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Showing 1 to 15 of 25 results Save | Export
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Sanetti, Lisa M. H.; Cook, Bryan G.; Cook, Lysandra – Learning Disabilities Research & Practice, 2021
Treatment fidelity refers to the extent to which an intervention is implemented as planned. If researchers do not assess and report treatment fidelity, or if treatment fidelity is shown to be low, findings from intervention studies are difficult to interpret, because the intervention may not have been implemented as planned. In this article, our…
Descriptors: Fidelity, Intervention, Program Implementation, Data Interpretation
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Nicholas D. Myers; Ahnalee M. Brincks; Seungmin Lee – Measurement in Physical Education and Exercise Science, 2024
Physical activity promotion is a best buy for public health because it has the potential to help individuals feel better, sleep better, and perform daily tasks more easily, in addition to providing disease prevention benefits. There is strong evidence that individual-level theory-based behavioral interventions are effective for increasing physical…
Descriptors: Physical Activity Level, Health Behavior, Health Promotion, Public Health
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Ha, Cheyeon – International Journal of Research & Method in Education, 2023
This study aims to introduce network meta-analysis (NMA) to provide educational researchers with an extended view of the reviewing educational research. Meta-analytic methods have been widely used in educational research reviews. However, weaknesses have emerged in the multi-group comparison analysis of educational studies where different…
Descriptors: Comparative Analysis, Network Analysis, Meta Analysis, Intervention
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Sandra Jo Wilson; Brian Freeman; E. C. Hedberg – Grantee Submission, 2024
As reporting of effect sizes in evaluation studies has proliferated, researchers and consumers of research need tools for interpreting or benchmarking the magnitude of those effect sizes that are relevant to the intervention, target population, and outcome measure being considered. Similarly, researchers planning education studies with social and…
Descriptors: Benchmarking, Effect Size, Meta Analysis, Statistical Analysis
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Heilmann, John; Miller, Jon F. – Perspectives of the ASHA Special Interest Groups, 2023
Purpose: In the early 1980s, researchers and speech-language pathologists (SLPs) collaborated to develop the Systematic Analysis of Language Transcripts (SALT). Research and development over the ensuing decades has culminated into SALT Solutions, a set of tools to assist SLPs to efficiently complete language sample analysis (LSA) with their…
Descriptors: Sampling, Language Usage, Data Analysis, Data Collection
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Pamela R. Buckley; Charleen J. Gust; Sarah Gonzalez Coffin; Sheba M. Aikawa; Christine M. Steeger; Fred C. Pampel – Prevention Science, 2025
Evidence reveals that minoritized groups face disparities, underscoring the need for interventions to address behavioral health inequities. This review examined which minoritized populations are represented in evidence-based preventive interventions (EBPIs) and whether they equitably benefit from these programs. Using the Blueprints for Healthy…
Descriptors: Minority Group Students, Evidence Based Practice, Intervention, Prevention
Sebahat Gok – ProQuest LLC, 2024
Many education researchers have advocated grounding abstract mathematical and scientific concepts in students' lived experiences, environmental interactions, and perceptions. This dissertation explores the causal effects of various grounding strategies in instructional settings, specifically on the topic of statistical sampling. The first chapter…
Descriptors: Teaching Methods, Attribution Theory, Statistics Education, Computer Simulation
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Pavelko, Stacey L.; Owens, Robert E., Jr. – Perspectives of the ASHA Special Interest Groups, 2023
Purpose: The purposes of this tutorial are (a) to describe a method of language sample analysis (LSA) referred to as SUGAR (Sampling Utterances and Grammatical Analysis Revised) and (b) to offer step-by-step instructions detailing how to collect, transcribe, analyze, and interpret the results of a SUGAR language sample. Method: The tutorial begins…
Descriptors: Sampling, Language Tests, Data Collection, Data Analysis
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Ahn, June; Nguyen, Ha; Campos, Fabio – Contemporary Issues in Technology and Teacher Education (CITE Journal), 2021
In the United States, teachers are expected to analyze data to inform instruction and improve student learning. Despite investments in data tools, researchers find that teachers often interact with data visualizations in limited ways. Researchers have called for data interpretation training for preservice teachers to increase teachers'…
Descriptors: Visual Aids, Professional Autonomy, Data Interpretation, Data Use
Rosenblum, L. Penny; Zebehazy, Kim T.; Gage, Nicholas A.; Beal, Carole R. – Grantee Submission, 2021
Introduction: Developing graphicacy skills is important for students with visual impairments if they are to succeed in science, technology, engineering, and mathematics (STEM) content. Teachers of students with visual impairments report that they lack resources to use in teaching students graphicacy skills. Methods: Forty-one students with visual…
Descriptors: Algebra, Data Interpretation, Visual Aids, Visual Impairments
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Deke, John; Finucane, Mariel; Thal, Daniel – National Center for Education Evaluation and Regional Assistance, 2022
BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…
Descriptors: Bayesian Statistics, Educational Research, Data Interpretation, Hypothesis Testing
Rosenblum, L. Penny; Zebehazy, Kim T.; Gage, Nicholas A.; Beal, Carole R. – Journal of Visual Impairment & Blindness, 2021
Introduction: Developing graphicacy skills is important for students with visual impairments if they are to succeed in science, technology, engineering, and mathematics (STEM) content. Teachers of students with visual impairments report that they lack resources to use in teaching students graphicacy skills. Methods: Forty-one students with visual…
Descriptors: Algebra, Data Interpretation, Visual Aids, Visual Impairments
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Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…
Descriptors: Intervention, Outcomes of Education, Randomized Controlled Trials, Data Use
Kraft, Matthew A. – Annenberg Institute for School Reform at Brown University, 2019
Researchers commonly interpret effect sizes by applying benchmarks proposed by Cohen over a half century ago. However, effects that are small by Cohen's standards are large relative to the impacts of most field-based interventions. These benchmarks also fail to consider important differences in study features, program costs, and scalability. In…
Descriptors: Data Interpretation, Effect Size, Intervention, Benchmarking
Sarah E. Long – ProQuest LLC, 2021
Missing values that fail to be appropriately accounted for may lead to reduced statistical power, biased estimators, reduced representativeness of the sample, and incorrect interpretations and conclusions (Gorelick, 2006). The current study provided an ontological perspective of data manipulation by explaining how statistical results can…
Descriptors: Statistics, Data Use, Student Records, School Holding Power
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