The cultivation methods of humanistic spirit in college English teaching and its influence on students' mental health based on deep learning

Abstract

The observation of the reform and progress in English language instruction reveals a discernible pattern characterised by a focus on proficiency, excellence, and expertise. Since the inception of prioritising knowledge transmission, there has been a gradual shift towards recognising the need of inclusive skills training and development. This has further evolved to place a strong emphasis on fostering excellence in English instruction, with a special focus on nurturing artistic proficiency. Therefore, enhancing the development of humanistic traits in college English instruction is not merely a component of English teaching reform, but rather emerges as the primary concern that English educators must confront. The present study introduces a novel approach, namely the swallow swarm optimisation with a stacked autoencoder (SSOA-SAE) model, to investigate the mental health of college students in the context of English language education. The objective of the SSOA-SAE model is to ascertain the approach to fostering the cultivation of the humanistic spirit in the domains of English instruction and mental health. The SSOA-SAE model is implemented by first executing the SAE model in order to perform the classification process effectively. Furthermore, the Single-Source Optimisation Algorithm (SSOA) is employed to successfully adjust the hyperparameters associated with the Stacked Autoencoder (SAE) model. This study investigates a comprehensive series of simulations conducted on the SSOA-SAE model, and afterwards compares the findings with those of other established models. The predictive accuracy of SSOA-SAE in assessing the mental well-being of students enrolled in English courses with a humanistic approach is evaluated to be 99.88%. The simulation results indicated that the SSOA-SAE model demonstrated superiority above contemporary methodologies.