33 citations · 42 across the 9 of their papers we have counts for
8 papers · 1 filter
Towards Reward Modeling for AI Tutors in Math Mistake Remediation
Kseniia Petukhova, Ekaterina Kochmar
Evaluating the pedagogical quality of AI tutors remains challenging: standard NLG metrics do not determine whether responses identify mistakes, scaffold reasoning, or avoid reveali…
How Teachers Can Use Large Language Models and Bloom's Taxonomy to Create Educational Quizzes
Sabina Elkins, Ekaterina Kochmar, Jackie C. K. Cheung +1
Question generation (QG) is a natural language processing task with an abundance of potential benefits and use cases in the educational domain. In order for this potential to be re…
How Useful are Educational Questions Generated by Large Language Models?
Sabina Elkins, Ekaterina Kochmar, Jackie C. K. Cheung +1
Controllable text generation (CTG) by large language models has a huge potential to transform education for teachers and students alike. Specifically, high quality and diverse ques…
Raising Student Completion Rates with Adaptive Curriculum and Contextual Bandits
Robert Belfer, Ekaterina Kochmar, Iulian Vlad Serban
We present an adaptive learning Intelligent Tutoring System, which uses model-based reinforcement learning in the form of contextual bandits to assign learning activities to studen…
Few-shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems
Devang Kulshreshtha, Muhammad Shayan, Robert Belfer +3
Existing work on generating hints in Intelligent Tutoring Systems (ITS) focuses mostly on manual and non-personalized feedback. In this work, we explore automatically generated que…
Question Personalization in an Intelligent Tutoring System
Sabina Elkins, Robert Belfer, Ekaterina Kochmar +2
This paper investigates personalization in the field of intelligent tutoring systems (ITS). We hypothesize that personalization in the way questions are asked improves student lear…
Deep Discourse Analysis for Generating Personalized Feedback in Intelligent Tutor Systems
Matt Grenander, Robert Belfer, Ekaterina Kochmar +3
We explore creating automated, personalized feedback in an intelligent tutoring system (ITS). Our goal is to pinpoint correct and incorrect concepts in student answers in order to…
Automated Personalized Feedback Improves Learning Gains in an Intelligent Tutoring System
Ekaterina Kochmar, Dung Do Vu, Robert Belfer +3
We investigate how automated, data-driven, personalized feedback in a large-scale intelligent tutoring system (ITS) improves student learning outcomes. We propose a machine learnin…