Internship Effect Prediction for Physical Education Majors Based on Artificial Neural Network

Abstract

Professional internship offers college students a golden chance to apply their theoretical knowledge to practice. Through internship, physical education (PE) majors can match the professional knowledge and skills learned at school with the competencies required by actual jobs. The relevant studies at home and abroad mainly attempt to improve the internship effect. This paper explores the influence of the diversity of job competencies on the internship effect of PE majors, and establishes a prediction model based on artificial neural network (ANN). Firstly, an evaluation index system (EIS) was constructed for the internship quality of PE majors, and a table was prepared for four types of internship jobs for PE majors, as well as their core competences. Then, the sample data for quality evaluation of PE majors’ internship were preprocessed and subjected to feature extraction, in the light of their sequential property. After that, a prediction model was proposed for the internship quality of PE majors, along with its optimization algorithm. The proposed model was proved effective through experiments.