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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
Wang, Yan; Ostrow, Korinn; Beck, Joseph; Heffernan, Neil – Grantee Submission, 2016
The focus of the learning analytics community bridges the gap between controlled educational research and data mining. Online learning platforms can be used to conduct randomized controlled trials to assist in the development of interventions that increase learning gains; datasets from such research can act as a treasure trove for inquisitive data…
Descriptors: Learning Analytics, Educational Research, Randomized Controlled Trials, Information Retrieval
Ostrow, Korinn S.; Selent, Doug; Wang, Yan; Van Inwegen, Eric G.; Heffernan, Neil T.; Williams, Joseph Jay – Grantee Submission, 2016
Researchers invested in K-12 education struggle not just to enhance pedagogy, curriculum, and student engagement, but also to harness the power of technology in ways that will optimize learning. Online learning platforms offer a powerful environment for educational research at scale. The present work details the creation of an automated system…
Descriptors: Learning Analytics, Technology Uses in Education, Randomized Controlled Trials, Automation