Deep learning in online education, a perspective of data modeling and algorithm analysis

Enze Yuan

doi:10.1117/12.2672688

28 March 2023 Deep learning in online education, a perspective of data modeling and algorithm analysis

Enze Yuan

Proceedings Volume 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022); 1259738 (2023) https://doi.org/10.1117/12.2672688
Event: Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 2022, Nanjing, China

Abstract

Nowadays, deep learning has been regarded as a key factor to determine education by researchers. Numerous studies have revealed that, when a student does deep learn rather than learning superficially, they tended to remember that knowledge for a longer time and had better mastery of knowledge. Deep learning has already somewhat applied to different stages of education. Thus, several experiments are used to illustrate how deep learning affected the quality of teaching. Through those experiments, it can be seen that the overall level of deep learning of students is at a medium level, but an individual typically varies widely from another one. Also, deep learning has a positive relationship with the quality of teaching. Moreover, deep learning model can be applied to the automatic classification of 4MAT questions. The purpose of this paper is to illustrate how deep learning affects online education, mainly from the perspective of data modeling and algorithm analysis.

Citation Download Citation

Enze Yuan "Deep learning in online education, a perspective of data modeling and algorithm analysis", Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 1259738 (28 March 2023); https://doi.org/10.1117/12.2672688

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