We will release our work on Goal-oriented Learning with LLM-powered Agentic Framework, which currently is under internal review of Microsoft. Stay tuned!
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.
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✨ 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
-
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
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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
-
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
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✨ 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
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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
-
✨ 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
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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
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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
-
✨ 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
-
✨ 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
-
✨ 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
-
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
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✨ 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
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✨ 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
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✨ 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
-
✨ 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
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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
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✨ 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