A Study on the Innovation of Instructional Management System in the Perspective of Machine Learning Supported Student Engagement Enhancement

The research uses machine learning in teaching management to innovate the traditional teaching management system, builds a teaching management system based on machine learning, carries out character recognition in the teaching management system through the LR algorithm, and recognizes students’ expressions and behaviors in the classroom by using AlexNet and ResNet50 networks. Requirement analysis is carried out according to user roles and application scenarios, and relevant functions are designed on the basis of system requirements. Through the teaching experiment method, the changes in student participation and teaching quality between the experimental group and the control group before and after the teaching experiment are compared to verify the actual effect of the teaching management system based on machine learning. The experimental and control groups before the experiment are at the same level in terms of student engagement and teaching quality. After the experiment, the experimental group far exceeded the control group in all dimensions of student engagement (behavioral engagement, cognitive engagement, affective engagement, social engagement, and overall engagement) and all indicators of teaching quality (students’ interest in learning, students’ attentiveness, the teaching process, the teaching results, and the classroom atmosphere), with a p-value of <0.05 for all dimensions. The experimental group showed a greater improvement in student engagement and teaching quality after the experiment compared to the preexperiment, while the control group The experimental group’s student engagement and teaching quality improved more than that before the experiment, while the control group made very little progress. The machine learning-based teaching management system in this paper has a positive effect on improving student engagement and teaching quality.