Enhancing Mental Health Education and Foreign Language Skills in Sports School Students: An Integrated Approach / Mejora de la educación sobre salud mental y las habilidades en lenguas extranjeras en estudiantes de escuelas deportivas: un enfoque integrado

Lay the foundation of quality education is an important prerequisite for cultivating students' core quality. According to the relevant characteristics of students 'psychology, scientific educational activities and effective mental health education can not only better explore students' learning interest and passion, gradually build high-quality psychological quality, cultivate excellent communication skills, but also improve students' initiative and promote their healthy development. Therefore, current research aimed is to propose the integration and application of mental health education and foreign language teaching for sports school students, firstly, the current situation of mental health among students in sports schools and the problems existing in English classroom teaching are elaborated, and corresponding methods for integrating mental health education into English teaching in sports schools are proposed. A comprehensive analysis of the value of mental health education in the implementation of English courses in sports schools can effectively promote students in sports schools to better understand English, and improve psychological literacy in sports competitions during the learning stage. Studying the integration of English courses and mental health education can help cultivate students' strong psychological resilience and ability to overcome difficulties, laying a solid foundation for future employment and lifelong development. In addition, an integrated approach to enhancing mental health education and foreign language skills in sports school students can lead to improved overall well-being and language proficiency, fostering holistic development. The research limitations and future directions were also discussed that the end of study.(AU)

Research on Emotion Analysis and Psychoanalysis Application With Convolutional Neural Network and Bidirectional Long Short-Term Memory.

This study mainly focuses on the emotion analysis method in the application of psychoanalysis based on sentiment recognition. The method is applied to the sentiment recognition module in the server, and the sentiment recognition function is effectively realized through the improved convolutional neural network and bidirectional long short-term memory (C-BiL) model. First, the implementation difficulties of the C-BiL model and specific sentiment classification design are described. Then, the specific design process of the C-BiL model is introduced, and the innovation of the C-BiL model is indicated. Finally, the experimental results of the models are compared and analyzed. Among the deep learning models, the accuracy of the C-BiL model designed in this study is relatively high irrespective of the binary classification, the three classification, or the five classification, with an average improvement of 2.47% in Diary data set, 2.16% in Weibo data set, and 2.08% in Fudan data set. Therefore, the C-BiL model designed in this study can not only successfully classify texts but also effectively improve the accuracy of text sentiment recognition.