A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM

• Published in: Artificial Intelligence in Education Vol. 12164; pp. 387 - 392
• Main Authors: Serban, Iulian Vlad, Gupta, Varun, Kochmar, Ekaterina, Vu, Dung D., Belfer, Robert, Pineau, Joelle, Courville, Aaron, Charlin, Laurent, Bengio, Yoshua
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 01.01.2020; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Data science; Deep learning; Dialogue-based tutoring system; Intelligent tutoring system; Interactive learning; Natural language processing; Personalized; Reinforcement learning; STEM
• ISBN: 3030522393; 9783030522391
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-52240-7_70

We present Korbit, a large-scale, open-domain, mixed-interface, dialogue-based intelligent tutoring system (ITS). Korbit uses machine learning, natural language processing and reinforcement learning to provide interactive, personalized learning online. Korbit has been designed to easily scale to thousands of subjects, by automating, standardizing and simplifying the content creation process. Unlike other ITS, a teacher can develop new learning modules for Korbit in a matter of hours. To facilitate learning across a wide range of STEM subjects, Korbit uses a mixed-interface, which includes videos, interactive dialogue-based exercises, question-answering, conceptual diagrams, mathematical exercises and gamification elements. Korbit has been built to scale to millions of students, by utilizing a state-of-the-art cloud-based micro-service architecture. Korbit launched its first course in 2019 and has over 7, 000 students have enrolled. Although Korbit was designed to be open-domain and highly scalable, A/B testing experiments with real-world students demonstrate that both student learning outcomes and student motivation are substantially improved compared to typical online courses.