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Multimodal Teaching Strategies of College English Based on Big Data Technology

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  • Linke Guo

    (Zhengzhou Sias University, China)

Abstract

With the rapid development of educational informatization, college English teaching is changing from traditional single mode to multi-mode teaching. However, there are difficulties in the evaluation of teaching effect and the optimization of teaching strategies in multimodal teaching. This study focuses on the application of big data technology in college English multimodal teaching, constructs a three-dimensional teaching model of “data-resources-interaction” and puts forward three research hypotheses. Through a semester-long comparative experiment, taking two parallel classes in a university as samples, we collected and analyzed students' learning behavior, test scores and teacher evaluation data. The empirical results show that data-supported multimodal resource adaptation, real-time feedback mechanism and teaching management optimization have significantly improved the teaching effect.

Suggested Citation

  • Linke Guo, 2025. "Multimodal Teaching Strategies of College English Based on Big Data Technology," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), IGI Global Scientific Publishing, vol. 20(1), pages 1-18, January.
    • Handle: RePEc:igg:jwltt0:v:20:y:2025:i:1:p:1-18
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    References listed on IDEAS

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    1. Hyun Suk Lee & Junga Lee, 2021. "Applying Artificial Intelligence in Physical Education and Future Perspectives," Sustainability, MDPI, vol. 13(1), pages 1-16, January.
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