ABSTRACT
The blended educational method has become a common way of teaching and learning in the post-COVID-19 era. However, the related research on the selection model for the blended design teaching service quality solution is still an important research gap during this period. Therefore, this study proposed a hybrid method of fuzzy analytic network process (FANP) and technique for order preference by similarity to ideal solution (TOPSIS) to analyse the dimensions, indicators and alternatives of blended design teaching service quality. As for the findings of this research, the dimension of assurance is the most vital factor, followed by responsiveness, reliability and empathy. Meanwhile, this research discovered that the top three significant alternatives are "Employees are trustworthy”, "Safe transaction mechanism and environment” and "Personalised needs of customers”. Also, we found that dimensions utilised to evaluate the quality of education service are similar whether in the post COVID-19 era, in the COVID-19 epidemic or prior to the COVID-19 pandemic. The main contribution of this study is to establish a multi-criteria decision-making (MCDM) model for the ranking of the blended design teaching service quality index and solution under a fuzzy environment. Finally, the research findings of this study have a guiding role, thereby becoming a guide for the industries related to hybrid design education to maintain good service quality in similar scenarios in the future. © 2023 by the authors.
ABSTRACT
Features extracted from aggregated data are often contaminated with errors. Errors in these features are usually difficult to handle, especially when the feature dimension is high. We construct an estimator of the feature effects in the context of a Poisson regression with a high dimensional feature and additive measurement errors. The procedure penalizes a target function that is specially designed to handle measurement errors. We perform optimization within a bounded region. Benefiting from the convexity of the constructed target function in this region, we establish the theoretical properties of the new estimator in terms of algorithmic convergence and statistical consistency. The numerical performance is demonstrated using simulation studies. We apply the method to analyze the possible effect of weather on the number of COVID-19 cases.
ABSTRACT
The coronavirus virus (COVID-19) epidemic has swept the world, with the World Health Organization defining it as a pandemic on March 11. This in turn has affected the approaches and methods used in education throughout the world. According to United Nations report, by the time of mid-April 2020, 94% of learners in more than 200 countries around the world have been affected, and 1.58 billion students from pre-school to higher education are affected. In response to increased learning needs regarding infection prevention, the Ministry of Education has also provided cloud educational resources and private online learning resources, platforms, and tools to schools at all levels to encourage teachers and students to make effective use of digital resources. Although the government provides abundant teaching resources, the implementation of distance teaching in college physical education still faced with many problems, such as the shortage of course resources, the lack of information literacy of teachers, the difficulty in implementing conventional teaching plans online, the limited conditions for students to exercise at home, and the doubts about online physical education. Therefore, this study proposes a new teaching method, and studies, analyzes and discusses this method. The method of experimental design was adopted in this study to divide the students into two groups: blended learning group (synchronous and asynchronous) and single type learning group (synchronous). The results show that blended learning students perform better than single type learning students in all these aspects, which proves the practicability and effectiveness of the proposed method. © The Author(s) 2021.