Construction and Application of a Big Data Analysis Platform for College Music Education for College Students' Mental Health

IF 0.5 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Xiaochen Wang, Tao Wang
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引用次数: 0

Abstract

In this study, the authors devised a big data-driven evaluation model to measure the effect of college music education, aiming at filling the gaps of poor accuracy and time-consuming results of music education effect evaluation. Firstly, the authors determined the effect of an evaluation system of music for learning, and the evaluation of this effect. Then, they carried out a simulation experiment. The literature review evidenced that few domestic research reports considered college students' communication fear. Thus, combining the characteristics of current college students' psychological counseling and the theory of communication fear, the authors tried to apply the music system desensitization therapy to address college students' communication fear, from the intervention effect, feasibility, and therapy as a psychological counseling method. The results showed that music system desensitization therapy eliminates college students' fear of communication, reduces speech anxiety, reduces shyness, and improves interpersonal communication skills.
面向大学生心理健康的高校音乐教育大数据分析平台的构建与应用
在这项研究中,作者设计了一个大的数据驱动的评估模型来衡量大学音乐教育的效果,旨在填补音乐教育效果评估准确性差、结果耗时的空白。首先,作者确定了音乐学习评价体系的效果,并对其效果进行了评价。然后,他们进行了模拟实验。文献综述表明,国内很少有研究报告考虑大学生的沟通恐惧。因此,结合当前大学生心理咨询的特点和沟通恐惧理论,从心理咨询的干预效果、可行性和治疗方法等方面,尝试运用音乐系统脱敏疗法来解决大学生的沟通恐惧。结果表明,音乐系统脱敏疗法消除了大学生对沟通的恐惧,减少了言语焦虑,减少了害羞,提高了人际沟通技能。
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来源期刊
International Journal of Data Warehousing and Mining
International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.40
自引率
0.00%
发文量
20
审稿时长
>12 weeks
期刊介绍: The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving
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