Visual Sorting Method for Public Computer Laboratory Teaching Based on Multi-Sensor Data Fusion

Currently, the classification of teaching visualization in public computer laboratories is mostly based on fixed standards, which are not directly related to teaching objectives. It is difficult to adjust the sorting according to the dynamic changes in students' learning status, and the processing time of sorting tasks is relatively long, resulting in increased time complexity. Therefore, a design and analysis of a visual ranking method for public computer laboratory teachig based on multi-sensor data fusion is proposed. Based on the current sorting requirements, use participatory classification to develop corresponding classification and sorting standards according to different teaching objectives, so that the sorting results are closely integrated with the teaching objectives, and complete the design of participatory classification and sorting simulation algorithms for teaching objectives; Build a multi-sensor data fusion public computer laboratory teaching visualization sorting model, adjust according to changes in learning status, and adopt adaptive teaching methods to achieve real-time scheduling and visualization sorting, shortening the processing time of sorting tasks. The test results indicate that the proposed method has relatively low time complexity, high specificity and stability, and better sorting performance.