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Jihyun Rho; Martina A. Rau – Educational Psychology Review, 2025
Misleading data visualizations have become a significant issue in our information-rich world due to their negative impact on informed decision-making. Consequently, it is crucial to understand the factors that make viewers vulnerable to misleading data visualizations and to explore effective instructional supports that can help viewers combat the…
Descriptors: Visual Aids, Decision Making, Data Use, Deception
Tappel, A. P. M.; Poortman, C. L.; Schildkamp, K.; Visscher, A. J. – Journal of Educational Change, 2023
Many innovations that are implemented in schools are initially successful, but fail to become part of the schools' habits and routines. Relatively little research has followed innovations in schools for a long(er) time. In addition, few reforms last long enough to be studied longitudinally. In this exploratory study, the authors aim to find a way…
Descriptors: Intervention, Sustainability, Educational Innovation, Data Use
Hiroaki Ogata; Changhao Liang; Yuko Toyokawa; Chia-Yu Hsu; Kohei Nakamura; Taisei Yamauchi; Brendan Flanagan; Yiling Dai; Kyosuke Takami; Izumi Horikoshi; Rwitajit Majumdar – Technology, Knowledge and Learning, 2024
This paper explores co-design in Japanese education for deploying data-driven educational technology and practice. Although there is a growing emphasis on data to inform educational decision-making and personalize learning experiences, challenges such as data interoperability and inconsistency with teaching goals prevent practitioners from…
Descriptors: Educational Technology, Instructional Design, Cooperation, Data Use
Marissa J. Filderman; Samantha A. Gesel – TEACHING Exceptional Children, 2024
Data-based decision making (DBDM) is a process of using student data to inform instructional decisions and intensify intervention for students whose data indicate inadequate academic and behavioral progress. Data teams, an important structure for DBDM, are a collaborative group of school faculty who meet to systematically analyze student data,…
Descriptors: Evidence Based Practice, Decision Making, Data Use, Intervention
Alexandra M. Pierce; Melissa A. Collier-Meek; Thea R. Bucherbeam; Lisa M. H. Sanetti – Communique, 2024
Students cannot experience the full potential benefits of an intervention unless they are receiving the intervention. This is the second installment in a three-part series on intervention fidelity designed to highlight the importance of ensuring classroom supports are implemented as intended. This article provides guidance related to measuring and…
Descriptors: Data Use, Decision Making, Intervention, Fidelity
Ansyari, Muhammad Fauzan; Groot, Wim; De Witte, Kristof – Journal of Professional Capital and Community, 2022
Purpose: Professional development interventions (PDIs) are crucial for equipping teachers to use data effectively. Relying on previous studies reporting on such interventions, this paper aims to identify and synthesise the goals, dimensions and conditions of PDIs for data use. This paper also examines the evidence of the effect of such…
Descriptors: Literature Reviews, Meta Analysis, Data Use, Faculty Development
Thomas Nordström; André Kalmendal; Lucija Batinovic – Review of Education, 2023
In order to produce the most reliable syntheses of the effectiveness of educational interventions, systematic reviews need to adhere to rigorous methodological standards. This meta-review investigated risk of bias occurring while conducting a systematic review and the presence of open science practices like data sharing and reproducibility of the…
Descriptors: Bias, Scientific Research, Data Use, Sharing Behavior
Roger Sheng So – ProQuest LLC, 2024
Understanding student engagement with the institution from the first day of classes to the end of the semester would help inform the institution of the potential risk that a student will drop out of a class or of the school. Learning Management Systems (LMS) record student interactions with the system and might be able to be used to identify…
Descriptors: Learning Management Systems, Data Use, At Risk Students, Learner Engagement
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
Rebecca Mazurik – ProQuest LLC, 2024
The implementation of Multi-Tiered System of Supports (MTSS) has been successful in multiple elementary systems across the United States. Providing three tiers of support for students struggling academically, social-emotionally, and behaviorally in the classroom setting and created success for many students until they reach the secondary level,…
Descriptors: Program Implementation, Multi Tiered Systems of Support, Secondary Education, Secondary School Teachers
Rebecca Mazurik – Society for Research on Educational Effectiveness, 2024
The implementation of Multi-Tiered System of Supports (MTSS) has been successful in elementary systems across the United States. For secondary schools, the implementation of MTSS has not been as successful. Secondary teachers often note difficulties include understanding data from different sources, what sources are available, and how it applies…
Descriptors: Program Implementation, Multi Tiered Systems of Support, Secondary Education, Secondary School Teachers
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
Chaparro, Erin A.; Horner, Rob; Algozzine, Bob; Daily, Jessica; Nese, Rhonda N. T. – Center on Positive Behavioral Interventions and Supports, 2022
With multiple sources of information available, knowing how to use data efficiently and effectively with limited resources is critical to the successful implementation of school-wide, classroom, and individual interventions. In this practice guide, we describe a scientifically-based approach for data-based decision-making called Team-Initiated…
Descriptors: Data Use, Problem Solving, Participative Decision Making, Positive Behavior Supports
HLP Writing Team – Council for Exceptional Children, 2024
High-Leverage Practices (HLPs) are a deceptively simple concept in the field of education. On the one hand it is amazing to have a list of key practices that all teachers should learn and be able to implement when teaching students of all backgrounds and ability levels, including those with disabilities. On the other, teaching is rarely simple,…
Descriptors: Educational Practices, Students with Disabilities, Cooperation, Data Use
Juan D’Brot; W. Chris Brandt – Region 5 Comprehensive Center, 2024
Evaluation is a critical component of continuous improvement in education. Robust evaluations enable engaged parties to determine program and intervention impact on key outcomes, identify areas for improvement, and guide future actions. Additionally, as educational systems increasingly focus on data-driven decisionmaking, evaluation becomes even…
Descriptors: Evaluation, Educational Improvement, Program Evaluation, Educational Practices