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

Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung D. Vu, Robert Belfer, Joelle Pineau, Aaron Couville, Laurent Charlin, Yoshua Bengio

Research output: Contribution to conferencePaperpeer-review

4 Citations (SciVal)


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.
Original languageEnglish
Publication statusPublished - 6 Jul 2020
EventAIED 2020: The 2020 conference on Artificial Intelligence in Education - Virtual, Ifrane, Morocco
Duration: 6 Jul 202010 Jul 2020


ConferenceAIED 2020
Abbreviated titleAIED 2020
Internet address


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