Research on the Construction of Teaching Mode Based on Big Data

DOI: https://doi.org/10.62517/jhet.202415637

Author(s)

Kun Liu, Wenjuan Shao, Fangyuan He

Affiliation(s)

College of Applied Science and Technology, Beijing Union University, Beijing, China

Abstract

With the rapid development of big data technology, data resources in the field of education are constantly enriched, which provides a new opportunity for the improvement and optimization of teaching mode. Based on big data technology, this paper constructs a data-driven refined teaching mode by analyzing the laws of teaching activities and learners' cognitive behavior. Firstly, the framework of introducing big data into the teaching mode is analyzed. The four key steps of big data application in education are elaborated: data collection, data cleaning and preprocessing, feature extraction and data analysis, and model construction and optimization. Then how to use big data for teaching activities is analyzed. Finally, from three aspects: the construction of adaptive learning system, personalized feedback and support, and dynamic classroom activity design, how to build an innovative teaching model through big data is discussed in detail. The model aims to improve the quality of teaching, provide personalized services for learners, and help them get targeted support, so as to maximize the learning effect.

Keywords

Big Data; Teaching Mode; Personalized Service; Classroom Activities

References

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