An analytical study of shortest path algorithms for learning paths in French courses with digital resources

Ying Chen1, Cen Peng1, Chenghui Wang 2
1School of Foreign Languages, Zhixing College of Hubei University, Wuhan, Hubei, 430011, China
2WH Auto Parts Industries Inc., Wuhan, Hubei, 430223, China

Abstract

Students have the problems of insufficient self-control, insufficient learning motivation and unplanned and unsystematic for independent learning of university French. In order to solve this problem effectively, this study proposes the reform of French blended education model guided by POA theory. In this paper, we design a hybrid intelligent teaching mode of university French guided by the output-oriented approach, improve it based on the mutation operation in the genetic algorithm, propose the adaptive mutation genetic algorithm, and optimize the BP neural network with this algorithm. The GA-BP neural network is trained through simulation experiments to verify the performance of the algorithm. Using SEM structural equation modeling, the measurement model of six dimensions, namely, learning effect, teaching effect, learning input, objective learning conditions, subjective learning factors and learning ability, is established, integrating factor analysis and path analysis, and relevant research hypotheses are proposed. The feasibility of the hypotheses is verified one by one through empirical research. The path coefficients between each variable in the model and the path coefficients of the factor loadings are all at the significant level of 0.000, and all of them are positive, the path coefficients’ validity is within the acceptable range, and the hypotheses proposed in this paper are all supported. Compared with the default path, 69.78% of the students in the recommended path for learning French think that the knowledge of the recommended learning path is easy to understand, and the learning path constructed on the basis of the educational resources of the output-oriented method can better satisfy the learning needs of the students compared with the default learning path.

Keywords: output-oriented method, genetic algorithm, SEM structural equations, BP neural network, French course learning