AI-Driven Interface Design for Intelligent Tutoring System Improves Student Engagement
This work addresses student engagement issues in educational technology, but it is incremental as it applies existing AI methods to interface design in a specific domain.
The paper tackled the problem of low student engagement in Intelligent Tutoring Systems (ITS) by exploring AI-driven interface designs, and found through A/B tests on over 20K students that these designs improved engagement factors by up to 25.13%.
An Intelligent Tutoring System (ITS) has been shown to improve students' learning outcomes by providing a personalized curriculum that addresses individual needs of every student. However, despite the effectiveness and efficiency that ITS brings to students' learning process, most of the studies in ITS research have conducted less effort to design the interface of ITS that promotes students' interest in learning, motivation and engagement by making better use of AI features. In this paper, we explore AI-driven design for the interface of ITS describing diagnostic feedback for students' problem-solving process and investigate its impacts on their engagement. We propose several interface designs powered by different AI components and empirically evaluate their impacts on student engagement through Santa, an active mobile ITS. Controlled A/B tests conducted on more than 20K students in the wild show that AI-driven interface design improves the factors of engagement by up to 25.13%.