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Sales, Adam C.; Prihar, Ethan B.; Gagnon-Bartsch, Johann A.; Heffernan, Neil T. – Journal of Educational Data Mining, 2023
Randomized A/B tests within online learning platforms represent an exciting direction in learning sciences. With minimal assumptions, they allow causal effect estimation without confounding bias and exact statistical inference even in small samples. However, often experimental samples and/or treatment effects are small, A/B tests are underpowered,…
Descriptors: Data Use, Research Methodology, Randomized Controlled Trials, Educational Technology
Sales, Adam C.; Pane, John F. – Journal of Research on Educational Effectiveness, 2021
Randomized evaluations of educational technology produce log data as a bi-product: highly granular data on student and teacher usage. These datasets could shed light on causal mechanisms, effect heterogeneity, or optimal use. However, there are methodological challenges: implementation is not randomized and is only defined for the treatment group,…
Descriptors: Educational Technology, Use Studies, Randomized Controlled Trials, Mathematics Curriculum
Sancenon, Vicente; Wijaya, Kharisma; Wen, Xavier Yue Shu; Utama, Diaz Adi; Ashworth, Mark; Ng, Kelvin Hongrui; Cheong, Alicia; Neo, Zhizhong – International Journal of Virtual and Personal Learning Environments, 2022
Although there is increasing acceptance that personalization improves learning outcomes, there is still limited experimental evidence supporting this claim. The aim of this study was to implement and evaluate the effectiveness of an adaptive recommendation system for Singapore primary and secondary education. The system leverages users trace data…
Descriptors: Academic Achievement, Electronic Learning, Learning Analytics, Learning Processes
McHugh, Douglas; Feinn, Richard; McIlvenna, Jeff; Trevithick, Matt – Education Sciences, 2021
Learner-centered coaching and feedback are relevant to various educational contexts. Spaced retrieval enhances long-term knowledge retention. We examined the efficacy of Blank Slate, a novel spaced retrieval software application, to promote learning and prevent forgetting, while gathering and analyzing data in the background about learners'…
Descriptors: Randomized Controlled Trials, Learning Analytics, Coaching (Performance), Formative Evaluation