Research on Academic Prediction and Intervention From the Perspective of Educational Big Data

Research on Academic Prediction and Intervention From the Perspective of Educational Big Data

Xiaoming Du, Shilun Ge, Nianxin Wang
Copyright: © 2022 |Pages: 14
DOI: 10.4018/IJICTE.315763
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Abstract

In the context of education big data, it uses data mining and learning analysis technology to accurately predict and effectively intervene in learning. It is helpful to realize individualized teaching and individualized teaching. This research analyzes student life behavior data and learning behavior data. A model of student behavior characteristics is constructed, and a robust multi-task learning method is used to construct an academic prediction model. According to the prediction results, different intervention measures are taken for students with academic excellence and academic difficulties. Finally, it takes the one-semester blended teaching course of a certain university as an example. The research results show that in terms of predictive models, through the analysis of student behavior characteristics data, the model can accurately identify the learning status of students. In terms of intervention, it can play a positive role in promoting students with high learning and can effectively promote students with learning difficulties.
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Literature Review

Regarding the core question of “How to accurately predict students' academic performance and conduct prescription intervention?”, scholars have carried out research on behavior characteristics, model construction and timely intervention, and began to pay attention to the diversity and comprehensiveness of data types, and the real-time nature of academic performance prediction and intervention.

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