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Evaluation feedback information for optimization of mental health courses with deep learning methods

  • Wenhua Liu
  • Yijie ZhangEmail author
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Abstract

In order to give full play to the value of mental health education courses in colleges and universities and help students understand the relevant knowledge, thus helping to alleviate their own psychological problems, this paper uses the evaluation feedback of mental health courses in colleges and universities to conduct in-depth learning, and further optimize the mental health education courses in colleges and universities. College students, as a seemingly relaxed group, actually bear tremendous pressure. Many pressures, such as study, life, emotion, interpersonal communication, and graduate employment, have seriously affected the mental health of college students. Increasingly prominent mental health problems have attracted the attention of colleges and universities. Domestic colleges and universities have gradually opened mental health education courses, aiming at helping students find breakthroughs in the problem, thereby promoting students’ physical and mental development and adapting to the current and developing social environment with the positive and normal psychological state. However, the existing mental health education curriculum in colleges and universities cannot play its role effectively. The general evaluation criteria make the teaching activities less effective, and the students fail to understand the content of the mental health education curriculum well. Therefore, this paper uses the evaluation feedback information of the mental health curriculum in colleges and universities to conduct an in-depth study, optimize the mental health curriculum, and improve the mental health of colleges and universities. The teaching mode of health course enables students to have a deeper understanding of the content of mental health education. It can really help students alleviate psychological pressure and solve psychological problems, which is conducive to the healthy development of universities and society.

Keywords

Deep learning Course optimization Evaluation feedback Deep confidence network 

Notes

Compliance with ethical standards

Conflict of interest

All Authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Psychology and Mental HealthHuaihe Hospital of Henan UniversityKaifeng CityChina

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