Applying Machine Learning Algorithm to Optimize Personalized Education Recommendation System
DOI:
https://doi.org/10.53469/jtpes.2024.04(01).14Keywords:
Machine learning, Optimization algorithm, Intelligent recommendation, Education system Logistics AutomationAbstract
In recent years, with the continuous progress and development of science and technology, especially the continuous development of artificial intelligence, machine algorithm and other technologies, the education system has also begun to carry out more personalized content from traditional functions. Traditional education systems often adopt a one-size-fits-all approach to teaching that does not take into account the unique needs and learning styles of each student. An education system personalized and optimized by machine learning algorithms can provide customized learning materials and recommendations based on each student's learning history, interests and abilities to improve learning outcomes, and machine learning algorithms can provide real-time feedback on student performance and adjust learning plans based on feedback. This makes the learning process more dynamic and personalized. It can therefore be applied to all types of education, including language learning, mathematics, science, etc. However, improving the efficiency of machine learning algorithms depends more on the improvement of numerical optimization algorithms, so it is necessary to summarize the optimization algorithms in large-scale machine learning. This paper tries to make a detailed overview of the existing machine learning algorithms in optimizing personalized education recommendation system, and introduces the algorithm optimization process.
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Copyright (c) 2024 Wangmei Chen, Zepeng Shen, Yiming Pan, Kai Tan, Cankun Wang
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
