Study on Accurate Early Warning and Intervention Model for Online Learning based on Multi-source Heterogeneous Data Fusion

10.6919/ICJE.202205_8(5).0038

Qianqian Ge；Cuncun Wei；Dongyan Wu

Multi-source Heterogeneous ； Data Fusion ； Online Learning ； Accurate Warning

International Core Journal of Engineering

8卷5期（2022 / 05 / 01）

312 - 315

英文

This paper proposes a precise early warning and intervention model for online learning based on multi-source data fusion. The model tracks and records students' multidisciplinary learning process data, analyzes learning characteristics using data mining methods, and makes quantifiable predictions about learning development, thus realizing personalized and accurate teaching services for the whole learning process data, facilitating analysis of the hidden learning trajectory behind the data, and effectively guiding personalized learning for personalized teaching and student management.

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