Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Liu, Tengwen | Bai, Yun | Li, Hao | Jiang, Shuai | Li, Qing*
Affiliations: Department of Foreign Languages, Cangzhou Normal University, Cangzhou, China
Correspondence: [*] Corresponding author: Qing Li, Department of Foreign Languages, Cangzhou Normal University, Cangzhou, China. E-mail: liqing_vip@outlook.com.
Abstract: With the continuous development and application of big data technology, its potential and value in the field of education are gradually emerging, especially in oral English teaching, big data is placed on high hopes. However, the research on how to effectively use big data to improve the efficiency of oral English teaching is still in its infancy. This study aims to fill this research gap and explore and analyze how oral English teaching strategies based on big data can improve teaching efficiency through in-depth literature review and empirical research. The results show that big data can help teachers assess students’ oral ability more accurately, and significantly improve students’ oral expression ability and learning efficiency by optimizing teaching strategies. However, oral English teaching strategies based on big data also have certain limitations, which need further research and improvement. This study provides a powerful theoretical basis and practical guidance for promoting the application of big data in oral English teaching.
Keywords: Big data, oral english teaching, teaching strategy, teaching efficiency, evaluation system
DOI: 10.3233/JCM-247493
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 4-5, pp. 2643-2656, 2024
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl