particularly during the campaign to 'clean the system of higher…
Descriptors: Private Sector, Private Education, Universities, Private Colleges
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
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
Jennifer Sdunzik; Ann M. Bessenbacher; Wilella D. Burgess; Asia M. Mohamud; Abdirisak Dalmar – American Journal of Evaluation, 2025
The success of development projects and evaluations hinges on having access to research protocols and methodologies that consider the needs and characteristics of stakeholders, subjects, and context while remaining rigorous and culturally sound. These efforts are often complicated by a dearth of tools that have been tested for validity and…
Descriptors: Foreign Countries, Program Evaluation, International Programs, Data Collection
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