We collect papers related to artificial intelligence (AI) and large language model (LLM) for education from top conferences, journals, and specialized domain-specific conferences. We then categorize them according to their specific tasks for better organization.

The overview section is organized as Survey, Analysis & Vision (including Comprehensive Survey, Empirical Analysis, and Position & Vision). ✨ indicates the papers that are related to LLM.

1. The Path to Conversational AI Tutors: Integrating Tutoring Best Practices and Targeted Technologies to Produce Scalable AI Agents

   Kirk Vanacore, Ryan S. Baker, Avery H. Closser, Jeremy Roschelle

   arXiv, 2026. preprint

2. Generative Artificial Intelligence and Agents in Research and Teaching

   Jussi S. Jauhiainen, Aurora Toppari

   arXiv, 2025. preprint

3. Opportunities and Challenges of LLMs in Education: An NLP Perspective

   Sowmya Vajjala, Bashar Alhafni, Stefano Bannò, Kaushal Kumar Maurya, Ekaterina Kochmar

   arXiv, 2025. preprint

4. Large Language Models for Education: A Survey

   Hanyi Xu, Wensheng Gan, Zhenlian Qi, Jiayang Wu, Philip S. Yu

   Journal of Machine Learning and Cybernetics, 2024. journal

5. Large Language Models for Education: A Survey and Outlook

   Shen Wang, Tianlong Xu, Hang Li, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, Qingsong Wen

   arXiv, 2024. preprint

6. Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges

   Qingyao Li, Lingyue Fu, Weiming Zhang, Xianyu Chen, Jingwei Yu, Wei Xia, Weinan Zhang, Ruiming Tang, Yong Yu

   arXiv, 2024. preprint

7. Survey of Computerized Adaptive Testing: A Machine Learning Perspective

   Qi Liu, Yan Zhuang, Haoyang Bi, Zhenya Huang, Weizhe Huang, Jiatong Li, Junhao Yu, Zirui Liu, Zirui Hu, Yuting Hong, Zachary A. Pardos, Haiping Ma, Mengxiao Zhu, Shijin Wang, Enhong Chen

   arXiv, 2024. preprint

8. Large Language Models in Education: Vision and Opportunities

   Wensheng Gan, Zhenlian Qi, Jiayang Wu, Jerry Chun-Wei Lin

   BigData, 2023. conference

9. A Comprehensive Survey on Deep Learning Techniques in Educational Data Mining

   Yuanguo Lin, Hong Chen, Wei Xia, Fan Lin, Zongyue Wang, Yong Liu

   arXiv, 2023. preprint

10. Reinforcement Learning for Education: Opportunities and Challenges

    Adish Singla, Anna N. Rafferty, Goran Radanovic, Neil T. Heffernan

    EDM-RL4ED, 2021. conference

1. The effect of ChatGPT on students’ learning performance, learning perception, and higher-order thinking: insights from a meta-analysis

   Jin Wang, Wenxiang Fan

   Nature, 2025. journal

2. From Pilots to Practices: A Scoping Review of GenAI-Enabled Personalization in Computer Science Education

   Iman Reihanian, Yunfei Hou, Qingquan Sun

   arXiv, 2025. preprint

3. A systematic review of AI-driven intelligent tutoring systems (ITS) in K-12 education

   Angélique Létourneau, Marion Deslandes Martineau, Patrick Charland, John Alexander Karran, Jared Boasen, Pierre Majorique Léger

   npj science of learning, 2025. journal

1. Multi-Agent Learning Path Planning via LLMs

   Haoxin Xu, Changyong Qi, Tong Liu, Bohao Zhang, Anna He, Bingqian Jiang, Longwei Zheng, Xiaoqing Gu

   arXiv, 2026. preprint

2. LearnMate: Enhancing Online Education with LLM-Powered Personalized Learning Plans and Support

   Xinyu Jessica Wang, Christine P. Lee, Bilge Mutlu

   CHI Extended Abstract, 2025. workshop

3. PlanGlow: Personalized Study Planning with an Explainable and Controllable LLM-Driven System

   Jiwon Chun, Yankun Zhao, Hanlin Chen, Meng Xia

   Learning@Scale, 2025. conference

4. Item-Difficulty-Aware Learning Path Recommendation: From a Real Walking Perspective

   Haotian Zhang, Shuanghong Shen, Bihan Xu, Zhenya Huang, Jinze Wu, Jing Sha, Shijin Wang

   KDD, 2024. conference

5. Privileged Knowledge State Distillation for Reinforcement Learning-based Educational Path Recommendation

   Qingyao Li, Wei Xia, Li'ang Yin, Jiarui Jin, Yong Yu

   KDD, 2024. conference

6. Doubly constrained offline reinforcement learning for learning path recommendation

   Yue Yun, Huan Dai, Rui An, Yupei Zhang, Xuequn Shang

   Knowledge-Based Systems (KBS), 2024. journal

7. Course Recommender Systems Need to Consider the Job Market

   Jibril Frej, Anna Dai, Syrielle Montariol, Antoine Bosselut, Tanja Käser

   SIGIR, 2024. conference

8. Modeling Balanced Explicit and Implicit Relations with Contrastive Learning for Knowledge Concept Recommendation in MOOCs

   Hengnian Gu, Zhiyi Duan, Pan Xie, Dongdai Zhou

   WWW, 2024. conference

9. Learning Structure and Knowledge Aware Representation with Large Language Models for Concept Recommendation

   Qingyao Li, Wei Xia, Kounianhua Du, Qiji Zhang, Weinan Zhang, Ruiming Tang, Yong Yu

   arXiv, 2024. preprint

10. Set-to-Sequence Ranking-based Concept-aware Learning Path Recommendation

    Xianyu Chen, Jian Shen, Wei Xia, Jiarui Jin, Yakun Song, Weinan Zhang, Weiwen Liu, Menghui Zhu, Ruiming Tang, Kai Dong, Dingyin Xia, Yong Yu

    AAAI, 2023. conference

11. Graph Enhanced Hierarchical Reinforcement Learning for Goal-oriented Learning Path Recommendation

    Qingyao Li, Wei Xia, Li'ang Yin, Jian Shen, Renting Rui, Weinan Zhang, Xianyu Chen, Ruiming Tang, Yong Yu

    CIKM, 2023. conference

12. MHRR: MOOCs Recommender Service With Meta Hierarchical Reinforced Ranking

    Yuchen Li, Haoyi Xiong, Linghe Kong, Rui Zhang, Fanqin Xu, Guihai Chen, Minglu Li

    TSC, 2023. journal

13. Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning

    Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill

    AAAI, 2022. conference

14. CurriculumTutor: An Adaptive Algorithm for Mastering a Curriculum

    Shabana K M, Chandrashekar Lakshminarayanan

    AIED, 2022. conference

15. Automatic Interpretable Personalized Learning

    Ethan Prihar, Aaron Haim, Adam Sales, Neil Heffernan

    Learning@Scale, 2022. conference

16. ConceptGuide: Supporting Online Video Learning with Concept Map-based Recommendation of Learning Path

    Chien-Lin Tang, Jingxian Liao, Hao-Chuan Wang, Ching-Ying Sung, Wen-Chieh Lin

    WWW, 2021. conference

17. Reinforcement Learning for the Adaptive Scheduling of Educational Activities

    A. Singla, Anna N. Rafferty, Goran Radanovic, N. Heffernan

    CHI, 2020. conference

18. Deep Reinforcement Learning for Adaptive Learning Systems

    Xiao Li, Hanchen Xu, Jinming Zhang, Hua-hua Chang

    arXiv, 2020. preprint

19. Learning Path Recommendation Based on Knowledge Tracing Model and Reinforcement Learning

    Dejun Cai, Yuan Zhang, Bintao Dai

    IEEE International Conference on Computer and Communications (ICCC), 2019. conference

20. Exploiting Cognitive Structure for Adaptive Learning

    Qi Liu, Shiwei Tong, Chuanren Liu, Hongke Zhao, Enhong Chen, Haiping Ma, Shijin Wang

    KDD, 2019. conference

21. Combining Adaptivity with Progression Ordering for Intelligent Tutoring Systems

    Tong Mu, Shuhan Wang, Erik Andersen, Emma Brunskill

    Learning@Scale, 2018. conference

22. The Effects of Adaptive Learning in a Massive Open Online Course on Learners' Skill Development

    Y. Rosen, I. Rushkin, Rob Rubin, Liberty Munson, Andrew M. Ang, G. Weber, Glenn Lopez, D. Tingley

    Learning@Scale, 2018. conference

23. Ontology-based Recommender System in Higher Education

    Charbel Obeid, Inaya Lahoud, Hicham El Khoury, Pierre-Antoine Champin

    WWW Companion, 2018. workshop

24. Program2Tutor: Combining Automatic Curriculum Generation with Multi-Armed Bandits for Intelligent Tutoring Systems

    Tong Mu, Karan Goel

    NeurIPS - Workshop on Teaching Machines Humans and Robots, 2017. workshop

1. PATS: Personality-Aware Teaching Strategies with Large Language Model Tutors

   Donya Rooein, Sankalan Pal Chowdhury, Mariia Eremeeva, Yuan Qin, Debora Nozza, Mrinmaya Sachan, Dirk Hovy

   arXiv, 2026. preprint

2. Rewarding How Models Think Pedagogically: Integrating Pedagogical Reasoning and Thinking Rewards for LLMs in Education

   Unggi Lee, Jiyeong Bae, Jaehyeon Park, Haeun Park, Taejun Park, Younghoon Jeon, Sungmin Cho, Junbo Koh, Yeil Jeong, Gyeonggeon Lee

   arXiv, 2026. preprint

3. ClassAid: A Real-time Instructor-AI-Student Orchestration System for Classroom Programming Activities

   Gefei Zhang, Guodao Sun, Meng Xia, Ronghua Liang

   arXiv, 2026. preprint

4. Letting Tutor Personas Speak Up for LLMs: Learning Steering Vectors from Dialogue via Preference Optimization

   Jaewook Lee, Alexander Scarlatos, Simon Woodhead, Andrew Lan

   arXiv, 2026. preprint

5. Designing AI Tutors for Interest-Based Learning: Insights from Human Instructors

   Abhishek Kulkarni, Sharon Lynn Chu

   arXiv, 2026. preprint

6. Evidence-Decision-Feedback: Theory-Driven Adaptive Scaffolding for LLM Agents

   Clayton Cohn, Siyuan Guo, Surya Rayala, Hanchen David Wang, Naveeduddin Mohammed, Umesh Timalsina, Shruti Jain, Angela Eeds, Menton Deweese, Pamela J. Osborn Popp, Rebekah Stanton, Shakeera Walker, Meiyi Ma, Gautam Biswas

   arXiv, 2026. preprint

7. Arapai: An Offline-First AI Chatbot Architecture for Low-Connectivity Educational Environments

   Joseph Walusimbi, Ann Move Oguti, Joshua Benjamin Ssentongo, Keith Ainebyona

   arXiv, 2026. preprint

8. LLM-powered Multi-agent Framework for Goal-oriented Learning in Intelligent Tutoring System

   Tianfu Wang, Yi Zhan, Jianxun Lian, Zhengyu Hu, Nicholas Jing Yuan, Qi Zhang, Xing Xie, Hui Xiong

   WWW, 2025. conference, code

9. Generative AI in Education: From Foundational Insights to the Socratic Playground for Learning

   Xiangen Hu, Sheng Xu, Richard Tong, Art Graesser

   arXiv, 2025. preprint

10. From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning

    David Dinucu-Jianu, Jakub Macina, Nico Daheim, Ido Hakimi, Iryna Gurevych, Mrinmaya Sachan

    arXiv, 2025. preprint, code

11. A Theory of Adaptive Scaffolding for LLM-Based Pedagogical Agents

    Clayton Cohn, Surya Rayala, Namrata Srivastava, Joyce Horn Fonteles, Shruti Jain, Xinying Luo, Divya Mereddy, Naveeduddin Mohammed, Gautam Biswas

    arXiv, 2025. preprint

12. Cultivating Helpful, Personalized, and Creative AI Tutors: A Framework for Pedagogical Alignment using Reinforcement Learning

    Siyu Song, Wentao Liu, Ye Lu, Ruohua Zhang, Tao Liu, Jinze Lv, Xinyun Wang, Aimin Zhou, Fei Tan, Bo Jiang, Hao Hao

    arXiv, 2025. preprint

13. Exploring Conversational Design Choices in LLMs for Pedagogical Purposes: Socratic and Narrative Approaches for Improving Instructor's Teaching Practice

    Si Chen, Isabel R. Molnar, Peiyu Li, Adam Acunin, Ting Hua, Alex Ambrose, Nitesh V. Chawla, Ronald Metoyer

    arXiv, 2025. preprint

14. An Experience Report on a Pedagogically Controlled Curriculum-Constrained AI Tutor for SE Education

    Lucia Happe, Dominik Fuchs, Luca Huttner, Kai Marquardt, Anne Koziolek

    arXiv, 2025. preprint

15. IntelliCode: A Multi-Agent LLM Tutoring System with Centralized Learner Modeling

    Jones David, Shreya Ghosh

    arXiv, 2025. preprint

16. AI tutoring can safely and effectively support students: An exploratory RCT in UK classrooms

    LearnLM Team, Eedi

    arXiv, 2025. preprint

17. AgentTutor: Empowering Personalized Learning with Multi-Turn Interactive Teaching in Intelligent Education Systems

    Yuxin Liu, Zeqing Song, Jiong Lou, Chentao Wu, Jie Li

    arXiv, 2025. preprint

18. LeafTutor: An AI Agent for Programming Assignment Tutoring

    Madison Bochard, Tim Conser, Alyssa Duran, Lazaro Martull, Pu Tian, Yalong Wu

    arXiv, 2025. preprint

19. Evolutionary Reinforcement Learning based AI tutor for Socratic Interdisciplinary Instruction

    Mei Jiang, Haihai Shen, Zhuo Luo, Bingdong Li, Wenjing Hong, Ke Tang, Aimin Zhou

    arXiv, 2025. preprint

20. Hierarchical Pedagogical Oversight: A Multi-Agent Adversarial Framework for Reliable AI Tutoring

    Saisab Sadhu, Ashim Dhor

    arXiv, 2025. preprint

21. Empowering Personalized Learning through a Conversation-based Tutoring System with Student Modeling

    Minju Park, Sojung Kim, Seunghyun Lee, Soonwoo Kwon, Kyuseok Kim

    CHI-LBW, 2024. workshop

22. An Educational Tool for Learning about Social Media Tracking, Profiling, and Recommendation

    Nicolas Pope, Juho Kahila, Jari Laru, Henriikka Vartiainen, Teemu Roos, Matti Tedre

    ICALT, 2024. conference

23. AutoTutor meets Large Language Models: A Language Model Tutor with Rich Pedagogy and Guardrails

    Sankalan Pal Chowdhury, Vilém Zouhar, Mrinmaya Sachan

    Learning@Scale, 2024. conference

24. SocraticLM: Exploring Socratic Personalized Teaching with Large Language Models

    Jiayu Liu, Zhenya Huang, Tong Xiao, Jing Sha, Jinze Wu, Qi Liu, Shijin Wang, Enhong Chen

    NeurIPS, 2024. conference

25. Personality-aware Student Simulation for Conversational Intelligent Tutoring Systems

    Zhengyuan Liu, Stella Xin Yin, Geyu Lin, Nancy F. Chen

    arXiv, 2024. preprint

26. Intelligent Tutor: Leveraging ChatGPT and Microsoft Copilot Studio to Deliver a Generative AI Student Support and Feedback System within Teams

    Wei-Yu Chen

    arXiv, 2024. preprint

27. Scaffolding Language Learning via Multi-modal Tutoring Systems with Pedagogical Instructions

    Zhengyuan Liu, Stella Xin Yin, Carolyn Lee, Nancy F. Chen

    arXiv, 2024. preprint

28. Apprentice Tutor Builder: A Platform For Users to Create and Personalize Intelligent Tutors

    Glen Smith, Adit Gupta, Christopher MacLellan

    arXiv, 2024. preprint

29. OATutor: An Open-source Adaptive Tutoring System and Curated Content Library for Learning Sciences Research

    Z. Pardos, Matthew Tang, Ioannis Anastasopoulos, Shreya K. Sheel, Ethan Zhang

    CHI, 2023. conference

30. AI-TA: Towards an Intelligent Question-Answer Teaching Assistant using Open-Source LLMs

    Yann Hicke, Anmol Agarwal, Qianou Ma, Paul Denny

    NeurIPS - Workshop on Generative AI for Education (GAIED), 2023. workshop

31. Empowering Private Tutoring by Chaining Large Language Models

    Yulin Chen, Ning Ding, Hai-Tao Zheng, Zhiyuan Liu, Maosong Sun, Bowen Zhou

    arXiv, 2023. preprint

32. How to Build an AI Tutor that Can Adapt to Any Course and Provide Accurate Answers Using Large Language Model and Retrieval-Augmented Generation

    Chenxi Dong

    arXiv, 2023. preprint

33. Personal Knowledge Graphs: Use Cases in e-learning Platforms

    Eleni Ilkou

    WWW Companion, 2022. workshop

34. ArgueTutor: An Adaptive Dialog-Based Learning System for Argumentation Skills

    Thiemo Wambsganss, C. Niklaus, Matthias Cetto, Matthias Söllner, S. Handschuh, J. Leimeister

    CHI, 2021. conference

35. An Interaction Design for Machine Teaching to Develop AI Tutors

    Daniel Weitekamp, Erik Harpstead, K. Koedinger

    CHI, 2020. conference

36. The Cognitive Tutor Authoring Tools (CTAT): Preliminary Evaluation of Efficiency Gains

    V. Aleven, B. McLaren, J. Sewall, K. Koedinger

    International Conference on Intelligent Tutoring Systems, 2006. conference

37. Locus of Feedback Control in Computer-Based Tutoring

    Albert T. Corbett, John R. Anderson

    CHI, 2001. conference

1. Investigating Self-regulated Learning Sequences within a Generative AI-based Intelligent Tutoring System

   Jie Gao, Shasha Li, Jianhua Zhang, Shan Li, Tingting Wang

   arXiv, 2026. preprint

2. GuideAI: A Real-time Personalized Learning Solution with Adaptive Interventions

   Ananya Shukla, Chaitanya Modi, Satvik Bajpai, Siddharth Siddharth

   arXiv, 2026. preprint

3. Everyone's using it but no one is allowed to talk about it: College Students' Experiences Navigating the Higher Education Environment in a Generative AI World

   Yue Fu, Yifan Lin, Yessica Wang, Sarah Tran, Alexis Hiniker

   arXiv, 2026. preprint

4. Same Feedback Different Source: How AI vs Human Feedback Shapes Learner Engagement

   Caitlin Morris, Pattie Maes

   arXiv, 2026. preprint

5. StoryLensEdu: Personalized Learning Report Generation through Narrative-Driven Multi-Agent Systems

   Leixian Shen, Yan Luo, Rui Sheng, Yujia He, Haotian Li, Leni Yang, Huamin Qu

   arXiv, 2026. preprint

6. Examining the Role of LLM-Driven Interactions on Attention and Cognitive Engagement in Virtual Classrooms

   Suleyman Ozdel, Can Sarpkaya, Efe Bozkir, Hong Gao, Enkelejda Kasneci

   arXiv, 2025. preprint

7. Exploring The Interaction-Outcome Paradox: Seemingly Richer and More Self-Aware Interactions with LLMs May Not Yet Lead to Better Learning

   Rahul R. Divekar, Sophia Guerra, Lisette Gonzalez, Natasha Boos

   arXiv, 2025. preprint

1. Simulated Students in Tutoring Dialogues: Substance or Illusion?

   Alexander Scarlatos, Jaewook Lee, Simon Woodhead, Andrew Lan

   arXiv, 2026. preprint

2. Towards Valid Student Simulation with Large Language Models

   Zhihao Yuan, Yunze Xiao, Ming Li, Weihao Xuan, Richard Tong, Mona Diab, Tom Mitchell

   arXiv, 2026. preprint

3. KASER: Knowledge-Aligned Student Error Simulator for Open-Ended Coding Tasks

   Zhangqi Duan, Nigel Fernandez, Andrew Lan

   arXiv, 2026. preprint

4. Agent4Edu: Generating Learner Response Data by Generative Agents for Intelligent Education Systems

   Weibo Gao, Qi Liu, Linan Yue, Fangzhou Yao, Rui Lv, Zheng Zhang, Hao Wang, Zhenya Huang

   AAAI, 2025. conference

5. Classroom Simulacra: Building Contextual Student Generative Agents in Online Education for Learning Behavioral Simulation

   Songlin Xu, Hao-Ning Wen, Hongyi Pan, Dallas Dominguez, Dong yin Hu, Xinyu Zhang

   CHI, 2025. conference

6. Evolution in Simulation: AI-Agent School with Dual Memory for High-Fidelity Educational Dynamics

   Sheng Jin, Haoming Wang, Zhiqi Gao, Yongbo Yang, Bao Chunjia, Chengliang Wang

   EMNLP Findings, 2025. conference

7. CoderAgent: Simulating Student Behavior for Personalized Programming Learning with Large Language Models

   Yi Zhan, Qi Liu, Weibo Gao, Zheng Zhang, Tianfu Wang, Shuanghong Shen, Junyu Lu, Zhenya Huang

   IJCAI, 2025. conference

8. LLM-powered Multi-agent Framework for Goal-oriented Learning in Intelligent Tutoring System

   Tianfu Wang, Yi Zhan, Jianxun Lian, Zhengyu Hu, Nicholas Jing Yuan, Qi Zhang, Xing Xie, Hui Xiong

   WWW, 2025. conference

9. AdaRD: An Adaptive Response Denoising Framework for Robust Learner Modeling

   Fangzhou Yao, Qi Liu, Linan Yue, Weibo Gao, Jiatong Li, Xin Li, Yuanjing He

   KDD, 2024. conference

10. Towards Modeling Learner Performance with Large Language Models

    Seyed Parsa Neshaei, Richard Lee Davis, Adam Hazimeh, Bojan Lazarevski, Pierre Dillenbourg, Tanja Käser

    arXiv, 2024. preprint

11. FOKE: A Personalized and Explainable Education Framework Integrating Foundation Models, Knowledge Graphs, and Prompt Engineering

    Silan Hu, Xiaoning Wang

    arXiv, 2024. preprint

12. EduAgent: Generative Student Agents in Learning

    Songlin Xu, Xinyu Zhang, Lianhui Qin

    arXiv, 2024. preprint

13. Visualizing Self-Regulated Learner Profiles in Dashboards: Design Insights from Teachers

    Paola Mejia-Domenzain, Eva Laini, Seyed Parsa Neshaei, Thiemo Wambsganss, Tanja Käser

    AIED, 2023. conference

14. Contextualizing Problems to Student Interests at Scale in Intelligent Tutoring System Using Large Language Models

    Gautam Yadav, Ying-Jui Tseng, Xiaolin Ni

    AIED - Workshop on Empowering Education with LLMs - the Next-Gen Interface and Content Generation, 2023. workshop

15. Mitigating Biases in Student Performance Prediction via Attention-Based Personalized Federated Learning

    Yun-Wei Chu, Seyyedali Hosseinalipour, Elizabeth Tenorio, Laura Cruz, Kerrie Douglas, Andrew Lan, Christopher Brinton

    CIKM, 2022. conference

16. Predicting Student Performance using Advanced Learning Analytics

    Ali Daud, Naif Radi Aljohani, Rabeeh Ayaz Abbasi, Miltiadis D. Lytras, Farhat Abbas, Jalal S. Alowibdi

    WWW Companion, 2017. workshop

1. Search-Efficient Computerized Adaptive Testing

   Yuting Hong, Shiwei Tong, Wei Huang, Yan Zhuang, Qi Liu, Enhong Chen, Xin Li, Yuanjing He

   CIKM, 2023. conference

2. GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing

   Hangyu Wang, Ting Long, Liang Yin, Weinan Zhang, Wei Xia, Qichen Hong, Dingyin Xia, Ruiming Tang, Yong Yu

   KDD, 2023. conference

3. A Bounded Ability Estimation for Computerized Adaptive Testing

   Yan Zhuang, Qi Liu, GuanHao Zhao, Zhenya Huang, Weizhe Huang, Zachary Pardos, Enhong Chen, Jinze Wu, Xin Li

   NeurIPS, 2023. conference

4. Fully Adaptive Framework: Neural Computerized Adaptive Testing for Online Education

   Yan Zhuang, Qi Liu, Zhenya Huang, Zhi Li, Shuanghong Shen, Haiping Ma

   AAAI, 2022. conference

5. A Robust Computerized Adaptive Testing Approach in Educational Question Retrieval

   Yan Zhuang, Qi Liu, Zhenya Huang, Zhi Li, Binbin Jin, Haoyang Bi, Enhong Chen, Shijin Wang

   SIGIR, 2022. conference

6. BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing

   Aritra Ghosh, Andrew Lan

   IJCAI, 2021. conference

1. Automated Feedback Generation for Undergraduate Mathematics: Development and Evaluation of an AI Teaching Assistant

   Aron Gohr, Marie-Amelie Lawn, Kevin Gao, Inigo Serjeant, Stephen Heslip

   arXiv, 2026. preprint

2. Machine-Assisted Grading of Nationwide School-Leaving Essay Exams with LLMs and Statistical NLP

   Andres Karjus, Kais Allkivi, Silvia Maine, Katarin Leppik, Krister Kruusmaa, Merilin Aruvee

   arXiv, 2026. preprint

3. How Uncertain Is the Grade? A Benchmark of Uncertainty Metrics for LLM-Based Automatic Assessment

   Hang Li, Kaiqi Yang, Xianxuan Long, Fedor Filippov, Yucheng Chu, Yasemin Copur-Gencturk, Peng He, Cory Miller, Namsoo Shin, Joseph Krajcik, Hui Liu, Jiliang Tang

   arXiv, 2026. preprint

4. Conversational Education at Scale: A Multi-LLM Agent Workflow for Procedural Learning and Pedagogic Quality Assessment

   Jiahuan Pei, Fanghua Ye, Xin Sun, Wentao Deng, Koen Hindriks, Junxiao Wang

   EMNLP Findings, 2025. conference

5. How well do Large Language Models Recognize Instructional Moves? Establishing Baselines for Foundation Models in Educational Discourse

   Kirk Vanacore, Rene F. Kizilcec

   arXiv, 2025. preprint

6. Large Language Models Approach Expert Pedagogical Quality in Math Tutoring but Differ in Instructional and Linguistic Profiles

   Ramatu Oiza Abdulsalam, Segun Aroyehun

   arXiv, 2025. preprint

7. Toward Trustworthy Difficulty Assessments: Large Language Models as Judges in Programming and Synthetic Tasks

   H. M. Shadman Tabib, Jaber Ahmed Deedar

   arXiv, 2025. preprint

8. Large Language Models As MOOCs Graders

   Shahriar Golchin, Nikhil Garuda, Christopher Impey, Matthew Wenger

   arXiv, 2024. preprint

9. From Automation to Augmentation: Large Language Models Elevating Essay Scoring Landscape

   Changrong Xiao, Wenxing Ma, Sean Xin Xu, Kunpeng Zhang, Yufang Wang, Qi Fu

   arXiv, 2024. preprint

10. Large Language Models as Partners in Student Essay Evaluation

    Toru Ishida, Tongxi Liu, Hailong Wang, William K. Cheung

    arXiv, 2024. preprint

1. ALIGNAgent: Adaptive Learner Intelligence for Gap Identification and Next-step guidance

   Bismack Tokoli, Luis Jaimes, Ayesha S. Dina

   arXiv, 2026. preprint

2. Misconception Diagnosis From Student-Tutor Dialogue: Generate Retrieve Rerank

   Joshua Mitton, Prarthana Bhattacharyya, Digory Smith, Thomas Christie, Ralph Abboud, Simon Woodhead

   arXiv, 2026. preprint

3. Zero-1-to-3: Domain-level Zero-shot Cognitive Diagnosis via One Batch of Early-bird Students towards Three Diagnostic Objectives

   Weibo Gao, Qi Liu, Hao Wang, Linan Yue, Haoyang Bi, Yin Gu, Fangzhou Yao, Zheng Zhang, Xin Li, Yuanjing He

   AAAI, 2024. conference

4. Symbolic Cognitive Diagnosis via Hybrid Optimization for Intelligent Education Systems

   Junhao Shen, Hong Qian, Wei Zhang, Aimin Zhou

   AAAI, 2024. conference

5. Path-Specific Causal Reasoning for Fairness-aware Cognitive Diagnosis

   Dacao Zhang, Kun Zhang, Le Wu, Mi Tian, Richang Hong, Meng Wang

   KDD, 2024. conference

6. ORCDF: An Oversmoothing-Resistant Cognitive Diagnosis Framework for Student Learning in Online Education Systems

   Hong Qian, Shuo Liu, Mingjia Li, Bingdong Li, Zhi Liu, Aimin Zhou

   KDD, 2024. conference

7. Capturing Homogeneous Influence among Students: Hypergraph Cognitive Diagnosis for Intelligent Education Systems

   Junhao Shen, Hong Qian, Shuo Liu, Wei Zhang, Bo Jiang, Aimin Zhou

   KDD, 2024. conference

8. Generative Students: Using LLM-Simulated Student Profiles to Support Question Item Evaluation

   Xinyi Lu, Xu Wang

   Learning@Scale, 2024. conference

9. Multivariate Cognitive Response Framework for Student Performance Prediction on MOOC

   Lianhong Wang, Xiaoyao Li, Zhihui Luo, Zinan Hu, Qing Yan

   TKDE, 2024. journal

10. Inductive Cognitive Diagnosis for Fast Student Learning in Web-Based Online Intelligent Education Systems

    Shuo Liu, Junhao Shen, Hong Qian, Aimin Zhou

    WWW, 2024. conference

11. Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive Paradigm

    Jiatong Li, Qi Liu, Fei Wang, Jiayu Liu, Zhenya Huang, Fangzhou Yao, Linbo Zhu, Yu Su

    WWW, 2024. conference

12. Endowing Interpretability for Neural Cognitive Diagnosis by Efficient Kolmogorov-Arnold Networks

    Shiwei Tong, Qi Liu, Runlong Yu, Wei Huang, Zhenya Huang, Zachary A Pardos, Weijie Jiang

    arXiv, 2024. preprint

13. Disentangling Cognitive Diagnosis with Limited Exercise Labels

    Xiangzhi Chen, Le Wu, Fei Liu, Lei Chen, Kun Zhang, Richang Hong, Meng Wang

    NeurIPS, 2023. conference

14. Leveraging Transferable Knowledge Concept Graph Embedding for Cold-Start Cognitive Diagnosis

    Weibo Gao, Hao Wang, Qi Liu, Fei Wang, Xin Lin, Linan Yue, Zheng Zhang, Rui Lv, Shijin Wang

    SIGIR, 2023. conference

15. Reconciling Cognitive Modeling with Knowledge Forgetting: A Continuous Time-aware Neural Network Approach

    Haiping Ma, Jingyuan Wang, Hengshu Zhu, Xin Xia, Haifeng Zhang, Xingyi Zhang, Lei Zhang

    IJCAI, 2022. conference

16. HierCDF: A Bayesian Network-based Hierarchical Cognitive Diagnosis Framework

    Jiatong Li, Fei Wang, Qi Liu, Mengxiao Zhu, Wei Huang, Zhenya Huang, Enhong Chen, Yu Su, Shijin Wang

    KDD, 2022. conference

17. Towards a New Generation of Cognitive Diagnosis

    Qi Liu

    IJCAI, 2021. conference

18. Item Response Ranking for Cognitive Diagnosis

    Shiwei Tong, Qi Liu, Runlong Yu, Wei Huang, Zhenya Huang, Zachary A Pardos, Weijie Jiang

    IJCAI, 2021. conference

19. RCD: Relation Map Driven Cognitive Diagnosis for Intelligent Education Systems

    Weibo Gao, Qi Liu, Zhenya Huang, Yu Yin, Haoyang Bi, Mu-Chun Wang, Jianhui Ma, Shijin Wang, Yu Su

    SIGIR, 2021. conference

20. Incremental Cognitive Diagnosis for Intelligent Education

    Shiwei Tong, Jiayu Liu, Yuting Hong, Zhenya Huang, Le Wu, Qi Liu, Wei Huang, Enhong Chen, Dan Zhang

    SIGIR, 2021. conference

21. Neural Cognitive Diagnosis for Intelligent Education Systems

    Fei Wang,Qi Liu,Enhong Chen,Zhenya Huang,Yuying Chen,Yu Yin,Zai Huang,Shijin Wang

    AAAI, 2020. conference

22. Proposition Entailment in Educational Applications using Deep Neural Networks

    Florin Bulgarov, Rodney Nielsen

    AAAI, 2019. conference

1. A Training-Free Large Reasoning Model-based Knowledge Tracing Framework for Unified Prediction and Prescription

   Unggi Lee, Joo Young Kim, Ran Ju, Minyoung Jung, Jeyeon Eo

   arXiv, 2026. preprint

2. Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Space

   Xingcheng Fu, Shengpeng Wang, Yisen Gao, Xianxian Li, Chunpei Li, Qingyun Sun, Dongran Yu

   arXiv, 2026. preprint

3. Problems With Large Language Models for Learner Modelling: Why LLMs Alone Fall Short for Responsible Tutoring in K--12 Education

   Danial Hooshyar, Yeongwook Yang, Gustav Sir, Tommi Karkkainen, Raija Hamalainen, Mutlu Cukurova, Roger Azevedo

   arXiv, 2025. preprint

4. PICKT: Practical Interlinked Concept Knowledge Tracing for Personalized Learning using Knowledge Map Concept Relations

   Wonbeen Lee, Channyoung Lee, Junho Sohn, Hansam Cho

   arXiv, 2025. preprint

5. Leveraging Pedagogical Theories to Understand Student Learning Process with Graph-based Reasonable Knowledge Tracing

   Jiajun Cui, Hong Qian, Bo Jiang, Wei Zhang

   KDD, 2024. conference

6. DyGKT: Dynamic Graph Learning for Knowledge Tracing

   Ke Cheng, Linzhi Peng, Pengyang Wang, Junchen Ye, Leilei Sun, Bowen Du

   KDD, 2024. conference

7. RIGL: A Unified Reciprocal Approach for Tracing the Independent and Group Learning Processes

   Xiaoshan Yu, Chuan Qin, Dazhong Shen, Shangshang Yang, Haiping Ma, Hengshu Zhu, Xingyi Zhang

   KDD, 2024. conference

8. Interpretable Knowledge Tracing with Multiscale State Representation

   Jianwen Sun, Fenghua Yu, Qian Wan, Qing Li, Sannyuya Liu, Xiaoxuan Shen

   WWW, 2024. conference

9. Question Difficulty Consistent Knowledge Tracing

   Guimei Liu, Huijing Zhan, Jung-jae Kim

   WWW, 2024. conference

10. Language Model Can Do Knowledge Tracing: Simple but Effective Method to Integrate Language Model and Knowledge Tracing Task

    Shangshang Yang, Linrui Qin, Xiaoshan Yu

    arXiv, 2024. preprint

11. Enhancing Deep Knowledge Tracing via Diffusion Models for Personalized Adaptive Learning

    Ming Kuo, Shouvon Sarker, Lijun Qian, Yujian Fu, Xiangfang Li, Xishuang Dong

    arXiv, 2024. preprint

12. Deep Attentive Model for Knowledge Tracing

    Xin-Peng Wang, Liang Chen, M. Zhang

    AAAI, 2023. conference

13. Improving Interpretability of Deep Sequential Knowledge Tracing Models with Question-centric Cognitive Representations

    Jiahao Chen, Zitao Liu, Shuyan Huang, Qiongqiong Liu, Weiqing Luo

    AAAI, 2023. conference

14. simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracing

    Zitao Liu, Qiongqiong Liu, Jiahao Chen, Shuyan Huang, Weiqi Luo

    ICLR, 2023. conference

15. Learning Behavior-oriented Knowledge Tracing

    Bihan Xu, Zhenya Huang, Jia-Yin Liu, Shuanghong Shen, Qi Liu, Enhong Chen, Jinze Wu, Shijin Wang

    KDD, 2023. conference

16. Adversarial Bootstrapped Question Representation Learning for Knowledge Tracing

    Jianwen Sun, Fenghua Yu, Sannyuya Liu, Yawei Luo, Ruxia Liang, Xiaoxuan Shen

    MM, 2023. conference

17. Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing

    Shangshang Yang, Xiaoshan Yu, Ye Tian, Xueming Yan, Haiping Ma, Xingyi Zhang

    NeurIPS, 2023. conference

18. Monitoring Student Progress for Learning Process-Consistent Knowledge Tracing

    Shuanghong Shen, Enhong Chen, Qi Liu, Zhenya Huang, Wei Huang, Yu Yin, Yu Su, Shijin Wang

    TKDE, 2023. journal

19. Fine-Grained Interaction Modeling with Multi-Relational Transformer for Knowledge Tracing

    Jiajun Cui, Zeyuan Chen, Aimin Zhou, Jianyong Wang, Wei Zhang

    TOIS, 2023. journal

20. Tracing Knowledge Instead of Patterns: Stable Knowledge Tracing with Diagnostic Transformer

    Yu Yin, Le Dai, Zhenya Huang, Shuanghong Shen, Fei Wang, Qi Liu, Enhong Chen, Xin Li

    WWW, 2023. conference

21. Enhancing Deep Knowledge Tracing with Auxiliary Tasks

    Zitao Liu, Qiongqiong Liu, Jiahao Chen, Shuyan Huang, Boyu Gao, Weiqing Luo, Jian Weng

    WWW, 2023. conference

22. Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations

    Sein Minn, Jill-Jenn Vie, Koh Takeuchi, Hisashi Kashima, Feida Zhu

    AAAI, 2022. conference

23. No Task Left Behind: Multi-Task Learning of Knowledge Tracing and Option Tracing for Better Student Assessment

    Suyeong An, Junghoon Kim, Minsam Kim, Juneyoung Park

    AAAI, 2022. conference

24. Predictive Student Modelling in an Online Reading Platform

    Effat Farhana, Teomara Rutherford, Collin Lynch

    AAAI, 2022. conference

25. HGKT: Introducing Hierarchical Exercise Graph for Knowledge Tracing

    Hanshuang Tong, Zhen Wang, Yun Zhou, Shiwei Tong, Wenyuan Han, Qi Liu

    SIGIR, 2022. conference

26. Assessing Student's Dynamic Knowledge State by Exploring the Question Difficulty Effect

    Shuanghong Shen, Zhenya Huang, Qi Liu, Yu Su, Shijin Wang, Enhong Chen

    SIGIR, 2022. conference

27. Improving Knowledge Tracing with Collaborative Information

    Ting Long, Jiarui Qin, Jian Shen, Weinan Zhang, Wei Xia, Ruiming Tang, Xiuqiang He, Yong Yu

    WSDM, 2022. conference

28. Contrastive Learning for Knowledge Tracing

    Wonsung Lee, Jaeyoon Chun, Youngmin Lee, Kyoungsoo Park, Sungrae Park

    WWW, 2022. conference

29. Learning Process-consistent Knowledge Tracing

    Shuanghong Shen, Qi Liu, Enhong Chen, Zhenya Huang, Wei Huang, Yu Yin, Yu Su, Shijin Wang

    KDD, 2021. conference

30. Enhancing Knowledge Tracing via Adversarial Training

    Xiaopeng Guo, Zhijie Huang, Jie Gao, Mingyu Shang, Maojing Shu, Jun Sun

    MM, 2021. conference

31. Tracing Knowledge State with Individual Cognition and Acquisition Estimation

    Ting Long, Yunfei Liu, Jian Shen, Weinan Zhang, Yong Yu

    SIGIR, 2021. conference

32. Temporal Cross-Effects in Knowledge Tracing

    Chenyang Wang, Weizhi Ma, Min Zhang, Chuancheng Lv, Fengyuan Wan, Huijie Lin, Taoran Tang, Yiqun Liu, Shaoping Ma

    WSDM, 2021. conference

33. Improving Knowledge Tracing via Pre-training Question Embeddings

    Yunfei Liu, Yang Yang, Xianyu Chen, Jian Shen, Haifeng Zhang, Yong Yu

    IJCAI, 2020. conference

34. Context-Aware Attentive Knowledge Tracing

    Aritra Ghosh, Neil Heffernan, Andrew S. Lan

    KDD, 2020. conference

35. Assessment Modeling: Fundamental Pre-training Tasks for Interactive Educational Systems

    Youngduck Choi, Youngnam Lee, Junghyun Cho, Jineon Baek, Dongmin Shin, Hangyeol Yu, Yugeun Shim, Seewoo Lee, Jonghun Shin, Chan Bae, Byungsoo Kim, Jaewe Heo

    arXiv, 2020. preprint

36. Knowledge Tracing with Sequential Key-Value Memory Networks

    Ghodai Abdelrahman, Qing Wang

    SIGIR, 2019. conference

37. EKT: Exercise-Aware Knowledge Tracing for Student Performance Prediction

    Qi Liu, Zhenya Huang, Yu Yin, Enhong Chen, Hui Xiong, Yu Su, Guoping Hu

    TKDE, 2019. journal

38. Augmenting Knowledge Tracing by Considering Forgetting Behavior

    Koki Nagatani, Qian Zhang, Masahiro Sato, Yan-Ying Chen, Francine Chen, Tomoko Ohkuma

    WWW, 2019. conference

39. Dynamic Key-Value Memory Networks for Knowledge Tracing

    Jiani Zhang, Xingjian Shi, Irwin King, Dit-Yan Yeung

    WWW, 2017. conference

40. Deep Knowledge Tracing

    Chris Piech, Jonathan Spencer, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas Guibas, Jascha Sohl-Dickstein

    NeurIPS, 2015. conference

1. ConvoLearn: A Dataset of Constructivist Tutor-Student Dialogue

   Mayank Sharma, Roy Pea, Hari Subramonyam

   arXiv, 2026. preprint

2. The Reel Deal: Designing and Evaluating LLM-Generated Short-Form Educational Videos

   Lazaros Stavrinou, Argyris Constantinides, Marios Belk, Vasos Vassiliou, Fotis Liarokapis, Marios Constantinides

   CHIGreece, 2025. conference

3. HealthCards: Exploring Text-to-Image Generation as Visual Aids for Healthcare Knowledge Democratizing and Education

   Qian Wu, Zheyao Gao, Longfei Gou, Yifan Hou, Qi Dou

   EMNLP, 2025. conference

4. Classic4Children: Adapting Chinese Literary Classics for Children with Large Language Model

   Jiali Chen, Xusen Hei, Yuqi Xue, Zihan Wu, Jiayuan Xie, Yi Cai

   NAACL Findings, 2025. conference

5. COGENT: A Curriculum-oriented Framework for Generating Grade-appropriate Educational Content

   Zhengyuan Liu, Stella Xin Yin, Dion Hoe-Lian Goh, Nancy F. Chen

   arXiv, 2025. preprint

6. Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models

   Yijia Shao, Yucheng Jiang, Theodore A. Kanell, Peter Xu, Omar Khattab, Monica S. Lam

   NAACL, 2024. conference

7. Generating Privacy-preserving Educational Data Records with Diffusion Model

   Quanlong Guan, Yanchong Yu, Xiujie Huang, Liangda Fang, Chaobo He, Lusheng Wu, Weiqi Luo, Guanliang Chen

   WWW, 2024. conference

8. Generating and Evaluating Tests for K-12 Students with Language Model Simulations: A Case Study on Sentence Reading Efficiency

   Eric Zelikman, Wanjing Anya Ma, Jasmine E. Tran, Diyi Yang, Jason D. Yeatman, Nick Haber

   EMNLP, 2023. conference

9. On the Automatic Generation and Simplification of Children's Stories

   Maria Valentini, Jennifer Weber, Jesus Salcido, Téa Wright, Eliana Colunga, Katharina Kann

   EMNLP, 2023. conference

10. FairytaleCQA: Integrating a Commonsense Knowledge Graph into Children's Storybook Narratives

    Jiaju Chen, Yuxuan Lu, Shao Zhang, Bingsheng Yao, Yuanzhe Dong, Ying Xu, Yunyao Li, Qianwen Wang, Dakuo Wang, Yuling Su

    arXiv, 2023. preprint

11. Robosourcing Educational Resources – Leveraging Large Language Models for Learnersourcing

    Paul Denny, Sami Sarsa, Arto Hellas, Juho Leinonen

    Learning@Scale - Workshop on Learnersourcing: Student-generated Content @ Scale, 2022. workshop

12. Linking Streets in OpenStreetMap to Persons in Wikidata

    Daria Gurtovoy, Simon Gottschalk

    WWW Companion, 2022. workshop

13. Personal Knowledge Graphs: Use Cases in e-learning Platforms

    Eleni Ilkou

    WWW Companion, 2022. workshop

14. Automatic Hierarchical Table of Contents Generation for Educational Videos

    Debabrata Mahapatra, Ragunathan Mariappan, Vaibhav Rajan

    WWW, 2018. conference

15. Automatic Generation of Quizzes from DBpedia According to Educational Standards

    Oscar Rodríguez Rocha, Catherine Faron Zucker

    WWW Companion, 2018. workshop

1. Instructor-Aligned Knowledge Graphs for Personalized Learning

   Abdulrahman AlRabah, Priyanka Kargupta, Jiawei Han, Abdussalam Alawini

   arXiv, 2026. preprint

2. Using structured knowledge and traditional word embeddings to generate concept representations in the educational domain

   Oghenemaro Anuyah, Ion Madrazo Azpiazu, Maria Soledad Pera

   WWW Companion, 2019. workshop

1. LLM Prompt Evaluation for Educational Applications

   Langdon Holmes, Adam Coscia, Scott Crossley, Joon Suh Choi, Wesley Morris

   arXiv, 2026. preprint

2. Exploring Iterative Enhancement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language Models

   Qiming Bao, Juho Leinonen, Alex Yuxuan Peng, Wanjun Zhong, Gaël Gendron, Timothy Pistotti, Alice Huang, Paul Denny, Michael Witbrock, Jiamou Liu

   AAAI, 2025. conference

3. Multiple-Choice Question Generation Using Large Language Models: Methodology and Educator Insights

   Giorgio Biancini, Alessio Ferrato, Carla Limongelli

   UMAP Adjunct, 2025. workshop

4. KAQG: A Knowledge‑Graph‑Enhanced RAG for Difficulty‑Controlled Question Generation

   Ching Han Chen, Ming Fang Shiu

   arXiv, 2025. preprint

5. Math Multiple Choice Question Generation via Human-Large Language Model Collaboration

   Jaewook Lee, Digory Smith, Simon Woodhead, Andrew Lan

   EDM, 2024. conference

6. Improving Automated Distractor Generation for Math Multiple-choice Questions with Overgenerate-and-rank

   Alexander Scarlatos, Wanyong Feng, Digory Smith, Simon Woodhead, Andrew Lan

   NAACL - BEA workshop, 2024. workshop

7. Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models

   Wanyong Feng, Jaewook Lee, Hunter McNichols, Alexander Scarlatos, Digory Smith, Simon Woodhead, Nancy Otero Ornelas, Andrew Lan

   NAACL findings, 2024. conference

8. Multiple Choice Questions and Large Languages Models: A Case Study with Fictional Medical Data

   Maxime Griot, Jean Vanderdonckt, Demet Yuksel, Coralie Hemptinne

   arXiv, 2024. preprint

9. Leveraging Large Language Models for Concept Graph Recovery and Question Answering in NLP Education

   Rui Yang, Boming Yang, Sixun Ouyang, Tianwei She, Aosong Feng, Yuang Jiang, Freddy Lecue, Jinghui Lu, Irene Li

   arXiv, 2024. preprint

10. ReadingQizMaker: A Human-NLP Collaborative System that Supports Instructors to Design High-Qality Reading Qiz Qestions

    Xinyi Lu, Simin Fan, Jessica Houghton, Lu Wang, Xu Wang

    CHI, 2023. conference

11. DeepQR: Neural-based Quality Ratings for Learnersourced Multiple-Choice Questions

    Lin Ni, Qiming Bao, Xiaoxuan Li, Qianqian Qi, Paul Denny, Jim Warren, Michael Witbrock, Jiamou Liu

    AAAI, 2022. conference

12. EQG-RACE: Examination-Type Question Generation

    Xin Jia, Wenjie Zhou, Xu Sun, Yunfang Wu

    AAAI, 2021. conference

13. Improving Learning Outcomes with Gaze Tracking and Automatic Question Generation

    Rohail Syed, Kevyn Collins-Thompson, Paul N. Bennett, Mengqiu Teng, Shane Williams, Dr. Wendy W. Tay, Shamsi Iqbal

    WWW, 2020. conference

1. Large Language Model Augmented Exercise Retrieval for Personalized Language Learning

   Austin Xu, Will Monroe, Klinton Bicknell

   Learning Analytics and Knowledge (LAK), 2024. conference

2. Fine-Grained Similarity Measurement between Educational Videos and Exercises

   Xin Wang, Wei Huang, Qi Liu, Yu Yin, Zhenya Huang, Le Wu, Jianhui Ma, Xue Wang

   MM, 2020. conference

1. Co-designing Large Language Model Tools for Project-Based Learning with K-12 Educators

   Prerna Ravi, John Masla, Gisella Kakoti, Grace Lin, Emma Anderson, Matt Taylor, Anastasia Ostrowski, Cynthia Breazeal, Eric Klopfer, Hal Abelson

   CHI, 2025. conference

2. LLMs are Biased Teachers: Evaluating LLM Bias in Personalized Education

   Iain Weissburg, Sathvika Anand, Sharon Levy, Haewon Jeong

   NAACL Findings, 2025. conference

3. A Humanoid Social Robot as a Teaching Assistant in the Classroom

   Thomas Sievers

   arXiv, 2025. preprint

4. Supporting Self-Reflection at Scale with Large Language Models: Insights from Randomized Field Experiments in Classrooms

   Harsh Kumar, Ruiwei Xiao, Benjamin Lawson, Ilya Musabirov, Jiakai Shi, Xinyuan Wang, Huayin Luo, Joseph Jay Williams, Anna Rafferty, John Stamper, Michael Liut

   Learning@Scale, 2024. conference

5. The Promises and Pitfalls of Using Language Models to Measure Instruction Quality in Education

   Paiheng Xu, Jing Liu, Nathan Jones, Julie Cohen, Wei Ai

   NAACL, 2024. conference

6. MathVC: An LLM-Simulated Multi-Character Virtual Classroom for Mathematics Education

   Murong Yue, Wijdane Mifdal, Yixuan Zhang, Jennifer Suh, Ziyu Yao

   arXiv, 2024. preprint

7. Simulating Classroom Education with LLM-Empowered Agents

   Zheyuan Zhang, Daniel Zhang-Li, Jifan Yu, Linlu Gong, Jinchang Zhou, Zhanxin Hao, Jianxiao Jiang, Jie Cao, Huiqin Liu, Zhiyuan Liu, Lei Hou, Juanzi Li

   arXiv, 2024. preprint

8. LearnerExp: Exploring and Explaining the Time Management of Online Learning Activity

   Huan He, Qinghua Zheng, Bo Dong

   WWW, 2019. conference

9. The Knowledge-Learning-Instruction Framework: Bridging the Science-Practice Chasm to Enhance Robust Student Learning

   K. Koedinger, Albert T. Corbett, C. Perfetti

   Cognitive Sciences, 2012. journal

1. Instructional Agents: LLM Agents Can Reduce Teaching Faculty Workload through Multi-Agent Instructional Design

   Huaiyuan Yao, Wanpeng Xu, Justin Turnau, Nadia Kellam, Hua Wei

   EACL, 2026. conference, code

1. Relying on LLMs: Student Practices and Instructor Norms are Changing in Computer Science Education

   Xinrui Lin, Heyan Huang, Shumin Shi, John Vines

   arXiv, 2026. preprint

2. Learning by Teaching: Engaging Students as Instructors of Large Language Models in Computer Science Education

   Xinming Yang, Haasil Pujara, Jun Li

   COLM, 2025. conference

3. Partnering with AI: A Pedagogical Feedback System for LLM Integration into Programming Education

   Niklas Scholz, Manh Hung Nguyen, Adish Singla, Tomohiro Nagashima

   ECTEL, 2025. conference

4. When Scaffolding Breaks: Investigating Student Interaction with LLM-Based Writing Support in Real-Time K-12 EFL Classrooms

   Junho Myung, Hyunseung Lim, Hana Oh, Hyoungwook Jin, Nayeon Kang, So-Yeon Ahn, Hwajung Hong, Alice Oh, Juho Kim

   arXiv, 2025. preprint

5. CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needs

   Majeed Kazemitabaar, Runlong Ye, Xiaoning Wang, Austin Z. Henley, Paul Denny, Michelle Craig, Tovi Grossman

   CHI, 2024. conference

6. Interactions with Prompt Problems: A New Way to Teach Programming with Large Language Models

   James Prather, Paul Denny, Juho Leinonen, David H. Smith IV, Brent N. Reeves, Stephen MacNeil, Brett A. Becker, Andrew Luxton-Reilly, Thezyrie Amarouche, Bailey Kimmel

   CHI, 2024. conference

7. ChatScratch: An AI-Augmented System Toward Autonomous Visual Programming Learning for Children Aged 6-12

   Liuqing Chen, Shuhong Xiao, Yunnong Chen, Ruoyu Wu, Yaxuan Song, Lingyun Sun

   CHI, 2024. conference

8. Exploring How Multiple Levels of GPT-Generated Programming Hints Support or Disappoint Novices

   Ruiwei Xiao, Xinying Hou, John Stamper

   CHI, 2024. conference

9. AI-Tutoring in Software Engineering Education

   Eduard Frankford, Clemens Sauerwein, Patrick Bassner, Stephan Krusche, Ruth Breu

   ICSE, 2024. conference

10. How Far Are We? The Triumphs and Trials of Generative AI in Learning Software Engineering

    Rudrajit Choudhuri, Dylan Liu, Igor Steinmacher, Marco Gerosa, Anita Sarma

    ICSE, 2024. conference

11. Evaluating the Effectiveness of LLMs in Introductory Computer Science Education: A Semester-Long Field Study

    Wenhan Lyu, Yimeng Wang, Tingting (Rachel)Chung, Yifan Sun, Yixuan Zhang

    Learning@Scale, 2024. conference

12. Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph Reasoning

    Markus J. Buehler

    arXiv, 2024. preprint

13. Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming

    Majeed Kazemitabaar, Justin Chow, Carl Ka To Ma, Barbara J. Ericson, David Weintrop, Tovi Grossman

    CHI, 2023. conference

1. Position: LLMs Can be Good Tutors in Foreign Language Education

   Jingheng Ye, Shen Wang, Deqing Zou, Yibo Yan, Kun Wang, Hai-Tao Zheng, Zenglin Xu, Irwin King, Philip S. Yu, Qingsong Wen

   EMNLP, 2025. conference

2. WordPlay: An Agent Framework for Language Learning Games

   Ariel Blobstein, Daniel Izmaylov, Tal Yifat, Michal Levy, Avi Segal, Avi Segal

   NeurIPS - Workshop on Generative AI for Education (GAIED), 2024. workshop

1. Exploring LLM-Powered Role and Action-Switching Pedagogical Agents for History Education in Virtual Reality

   Zihao Zhu, Ao Yu, Xin Tong, Pan Hui

   CHI, 2025. conference

1. MathTutorBench: A Benchmark for Measuring Open-ended Pedagogical Capabilities of LLM Tutors

   Jakub Macina, Nico Daheim, Ido Hakimi, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan

   EMNLP, 2025. conference

2. MathEDU: Towards Adaptive Feedback for Student Mathematical Problem-Solving

   Wei-Ling Hsu, Yu-Chien Tang, An-Zi Yen

   arXiv, 2025. conference

3. One Size doesn’t Fit All: A Personalized Conversational Tutoring Agent for Mathematics Instruction

   Ben Liu, Jihan Zhang, Fangquan Lin, Xu Jia, Min Peng

   arXiv, 2025. preprint

4. Mathemyths: Leveraging Large Language Models to Teach Mathematical Language through Child-AI Co-Creative Storytelling

   Chao Zhang, Xuechen Liu, Katherine Ziska, Soobin Jeon, Chi-Lin Yu, Ying Xu

   CHI, 2024. conference

1. CaseMaster: Designing and Evaluating a Probe for Oral Case Presentation Training with LLM Assistance

   Yang Ouyang, Yuansong Xu, Chang Jiang, Yifan Jin, Haoran Jiang, Quan Li

   arXiv, 2026. preprint

2. DischargeSim: A Simulation Benchmark for Educational Doctor–Patient Communication at Discharge

   Zonghai Yao, Michael Sun, Won Seok Jang, SUNJAE KWON, Soie Kwon, Hong Yu

   EMNLP, 2025. conference

3. HealthCards: Exploring Text-to-Image Generation as Visual Aids for Healthcare Knowledge Democratizing and Education

   Qian Wu, Zheyao Gao, Longfei Gou, Yifan Hou, Qi Dou

   EMNLP, 2025. conference

4. Leveraging Large Language Model as Simulated Patients for Clinical Education

   Yanzeng Li, Cheng Zeng, Jialun Zhong, Ruoyu Zhang, Minhao Zhang, Lei Zou

   arXiv, 2024. preprint

1. PatientSim: A Persona-Driven Simulator for Realistic Doctor-Patient Interactions

   Daeun Kyung, Hyunseung Chung, Seongsu Bae, Jiho Kim, Jae Ho Sohn, Taerim Kim, Soo Kyung Kim, Edward Choi

   arXiv, 2025. preprint

2. LLM-Powered AI Tutors with Personas for d/Deaf and Hard-of-Hearing Online Learners

   Haocong Cheng, Si Chen, Christopher Perdriau, Yun Huang

   arXiv, 2024. preprint

1. Visual Reasoning Benchmark: Evaluating Multimodal LLMs on Classroom-Authentic Visual Problems from Primary Education

   Mohamed Huti, Alasdair Mackintosh, Amy Waldock, Dominic Andrews, Maxime Lelievre, Moritz Boos, Tobias Murray, Paul Atherton, Robin A. A. Ince, Oliver G. B. Garrod

   arXiv, 2026. preprint

2. CASTLE: A Comprehensive Benchmark for Evaluating Student-Tailored Personalized Safety in Large Language Models

   Rui Jia, Ruiyi Lan, Fengrui Liu, Zhongxiang Dai, Bo Jiang, Jing Shao, Jingyuan Chen, Guandong Xu, Fei Wu, Min Zhang

   arXiv, 2026. preprint

3. ISD-Agent-Bench: A Comprehensive Benchmark for Evaluating LLM-based Instructional Design Agents

   YoungHoon Jeon, Suwan Kim, Haein Son, Sookbun Lee, Yeil Jeong, Unggi Lee

   arXiv, 2026. preprint

4. MathTutorBench: A Benchmark for Measuring Open-ended Pedagogical Capabilities of LLM Tutors

   Jakub Macina, Nico Daheim, Ido Hakimi, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan

   EMNLP, 2025. conference

5. VisualEDU: A Benchmark for Assessing Coding and Visual Comprehension through Educational Problem-Solving Video Generation

   Hao Chen, TIANYU SHI, Pengran huang, Zeyuan Li, Jiahui Pan, Qianglong Chen, Lewei He

   EMNLP Findings, 2025. conference

6. Towards Robust Evaluation of STEM Education: Leveraging MLLMs in Project-Based Learning

   Yanhao Jia, Xinyi Wu, Qinglin Zhang, Yiran Qin, Luwei Xiao, Shuai Zhao

   arXiv, 2025. preprint

7. Benchmarking the Pedagogical Knowledge of Large Language Models

   Maxime Lelièvre, Amy Waldock, Meng Liu, Natalia Valdés Aspillaga, Alasdair Mackintosh, María José Ogando Portela, Jared Lee, Paul Atherton, Robin A. A. Ince, Oliver G. B. Garrod

   arXiv, 2025. preprint

8. From Answers to Questions: EQGBench for Evaluating LLMs' Educational Question Generation

   Chengliang Zhou, Mei Wang, Ting Zhang, Qiannan Zhu, Jian Li, Hua Huang

   arXiv, 2025. preprint

9. EduNLP: Towards a Unified and Modularized Library for Educational Resources

   Zhenya Huang, Yuting Ning, Longhu Qin, Shiwei Tong, Shangzi Xue, Tong Xiao, Xin Lin, Jiayu Liu, Qi Liu, Enhong Chen, Shijing Wang

   arXiv, 2024. preprint

10. E-EVAL: A Comprehensive Chinese K-12 Education Evaluation Benchmark for Large Language Models

    Jinchang Hou, Chang Ao, Haihong Wu, Xiangtao Kong, Zhigang Zheng, Daijia Tang, Chengming Li, Xiping Hu, Ruifeng Xu, Shiwen Ni, Min Yang

    arXiv, 2024. preprint

11. Experimental Interface for Multimodal and Large Language Model Based Explanations of Educational Recommender Systems

    Hasan Abu-Rasheed, Christian Weber, Madjid Fathi

    arXiv, 2024. preprint

12. pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models

    Zitao Liu, Qiongqiong Liu, Jiahao Chen, Shuyan Huang, Jiliang Tang, Weiqing Luo

    NeurIPS, 2022. conference

1. FoundationalASSIST: An Educational Dataset for Foundational Knowledge Tracing and Pedagogical Grounding of LLMs

   Eamon Worden, Cristina Heffernan, Neil Heffernan, Shashank Sonkar

   arXiv, 2026. preprint

2. EduEVAL-DB: A Role-Based Dataset for Pedagogical Risk Evaluation in Educational Explanations

   Javier Irigoyen, Roberto Daza, Aythami Morales, Julian Fierrez, Francisco Jurado, Alvaro Ortigosa, Ruben Tolosana

   arXiv, 2026. preprint

3. IntrEx: A Dataset for Modeling Engagement in Educational Conversations

   Xingwei Tan, Mahathi Parvatham, Chiara Gambi, Gabriele Pergola

   EMNLP Findings, 2025. conference

4. QACP: An Annotated Question Answering Dataset for Assisting Chinese Python Programming Learners

   Rui Xiao, Lu Han, Xiaoying Zhou, Jiong Wang, Na Zong, Pengyu Zhang

   arXiv, 2024. preprint

5. PTADisc: A Cross-Course Dataset Supporting Personalized Learning in Cold-Start Scenarios

   Liya Hu, Zhiang Dong, Jingyuan Chen, Guifeng Wang, Zhihua Wang, Zhou Zhao, Fei Wu

   NeurIPS, 2023. conference

6. EdNet: A Large-Scale Hierarchical Dataset in Education

   Youngduck Choi, Youngnam Lee, Dongmin Shin, Junghyun Cho, Seoyon Park, Seewoo Lee, Jineon Baek, Byungsoo Kim, Youngjun Jang

   AIED, 2020. conference