A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM
This addresses the challenge of providing scalable, personalized online learning for STEM students, though it appears incremental as it builds on existing ITS concepts with a focus on scalability and mixed interfaces.
The authors tackled the problem of scaling personalized STEM education by developing Korbit, a large-scale, open-domain, mixed-interface dialogue-based intelligent tutoring system, which improved student learning outcomes and motivation compared to typical online courses, as shown by A/B testing with real-world students.
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.