| Issue |
E3S Web Conf.
Volume 218, 2020
2020 International Symposium on Energy, Environmental Science and Engineering (ISEESE 2020)
|
|
|---|---|---|
| Article Number | 02007 | |
| Number of page(s) | 10 | |
| Section | New Energy Development and Energy Sustainable Development Optimization | |
| DOI | https://doi.org/10.1051/e3sconf/202021802007 | |
| Published online | 11 December 2020 | |
Research on Active Aging Learning and Satisfaction in the Elderly in the age of artificial intelligence
1
The Education Science Department, Zhaoqing University, Zhaoqing city, 526061, China
2
School of Public Administration, Nanfang College of Sun Yat-sen University, Guangzhou, Guangdong, 510000, China
* Corresponding author. Email: 306470714@qq.com
At present, artificial intelligence has become an important driving force for a new round of technological revolution and industrial transformation. Under the background of the increasingly significant trend of global population aging, it is an important issue to consider how to serve cognitive aging and geriatric linguistics research based on artificial intelligence technology to serve the transformation of the elderly from healthy aging, active aging to active aging. The research and application of artificial intelligence based geriatric linguistics and services for the aged include at least three fields: basic research on gerontology, detection of aging and diseases, and cognitive rehabilitation of aging language.This study explores the correlation between active aging learning and satisfaction among senior citizens. Taking the students from the Senior College of Central Taiwan as the research object, the Active Aging Learning and Satisfaction Questionnaire was used as the research tool. A total of 440 copies were sent out using a convenient sampling method. 400 questionnaires, deducted 20 incomplete questionnaires, effectively recovered 380 points, and the effective recovery rate was 86.36%. SPSS (Satistical Package for the Social Science) for Window statistical suite software was used as an analysis tool for descriptive statistics Data analysis was performed by statistical methods such as single factor variation analysis, regression analysis, item analysis, and factor analysis. The results of statistical analysis show that there is a significant difference in active aging learning and satisfaction among older people. In addition, research has found that the relationship between active aging learning and satisfaction has predictive power. Based on preliminary research, researchers have found that active aging learning has an effect on improving the satisfaction of older people, and makes relevant suggestions for future research and teaching units.
© The Authors, published by EDP Sciences, 2020
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