Optimization measures for students' autonomous learning based on deep learning and human-computer interaction technology

被引：0

作者：

Chen, Yi ^{[1
]}

Lin, Xiaopin ^{[2
]}

Li, Zheng ^{[3
]}

机构：

[1] Hubei Polytech Univ, Sch Econ & Management, Huangshi, Hubei, Peoples R China

[2] Zhejiang Prov Hangzhou 14 High Sch, Hangzhou, Zhejiang, Peoples R China

[3] Shanghai Lida Univ, Coll Finance & Econ, Shanghai 200000, Peoples R China

来源：

JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING | 2024年 / 24卷 / 4-5期

关键词：

Micro-video design; human-computer interaction; teaching experiment; autonomous learning ability; knowledge test; MICRO;

D O I：

10.3233/JCM-247554

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In order to effectively improve students' learning outcomes and teachers' teaching quality, this paper explores an optimization measure for students' autonomous learning based on deep learning and Human-Computer Interaction (HCI) technology. Our proposed optimization measure constructs an interactive micro-video teaching model from teaching resources, teaching process, and teaching evaluation perspectives. The experimental results demonstrate that our proposed optimization measure can effectively improve students' learning outcomes and satisfaction while enhancing their autonomous learning abilities and learning motivations.

引用

页码：3079 / 3091

页数：13

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