An Intelligent Experimental Aid System Taking Sound Velocity Measurement Experiment as an Example

Abstract

With the continuous progress of educational technology, laboratory teaching is facing the important task of enhancing students' active learning and understanding. The study aims to develop a set of this intelligent experimental assistance system to solve the “black box” phenomenon that prevails in university physics experimental teaching. The system adopts video recognition technology and deep learning algorithms to monitor and optimize students' operations in the sound velocity measurement experiment in real time. The results show that the system significantly improves students' experimental ability, reduces the instructor's burden, and opens up a new way of thinking for physics experiment teaching.