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.

中文翻译：

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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开发

随着科学技术的不断发展，计算机辅助教学已成为学校教学的一种普遍模式。从目前的情况可以看出，目前的计算机辅助教学大多用多媒体代替了传统的教学模式，没有起到功能教学的作用，教师在教学中无法有效地掌握学生的心理思想。基于此，本研究将机器学习预测和人工智能KNN算法结合到实际教学中。此外，本研究收集视频和教学图像以识别学生的特征行为，并从组特征识别中区分出单个特征，并可以详细检测学生的表情识别。此外，本研究还设计了一个案例研究来分析算法的性能。