SI-BIME Smart Learning Multimedia Platform for Students: a Solution for the Pandemic-19 in the Regions

The impact of the Covid-19 pandemic is not only experienced by a handful of people but by all lines of life in this world. One of the biggest impacts is related to the provision of education at the primary, secondary, and senior levels. This study uses the prototype method which is targeted to produce applications that are ready to be implemented to produce an intelligent learning application. This study uses a quantitative method for evaluating results. This study aims to assist schools, especially those in the regions, in overcoming the problem of decreased learning activity because it has been identified as the cause of decreased student learning outcomes. This research was conducted at the high school level because students were prepared to continue to a higher level. This research resulted in a smart learning SI-BIME (BINUS Multimedia Edutainment Information System) which was prepared to support e-learning-based learning processes in schools. Based on the evaluation of learning, the results of this study proved to be very helpful for schools and support a better learning process. As well as focus group discussions with school authorities, students, and parent representatives, assessments are also provided by higher-level authorities. The results of this study can also help schools and teachers to prepare better learning media for students and can be used comprehensively and sustainably even though COVID-19 is over. © 2022 IEEE.

GEOGRAPHICAL SEVIRD COVID-19 MODEL WITH TRAVEL RESTRICTIONS

Susceptible-Infected-Recovered (SIR) models have been widely used to study the spread of Covid-19. These models have been improved to include other states (e.g., exposed, deceased) as well as geographical level transmission dynamics. In this paper, we present an extension to an existing SEVIRD (Susceptible - Exposed - Vaccinated - Infected - Recovered - Death) model to include the effect of air and maritime travel as well as travel restrictions. We use the model to simulate the spread of Covid-19 through 13 different countries. The case study shown illustrates how the model can be used for rapid prototyping at a geographical level and adapted to include changing policies. © 2022 Society for Modeling & Simulation International (SCS)

Instructional Design for Socially Distanced Compliance Audit.

The COVID-19 pandemic made being socially distant an essential practice to upskill employees. As employers incorporate measures to keep employees socially distant from one another, they also need to consider technology to make this practice possible. Our project with a large state-wide, multi-campus food bank (FB) in the pacific northwest occurred during the late summer and early fall of 2020. The FB partnered with our group of three graduate students and one faculty member to improve self-audits of their coolers. This project used technology and rapid prototyping to design an instructional intervention that allowed social distancing in a workplace where employees were required to be present. We conducted a front-end analysis including training requirements, learner and environmental analysis and task analysis. This article describes the process of the analyses and design of instructional materials that allowed the FB to scale their audit process to their other warehouses.

Instructional design with ADDIE and rapid prototyping for blended learning: validation and its acceptance in the context of TVET Bangladesh.

Following COVID-19, the global educational landscape shifted dramatically. Almost every educational institute in Bangladesh undertook a strategic move to begin offering online or blended learning courses to mitigate the challenges created by the pandemic. The TVET sector, particularly the polytechnic institute of Bangladesh, endeavored to explore the blended learning approach as an immediate and long-term solution to address the educational dislocation caused by the pandemic. This study attempts to conceptualize a pedagogical design based on the ADDIE and rapid prototyping model to make a reliable and robust instructional design to be used in the blended learning context. A content validity index (CVI) was used to validate the proposed model; a technology acceptance model (TAM) was employed to examine its acceptability to students; and finally, students' academic performances were analysed to evaluate the overall performance of the proposed instructional design. The findings reveal that the proposed instructional design can be a reliable and valid pedagogical approach to be implemented in the blended learning context for polytechnic students. The proposed instructional design may help TVET educators and course designers to create a robust blended learning environment in the TVET sector and in other similar disciplines, such as science and engineering education.

DEVELOPMENT AND VALIDATION OF AN ENZYME-LINKED IMMUNOASSAY KIT FOR DIAGNOSIS AND SURVEILLANCE OF COVID-19.

There is a massive demand to identify alternative methods to detect new cases of COVID-19 as well as to investigate the epidemiology of the disease. In many countries, importation of commercial kits poses a significant impact on their testing capacity and increases the costs for the public health system. We have developed an ELISA to detect IgG antibodies against SARS-CoV-2 using a recombinant viral nucleocapsid (rN) protein expressed in E. coli. Using a total of 894 clinical samples we showed that the rN-ELISA was able to detect IgG antibodies against SARS-CoV-2 with high sensitivity (97.5%) and specificity (96.3%) when compared to a commercial antibody test. After three external validation studies, we showed that the test accuracy was higher than 90%. The rN-ELISA IgG kit constitutes a convenient and specific method for the large-scale determination of SARS-CoV-2 antibodies in human sera with high reliability.

Development and validation of an enzyme-linked immunoassay kit for diagnosis and surveillance of COVID-19.

There is a massive demand to identify alternative methods to detect new cases of COVID-19 as well as to investigate the epidemiology of the disease. In many countries, importation of commercial kits poses a significant impact on their testing capacity and increases the costs for the public health system. We have developed an ELISA to detect IgG antibodies against SARS-CoV-2 using a recombinant viral nucleocapsid (rN) protein expressed in E. coli. Using a total of 894 clinical samples we showed that the rN-ELISA was able to detect IgG antibodies against SARS-CoV-2 with high sensitivity (97.5%) and specificity (96.3%) when compared to a commercial antibody test. After three external validation studies, we showed that the test accuracy was higher than 90%. The rN-ELISA IgG kit constitutes a convenient and specific method for the large-scale determination of SARS-CoV-2 antibodies in human sera with high reliability.