45 citations · 94 across the 12 of their papers we have counts for
12 papers
Using Auxiliary Data to Boost Precision in the Analysis of A/B Tests on an Online Educational Platform: New Data and New Results
Adam C. Sales, Ethan B. Prihar, Johann A. Gagnon-Bartsch +1
Randomized A/B tests within online learning platforms represent an exciting direction in learning sciences. With minimal assumptions, they allow causal effect estimation without co…
Modeling and Analyzing Scorer Preferences in Short-Answer Math Questions
Mengxue Zhang, Neil Heffernan, Andrew Lan
Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for…
Automatic Short Math Answer Grading via In-context Meta-learning
Mengxue Zhang, Sami Baral, Neil Heffernan +1
Automatic short answer grading is an important research direction in the exploration of how to use artificial intelligence (AI)-based tools to improve education. Current state-of-t…
Reinforcement Learning for Education: Opportunities and Challenges
Adish Singla, Anna N. Rafferty, Goran Radanovic +1
This survey article has grown out of the RL4ED workshop organized by the authors at the Educational Data Mining (EDM) 2021 conference. We organized this workshop as part of a commu…
MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education
Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar +4
Since the introduction of the original BERT (i.e., BASE BERT), researchers have developed various customized BERT models with improved performance for specific domains and tasks by…
Classifying Math KCs via Task-Adaptive Pre-Trained BERT
Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar +4
Educational content labeled with proper knowledge components (KCs) are particularly useful to teachers or content organizers. However, manually labeling educational content is labo…
Precise Unbiased Estimation in Randomized Experiments using Auxiliary Observational Data
Johann A. Gagnon-Bartsch, Adam C. Sales, Edward Wu +4
Randomized controlled trials (RCTs) are increasingly prevalent in education research, and are often regarded as a gold standard of causal inference. Two main virtues of randomized…
Achieving User-Side Fairness in Contextual Bandits
Wen Huang, Kevin Labille, Xintao Wu +2
Personalized recommendation based on multi-arm bandit (MAB) algorithms has shown to lead to high utility and efficiency as it can dynamically adapt the recommendation strategy base…
Context-Aware Attentive Knowledge Tracing
Aritra Ghosh, Neil Heffernan, Andrew S. Lan
Knowledge tracing (KT) refers to the problem of predicting future learner performance given their past performance in educational applications. Recent developments in KT using flex…
The Utility of Clustering in Prediction Tasks
Shubhendu Trivedi, Zachary A. Pardos, Neil T. Heffernan
We explore the utility of clustering in reducing error in various prediction tasks. Previous work has hinted at the improvement in prediction accuracy attributed to clustering algo…
A Methodology for Discovering how to Adaptively Personalize to Users using Experimental Comparisons
Joseph Jay Williams, Neil Heffernan
We explain and provide examples of a formalism that supports the methodology of discovering how to adapt and personalize technology by combining randomized experiments with variabl…
Using and Designing Platforms for In Vivo Education Experiments
Joseph Jay Williams, Korinn Ostrow, Xiaolu Xiong +6
In contrast to typical laboratory experiments, the everyday use of online educational resources by large populations and the prevalence of software infrastructure for A/B testing l…