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Adam Sales; Ethan Prihar; Johann Gagnon-Bartsch; Neil Heffernan – Society for Research on Educational Effectiveness, 2023
Background: Randomized controlled trials (RCTs) give unbiased estimates of average effects. However, positive effects for the majority of students may mask harmful effects for smaller subgroups, and RCTs often have too small a sample to estimate these subgroup effects. In many RCTs, covariate and outcome data are drawn from a larger database. For…
Descriptors: Learning Analytics, Randomized Controlled Trials, Data Use, Accuracy
Yanping Pei; Adam Sales; Johann Gagnon-Bartsch – Grantee Submission, 2024
Randomized A/B tests within online learning platforms enable us to draw unbiased causal estimators. However, precise estimates of treatment effects can be challenging due to minimal participation, resulting in underpowered A/B tests. Recent advancements indicate that leveraging auxiliary information from detailed logs and employing design-based…
Descriptors: Randomized Controlled Trials, Learning Management Systems, Causal Models, Learning Analytics
Benjamin A. Motz; Öykü Üner; Harmony E. Jankowski; Marcus A. Christie; Kim Burgas; Diego del Blanco Orobitg; Mark A. McDaniel – Grantee Submission, 2023
For researchers seeking to improve education, a common goal is to identify teaching practices that have causal benefits in classroom settings. To test whether an instructional practice exerts a causal influence on an outcome measure, the most straightforward and compelling method is to conduct an experiment. While experimentation is common in…
Descriptors: Learning Analytics, Experiments, Learning Processes, Learning Management Systems
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