STEMM Institute Press
Science, Technology, Engineering, Management and Medicine
Research on Big Data-driven Personalized Teaching Models in Higher Education
DOI: https://doi.org/10.62517/jbdc.202401404
Author(s)
Xinyi Wu*, Xinjiu Xie, Huiling Mo
Affiliation(s)
Guangzhou College of Commerce, Guangzhou, Guangdong, China *Corresponding Author.
Abstract
Personalized teaching mode has become an important direction of education reform as an effective way to enhance students' learning effect and interest. This study aims to explore how to support personalized teaching through big data technology to enhance students' independent learning ability and learning interest. Through the analysis and mining of students' learning data, combined with the intelligent learning system, the study demonstrates how to customize learning paths and teaching resources according to students' individual needs. The study shows that personalized teaching based on big data can effectively improve the teaching effect and promote the personalization and autonomy of students' learning. The study conclusions show that the big data-driven personalized teaching model provides new ideas and solutions for the future development of higher education.
Keywords
Personalized Instruction; Learning Resources; Big Data; Teacher Competence
References
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