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Development of computer aided classroom teaching system based on machine learning prediction and artificial intelligence KNN algorithm

机译:基于机器学习预测和人工智能KNN算法的计算机辅助课堂教学系统的开发

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摘要

With the continuous development of science and technology, computer-aided teaching has become a common mode of school teaching. From the current situation, it can be seen that the current computer-aided teaching mostly replaces the traditional teaching mode with multimedia, and does not play the role of functional teaching, and teachers cannot effectively grasp the students' psychological thoughts in teaching. Based on this, this study combines machine learning prediction and artificial intelligence KNN algorithm to actual teaching. Moreover, this study collects video and instructional images for student feature behavior recognition, and distinguishes individual features from group feature recognition, and can detect student expression recognition in detail. In addition, this study designed a case study to analyze the performance of the algorithm. From the experimental results, it can be seen that the proposed algorithm has certain effects and can be used as an algorithm to assist the teaching process and can provide theoretical reference for subsequent related research.
机译:随着科学技术的不断发展,计算机辅助教学已成为众多学校教学模式。从目前的情况来看,可以看出,目前的计算机辅助教学大多用多媒体取代传统教学模式,并不发挥功能教学的作用,教师不能有效地掌握教学的心理思想。基于此,本研究将机器学习预测和人工智能KNN算法与实际教学结合起来。此外,本研究收集学生特征行为识别的视频和教学图像,并区分各个特征从组特征识别,并且可以详细地检测学生表达识别。此外,本研究设计了一种案例研究,分析了算法的性能。从实验结果可以看出,所提出的算法具有一定的效果,可以用作帮助教学过程的算法,并可以为随后的相关研究提供理论参考。

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