Publications

Journal Papers

  1. Matayoshi, J., Karumbaiah, S. (2024) Analyzing transitions in sequential data with marginal models. Journal of Educational Data Mining 16 (1), 197-232. [PDF] [Code]
  2. Matayoshi, J., Uzun, H. (2022) Learning, forgetting, and the correlation of knowledge in knowledge space theory. Journal of Mathematical Psychology 109. [Preprint PDF] [Link]
  3. Matayoshi, J. (2021) Approximately counting and sampling knowledge states. British Journal of Mathematical and Statistical Psychology 75 (2), 293-318. [Preprint PDF] [Code] [Link]
  4. Matayoshi, J., Cosyn, E., Uzun, H. (2021) Are we there yet? Evaluating the effectiveness of a recurrent neural network-based stopping algorithm for an adaptive assessment. International Journal of Artificial Intelligence in Education 31 (2), 304-336. [Preprint PDF] [Link]
  5. Cosyn, E., Uzun, H., Doble, C., Matayoshi, J. (2021) A practical perspective on knowledge space theory: ALEKS and its data. Journal of Mathematical Psychology 101. [Preprint PDF] [Link]
  6. Matayoshi, J., Karumbaiah, S. (2020) Adjusting the L statistic when self-transitions are excluded in affect dynamics. Journal of Educational Data Mining 12 (4), 1-23. [PDF] [Code]
  7. Matayoshi, J. (2020) Well-graded families and the union-closed sets conjecture. The Electronic Journal of Combinatorics 27 (1), P1.64 [PDF] [Code]
  8. Doble, C., Matayoshi, J., Cosyn, E., Uzun, H., Karami, A. (2019) A data-based simulation study of reliability for an adaptive assessment based on knowledge space theory. International Journal of Artificial Intelligence in Education 29 (2), 258-282. [Preprint PDF] [Link] [Shared Link]
  9. Matayoshi, J. (2017) On the properties of well-graded partially union-closed families. Journal of Mathematical Psychology 80, 15-21. [Preprint PDF] [Link]
  10. Matayoshi, J. (2013) An application of random polynomials to wireless communications. Neural, Parallel, and Scientific Computations 21, 173-184. [PDF]
  11. Matayoshi, J. (2012) The K-level crossings of a random algebraic polynomial with dependent coefficients. Statistics and Probability Letters 82 (1), 203-211. [Preprint PDF] [Link]
  12. Matayoshi, J. (2012) The real zeros of a random algebraic polynomial with dependent coefficients. Rocky Mountain Journal of Mathematics 42 (3), 1015-1034. [PDF]

Peer-Reviewed Conference Papers

  1. Matayoshi, J., Cosyn, E., Lechuga, C., Uzun, H. (2024) An evaluation of a placement assessment for an adaptive learning system. Proceedings of the 17th International Conference on Educational Data Mining, 594-601. [PDF]
  2. Matayoshi, J., Uzun, H., Cosyn, E. (2023) Analyzing response times and answer feedback tags in an adaptive assessment. International Conference on Artificial Intelligence in Education, AIED 2023, 296-301. [Preprint PDF] [Link]
  3. Matayoshi, J., Uzun, H., Cosyn, E. (2022) Using a randomized experiment to compare the performance of two adaptive assessment engines. Proceedings of the 15th International Conference on Educational Data Mining, 821-827. [PDF]
  4. Matayoshi, J., Cosyn, E., Uzun, H. (2022) Does practice make perfect? Analyzing the relationship between higher mastery and forgetting in an adaptive learning system. Proceedings of the 15th International Conference on Educational Data Mining, 316-324. [PDF]
  5. Matayoshi, J., Karumbaiah, S. (2021) Investigating the validity of methods used to adjust for multiple comparisons in educational data mining. Proceedings of the 14th International Conference on Educational Data Mining, 33-45. [PDF] [Code]
  6. Matayoshi, J., Cosyn, E., Uzun, H. (2021) Evaluating the impact of research-based updates to an adaptive assessment. International Conference on Artificial Intelligence in Education, AIED 2021, 451-456. [Preprint PDF] [Link]
  7. Cunningham, J., Mukhopadhyay, R., Jain, R., Matayoshi, J., Cosyn, E., Uzun, H. (2021) Identifying at-risk calculus students before course start. International Conference on Artificial Intelligence in Education, AIED 2021, 124-128. [Preprint PDF] [Link]
  8. Matayoshi, J., Karumbaiah, S. (2021) Using marginal models to adjust for statistical bias in the analysis of state transitions. Proceedings of the 11th International Conference on Learning Analytics and Knowledge, 449-455. [Preprint PDF] [Code] [Link]
  9. Matayoshi, J., Uzun, H., Cosyn, E. (2020) Studying retrieval practice in an intelligent tutoring system. Proceedings of the Seventh ACM Conference on Learning @ Scale, 51-62. [Preprint PDF] [Link] Best Paper Award Co-Winner
  10. Matayoshi, J., Uzun, H., Cosyn, E. (2019) Deep (un)learning: Using neural networks to model retention and forgetting in an adaptive learning system. 20th International Conference on Artificial Intelligence in Education, AIED 2019, 258-269. [Preprint PDF] [Link]
  11. Matayoshi, J., Cosyn, E., Uzun, H. (2019) Using recurrent neural networks to build a stopping algorithm for an adaptive assessment. 20th International Conference on Artificial Intelligence in Education, AIED 2019, 179-184. [Preprint PDF] [Link]
  12. Matayoshi, J., Cosyn, E. (2018) Identifying student learning patterns with semi-supervised machine learning models. Proceedings of the 26th International Conference on Computers in Education, C1: ICCE Sub-Conference on Artificial Intelligence in Education/Intelligent Tutoring Systems (AIED/ITS) and Adaptive Learning, 11-20. [PDF]
  13. Matayoshi, J., Granziol, U., Doble, C., Uzun, H., Cosyn, E. (2018) Forgetting curves and testing effect in an adaptive learning and assessment system. Proceedings of the 11th International Conference on Educational Data Mining, 607-612. [PDF]

Peer-Reviewed Workshop Papers

  1. Matayoshi, J., Cosyn, E., Uzun, H., Kurd-Misto, E. (2024) Going for the gold (standard): Validating a quasi-experimental study with a randomized experiment comparing mastery learning thresholds. Workshop on Causal Inference in Educational Data Mining, EDM 2024. [PDF]
  2. Matayoshi, J., Lechuga, C. (2020) Automated matching of ITS problems with textbook content. Proceedings of the Second Workshop on Intelligent Textbooks, 21st International Conference on Artificial Intelligence in Education, AIED 2020. [PDF] [Code]

Workshop Demos

  1. Lechuga, C., Matayoshi, J. (2020) An alternative to intelligent textbooks with ALEKS. Proceedings of the Second Workshop on Intelligent Textbooks, 21st International Conference on Artificial Intelligence in Education, AIED 2020. [Demo]

Patents/Patent Applications

  1. Matayoshi, J., Cosyn, E. (2024) Neural Network-Based Assessment Engine for the Determination of a Knowledge State. U.S. Patent Appl. No. 18/536,844. [PDF]
  2. Cosyn, E., Matayoshi, J. (2020) Negative learning behavior alert system. U.S. Patent No. 10,713,965. [PDF] [Link]

Dissertations

  1. Matayoshi, J. (2009) On the zeros of random polynomials. Doctoral Dissertation. University of California, Irvine. [PDF]