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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
Desiree Walton – ProQuest LLC, 2023
Decision-making, a key factor of organizational performance, is based on information retrieved from processing raw data. As businesses and consumers are shifting toward digital channels, more and more data is being generated through digital services and electronic devices. Big Data is argued to have significant benefits to businesses, and yet data…
Descriptors: Data Analysis, Data Collection, Construction Industry, Construction Management
McLeod, Bryce D.; Jensen-Doss, Amanda; Lyon, Aaron R.; Douglas, Susan; Beidas, Rinad S. – Grantee Submission, 2022
Mental health organizations that serve youth are under pressure to adopt measurement-based care (MBC), defined as the continuous collection of client-report data used to support clinical decision making as part of standard care. However, few frameworks exist to help leadership ascertain how to select an MBC approach for a clinical setting. This…
Descriptors: Mental Health Programs, Measurement, Evidence Based Practice, Youth
Bekir Duz – ProQuest LLC, 2023
This action research study investigates the role of Data-Based Decision-Making (DBDM) in increasing academic outcomes within a charter school network. During Cycle 1, interviews and focus groups with teachers, interventionists, and school deans shed light on critical themes, including leadership, data collection, analytic capacity, and a culture…
Descriptors: Data Use, Decision Making, Outcomes of Education, Educational Improvement
Morris, Kelsey; Feinberg, Adam – Center on Positive Behavioral Interventions and Supports, 2022
Prioritizing social, emotional, and behavioral supports is essential for student success. By establishing systems to support students' social (how they interact), emotional (how they feel), and behavioral (how they act) needs and growth, educators and leaders can ensure that all students have full access to instruction and the essential skills for…
Descriptors: Fidelity, Data Collection, Positive Behavior Supports, Multi Tiered Systems of Support
Hollands, Fiona; Kushner, Anna – Phi Delta Kappan, 2021
Making evidence-based decisions in schools seems like an impossible task when hundreds of activities are available, the evidence base fails to address most of them, and budget deadlines are immovable. In addition, different stakeholders hold different views on what it means for a program, strategy, or intervention to "work." Fiona…
Descriptors: Evidence Based Practice, Decision Making, Cost Effectiveness, Program Implementation
Pratt-Williams, Jaunelle; Harris, Julie; Saucedo, Daniela; Mislevy, Jessica – Regional Educational Laboratory Appalachia, 2021
Regional Educational Laboratory Appalachia researchers developed the Cost-Feasibility Analysis (CFA) Toolkit to help education leaders estimate whether implementing supplemental online programs is affordable given a school or district's available resources. The CFA Toolkit guides users through a four-stage process that yields cost information that…
Descriptors: Cost Effectiveness, Feasibility Studies, Supplementary Education, Online Courses
Mason, Erica N.; Smith, R. Alex – Intervention in School and Clinic, 2020
Intervention dosage is an often-overlooked aspect of implementation fidelity. Tracking intervention dosage is critical for ensuring students with disabilities were present for and received the intervention for as many minutes as intended. Used in tandem with student performance data, intervention dosage can provide a clearer picture of…
Descriptors: Intervention, Program Implementation, Fidelity, Students with Disabilities
Crawford, Jane C.; Bergeson, Ryan M.; Dierker, Wayne J. – ProQuest LLC, 2019
The problem statement for this project-based learning was loose coupling, when applied to the PBIS framework, translates into major gaps with district-wide implementation of Tier II and Tier III interventions. Additionally, lack of superintendent-adaptive schools' knowledge and practices impact fidelity of implementation. Tier II and Tier III…
Descriptors: Problem Based Learning, Positive Behavior Supports, Program Implementation, School Districts
Culver, K. C.; Harper, Jordan; Kezar, Adrianna – Pullias Center for Higher Education, 2021
A customized guide about liberatory design thinking processes that have been tested within college settings to support changes that enhance equity in policies and practices within institutions. This research is based on case studies of several institutions, including focus group interviews with the campus design teams and an analysis of artifacts.…
Descriptors: Design, Program Design, Colleges, Universities
Dierker, Wayne J.; Crawford, Jane C.; Bergeson, Ryan M. – ProQuest LLC, 2019
The problem statement for this project based learning was loose coupling, when applied to the PBIS framework, translates into major gaps with district wide implementation of Tier II and Tier III interventions. Additionally, lack of superintendent adaptive schools' knowledge and practices impact fidelity of implementation. Tier II and Tier III…
Descriptors: Problem Based Learning, Positive Behavior Supports, Program Implementation, School Districts
Conley, Kathleen M.; Horner, Robert H.; McIntosh, Kent – Technical Assistance Center on Positive Behavioral Interventions and Supports, 2019
A core feature of Positive Behavioral Interventions and Supports (PBIS) is the collection, summary, and use of data for iterative decision-making. The initial design of support and the adaptations that make behavior support match cultural, organizational, and personal needs require that a support team have functional information to guide…
Descriptors: Positive Behavior Supports, Elementary School Students, Decision Making, Progress Monitoring
Attaran, Mohsen; Stark, John; Stotler, Derek – Industry and Higher Education, 2018
Business leaders around the world are using emerging technologies to capitalize on data, to create business value and to compete effectively in a digitally driven world. They rely on data analytics to accelerate time to insight and to gain a better understanding of their customers' needs and wants. However, big data and data analytics solutions in…
Descriptors: Models, Higher Education, Data Collection, Program Implementation
Flannery, K. Brigid; Kato, Mimi McGrath; Horner, Robert H. – Technical Assistance Center on Positive Behavioral Interventions and Supports, 2019
Using data for decision-making is critical for schoolwide leadership teams and has been shown to enhance both social and academic outcomes for students (Faria et al., 2017). Using data effectively, however, requires that teams have a clear vision about the type of data, format of data presentation, and process for using data. To avoid expending…
Descriptors: High School Students, Data Use, Outcomes of Education, Positive Behavior Supports
Pak, Katie; Desimone, Laura M. – Phi Delta Kappan, 2019
Under both No Child Left Behind and the Every Student Succeeds Act, school leaders have been mandated to employ data-driven decision-making (DDDM) to diagnose student needs, implement targeted supports, and design school improvements. However, district administrators tasked with developing principals' DDDM capacity face a tough road. The authors…
Descriptors: Principals, Decision Making, Capacity Building, Evidence Based Practice