ABSTRACT
Due to Covid-19, educational institutions had to change traditional educational practices to virtual modality, representing significant challenges on the planning, mediating, and evaluating processes. Learning analytics are a set of innovative tools in the pedagogical area, in which the use of data can contribute to the improvement of courses and educational policies. This work aims to carry out a descriptive reflection of the learning analytics evaluating the effect of the pandemic on the overall performance of the subject. For this purpose, a quantitative investigation was carried out by studying the grades in the subject of Chemistry I during the 2018-2021 period at the UNED, Costa Rica. The overall performance and approval of the subject experienced an increase in the average grade during the period 2020-2021. In addition, some significant differences were found between the mean grades according to the demographic regions of the country. However, it is necessary to make efforts in order to measure the quality of the learning achieved in the subject and the degree of satisfaction of the students according to the learning objectives that have been achieved in the course.
ABSTRACT
Emergency Remote Teaching (ERE) is an educational procedure that involves the use of distance learning solutions in scenarios in which the teaching process would otherwise be face-to-face or guided by hybrid resources;these techniques are meant to be an alternative during a crisis and are to be ceased once the emergency subsides. In this research paper, an Emergency Remote Teaching Strategy in Laboratories (EREL) was developed under the Extended Laboratory Model (LE), to be applied and evaluated in academical subjects that involve chemical experimentation laboratories at the Universidad Estatal a Distancia de Costa Rica (UNED-CR). The project assesses the effectiveness of the EREL from the perspective of the students, the teachers, and the development process of face-to-face experiments. According to the perception of the students, home experiments contributed to a greater extent (most effectively) in the understanding of the chemical concepts related to each subject. However, according to the perception of the teachers, the students must improve in aspects such as the safe handling of chemical substances and the correct usage of laboratory instruments, as well as the development of laboratory skills. EREL in the COVID-19 context is valued positively by the teaching staff and the students;nevertheless, it was also clear that a single face-to-face session is not enough for students to acquire the basic technical skills of laboratory subjects, which makes returning to traditional learning a priority, keeping the use of resources such as Remote Experimentation Manuals (MPR) as a complement in laboratory subjects.
ABSTRACT
Introduction: The COVID-19 disease caused by SARS-CoV-2 became a pandemic as of March 2020. Among the clinical manifestations of the peripheral nervous system may appear anosmia and ageusia. Objective: Demonstrate the importance of clinical and epidemiological diagnosis in the certainty criterion of COVID-19. Case presentation: 17-year-old male adolescent with loss of smell and family history of COVID-19, so he was left alone at home due to the admission in hospital of his family;he had two negative polymerase chain reaction tests in the first instance, without clinical picture of the apparent disease, until approximately 10 days after the appearance of the symptoms of the family, which begins with total loss of smell;the same test is repeated, which is negative again and he is referred to consultation for the study of anosmia. He was attended in Pediatrics service, a complete study is indicated and the interconsultation with the specialist of otolaryngology is carried out. All the complementary laboratory, microbiology and imaging tests were negative, so it was decided, due to the suspicion of COVID-19 and the family history, to perform serology for antibodies against SARS-CoV-2, which resulted in positive IgG. Conclusion: The retrospective clinical and epidemiological diagnosis allowed the certainty criterion of COVID-19 disease. © 2021, Editorial Ciencias Medicas. All rights reserved.
ABSTRACT
BANGLADESH. What this article is about: This article details the co-design, implementation and early evaluation results of an initiative for promoting the consumption of nutritious foods in adolescents. The initiative involved school and community activities, social media and celebrity endorsements and a pledge for individual and collective action. Key messages: * Despite baseline surveys indicating that many adolescents had poor access to the internet, a social media-focused intervention proved to be an effective strategy to target this group during the COVID-19 pandemic when internet usage increased dramatically. * By building a narrative that tapped into adolescents' motivations, the Bhalo Khabo Bhalo Thakbo campaign was able to spark the interest and engagement of adolescents for improving their consumption of nutritious foods.
ABSTRACT
Background and objective: Many trends are being raised across global countries for the novel disease 'Corona-Virus' (COVID-19). Shelter-in-place (SIP) orders are implemented worldwide to reduce the proliferation rate of this virus. Since the World Health Organization (WHO) proclaimed it as 'pandemic,' its emergent state prevails worldwide. As a successor of SARS-CoV-2, higher destruction has been enforced on human lives intolerably. However, the prior detection could help shorten this disease's proliferation rate;various prediction and diagnosis tools are useful with artificial intelligence. These tools might assist in preventive measures against the virus infection. The main objective of this article is two-folded. First, to explore the application of soft computing techniques, the overview of machine learning (ML), deep learning (DL), internet of things (IoT), and support vector machines (SVM) have been interpreted concerning COVID-19 analysis. Next, to analyze performance, a comparative study has been represented to show that the soft computing models outperform some of the prevailed analytical models on the COVID-19. Method: To forecast and predict a pandemic outbreak, Cauchy distribution probabilistic approaches are applied. An extensive study of mathematical and theoretical, and approximate models based on soft computing done for COVID-19 prediction. Consecutively, some curious factor such as infection rate based on age groups could be forecasted. Also, Sick rate, and immunity rate during the quarantine period have been analyzed for nearly 500 sample tests taken globally. Result: This research scopes for extensive analysis of COVID-19 entitled to health policies. It would facilitate the technocrats to develop heuristic models for this wide-spread disease through forecasting of real-time data. It also addresses the statistical analysis of COVID-19 articles and future scope for technocrats regarding COVID-19 prediction and diagnosis. © 2020 Ubiquity Press. All rights reserved.