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Peer reviewed
Direct linkMike Coldwell; Nick Moore – British Educational Research Journal, 2024
Discussions of randomised controlled trials (RCTs) in education that do not show an impact regularly focus on the intervention and how it failed to impact on expected measures, with typologies identifying persistent critical points of failure. This paper uses one such RCT--the Integrating English programme--to exemplify the application of a new…
Descriptors: Randomized Controlled Trials, Failure, Models, Evaluation
Arman Miri; Akram Karimi-Shahanjarini; Maryam Afshari; Saeed Bashirian; Leili Tapak – Health Education Research, 2024
This systematic review aimed to assess the features and effectiveness of individual-level randomized controlled trials targeting COVID-19 misinformation. The selection process included rigorous criteria, resulting in the inclusion of 24 individual studies from 21 papers. The majority of studies were conducted in high-income countries, with the…
Descriptors: Randomized Controlled Trials, COVID-19, Pandemics, Misinformation
Dahlia K. Remler; Gregg G. Van Ryzin – American Journal of Evaluation, 2025
This article reviews the origins and use of the terms quasi-experiment and natural experiment. It demonstrates how the terms conflate whether variation in the independent variable of interest falls short of random with whether researchers find, rather than intervene to create, that variation. Using the lens of assignment--the process driving…
Descriptors: Quasiexperimental Design, Research Design, Experiments, Predictor Variables
Peter J. Godolphin; Nadine Marlin; Chantelle Cornett; David J. Fisher; Jayne F. Tierney; Ian R. White; Ewelina Rogozinska – Research Synthesis Methods, 2024
Individual participant data (IPD) meta-analyses of randomised trials are considered a reliable way to assess participant-level treatment effect modifiers but may not make the best use of the available data. Traditionally, effect modifiers are explored one covariate at a time, which gives rise to the possibility that evidence of treatment-covariate…
Descriptors: Meta Analysis, Randomized Controlled Trials, Statistical Analysis, Participant Characteristics
Beth Chance; Karen McGaughey; Sophia Chung; Alex Goodman; Soma Roy; Nathan Tintle – Journal of Statistics and Data Science Education, 2025
"Simulation-based inference" is often considered a pedagogical strategy for helping students develop inferential reasoning, for example, giving them a visual and concrete reference for deciding whether the observed statistic is unlikely to happen by chance alone when the null hypothesis is true. In this article, we highlight for teachers…
Descriptors: Simulation, Sampling, Randomized Controlled Trials, Hypothesis Testing
Zuchao Shen; Walter Leite; Huibin Zhang; Jia Quan; Huan Kuang – Journal of Experimental Education, 2025
When designing cluster-randomized trials (CRTs), one important consideration is determining the proper sample sizes across levels and treatment conditions to cost-efficiently achieve adequate statistical power. This consideration is usually addressed in an optimal design framework by leveraging the cost structures of sampling and optimizing the…
Descriptors: Randomized Controlled Trials, Feasibility Studies, Research Design, Sample Size
Onur Dönmez; Yavuz Akbulut; Gözde Zabzun; Berrin Köseoglu – Applied Cognitive Psychology, 2025
This study investigates the effect of survey order in measuring self-reported cognitive load. Understanding how survey order influences responses is crucial, but it has been largely overlooked in the context of cognitive load. Using a 2 × 2 experimental design with 319 high school students, the study manipulated intrinsic cognitive load (ICL)…
Descriptors: Surveys, Test Construction, Measurement, Cognitive Processes
William Herbert Yeaton – International Journal of Research & Method in Education, 2024
Though previously unacknowledged, a SMART (Sequential Multiple Assignment Randomized Trial) design uses both regression discontinuity (RD) and randomized controlled trial (RCT) designs. This combination structure creates a conceptual symbiosis between the two designs that enables both RCT- and previously unrecognized, RD-based inferential claims.…
Descriptors: Research Design, Randomized Controlled Trials, Regression (Statistics), Inferences
Andres Jung; Tobias Braun; Susan Armijo-Olivo; Dimitris Challoumas; Kerstin Luedtke – Research Synthesis Methods, 2024
External validity is an important parameter that needs to be considered for decision making in health research, but no widely accepted measurement tool for the assessment of external validity of randomized controlled trials (RCTs) exists. One of the most limiting factors for creating such a tool is probably the substantial heterogeneity and lack…
Descriptors: Randomized Controlled Trials, Validity, Delphi Technique, Definitions
Andrija Babic; Ognjen Barcot; Tomislav Viskovic; Frano Šaric; Aleksandar Kirkovski; Ivana Barun; Zvonimir Križanac; Roshan Arjun Ananda; Yuli Viviana Fuentes Barreiro; Narges Malih; Daiana Anne-Marie Dimcea; Josipa Ordulj; Ishanka Weerasekara; Matteo Spezia; Marija Franka Žuljevic; Jelena Šuto; Luca Tancredi; Andela Pijuk; Susanna Sammali; Veronica Iascone; Thilo Groote; Tina Poklepovic Pericic; Livia Puljak – Research Synthesis Methods, 2024
Risk of bias (RoB) assessment is essential to the systematic review methodology. The new version of the Cochrane RoB tool for randomized trials (RoB 2) was published in 2019 to address limitations identified since the first version of the tool was published in 2008 and to increase the reliability of assessments. This study analyzed the frequency…
Descriptors: Risk, Bias, Use Studies, Meta Analysis
Debbie L. Hahs-Vaughn; Christine Depies DeStefano; Christopher D. Charles; Mary Little – American Journal of Evaluation, 2025
Randomized experiments are a strong design for establishing impact evidence because the random assignment mechanism theoretically allows confidence in attributing group differences to the intervention. Growth of randomized experiments within educational studies has been widely documented. However, randomized experiments within education have…
Descriptors: Educational Research, Randomized Controlled Trials, Research Problems, Educational Policy
Gerald Gartlehner; Leila Kahwati; Rainer Hilscher; Ian Thomas; Shannon Kugley; Karen Crotty; Meera Viswanathan; Barbara Nussbaumer-Streit; Graham Booth; Nathaniel Erskine; Amanda Konet; Robert Chew – Research Synthesis Methods, 2024
Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and usability. With the release of large language models (LLMs), new possibilities have emerged to…
Descriptors: Data Collection, Evidence, Synthesis, Language Processing
Download full textBeverly L. Kahn – Scholarship and Practice of Undergraduate Research, 2024
The Research-Aligned Mentorship (RAM) program at Farmingdale State College is changing the trajectories of racial minority students, students of low socioeconomic status, and first-generation undergraduate students. This article reviews the RAM program from 2016 through 2022. During that period, Farmingdale welcomed seven cohorts of RAM Scholars,…
Descriptors: Randomized Controlled Trials, Minority Group Students, First Generation College Students, Mentors
Huibin Zhang; Zuchao Shen; Walter L. Leite – Journal of Experimental Education, 2025
Cluster-randomized trials have been widely used to evaluate the treatment effects of interventions on student outcomes. When interventions are implemented by teachers, researchers need to account for the nested structure in schools (i.e., students are nested within teachers nested within schools). Schools usually have a very limited number of…
Descriptors: Sample Size, Multivariate Analysis, Randomized Controlled Trials, Correlation
Yongtian Cheng; K. V. Petrides – Educational and Psychological Measurement, 2025
Psychologists are emphasizing the importance of predictive conclusions. Machine learning methods, such as supervised neural networks, have been used in psychological studies as they naturally fit prediction tasks. However, we are concerned about whether neural networks fitted with random datasets (i.e., datasets where there is no relationship…
Descriptors: Psychological Studies, Artificial Intelligence, Cognitive Processes, Predictive Validity
