A study on the application of using big data information technology to implement physics laboratory courses in universitiesGuanqi Tao, Yinshu Wang, Yina Fan
- Applied Mathematics
- Engineering (miscellaneous)
- Modeling and Simulation
- General Computer Science
In today’s fast development of big data information technology, the traditional physics experiment method is difficult to adapt to the new curriculum reform physics experiment course objectives. The key topic of concern today is how to use big data information technology and physics experiment course integration for teaching. This study mainly uses the fuzzy comprehensive evaluation algorithm in big data information technology to study and analyze the physics laboratory courses in colleges and universities. Firstly, according to the principles and methods of the fuzzy comprehensive evaluation method, the model of a fuzzy comprehensive evaluation of university physics laboratory teaching is established, and the index system and evaluation level criteria of university physics laboratory teaching are established. Then the weights of each factor of the index system were determined using fuzzy comprehensive evaluation, and the evaluation results combining qualitative and quantitative were obtained by processing the data. Finally, the results were obtained regarding teaching attitude, teaching content, and teaching effect: the weights of good 55%, 64% and 38% performed better than other evaluation grades. Regarding teaching implementation: 54% weight of good evaluation is greater than other evaluation grades. From the evaluation grade, the average weight of a good grade is 48.25% greater than the other three categories, and the weight performance is better. This study is conducive to improving the experimental application ability of college students and thus has important historical significance for the development of physics in China.