Study on Student-centered artificial intelligence online teaching + home learning model during the COVID-19 epidemic

Abstract

With the rapid development of Internet technology, traditional online learning can no longer meet the adaptive learning needs of students, and smart education concepts, such as mushrooms, use data generated by traditional platforms to use machine learning and depth. Artificial intelligence technology with learning as a means has gradually become a new research hotspot through re-analysis technology. How to further use these big data resources for adaptive learning and push to improve the quality of student training has become an important issue in the current research field. For the protection of students' learning during the COVID-19 epidemic prevention and control, national universities, primary schools and secondary schools solved the problem of “Classes Suspended but Learning Continue” through online teaching. Students learn online at home and the family plays a vital role as a special classroom. Based on the analysis of the factors affecting home study, this article compares the live broadcast platforms and constructs a student-centered network broadcast + home learning model under the epidemic situation. After the implementation effect investigation, the evaluation effect is good. It is hoped that this model can provide a reference for teachers and students in the new situation and solve some problems currently facing online teaching at home.

Keywords

• COVID-19
• Network Broadcast Teaching
• Home Study