Publicaciones

Selección de referencias recientes sobre ALEKS y la Teoría de los espacios del conocimiento

C. Lechuga, S. Doroudi. Three Algorithms for Grouping Students: A Bridge Between Personalized Tutoring System Data and Classroom Pedagogy. International Journal of Artificial Intelligence in Education, 2022.

J. Matayoshi, H. Uzun. Learning, forgetting, and the correlation of knowledge in knowledge space theory. Journal of Mathematical Psychology, Volume 109, 2022.

J. Matayoshi, E. Cosyn, H. Uzun. 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 (pp. 316-324). Durham, United Kingdom, 2022.

E. Cosyn, H. Uzun, C. Doble, & J. Matayoshi. A practical perspective on knowledge space theory: ALEKS and its data. Journal of Mathematical Psychology, Volume 101, 2021. 

J. Matayoshi, E. Cosyn, & H. Uzun. 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, 2021.

J. Matayoshi, C. Lechuga. 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.

J. Matayoshi, H. Uzun, & E. Cosyn. Studying Retrieval Practice in an Intelligent Tutoring System. Proceedings of the 7th ACM Conference on Learning at Scale (pp. 51-62). 2020.

J. Matayoshi, H. Uzun, & E. Cosyn. Deep (Un)Learning: Using Neural Networks to Model Retention and Forgetting in an Adaptive Learning System. Proceedings of the 20th International Conference on Artificial Intelligence in Education (pp. 258-569). Chicago, IL, 2019.

J. Matayoshi, E. Cosyn, & H. Uzun. Using Recurrent Neural Networks to Build a Stopping Algorithm for an Adaptive Assessment. Proceedings of the 20th International Conference on Artificial Intelligence in Education (pp. 179-184). Chicago, IL, 2019.

C. Doble, J. Matayoshi, E. Cosyn, H. Uzun, & A. Karami. 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, 2019.

J. Matayoshi & E. Cosyn. Identifying Student Learning Patterns with Semi-Supervised Machine Learning Models. Proceedings of the 26th International Conference on Computers in Education (pp. 11-20). Manila, Filipinas, 2018.

J. Matayoshi, U. Granziol, C. Doble, H. Uzun, & E. Cosyn. Forgetting curves and testing effect in an adaptive learning and assessment system. Proceedings of the 11th International Conference on Educational Data Mining (pp. 607-612). Búfalo, NY, 2018.

J. Doignon & J.-C. Falmagne. Knowledge spaces and learning spaces. In Batchelder et al. (Eds.), New Handbook of Mathematical Psychology (pp. 274-321). Cambridge University Press, 2016.

J.-C. Falmagne, D. Albert, C. Doble, D. Eppstein, & X. Hu (Eds). Knowledge Spaces: Applications in Education. Springer-Verlag, 2013.

J.-C. Falmagne & J.-P. Doignon. Learning Spaces. Springer-Verlag, 2011.