A Solution to Improve Productivity for Remote Students and E-Learners

Autor: Wenlin Zhang, Xueting Ren, Guolu Yin, Wenlong Yu, Jin Xie
Rok vydání: 2021
Předmět:
Zdroj: 2021 the 6th International Conference on Distance Education and Learning.
DOI: 10.1145/3474995.3475023
Popis: The background of "improving productivity for remote workers and students" is based on a worldwide survey conducted by AACSB. 79% of schools have suspended face-to-face activities (that is, for all students) and converted all face-to-face courses to online or other platforms. Only 21% of schools only convert courses involving students affected by travel restrictions into online education. In the face of COVID-19's failure to start school normally, the school's evolving online teaching and the decline in learning efficiency, the author decided to provide a solution for students who want to make breakthroughs in self-study, as well as teachers and remote workers who need feedback in online live broadcast Solution-Develop a plug-in that can help students and teachers improve the efficiency of learning online courses. The currently selected basic functions are human face concentration recognition and monitoring, scientific learning models based on multiple learning methods such as the Pomodoro Technique and Ebbinghaus curve, web page locking, personalized anthropomorphic AI companion reading growth reward mechanism, real-time note centre and so on.
Databáze: OpenAIRE