Research on the Data Analysis Scheme of Flexible And Personalized Curriculum Design of University Mathematics
Journal: Journal of Higher Education Research DOI: 10.32629/jher.v6i5.4587
Abstract
Flexible and personalized curriculum design can adjust teaching content in real time according to the learning situation feedback from students, which is crucial for promoting students' personalized curriculum development. Such design is highly dependent on the accurate grasp and dynamic response to students' learning situation. However, there are relatively few studies on flexible and personalized curriculum design schemes. Therefore, this paper constructs a set of schemes for learning situation collection, analysis, and flexible personalized curriculum design in university mathematics. It collects learning situation data from multiple scenarios, and after data cleaning, deduplication, and standardization, uses methods such as statistical analysis, knowledge graph, and machine learning to conduct learning situation analysis. Based on this, a flexible and personalized curriculum design scheme with hierarchical real-time adjustment is designed. In addition, this paper also provides rules and measures for the protection of students' private data. This study offers a feasible scheme for realizing precise and personalized teaching.
Keywords
learning situation data; data collection and analysis; flexible and personalized course design
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[5] Wu, G. J. Post-human condition and chinese educational practices: education's end or lifelong education? — Philosophical reflections on education in the age of artificial intelligence, Journal of East China Normal University(Educational Sciences), 2019, 37(01): 1-15+164.
[6] Yuan, J., Wu, F. The shift in the logic of knowledge production in the age of AI and educational responses, Chinese Journal of Distance Education, 2025, 45(07): 20-34.
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