M. Nguyen, S. Tschiatschek, and A. Singla. Proceedings of the 17th International Conference on Educational Data Mining, page 341--348. Atlanta, Georgia, USA, International Educational Data Mining Society, (July 2024)
M. Demirtas, M. Fowler, and K. Cunningham. Proceedings of the 17th International Conference on Educational Data Mining, page 53--67. Atlanta, Georgia, USA, International Educational Data Mining Society, (July 2024)
D. Shchepakin, S. Sankaranarayanan, and D. Zimmaro. Proceedings of the 17th International Conference on Educational Data Mining, page 18--29. Atlanta, Georgia, USA, International Educational Data Mining Society, (July 2024)
S. Zhao, and S. Sahebi. Proceedings of the 17th International Conference on Educational Data Mining, page 927--932. Atlanta, Georgia, USA, International Educational Data Mining Society, (July 2024)
G. Zhou, T. Umada, and S. D\textquotesingleMello. Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, page 295-305. ACM, (2022)User tracing provide evidence of learning, but scalar parameters are better than sequences.
A. Emerson, M. Geden, A. Smith, E. Wiebe, B. Mott, K. Boyer, and J. Lester. Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization, page 62-70. ACM, (July 2020)Mini-language Prime, block-based environment, about 20 problems on the Web. Could predict performance in any order..
K. Rivers, E. Harpstead, and K. Koedinger. Proceedings of the 2016 ACM Conference on International Computing Education Research - ICER \textquotesingle16, ACM Press, (2016)
J. Zhang, X. Shi, I. King, and D. Yeung. Proceedings of the 26th International Conference on World Wide Web, page 765--774. Republic and Canton of Geneva, Switzerland, International World Wide Web Conferences Steering Committee, (2017)
K. Rivers, E. Harpstead, and K. Koedinger. Proceedings of the 2016 ACM Conference on International Computing Education Research, page 143--151. New York, NY, USA, ACM, (2016)