Research and Development

Item Response Theory


Fundamentals of Item Response Theory by Ronald K. Hambleton, Hariharan Swaminathan and H. Jane Rogers, The Theory and Practice of Item Response Theory by Rafael J. de Ayala, Item Response Theory for Psychologists by Susan E. Embretson and Steven P. Reise, Handbook of Modern Item Response Theory edited by Wim J. van der Linden and Ronald K. Hambleton, Applications of Item Response Theory to Practical Testing Problems by Frederic M. Lord and Item Response Theory: Principles and Applications by Ronald K. Hambleton and Hariharan Swaminathan.


Multidimensional Item Response Theory by Mark D. Reckase and A Basis for Multidimensional Item Response Theory by Roderick P. McDonald.

Conjunction and Disjunction

Conjunctive and Disjunctive Item Response Functions by Frederic M. Lord and Models for Locally Dependent Responses: Conjunctive Item Response Theory by Robert J. Jannarone.


Polytomous Item Response Theory Models by Remo Ostini and Michael L. Nering and Handbook of Polytomous Item Response Theory Models edited by Michael L. Nering and Remo Ostini.


Chronometric Analysis of Intelligence by Arthur R. Jensen, Use of Response Time for Measuring Cognitive Ability by Patrick Kyllonen and Jiyun Zu, Timed Testing: An Approach Using Item Response Theory by David Thissen, Models for Speed and Time-limit Tests by Edward E. Roskam, Development and Calibration of an Item Response Model that Incorporates Response Time by Tianyou Wang and Bradley A. Hanson, A Hierarchical Framework for Modeling Speed and Accuracy on Test Items by Wim J. van der Linden and Conceptual Issues in Response‐time Modeling by Wim J. van der Linden.

Intelligent Tutoring Systems

Item Reponse Theory in Intelligent Tutoring Systems by Lieuwe Rekker.

Knowledge Tracing

Knowledge Tracing: Modeling the Acquisition of Procedural Knowledge by Albert T. Corbett and John R. Anderson, Individualized Bayesian Knowledge Tracing Models by Michael V. Yudelson, Kenneth R. Koedinger and Geoffrey J. Gordon, Using Item Response Theory to Refine Knowledge Tracing by Yanbo Xu and Jack Mostow, Integrating Knowledge Tracing and Item Response Theory: A Tale of Two Frameworks by Mohammad M. Khajah, Yun Huang, José P. González-Brenes, Michael C. Mozer and Peter Brusilovsky, Deep Knowledge Tracing by Chris Piech, Jonathan Bassen, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas J. Guibas and Jascha Sohl-Dickstein and Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory by Chun-Kit Yeung.

Student Modeling

Computational Modeling of Cognition and Behavior by Simon Farrell and Stephan Lewandowsky, A Review of Recent Advances in Learner and Skill Modeling in Intelligent Learning Environments by Michel C. Desmarais and Ryan S. Baker, Student Modeling Approaches: A Literature Review for the Last Decade by Konstantina Chrysafiadi and Maria Virvou, A Machine Learning Approach for Automatic Student Model Discovery by Nan Li, William W. Cohen, Kenneth R. Koedinger and Noboru Matsuda, Cognitive Psychology Meets Psychometric Theory: On the Relation between Process Models for Decision Making and Latent Variable Models for Individual Differences by Han L. J. van der Maas, Dylan Molenaar, Gunter Maris, Rogier A. Kievit and Denny Borsboom, Automated Student Model Improvement by Kenneth R. Koedinger, Elizabeth A. McLaughlin and John C. Stamper, Dynamic Cognitive Tracing: Towards Unified Discovery of Student and Cognitive Models by José P. González-Brenes and Jack Mostow, General and Efficient Cognitive Model Discovery Using a Simulated Student by Nan Li, Eliane Stampfer, William Cohen and Kenneth Koedinger and A Brief Overview of Metrics for Evaluation of Student Models by Radek Pelánek.

Item Generation and Evaluation

Automatic Item Generation: Theory and Practice edited by Mark J. Gierl and Thomas M. Haladyna, Algorithmic Exam Generation by Omer Geiger and Shaul Markovitch, Personalized Curriculum Sequencing Utilizing Modified Item Response Theory for Web-based Instruction by Chih-Ming Chen, Chao-Yu Liu and Mei-Hui Chang, Testing the Test: Item Response Curves and Test Quality by Gary A. Morris, Lee Branum-Martin, Nathan Harshman, Stephen D. Baker, Eric Mazur, Suvendra Dutta, Taha Mzoughi and Veronica McCauley and Construction and Analysis of Educational Tests Using Abductive Machine Learning by El-Sayed M. El-Alfy and Radwan E. Abdel-Aal.

Machine Learning

Analysis of Instance Hardness in Machine Learning Using Item Response Theory by Ricardo B. C. Prudêncio, José Hernández-Orallo and Adolfo Martınez-Usó, Making Sense of Item Response Theory in Machine Learning by Fernando Martínez-Plumed, Ricardo B. C. Prudêncio, Adolfo Martínez-Usó and José Hernández-Orallo, Item Response Theory in AI: Analysing Machine Learning Classifiers at the Instance Level by Fernando Martínez-Plumed, Ricardo B. C. Prudêncio, Adolfo Martínez-Usó and José Hernández-Orallo, Understanding Deep Learning Performance through an Examination of Test Set Difficulty: A Psychometric Case Study by John P. Lalor, Hao Wu, Tsendsuren Munkhdalai and Hong Yu, Comparing Human and DNN-ensemble Response Patterns for Item Response Theory Model Fitting by John P. Lalor, Hao Wu and Hong Yu and Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds by John P. Lalor, Hao Wu and Hong Yu.