As online learning platforms become more popular and deeply integrated into education, understanding their effectiveness and what drives that effectiveness becomes increasingly important. While there is extensive prior research illustrating the benefits of intelligent tutoring systems (ITS) for student learning, there is comparatively less focus…

Increasing use of intelligent tutoring systems in education calls for analytic methods that can unravel students' learning behaviors. In this study, we explore a latent variable modeling approach for tracking learning flow during computer-interactive artificial tutoring. The study considers three models that give discrete profiles of a latent…

Background: The data revolution in education has led to more data collection, more randomized controlled trials (RCTs), and more data collection within RCTs. Often following IES recommendations, researchers studying program effectiveness gather data on how the intervention was implemented. Educational implementation data can be complex, including…

Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data on study students' performance, behavior, learning processes, and outcomes in authentic learning environments. As educational research increasingly uses methods and data collection from such platforms, it is…

Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data to study students' performance, behavior, learning processes, and outcomes in authentic learning environments. As educational research increasingly uses methods and data collection from such platforms, it is…

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…

Education researchers frequently have to choose between statistical models for their data, and in many cases the candidate models or parameters can be listed in a sequence, m=1,...,M, from less preferable choices to more. For instance, in choosing a bandwidth for regression discontinuity designs, researchers would favor the largest possible…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…