preprints.org > computer science and mathematics > artificial intelligence and machine learning > doi: 10.20944/preprints202408.1887.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 25 August 2024 / Approved: 26 August 2024 / Online: 27 August 2024 (00:34:19 CEST)

Traditional classroom teaching model can no longer meet the needs of students' ability development. As a new model actively advocated in the modern education concept, personalized teaching focuses on the development needs of students and emphasizes respect for students' individualized growth. In this work, we utilize deep learning method to recommend teaching strategies for different features of students. Specifically, the proposed method includes the construction of a multi-layer neural network model, which can analyze students' multi-dimensional learning data and behavior patterns, so as to recommend the most suitable teaching strategies for individual students. Through data collection and preprocessing, model architecture design, model training and optimization, the model gradually improves the accuracy of prediction and recommendation. Experimental analysis verifies the effectiveness of the model through field teaching experiments, and the results show that the personalized teaching strategy based on deep learning can significantly improve the learning effect and participation of students.

Personalized Teaching; Strategies Selection; Deep Learning; Individual Development

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

* All users must log in before leaving a comment