@inproceedings{7b3bccae01a8460299116bf2881a3d51,
title = "Raising Student Completion Rates with Adaptive Curriculum and Contextual Bandits",
abstract = "We present an adaptive learning Intelligent Tutoring System, which uses model-based reinforcement learning in the form of contextual bandits to assign learning activities to students. The model is trained on the trajectories of thousands of students in order to maximize their exercise completion rates and continues to learn online, automatically adjusting itself to new activities. A randomized controlled trial with students shows that our model leads to superior completion rates and significantly improved student engagement when compared to other approaches. Our approach is fully-automated unlocking new opportunities for learning experience personalization.",
keywords = "Contextual bandits, ITS, LinUCB, Personalized learning",
author = "Robert Belfer and Ekaterina Kochmar and Serban, {Iulian Vlad}",
year = "2022",
month = jul,
day = "27",
doi = "10.1007/978-3-031-11644-5_74",
language = "English",
isbn = "9783031116438",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "724--730",
editor = "Rodrigo, {Maria Mercedes} and Noburu Matsuda and Cristea, {Alexandra I.} and Vania Dimitrova",
booktitle = "Artificial Intelligence in Education - 23rd International Conference, AIED 2022, Proceedings",
note = "23rd International Conference on Artificial Intelligence in Education, AIED 2022 ; Conference date: 27-07-2022 Through 31-07-2022",
}