Effective Learning Behavior of Students’ Internet Based on Data Mining

Yang, Jixiang

doi:10.1109/icbaie52039.2021.9390049

Cited by 6 publications

(1 citation statement)

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“…Data mining aims to uncover patterns and other valuable information by sorting through large data sets [12]. As a discipline of computer science, its techniques include statistics, online analysis processing, intelligence retrieval, machine learning, expert system, and pattern recognition [13,14]. Typical data mining methods include decision tree, artificial neural network (ANN), support vector machine (SVM), and naive Bayes classifier.…”

Section: Data Miningmentioning

confidence: 99%

Learning Behavior Based on Data Mining Technology

Wang

Zhang

Guan

2022

Security and Communication Networks

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With the release of the Education Informatization 2.0 Action Plan and the rapid development of learning analysis technology, educational data mining becomes a new research direction. Data mining can improve teachers’ teaching methods and students’ learning skills by acquiring information hidden in the educational data. Based on the learning behavior data of college students, this paper uses BP neural network, a data mining method, to predict their comprehensive evaluation results. The results show that there is a close relationship between students’ learning behavior and their comprehensive scores. In addition, models of naive Bayes, logistic regression, and decision tree are established for verification and comparison. Compared with other models, BP neural network model has higher prediction accuracy and better performance. It can serve as an important basis to improve students’ learning methods and teachers’ teaching methods.

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Section: Data Miningmentioning

confidence: 99%