Big Data Methodology and Teaching Innovation of English Writing

Liuchun Wen

2022

Abstract

In the context of the era of big data, higher vocational English writing courses should make full use of Internet technology and massive information data to build a new teaching model in terms of teaching concepts, teaching forms, teaching resources, and teaching evaluation. Employing big data methodology and statistics analysis, this paper explores the English compositions with the same topic for millions of students in 2016. The adopted instruments include SPSS software, Matlab, SAS, Python software. Different graphs, pictures and tables show the situation of students’ participating in the competition in each area, modification and score change of students’ writing, and dimensional changes of students’ writing. The study shows that the continuous development of information technology provides new auxiliary means and tools for writing teaching. Big data brings opportunities and challenges to traditional English writing teaching.

Paper Citation

in Harvard Style

Wen L. (2022). Big Data Methodology and Teaching Innovation of English Writing. In Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME; ISBN 978-989-758-630-9, SciTePress, pages 256-260. DOI: 10.5220/0011909900003613

in Bibtex Style

@conference{nmdme22,
author={Liuchun Wen},
title={Big Data Methodology and Teaching Innovation of English Writing},
booktitle={Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME},
year={2022},
pages={256-260},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011909900003613},
isbn={978-989-758-630-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME
TI - Big Data Methodology and Teaching Innovation of English Writing
SN - 978-989-758-630-9
AU - Wen L.
PY - 2022
SP - 256
EP - 260
DO - 10.5220/0011909900003613
PB - SciTePress