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Calvi, Michael; Vieira, Ana Paula Alves; Georgiou, George; Parrila, Rauno – Australasian Journal of Special and Inclusive Education, 2023
A number of studies have examined the effects of reading interventions for younger readers; however, there does not appear to be any existing syntheses examining the effect of reading interventions on students in Years 7--12. The purpose of this study was to establish whether such a synthesis is feasible by reviewing the methodological quality of…
Descriptors: Reading Instruction, Intervention, Secondary School Students, Reading Research
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Zuchao Shen; Ben Kelcey – Society for Research on Educational Effectiveness, 2023
I. Purpose of the Study: Detecting whether interventions work or not (through main effect analysis) can provide empirical evidence regarding the causal linkage between malleable factors (e.g., interventions) and learner outcomes. In complement, moderation analyses help delineate for whom and under what conditions intervention effects are most…
Descriptors: Intervention, Program Effectiveness, Evidence, Research Design
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Ishita Ahmed; Masha Bertling; Lijin Zhang; Andrew Ho; Prashant Loyalka; Scott Rozelle; Ben Domingue – Society for Research on Educational Effectiveness, 2023
Background: Evidence from education randomized controlled trials (RCTs) in low- and middle-income countries (LMICs) demonstrates how interventions can improve children's educational achievement [1, 2, 3, 4]. RCTs assess the impact of an intervention by comparing outcomes--aggregate test scores--between treatment and control groups. A review of…
Descriptors: Randomized Controlled Trials, Educational Research, Outcome Measures, Research Design
Ishita Ahmed; Masha Bertling; Lijin Zhang; Andrew D. Ho; Prashant Loyalka; Hao Xue; Scott Rozelle; Benjamin W. Domingue – Annenberg Institute for School Reform at Brown University, 2023
Researchers use test outcomes to evaluate the effectiveness of education interventions across numerous randomized controlled trials (RCTs). Aggregate test data--for example, simple measures like the sum of correct responses--are compared across treatment and control groups to determine whether an intervention has had a positive impact on student…
Descriptors: Randomized Controlled Trials, Educational Research, Outcome Measures, Research Design
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Louise D. Denne; Gwenllian Moody; Elinor Coulman; David Gillespie; Kate Ingarfield; Nicholas Manktelow; Corinna F. Grindle; J. Carl Hughes; Zac Taylor; Richard P. Hastings – Journal of Applied Research in Intellectual Disabilities, 2025
Background: There is a paucity of research into interventions that help people with intellectual disabilities learn to read. This feasibility study examines whether an online reading programme, Headsprout, with additional support strategies and supervision (the intervention), can be delivered by support workers/family carers and the feasibility of…
Descriptors: Reading Skills, Reading Instruction, Intellectual Disability, Online Courses
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James Soland – Journal of Research on Educational Effectiveness, 2024
When randomized control trials are not possible, quasi-experimental methods often represent the gold standard. One quasi-experimental method is difference-in-difference (DiD), which compares changes in outcomes before and after treatment across groups to estimate a causal effect. DiD researchers often use fairly exhaustive robustness checks to…
Descriptors: Item Response Theory, Testing, Test Validity, Intervention
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Garret J. Hall; Sophia Putzeys; Thomas R. Kratochwill; Joel R. Levin – Educational Psychology Review, 2024
Single-case experimental designs (SCEDs) have a long history in clinical and educational disciplines. One underdeveloped area in advancing SCED design and analysis is understanding the process of how internal validity threats and operational concerns are avoided or mitigated. Two strategies to ameliorate such issues in SCED involve replication and…
Descriptors: Research Design, Graphs, Case Studies, Validity
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Kylie E. Hunter; Mason Aberoumand; Sol Libesman; James X. Sotiropoulos; Jonathan G. Williams; Jannik Aagerup; Rui Wang; Ben W. Mol; Wentao Li; Angie Barba; Nipun Shrestha; Angela C. Webster; Anna Lene Seidler – Research Synthesis Methods, 2024
Increasing concerns about the trustworthiness of research have prompted calls to scrutinise studies' Individual Participant Data (IPD), but guidance on how to do this was lacking. To address this, we developed the IPD Integrity Tool to screen randomised controlled trials (RCTs) for integrity issues. Development of the tool involved a literature…
Descriptors: Integrity, Randomized Controlled Trials, Participant Characteristics, Computer Software
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Nianbo Dong; Benjamin Kelcey; Jessaca Spybrook; Yanli Xie; Dung Pham; Peilin Qiu; Ning Sui – Grantee Submission, 2024
Multisite trials that randomize individuals (e.g., students) within sites (e.g., schools) or clusters (e.g., teachers/classrooms) within sites (e.g., schools) are commonly used for program evaluation because they provide opportunities to learn about treatment effects as well as their heterogeneity across sites and subgroups (defined by moderating…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Educational Research, Effect Size
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Xinhe Wang; Ben B. Hansen – Society for Research on Educational Effectiveness, 2024
Background: Clustered randomized controlled trials are commonly used to evaluate the effectiveness of treatments. Frequently, stratified or paired designs are adopted in practice. Fogarty (2018) studied variance estimators for stratified and not clustered experiments and Schochet et. al. (2022) studied that for stratified, clustered RCTs with…
Descriptors: Causal Models, Randomized Controlled Trials, Computation, Probability
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Justin Boutilier; Jonas Jonasson; Hannah Li; Erez Yoeli – Society for Research on Educational Effectiveness, 2024
Background: Randomized controlled trials (RCTs), or experiments, are the gold standard for intervention evaluation. However, the main appeal of RCTs--the clean identification of causal effects--can be compromised by interference, when one subject's actions can influence another subject's behavior or outcomes. In this paper, we formalize and study…
Descriptors: Randomized Controlled Trials, Intervention, Mathematical Models, Interference (Learning)
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Wendy Castillo; Lindsay Dusard – Society for Research on Educational Effectiveness, 2024
Background: The emergence of causal research in education was almost strictly quantitative twenty years ago, however, that landscape has changed considerably. The number of intervention studies fielded and completed annually has increased substantially, and the quality of the evaluations is much more robust, including paying much greater attention…
Descriptors: Randomized Controlled Trials, Educational Research, Equal Education, Educational Policy
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Huang, Francis L.; Zhang, Bixi; Li, Xintong – Journal of Research on Educational Effectiveness, 2023
Binary outcomes are often analyzed in cluster randomized trials (CRTs) using logistic regression and cluster robust standard errors (CRSEs) are routinely used to account for the dependent nature of nested data in such models. However, CRSEs can be problematic when the number of clusters is low (e.g., < 50) and, with CRTs, a low number of…
Descriptors: Robustness (Statistics), Error of Measurement, Regression (Statistics), Multivariate Analysis
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Maite Alguacil; Noemí Herranz-Zarzoso; José C. Pernías; Gerardo Sabater-Grande – Journal of Computing in Higher Education, 2024
Cheating in online exams without face-to-face proctoring has been a general concern for academic instructors during the crisis caused by COVID-19. The main goal of this work is to evaluate the cost of these dishonest practices by comparing the academic performance of webcam-proctored students and their unproctored peers in an online gradable test.…
Descriptors: Cheating, Computer Assisted Testing, Randomized Controlled Trials, Supervision
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A. E. Ades; Nicky J. Welton; Sofia Dias; David M. Phillippo; Deborah M. Caldwell – Research Synthesis Methods, 2024
Network meta-analysis (NMA) is an extension of pairwise meta-analysis (PMA) which combines evidence from trials on multiple treatments in connected networks. NMA delivers internally consistent estimates of relative treatment efficacy, needed for rational decision making. Over its first 20 years NMA's use has grown exponentially, with applications…
Descriptors: Network Analysis, Meta Analysis, Medicine, Clinical Experience
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