To support online learners at a large scale, extensive studies have adopted machine learning (ML) techniques to analyze students' artifacts and predict their learning outcomes automatically. However, limited attention has been paid to the fairness of prediction with ML in educational settings. This study intends to fill the gap by introducing a…

Randomized A/B tests allow causal estimation without confounding but are often under-powered. This paper uses a new dataset, including over 250 randomized comparisons conducted in an online learning platform, to illustrate a method combining data from A/B tests with log data from users who were not in the experiment. Inference remains exact and…

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…

Understanding fraction magnitudes is foundational for later math achievement. To represent a fraction "x/y," children are often taught to use "partitioning": break the whole into "y" parts, and shade in "x" parts. Past research has shown that partitioning on number lines supports children's fraction…

In recent years, there has been a proliferation of adaptive learner models that seek to predict student correctness. Improvements on earlier models have shown that separate predictors for prior successes, failures, and recent performance further improve fit while remaining interpretable. However, students who engage in "gaming" or other…

Recent work in predictive modeling has called for increased scrutiny of how models generalize between different populations within the training data. Using interaction data from 69,174 students who used an online mathematics platform over an entire school year, we trained a sensor-free affect detection model and studied its generalizability to…

Traditional professional development is often characterized as being expensive, time consuming, and lacking impact. In contrast, online professional development provides greater flexibility and is becoming increasingly popular for school personnel. In this article, we report the process and outcomes of gathering feedback to adapt traditional…

In the e-learning context, social network analysis (SNA) can be used to build understanding around the ways students participate and interact in online forums. This study contributes to the growing body of research that uses statistical methods to test hypotheses about structures in social networks. Specifically, we show how statistical analysis…