Evaluation of Online Teaching Quality of Basic Education Based on Artificial Intelligence

Moyan Li, Yawen Su

Abstract


In the age of the Internet, basic education faces several new challenges: the lack of deep integration of artificial intelligence (AI), and the relatively poor quality of online teaching. To cope with these challenges, this paper designs an evaluation method for online teaching quality of basic education in the context of the AI. Firstly, the application of the AI in basic education was analyzed, and the promoting effect of online teaching on basic education was confirmed. On this basis, the entropy weight method and grey clustering analysis were introduced to evaluate the online teaching quality of basic ed-ucation. Based on the proposed model, several strategies were proposed to improve the quality of online teaching in basic education. The research re-sults provide a good reference for the application of online teaching and AI in basic education.

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Copyright (c) 2020 Moyan Li, Yawen Su


International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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