The reference shelf.

Circuit Complexity of Hierarchical Knowledge Tracing and Implications for Log-Precision Transformers

Naiming Liu; Richard Baraniuk; Shashank Sonkar

arXiv preprint arXiv:2603.23823v1 [cs.LG], 25 March 2026

DOI: 10.48550/arxiv.2603.23823

Coasting Through Class: Learning Opportunity Loss from Practice Avoidance During Individual Seatwork

Ashish Gurung; Jordan Gutterman; Danielle R. Thomas; Mingyu Feng; Vincent Aleven; Kenneth R. Koedinger

Proceedings of the Thirteenth ACM Conference on Learning @ Scale (L@S 2026)

DOI: 10.1145/3774398.3811601

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

Eamon Worden; Cristina Heffernan; Neil Heffernan; Shashank Sonkar

arXiv preprint arXiv:2602.00070v1 [cs.CY], 20 January 2026

DOI: 10.48550/arxiv.2602.00070

Fractional Information Gain: A Personalization Metric for Black-Box Predictive Models

S. Thomas Christie; Markus Hauru; Anna N. Rafferty

Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con 2026), Volume 1: Full Papers, pp. 109–116, National Council on Measurement in Education (NCME)

Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions

Danielle R. Thomas; Marie Cynthia Abijuru Kamikazi; Ashish Gurung; Ishan Miglani; Shivang Gupta; Zachary Levonian; Conrad Borchers; Kenneth R. Koedinger

arXiv preprint 2609.36502v1 [cs.HC]

DOI: 10.48550/arxiv.2609.36502

Cognitive Fluctuations Enhanced Attention Network for Knowledge Tracing

Mingliang Hou; Xueyi Li; Teng Guo; Zitao Liu; Mi Tian; Renqiang Luo; Weiqi Luo

Proceedings of the AAAI Conference on Artificial Intelligence 39(13) (AAAI-25), pp. 14265–14273

DOI: 10.1609/aaai.v39i13.33562

Rethinking and Improving Student Learning and Forgetting Processes for Attention Based Knowledge Tracing Models

Youheng Bai; Xueyi Li; Zitao Liu; Yaying Huang; Mi Tian; Weiqi Luo

Proceedings of the AAAI Conference on Artificial Intelligence 39(27) (AAAI-25), pp. 27822–27830

DOI: 10.1609/aaai.v39i27.34998

Starting Seatwork Earlier as a Valid Measure of Student Engagement

Ashish Gurung; Jionghao Lin; Zhongtian Huang; Conrad Borchers; Ryan S. Baker; Vincent Aleven; Kenneth R. Koedinger

Proceedings of the 18th International Conference on Educational Data Mining (EDM 2025), pp. 303–316

DOI: 10.5281/zenodo.15870183

Uncertainty-aware Knowledge Tracing

Weihua Cheng; Hanwen Du; Chunxiao Li; Ersheng Ni; Liangdi Tan; Tianqi Xu; Yongxin Ni

Proceedings of the AAAI Conference on Artificial Intelligence 39(27) (AAAI-25), pp. 27905–27913

DOI: 10.1609/aaai.v39i27.35007

A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing Models

Hengyuan Zhang; Zitao Liu; Chenming Shang; Dawei Li; Yong Jiang

ACM Transactions on Knowledge Discovery from Data 19(2), pp. 1–25 (2025); deposited copy is the arXiv preprint arXiv:2403.07322v3 [cs.CY], 5 July 2024

DOI: 10.1145/3674840

A Unified Model of Arithmetic With Whole Numbers, Fractions, and Decimals

David W. Braithwaite; Robert S. Siegler

Psychological Review, 131(2), 431–455

DOI: 10.1037/rev0000440

DGEKT: A Dual Graph Ensemble Learning Method for Knowledge Tracing

Chaoran Cui; Yumo Yao; Chunyun Zhang; Hebo Ma; Yuling Ma; Zhaochun Ren; Chen Zhang; James Ko

ACM Transactions on Information Systems 42(3), article 78, pp. 1–24

DOI: 10.1145/3638350

DyGKT: Dynamic Graph Learning for Knowledge Tracing

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

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’24), pp. 409–420

DOI: 10.1145/3637528.3671773

Enhancing Length Generalization for Attention Based Knowledge Tracing Models with Linear Biases

Xueyi Li; Youheng Bai; Teng Guo; Zitao Liu; Yaying Huang; Xiangyu Zhao; Feng Xia; Weiqi Luo; Jian Weng

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI-24), Main Track, pp. 5918–5926

DOI: 10.24963/ijcai.2024/654

Extending Context Window of Attention Based Knowledge Tracing Models via Length Extrapolation

Xueyi Li; Youheng Bai; Teng Guo; Ying Zheng; Mingliang Hou; Bojun Zhan; Yaying Huang; Zitao Liu; Boyu Gao; Weiqi Luo

ECAI 2024 (27th European Conference on Artificial Intelligence), Frontiers in Artificial Intelligence and Applications vol. 392, IOS Press, pp. 1479–1486

DOI: 10.3233/faia240651

Predictive, scalable and interpretable knowledge tracing on structured domains

Hanqi Zhou; Robert Bamler; Charley M. Wu; Álvaro Tejero-Cantero

The Twelfth International Conference on Learning Representations (ICLR 2024), pp. 35609–35622

Revisiting Knowledge Tracing: A Simple and Powerful Model

Xiaoxuan Shen; Fenghua Yu; Yaqi Liu; Ruxia Liang; Qian Wan; Kai Yang; Jianwen Sun

Proceedings of the 32nd ACM International Conference on Multimedia (MM '24), pp. 263–272

DOI: 10.1145/3664647.3681205

An astonishing regularity in student learning rate

Kenneth R. Koedinger; Paulo F. Carvalho; Ran Liu; Elizabeth A. McLaughlin

Proceedings of the National Academy of Sciences (PNAS) 120(13), e2221311120

DOI: 10.1073/pnas.2221311120

Enhancing Deep Knowledge Tracing with Auxiliary Tasks

Zitao Liu; Qiongqiong Liu; Jiahao Chen; Shuyan Huang; Boyu Gao; Weiqi Luo; Jian Weng

Proceedings of the ACM Web Conference 2023 (WWW '23), pp. 4178–4187

DOI: 10.1145/3543507.3583866

Forgetting-aware Linear Bias for Attentive Knowledge Tracing

Yoonjin Im; Eunseong Choi; Heejin Kook; Jongwuk Lee

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM '23), pp. 3958–3962

DOI: 10.1145/3583780.3615191

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

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

Proceedings of the AAAI Conference on Artificial Intelligence 37(12) (AAAI-23), pp. 14196–14204

DOI: 10.1609/aaai.v37i12.26661

Knowledge Tracing Model and Student Profile Based on Clustering-Neural-Network

Jianghua Xia; Han Wang; Qingfeng Zhuge; Edwin Hsing-Mean Sha

Applied Sciences, 13(9), article 5220

DOI: 10.3390/app13095220

Pizzas or no pizzas: An advantage of word problems in fraction arithmetic?

T.M.M. Mostert; M. Hickendorff

Learning and Instruction, 86, article 101775

DOI: 10.1016/j.learninstruc.2023.101775

Towards Robust Knowledge Tracing Models via k-Sparse Attention

Shuyan Huang; Zitao Liu; Xiangyu Zhao; Weiqi Luo; Jian Weng

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '23), pp. 2441–2445

DOI: 10.1145/3539618.3592073

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

Proceedings of the ACM Web Conference 2023 (WWW '23), pp. 855–864

DOI: 10.1145/3543507.3583255

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

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

Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '22), pp. 427–437

DOI: 10.1145/3477495.3531939

Bi-CLKT: Bi-Graph Contrastive Learning based Knowledge Tracing

Xiangyu Song; Jianxin Li; Qi Lei; Wei Zhao; Yunliang Chen; Ajmal Mian

Knowledge-Based Systems 241, article 108274 (April 2022)

DOI: 10.1016/j.knosys.2022.108274

DAGKT: Difficulty and Attempts Boosted Graph-Based Knowledge Tracing

Rui Luo; Fei Liu; Wenhao Liang; Yuhong Zhang; Chenyang Bu; Xuegang Hu

Neural Information Processing: 29th International Conference, ICONIP 2022, Virtual Event, November 22–26, 2022, Proceedings, Part II (Lecture Notes in Computer Science, Springer, published 2023), pp. 255–266

DOI: 10.1007/978-3-031-30108-7_22

Introducing Problem Schema with Hierarchical Exercise Graph for Knowledge Tracing

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

Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '22), pp. 405–415

DOI: 10.1145/3477495.3532004

Modifying Deep Knowledge Tracing for Multi-step Problems

Qiao Zhang; Zeyu Chen; Natasha Lalwani; Christopher J. MacLellan

Proceedings of the 15th International Conference on Educational Data Mining (EDM 2022), Durham, United Kingdom, pp. 684–688

DOI: 10.5281/zenodo.6853145

Enhancing Knowledge Tracing via Adversarial Training

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

Proceedings of the 29th ACM International Conference on Multimedia (MM '21), pp. 367–375

DOI: 10.1145/3474085.3475554

Examining Student Effort on Help through Response Time Decomposition

Ashish Gurung; Anthony F. Botelho; Neil T. Heffernan

LAK21: 11th International Learning Analytics and Knowledge Conference, April 12–16, 2021, Irvine, CA, USA. ACM, pp. 292–301

DOI: 10.1145/3448139.3448167

Learning Process-consistent Knowledge Tracing

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

Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’21), pp. 1452–1460

DOI: 10.1145/3447548.3467237

Logistic Knowledge Tracing: A Constrained Framework for Learner Modeling

Philip I. Pavlik Jr.; Luke G. Eglington; Leigh M. Harrell-Williams

IEEE Transactions on Learning Technologies, 14(5), pp. 624–639

DOI: 10.1109/tlt.2021.3128569

Temporal Cross-Effects in Knowledge Tracing

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

Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM '21), pp. 517–525

DOI: 10.1145/3437963.3441802

Tracing Knowledge State with Individual Cognition and Acquisition Estimation

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

Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '21), pp. 173–182

DOI: 10.1145/3404835.3462827

Accurate and Interpretable Sensor-free Affect Detectors via Monotonic Neural Networks

Andrew S. Lan; Anthony Botelho; Shamya Karumbaiah; Ryan S. Baker; Neil Heffernan

Companion Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK20), poster paper

Context-Aware Attentive Knowledge Tracing

Aritra Ghosh; Neil Heffernan; Andrew S. Lan

Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD ’20), pp. 2330–2339

DOI: 10.1145/3394486.3403282

GIKT: A Graph-Based Interaction Model for Knowledge Tracing

Yang Yang; Jian Shen; Yanru Qu; Yunfei Liu; Kerong Wang; Yaoming Zhu; Weinan Zhang; Yong Yu

Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part I (Lecture Notes in Computer Science, Springer, published 2021), pp. 299–315

DOI: 10.1007/978-3-030-67658-2_18

qDKT: Question-Centric Deep Knowledge Tracing

Shashank Sonkar; Andrew E. Waters; Andrew S. Lan; Phillip J. Grimaldi; Richard G. Baraniuk

Proceedings of the 13th International Conference on Educational Data Mining (EDM 2020), pp. 677–681

RKT: Relation-Aware Self-Attention for Knowledge Tracing

Shalini Pandey; Jaideep Srivastava

Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), pp. 1205–1214

DOI: 10.1145/3340531.3411994

Structure-based Knowledge Tracing: An Influence Propagation View

Shiwei Tong; Qi Liu; Wei Huang; Zhenya Huang; Enhong Chen; Chuanren Liu; Haiping Ma; Shijin Wang

2020 IEEE International Conference on Data Mining (ICDM), pp. 541–550

DOI: 10.1109/icdm50108.2020.00063

Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing

Youngduck Choi; Youngnam Lee; Junghyun Cho; Jineon Baek; Byungsoo Kim; Yeongmin Cha; Dongmin Shin; Chan Bae; Jaewe Heo

Proceedings of the Seventh ACM Conference on Learning @ Scale (L@S '20), pp. 341–344

DOI: 10.1145/3386527.3405945

When is Deep Learning the Best Approach to Knowledge Tracing?

Theophile Gervet; Ken Koedinger; Jeff Schneider; Tom Mitchell

Journal of Educational Data Mining, 12(3), pp. 31–54

DOI: 10.5281/zenodo.4143614

A Self-Attentive model for Knowledge Tracing

Shalini Pandey; George Karypis

Proceedings of the 12th International Conference on Educational Data Mining (EDM 2019), pp. 384–389

Augmenting Knowledge Tracing by Considering Forgetting Behavior

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

Proceedings of the 2019 World Wide Web Conference (WWW '19), pp. 3101–3107

DOI: 10.1145/3308558.3313565

DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Skills

Benoît Choffin; Fabrice Popineau; Yolaine Bourda; Jill-Jênn Vie

Proceedings of the 12th International Conference on Educational Data Mining (EDM 2019)

DOI: 10.48550/arxiv.1905.06873

Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory

Chun-Kit Yeung

Proceedings of the 12th International Conference on Educational Data Mining (EDM 2019), pp. 683–686

Graph-based Knowledge Tracing: Modeling Student Proficiency Using Graph Neural Network

Hiromi Nakagawa; Yusuke Iwasawa; Yutaka Matsuo

IEEE/WIC/ACM International Conference on Web Intelligence (WI '19), pp. 156–163

DOI: 10.1145/3350546.3352513

Knowledge Query Network for Knowledge Tracing: How Knowledge Interacts with Skills

Jinseok Lee; Dit-Yan Yeung

Proceedings of the 9th International Conference on Learning Analytics & Knowledge (LAK19), pp. 491–500

DOI: 10.1145/3303772.3303786

Knowledge Tracing with Sequential Key-Value Memory Networks

Ghodai Abdelrahman; Qing Wang

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '19), pp. 175–184

DOI: 10.1145/3331184.3331195

Addressing Two Problems in Deep Knowledge Tracing via Prediction-Consistent Regularization

Chun-Kit Yeung; Dit-Yan Yeung

Proceedings of the Fifth Annual ACM Conference on Learning at Scale (L@S 2018), pp. 1–10

DOI: 10.1145/3231644.3231647

Closing the Loop: Automated Data-Driven Cognitive Model Discoveries Lead to Improved Instruction and Learning Gains

Ran Liu; Kenneth R. Koedinger

Journal of Educational Data Mining, 9(1), pp. 25–41

DOI: 10.5281/zenodo.3554625

Dynamic Key-Value Memory Networks for Knowledge Tracing

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

Proceedings of the 26th International Conference on World Wide Web (WWW '17), pp. 765–774

DOI: 10.1145/3038912.3052580

How to make ‘more’ better? Principles for effective use of multiple representations to enhance students’ learning about fractions

Martina A. Rau; Percival G. Matthews

ZDM Mathematics Education, 49(4), 531–544

DOI: 10.1007/s11858-017-0846-8

Improving Sensor-Free Affect Detection Using Deep Learning

Anthony F. Botelho; Ryan S. Baker; Neil T. Heffernan

Artificial Intelligence in Education: 18th International Conference, AIED 2017, Wuhan, China, June 28 – July 1, 2017, Proceedings (Lecture Notes in Computer Science), pp. 40–51

DOI: 10.1007/978-3-319-61425-0_4

Incorporating Rich Features into Deep Knowledge Tracing

Liang Zhang; Xiaolu Xiong; Siyuan Zhao; Anthony Botelho; Neil T. Heffernan

Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale (L@S 2017), pp. 169–172

DOI: 10.1145/3051457.3053976

Going Deeper with Deep Knowledge Tracing

Xiaolu Xiong; Siyuan Zhao; Eric G. Van Inwegen; Joseph E. Beck

Proceedings of the 9th International Conference on Educational Data Mining (EDM 2016), pp. 545–550

How Deep is Knowledge Tracing?

Mohammad Khajah; Robert V. Lindsey; Michael C. Mozer

Proceedings of the 9th International Conference on Educational Data Mining (EDM 2016), pp. 94–101

When to Block versus Interleave Practice? Evidence Against Teaching Fraction Addition before Fraction Multiplication

Rony Patel; Ran Liu; Kenneth R. Koedinger

Proceedings of the 38th Annual Conference of the Cognitive Science Society (CogSci 2016), pp. 2069–2074

Deep Knowledge Tracing

Chris Piech; Jonathan Bassen; Jonathan Huang; Surya Ganguli; Mehran Sahami; Leonidas Guibas; Jascha Sohl-Dickstein

Advances in Neural Information Processing Systems 28 (NIPS 2015)

How Should Intelligent Tutoring Systems Sequence Multiple Graphical Representations of Fractions? A Multi-Methods Study

M. A. Rau; V. Aleven; N. Rummel; Z. Pardos

International Journal of Artificial Intelligence in Education 24(2), pp. 125–161

DOI: 10.1007/s40593-013-0011-7

Individualized Bayesian Knowledge Tracing Models

Michael V. Yudelson; Kenneth R. Koedinger; Geoffrey J. Gordon

Artificial Intelligence in Education: 16th International Conference, AIED 2013, Memphis, TN, USA, July 9–13, 2013, Proceedings (Lecture Notes in Computer Science 7926), pp. 171–180

DOI: 10.1007/978-3-642-39112-5_18

Automated Student Model Improvement

Kenneth R. Koedinger; Elizabeth A. McLaughlin; John C. Stamper

Proceedings of the 5th International Conference on Educational Data Mining (EDM 2012), pp. 17–24

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

Kenneth R. Koedinger; Albert T. Corbett; Charles Perfetti

Cognitive Science, 36(5), pp. 757–798

DOI: 10.1111/j.1551-6709.2012.01245.x

An integrated theory of whole number and fractions development

Robert S. Siegler; Clarissa A. Thompson; Michael Schneider

Cognitive Psychology 62(4), pp. 273–296

DOI: 10.1016/j.cogpsych.2011.03.001

How reform curricula in the USA and Korea present multiplication and division of fractions

Ji-Won Son; Sharon L. Senk

Educational Studies in Mathematics, 74(2), pp. 117–142

DOI: 10.1007/s10649-010-9229-6

Intelligent Tutoring Systems with Multiple Representations and Self-Explanation Prompts Support Learning of Fractions

Martina A. Rau; Vincent Aleven; Nikol Rummel

Proceedings of the 14th International Conference on Artificial Intelligence in Education (AIED 2009), Frontiers in Artificial Intelligence and Applications vol. 200, pp. 441–448, IOS Press

DOI: 10.3233/978-1-60750-028-5-441

Performance Factors Analysis: A New Alternative to Knowledge Tracing

Philip I. Pavlik Jr.; Hao Cen; Kenneth R. Koedinger

Artificial Intelligence in Education (AIED 2009), Frontiers in Artificial Intelligence and Applications, 200, pp. 531–538

The structure of students’ beliefs about the use of representations and their performance on the learning of fractions

Areti Panaoura; Athanasios Gagatsis; Eleni Deliyianni; Iliada Elia

Educational Psychology, 29(6), pp. 713–728

DOI: 10.1080/01443410903229437

An effective metacognitive strategy: learning by doing and explaining with a computer-based Cognitive Tutor

Vincent A.W.M.M. Aleven; Kenneth R. Koedinger

Cognitive Science 26(2), pp. 147–179

DOI: 10.1207/s15516709cog2602_1

Knowledge Tracing: Modeling the Acquisition of Procedural Knowledge

Albert T. Corbett; John R. Anderson

User Modeling and User-Adapted Interaction, 4(4), pp. 253–278

DOI: 10.1007/bf01099821

WikiSkill: Compiling Agent Experience into Persistent Knowledge for Skill Evolution

Liyan Tang; Cyrus Rashtchian; Chun-Sung Ferng; Andrew Tomkins; Da-Cheng Juan; Tu Vu

arXiv preprint arXiv:2608.27454v1

Applying science of learning in education: Infusing psychological science into the curriculum

Victor A. Benassi; Catherine E. Overson; Christopher M. Hakala

Society for the Teaching of Psychology, STP e-Books series (edited volume, ISBN 978-1-941804-29-2)