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

Accepted version
Peer-reviewed

Type

Conference Object

Change log

Authors

Serban, IV 
Gupta, V 
Kochmar, E 
Vu, DD 
Belfer, R 

Abstract

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 widerange 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 on machine learning, and since then 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.

Description

Keywords

Intelligent tutoring system, Dialogue-based tutoring system, Natural language processing, Reinforcement learning, Deep learning, Personalized, Interactive learning, Data science, STEM

Journal Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Conference Name

Journal ISSN

0302-9743
1611-3349

Volume Title

12164 LNAI

Publisher

Springer International Publishing

Rights

All rights reserved