OATutor: An Open-source Adaptive Tutoring System and Curated Content Library for Learning Sciences Research

被引:11
|
作者
Pardos, Zachary A. [1 ]
Tang, Matthew [2 ]
Anastasopoulos, Ioannis [1 ]
Sheel, Shreya K. [1 ]
Zhang, Ethan [2 ]
机构
[1] Univ Calif Berkeley, Sch Educ, Berkeley, CA 94720 USA
[2] Univ Calif Berkeley, EECS, Berkeley, CA USA
关键词
Adaptive learning; intelligent tutoring systems; open source; OER; content authoring; research through design; replicable research; COGNITIVE TUTOR; PLATFORM;
D O I
10.1145/3544548.3581574
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Despite decades long establishment of effective tutoring principles, no adaptive tutoring system has been developed and open-sourced to the research community. The absence of such a system inhibits researchers from replicating adaptive learning studies and extending and experimenting with various tutoring system design directions. For this reason, adaptive learning research is primarily conducted on a small number of proprietary platforms. In this work, we aim to democratize adaptive learning research with the introduction of the first open-source adaptive tutoring system based on Intelligent Tutoring System principles. The system, we call Open Adaptive Tutor (OATutor), has been iteratively developed over three years with field trials in classrooms drawing feedback from students, teachers, and researchers. The MIT-licensed source code includes three creative commons (CC BY) textbooks worth of algebra problems, with tutoring supports authored by the OATutor project. Knowledge Tracing, an A/B testing framework, and LTI support are included.
引用
收藏
页数:17
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