Awesome Artificial Intelligence and Large Language Model for Education

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.

✨ indicates the papers that are related to LLM.

Content

1. Survey
1.1 Comprehensive Survey	1.2 Task-Specific Survey
2. Tutoring And Personalized Learning
2.1 Learning Path Recommendation	2.2 Student Profiling
2.3 Tutoring System
3. Assessment
3.1 Adaptive Testing	3.2 Automated Grading
3.3 Cognitive Diagnosis	3.4 Knowledge Tracing
3.5 Question Generation	3.6 Question Retrieval
4. Material Preparation
4.1 Content Generation	4.2 Knowledge Structuring
5. Specific Scenario
5.1 Computer Science	5.2 Math
5.3 Medicine
6. Aided Teaching
7. Dataset & Benchmark
7.1 Benchmark	7.2 Dataset

Survey

Comprehensive Survey

✨ 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
✨ 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
✨ 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
✨ Large Language Models in Education: Vision and Opportunities

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

BigData, 2023. conference
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
Reinforcement Learning for Education: Opportunities and Challenges

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

EDM-RL4ED, 2021. conference

Task-Specific Survey

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

Tutoring And Personalized Learning

Learning Path Recommendation

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
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
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
Course Recommender Systems Need to Consider the Job Market

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

SIGIR, 2024. conference
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
✨ 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
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
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
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
Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning

Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill

AAAI, 2022. conference
CurriculumTutor: An Adaptive Algorithm for Mastering a Curriculum

Shabana K M, Chandrashekar Lakshminarayanan

AIED, 2022. conference
Automatic Interpretable Personalized Learning

Ethan Prihar, Aaron Haim, Adam Sales, Neil Heffernan

Learning@Scale, 2022. conference
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
Reinforcement Learning for the Adaptive Scheduling of Educational Activities

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

CHI, 2020. conference
Deep Reinforcement Learning for Adaptive Learning Systems

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

arXiv, 2020. preprint
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
Exploiting Cognitive Structure for Adaptive Learning

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

KDD, 2019. conference
Combining Adaptivity with Progression Ordering for Intelligent Tutoring Systems

Tong Mu, Shuhan Wang, Erik Andersen, Emma Brunskill

Learning@Scale, 2018. conference
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
Ontology-based Recommender System in Higher Education

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

WWW Companion, 2018. workshop
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

Student Profiling

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

Silan Hu, Xiaoning Wang

arXiv, 2024. preprint
✨ EduAgent: Generative Student Agents in Learning

Songlin Xu, Xinyu Zhang, Lianhui Qin

arXiv, 2024. preprint
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
✨ 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
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
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

Tutoring System

✨ 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
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
✨ 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
✨ Personality-aware Student Simulation for Conversational Intelligent Tutoring Systems

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

arXiv, 2024. preprint
✨ 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
✨ Scaffolding Language Learning via Multi-modal Tutoring Systems with Pedagogical Instructions

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

arXiv, 2024. preprint
✨ Apprentice Tutor Builder: A Platform For Users to Create and Personalize Intelligent Tutors

Glen Smith, Adit Gupta, Christopher MacLellan

arXiv, 2024. preprint
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
✨ 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
✨ 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), 2023. workshop
✨ Empowering Private Tutoring by Chaining Large Language Models

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

arXiv, 2023. preprint
✨ 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
Personal Knowledge Graphs: Use Cases in e-learning Platforms

Eleni Ilkou

WWW Companion, 2022. workshop
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
An Interaction Design for Machine Teaching to Develop AI Tutors

Daniel Weitekamp, Erik Harpstead, K. Koedinger

CHI, 2020. conference
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
Locus of Feedback Control in Computer-Based Tutoring

Albert T. Corbett, John R. Anderson

CHI, 2001. conference

Assessment

Adaptive Testing

Search-Efficient Computerized Adaptive Testing

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

CIKM, 2023. conference
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
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
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
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
BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing

Aritra Ghosh, Andrew Lan

IJCAI, 2021. conference

Automated Grading

✨ Large Language Models As MOOCs Graders

Shahriar Golchin, Nikhil Garuda, Christopher Impey, Matthew Wenger

arXiv, 2024. preprint
✨ 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
✨ Large Language Models as Partners in Student Essay Evaluation

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

arXiv, 2024. preprint

Cognitive Diagnosis

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
Symbolic Cognitive Diagnosis via Hybrid Optimization for Intelligent Education Systems

Junhao Shen, Hong Qian, Wei Zhang, Aimin Zhou

AAAI, 2024. conference
Path-Specific Causal Reasoning for Fairness-aware Cognitive Diagnosis

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

KDD, 2024. conference
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
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
✨ Generative Students: Using LLM-Simulated Student Profiles to Support Question Item Evaluation

Xinyi Lu, Xu Wang

Learning@Scale, 2024. conference
Multivariate Cognitive Response Framework for Student Performance Prediction on MOOC

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

TKDE, 2024. journal
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
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
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
Disentangling Cognitive Diagnosis with Limited Exercise Labels

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

NeurIPS, 2023. conference
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
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
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
Towards a New Generation of Cognitive Diagnosis

Qi Liu

IJCAI, 2021. conference
Item Response Ranking for Cognitive Diagnosis

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

IJCAI, 2021. conference
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
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
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
Proposition Entailment in Educational Applications using Deep Neural Networks

Florin Bulgarov, Rodney Nielsen

AAAI, 2019. conference

Knowledge Tracing

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
DyGKT: Dynamic Graph Learning for Knowledge Tracing

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

KDD, 2024. conference
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
Interpretable Knowledge Tracing with Multiscale State Representation

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

WWW, 2024. conference
Question Difficulty Consistent Knowledge Tracing

Guimei Liu, Huijing Zhan, Jung-jae Kim

WWW, 2024. conference
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
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
Deep Attentive Model for Knowledge Tracing

Xin-Peng Wang, Liang Chen, M. Zhang

AAAI, 2023. conference
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
simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracing

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

ICLR, 2023. conference
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
Adversarial Bootstrapped Question Representation Learning for Knowledge Tracing

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

MM, 2023. conference
Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing

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

NeurIPS, 2023. conference
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
Fine-Grained Interaction Modeling with Multi-Relational Transformer for Knowledge Tracing

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

TOIS, 2023. journal
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
Enhancing Deep Knowledge Tracing with Auxiliary Tasks

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

WWW, 2023. conference
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
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
Predictive Student Modelling in an Online Reading Platform

Effat Farhana, Teomara Rutherford, Collin Lynch

AAAI, 2022. conference
HGKT: Introducing Hierarchical Exercise Graph for Knowledge Tracing

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

SIGIR, 2022. conference
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
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
Contrastive Learning for Knowledge Tracing

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

WWW, 2022. conference
Learning Process-consistent Knowledge Tracing

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

KDD, 2021. conference
Enhancing Knowledge Tracing via Adversarial Training

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

MM, 2021. conference
Tracing Knowledge State with Individual Cognition and Acquisition Estimation

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

SIGIR, 2021. conference
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
Improving Knowledge Tracing via Pre-training Question Embeddings

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

IJCAI, 2020. conference
Context-Aware Attentive Knowledge Tracing

Aritra Ghosh, Neil Heffernan, Andrew S. Lan

KDD, 2020. conference
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
Knowledge Tracing with Sequential Key-Value Memory Networks

Ghodai Abdelrahman, Qing Wang

SIGIR, 2019. conference
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
Augmenting Knowledge Tracing by Considering Forgetting Behavior

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

WWW, 2019. conference
Dynamic Key-Value Memory Networks for Knowledge Tracing

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

WWW, 2017. conference
Deep Knowledge Tracing

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

NeurIPS, 2015. conference

Question Generation

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

Jaewook Lee, Digory Smith, Simon Woodhead, Andrew Lan

EDM, 2024. conference
✨ 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
✨ 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
✨ 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
✨ 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
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
EQG-RACE: Examination-Type Question Generation

Xin Jia, Wenjie Zhou, Xu Sun, Yunfang Wu

AAAI, 2021. conference
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

Question Retrieval

✨ Large Language Model Augmented Exercise Retrieval for Personalized Language Learning

Austin Xu, Will Monroe, Klinton Bicknell

Learning Analytics and Knowledge (LAK), 2024. conference
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

Material Preparation

Content Generation

✨ 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
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
✨ 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
✨ 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
✨ 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
✨ 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
Linking Streets in OpenStreetMap to Persons in Wikidata

Daria Gurtovoy, Simon Gottschalk

WWW Companion, 2022. workshop
Personal Knowledge Graphs: Use Cases in e-learning Platforms

Eleni Ilkou

WWW Companion, 2022. workshop
Automatic Hierarchical Table of Contents Generation for Educational Videos

Debabrata Mahapatra, Ragunathan Mariappan, Vaibhav Rajan

WWW, 2018. conference
Automatic Generation of Quizzes from DBpedia According to Educational Standards

Oscar Rodríguez Rocha, Catherine Faron Zucker

WWW Companion, 2018. workshop

Knowledge Structuring

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

Specific Scenario

Computer Science

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

Ruiwei Xiao, Xinying Hou, John Stamper

CHI, 2024. conference
✨ AI-Tutoring in Software Engineering Education

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

ICSE, 2024. conference
✨ 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
✨ 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
✨ Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph Reasoning

Markus J. Buehler

arXiv, 2024. preprint
✨ 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

Math

✨ 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

Medicine

✨ 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

Aided Teaching

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

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

arXiv, 2024. preprint
LearnerExp: Exploring and Explaining the Time Management of Online Learning Activity

Huan He, Qinghua Zheng, Bo Dong

WWW, 2019. conference
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

Dataset & Benchmark

Benchmark

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

Hasan Abu-Rasheed, Christian Weber, Madjid Fathi

arXiv, 2024. preprint
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

Dataset

✨ 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
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
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

The-RunningSnail/awesome-ai-llm4education

Awesome Artificial Intelligence and Large Language Model for Education