An Iterative Optimization Algorithm Study of Virtual Reality Technology in Self-Efficacy Enhancement for College Students

Abstract

This paper discusses the application of virtual reality technology in enhancing college students’ selfefficacy and proposes an iterative optimization algorithm based on learning experience. By analyzing self-efficacy, the application of virtual reality technology machines in education, and combining relevant theories and empirical studies, the structural equation model of virtual reality technology influencing college students’ self-efficacy is constructed. The original structural equation model is optimized by using algorithms such as stochastic gradient descent method and stochastic average gradient, and the effectiveness of the algorithms is verified through experiments. This paper concludes that virtual reality technology can significantly improve college students’ self-efficacy, and the proposed iterative optimization algorithm can effectively improve the prediction accuracy and fit of the original structural equation model.