LLMs for Intelligent Tutoring
Essential Readings
General Overview and Background
Overview of the Learning Sciences Principles
Technology-enhanced Educational Approaches
Pre-LLM Intelligent Tutoring Systems (ITS)
- A Large-Scale, Open-Domain, Mixed-Interface
Dialogue-Based ITS for STEM (Serban et al., 2020)
- AutoTutor and Family:
A Review of 17 Years of Natural Language Tutoring (Nye et al., 2014)
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Gaze tutor: A gaze-reactive intelligent tutoring system (D'Mello et al., 2012)
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Intelligent tutoring systems (Graesser et al., 2012)
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Data mining in education (Romero and Ventura, 2012)
- Beetle II: A System for Tutoring and Computational Linguistics
Experimentation (Dzikovska et al., 2010)
- AutoTutor 3-D Simulations: Analyzing Users' Actions and Learning
Trends (Graesser et al., 2006)
- Individualizing Self-Explanation
Support for Ill-Defined Tasks in Constraint-based Tutors (Weerasinghe and Mitrovic, 2006)
- AutoTutor: a Tutor with Dialogue in Natural
Language (Graesser et al., 2004)
- KERMIT: A constraint-based
tutor for database modeling (Suraweera and Mitrovic, 2002)
- Interactive Conceptual Tutoring in
Atlas-Andes (Rose et al., 2000)
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Jacob - An Animated Instruction Agent in Virtual Reality (Evers and Nijholt, 2000)
LLMs in STEM Education and Development of ITS
- AutoTutor meets Large Language Models:
A Language Model Tutor with Rich Pedagogy and Guardrails (Chowdhury et al., 2024)
- Stepwise Verification and Remediation of Student Reasoning Errors
with Large Language Model Tutors (Daheim et al., 2024)
- Leveraging the potential of large language models in education
through playful and game-based learning (Huber et al., 2024)
- The GPT Surprise: Offering Large Language Model Chat in a
Massive Coding Class Reduced Engagement but Increased Adopters Exam Performances (Nie et al., 2024)
- The FineWeb Datasets: Decanting the Web
for the Finest Text Data at Scale (Penedo et al., 2024)
- Backtracing: Retrieving the Cause of the
Query (Wang et al., 2024)
- Bridging the Novice-Expert Gap via Models of Decision-Making:
A Case Study on Remediating Math Mistakes (Wang et al., 2024)
- Book2Dial: Generating Teacher Student Interactions from
Textbooks for Cost-Effective Development of Educational Chatbots (Wang et al., 2024)
- Large Language Models for education:
A survey and outlook (Wang et al., 2024)
- MATHDIAL: A Dialogue Tutoring Dataset with Rich Pedagogical
Properties Grounded in Math Reasoning Problems (Macina et al., 2023)
- GPTeach: Interactive TA Training with GPT-based Students (Markel et al., 2023)
- CLASS: A Design Framework for Building Intelligent
Tutoring Systems Based on Learning Science Principles (Sonkar et al., 2023)
- The BEA 2023 Shared Task on Generating AI Teacher Responses
in Educational Dialogues (Tack et al., 2023)
- NAISTeacher: A Prompt and Rerank Approach to Generating Teacher
Utterances in Educational Dialogues (Vasselli et al., 2023)
- Is ChatGPT a Good Teacher Coach? Measuring Zero-Shot Performance For Scoring and
Providing Actionable Insights on Classroom Instruction (Wang and Demszky, 2023)
- Demographic Predictors of Students’ Science Participation over the
Age of 16: an Australian Case Study (Cooper et al., 2020)
Feedback, Hints, and Questions Generation
- Navigating the Landscape of Hint Generation Research:
From the Past to the Future (Jangra et al., 2024)
- More Insightful Feedback for Tutoring: Enhancing Generation
Mechanisms and Automatic Evaluation (Liermann et al., 2024)
- Automated Distractor and Feedback Generation for Math Multiple-choice
Questions via In-context Learning (McNichols et al., 2024)
- Improving the Validity of Automatically
Generated Feedback via Reinforcement Learning (Scarlatos et al., 2024)
- Automatic Generation of Question Hints for Mathematics Problems
using Large Language Models in Educational Technology (Tonga et al., 2024)
- Automating Human Tutor-Style Programming Feedback:
Leveraging GPT-4 Tutor Model for Hint Generation and GPT-3.5 Student Model for Hint Validation
(Phung et al., 2023)
- Next-Step Hint Generation for Introductory Programming
Using Large Language Models (Roest et al., 2023)
- Automated Data-Driven Generation of Personalized Pedagogical
Interventions in Intelligent Tutoring Systems (Kochmar et al., 2022)
- Few-shot Question Generation for Personalized Feedback
in Intelligent Tutoring Systems (Kulshreshtha et al., 2022)
- Deep Discourse Analysis for Generating
Personalized Feedback in Intelligent Tutor Systems (Grenander et al., 2021)
- Automated Personalized Feedback Improves Learning
Gains in An Intelligent Tutoring System (Kochmar et al., 2020)
- Mathematical Language Processing:
Automatic Grading and Feedback for Open Response Mathematical Questions (Lan et al., 2015)
User Studies
- How Teachers Can Use Large Language Models and Bloom’s Taxonomy
to Create Educational Quizzes (Elkins et al., 2024)
- Designing Prompt Analytics Dashboards to Analyze
Student-ChatGPT Interactions in EFL Writing (Kim et al., 2024)
- How to Teach Programming in the AI Era?
Using LLMs as a Teachable Agent for Debugging (Ma et al., 2024)
- Tutor CoPilot: A Human-AI Approach for
Scaling Real-Time Expertise (Wang et al., 2024)
- Improving Teachers’ Questioning Quality through Automated
Feedback: A Mixed-Methods Randomized Controlled Trial in Brick-and-Mortar Classrooms (Demszky et al., 2023)
- How Useful are Educational Questions Generated
by Large Language Models? (Elkins et al., 2023)
- GPTeach: Interactive TA Training with
GPT-based Students (Markel et al., 2023)
- Is ChatGPT a Good Teacher Coach? Measuring
Zero-Shot Performance For Scoring and Providing Actionable Insights on Classroom
Instruction (Wang and Demszky, 2023)
- A New Era: Intelligent Tutoring Systems Will Transform
Online Learning for Millions (St-Hilaire et al., 2022)
- A Comparative Study of Learning Outcomes for
Online Learning Platforms (St-Hilaire et al., 2021)
- Integrating Model-Driven and Data-Driven Techniques
for Analyzing Learning Behaviors in Open-Ended Learning Environments (Kinnebrew et al., 2015)
Evaluation of ITS
Ethical Considerations
Datasets
Educational Toolkits