5 papers
A Causal Framework for Estimating Heterogeneous Effects of On-Demand Tutoring
Kirk Vanacore, Danielle R Thomas, Digory Smith +3
This paper introduces a scalable causal inference framework for estimating the immediate, session-level effects of on-demand human tutoring embedded within adaptive learning system…
Misconception Diagnosis From Student-Tutor Dialogue: Generate, Retrieve, Rerank
Joshua Mitton, Prarthana Bhattacharyya, Digory Smith +3
Timely and accurate identification of student misconceptions is key to improving learning outcomes and pre-empting the compounding of student errors. However, this task is highly d…
AI tutoring can safely and effectively support students: An exploratory RCT in UK classrooms
LearnLM Team, Eedi, : +33
One-to-one tutoring is widely considered the gold standard for personalized education, yet it remains prohibitively expensive to scale. To evaluate whether generative AI might help…
PIIvot: A Lightweight NLP Anonymization Framework for Question-Anchored Tutoring Dialogues
Matthew Zent, Digory Smith, Simon Woodhead
Personally identifiable information (PII) anonymization is a high-stakes task that poses a barrier to many open-science data sharing initiatives. While PII identification has made…
Improving the Validity of Automatically Generated Feedback via Reinforcement Learning
Alexander Scarlatos, Digory Smith, Simon Woodhead +1
Automatically generating feedback via large language models (LLMs) in intelligent tutoring systems and online learning platforms has the potential to improve the learning outcomes…