Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 4 de 4
Filter
1.
Chinese Journal of Parasitology and Parasitic Diseases ; 40(4):507-510, 2022.
Article in Chinese | EMBASE | ID: covidwho-2320956

ABSTRACT

The COVID-19 pandemic has promoted the development of online teaching in various educational institutions. Different online teaching practice has shown advantages and potential problems. The combination of online and offline teaching (mixed teaching) is a new teaching practice that can exert its advantages simultaneously, and has been wildly used during the COVID-19 pandemic, even being extended to the post-pandemic era. Medical parasitology is a foundation course for medicine and a bridging course towards clinical medicine and preventive medicine. The traditional teaching of medical parasitology has presented many limitations, including outdated teaching concepts and practices, and the disconnection between theory teaching and practice teaching. In response to these difficulties, many innovative ideas and measures have been taken o reform the teaching practice of the foundation medical courses, including updating teaching program, adopting innovative teaching practice (such as blended teaching), and promoting the teaching evaluation method. In this paper, we concluded the blended teaching tools, platforms, manners, effects and evaluation methods in medical parasitology in China during the COVID-19 pandemic to provide information for the teaching reform in the post-pandemic era.Copyright © 2022, National Institute of Parasitic Diseases. All rights reserved.

2.
6th International Conference on Education and Multimedia Technology, ICEMT 2022 ; : 34-38, 2022.
Article in English | Scopus | ID: covidwho-2153129

ABSTRACT

Facing the challenge of COVID-19 pandemic, online education rapidly occupied the daily teaching in China, which promoted the development of "Online+Offline"(blended) teaching. Medical Parasitology majorly aims to cultivate students' basic knowledge of Parasitology and the ability of "diagnosis and control of parasitic diseases". The Massive Online Open Course (MOOC), intelligent teaching software and Parasitology multimedia laboratory are used for blended teaching. Theoretical teaching includes intensive lectures, self-learning and flipped classrooms. Practices are taught in blended manner. The most representative means is the flipped classroom integrating learning with application through "case discussion - laboratory examination - uploading diagnosis basis on line - group report for peer learning". An evaluation combining formative and summative evaluation, online and offline assessment is jointly applied. We selected Clinic Medicine major as the experimental group, the Basic Medicine, Medical Experimental Technology and Biotechnology majors as the control group. The experimental group was taught in the blended teaching mode of "combining virtuality with reality, learning with application";and the control group was taught in the traditional mode of lectures in big group and practices in small groups. The scores of the final computer test and the final offline experimental test were used in comparison. The experiment and theory scores of the experimental group are both significantly higher than that of the control group. The blended teaching is highly recognized by our students, and the teaching mode has been widely demonstrated and recommended to other courses in and out of the university. This mode comprehensively cultivated students' basic knowledge of Parasitology, and the ability of diagnosis and control of parasitic diseases. This blended teaching mode of "combining virtuality with reality, learning with application"effectively improved students' academic performance and application abilities, and well cultivated students' thinking of diagnosis and control of parasitic diseases. © 2022 ACM.

3.
Chinese Journal of Parasitology and Parasitic Diseases ; 40(4):507-510, 2022.
Article in Chinese | Scopus | ID: covidwho-2080954

ABSTRACT

The COVID-19 pandemic has promoted the development of online teaching in various educational institutions. Different online teaching practice has shown advantages and potential problems. The combination of online and offline teaching (mixed teaching) is a new teaching practice that can exert its advantages simultaneously, and has been wildly used during the COVID-19 pandemic, even being extended to the post-pandemic era. Medical parasitology is a foundation course for medicine and a bridging course towards clinical medicine and preventive medicine. The traditional teaching of medical parasitology has presented many limitations, including outdated teaching concepts and practices, and the disconnection between theory teaching and practice teaching. In response to these difficulties, many innovative ideas and measures have been taken o reform the teaching practice of the foundation medical courses, including updating teaching program, adopting innovative teaching practice (such as blended teaching), and promoting the teaching evaluation method. In this paper, we concluded the blended teaching tools, platforms, manners, effects and evaluation methods in medical parasitology in China during the COVID-19 pandemic to provide information for the teaching reform in the post-pandemic era. © 2022, National Institute of Parasitic Diseases. All rights reserved.

4.
Proc. - Int. Conf. Public Health Data Sci., ICPHDS ; : 283-289, 2020.
Article in English | Scopus | ID: covidwho-1142827

ABSTRACT

The COVID-19 pandemic situation is aggravating in the United States, and due to its high infection rate, it seems hard to predict the number of infected people. In this research, we carry out machine learning methods such as linear regression and neuron networks to make predictions on the number of positive cases of COVID-19. We also collect state-level data to generate predictions by linear regression and we find that the data from two states-Georgia and Massachusetts-can be used to predict the number of infections nationwide. After dividing our dataset into 3 consecutive time periods and training different models to fit each corresponding data, we compare mean square error (MSE) values to draw the conclusion that for the first time period the Lasso performs better than Ridge, for the second time period the Ridge and Lasso behave similarly on our data, and for the third period time the Ridge fits our data better than Lasso. Furthermore, from the general perspective regardless of 3 time periods we find that single variable linear regression performs more accurately than fully connected neural network. © 2020 IEEE.

SELECTION OF CITATIONS
SEARCH DETAIL