Research On Performance Prediction And Tiered Teaching Practice For Secondary School Students Based On Machine Learning

With the development of modern technology and the increasing emphasis on vocational education in China,the research of applying advanced technologies to secondary vocational education has received more and more attention.As an important research direction in the field of artificial intelligence,machine learning has shown strong advantages in student performance prediction and student behavior modeling,and gradually becomes a powerful tool in educational data mining.Therefore,it is important to consider how to combine machine learning with traditional teaching methods to improve teaching quality.In this context,this study aims to investigate the application of machine learning in the prediction of secondary school students’ performance,and to conduct practical research and analysis of machine learning prediction results in combination with tiered teaching methods,taking the course "Microcomputer Principles" of secondary school computer major as an example.The main contents of this paper are as follows:(1)To investigate the effectiveness of machine learning models in student performance prediction,three datasets oriented to different practical educational tasks are selected,covering bi-classification prediction of whether graduate students can be admitted,whether graduates can successfully obtain internship opportunities and multi-classification prediction of secondary school students’ final grades.On this basis,the performance of seven common machine learning models is compared,and based on the experimental results,the appropriate machine learning models are selected for the prediction of students’ performance in the course "Microcomputer Principles" in computer science classes in internship secondary schools.(2)In order to further exploit the application of machine learning in secondary teaching scenarios,a teaching framework based on machine learning and tiered teaching method is designed.It can be used to develop corresponding teaching objectives and teaching contents for different levels of students respectively based on the classification prediction results of machine learning models,and design the actual teaching process,post-class assignments,and evaluation process to improve the quality of the traditional teaching mode.It provides a novel idea for the deep integration of advanced technology and actual teaching scenarios.(3)In order to verify the performance of machine learning and tiered teaching method in practical teaching,the course "Microcomputer Principles" for secondary computer application majors is explored as a research target.The proposed tiered teaching method based on machine learning classification prediction results is implemented specifically in the target class according to the requirements of the syllabus and overall teaching objectives,while the traditional lecture method is used as a control experiment in the other class.The effectiveness is evaluated by designing test papers and questionnaires at the end of the semester,and the results of the study show that the proposed teaching framework is effective in increasing students’ self-confidence and improving overall student performance.