Work

Using Baidu Index Data to Explore the Spatiotemporal Characteristics of Public Concern towards Online English Learning

Year: 2024

Type: article

Abstract: This study examines the spatiotemporal dynamics of public interest in online English learning, particularly for young learners in China from June 2020 to June 2024 using Baidu Index data.Relevant keywords were selected and demographic filters were applied to focus on users aged 19+.The analysis revealed a surge in interest during the COVID-19 pandemic's early stages, followed by a decline.Eastern regions showed higher concern, and parents and educators were key contributors to search volumes.External factors, including policy changes and the pandemic, significantly influenced public sentiment.The findings underscore the dynamic nature of public concern and the need for educators and policymakers to adapt to these trends in shaping the future of online English education.

Source: International Journal of Education and Teaching

DOI: 10.51483/ijedt.4.2.2024.60-76

Authors: Hao Wang, Yi Xiao

Institution: Chongqing Three Gorges University

Language: English

Topic: English Language Learning and Teaching

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: bronze

Funders: Baidu, Szegedi Tudományegyetem