EEG Technology Interface: Synchronous Online Education Assistance System

Online Education is widely used in schools and institutions due to its convenience. However, during online classes, students may lack access to instant feedback that solves their confusion, and their instructors may face difficulty in judging students' learning status to determine their level of comprehension. To realize remote real-time detection of student's learning status and improve study efficiency, this paper proposes an online education assistance system based on single-channel EEG. In this system, recorded EEG data will be upheld into a prediction model based on the Optimizable Ensemble Model, and the predicted results will be transformed into the MYSQL database. This database will provide real-time data on a developed web page. On the web page, instructors can identify students' confusion status and attention level to provide instant learning assistance, which solves students' confusion.