Construction and Simulation of a Data-driven Blended Teaching 'Video Recording Technology' Course Evaluation System Based on Improved Genetic Algorithm

With the development of modern educational technology, blended teaching has become an important teaching mode in higher education. In this paper, a data-driven hybrid teaching “video technology” course evaluation system based on improved genetic algorithm is proposed and simulated. Firstly, the current status of the application of improved genetic algorithm in higher education and its application in optimization problems are introduced through literature review. Second, a mathematical model of the data-driven hybrid teaching “video technology” course evaluation system based on improved genetic algorithm is constructed. By introducing the improved genetic algorithm mathematical model, the evaluation model is optimized to improve the accuracy and efficiency of evaluation. At the same time, combined with video technology teaching, real-time monitoring and recording of the classroom teaching process is realized, which provides rich data support for course evaluation. Finally, the constructed course evaluation system was simulated and studied. The performance of the system was verified by simulating the actual teaching process and collecting relevant data. The simulation results show that the data-driven hybrid teaching “video technology” course evaluation system based on improved genetic algorithm can accurately reflect the teaching process.