COVID-19 impacts on agriculture and food systems in Nepal: Implications for SDGs.

This paper proposes an integrated approach towards rapid decision-making in the agricultural sector aimed at improvement of its resilience. Methodologically, we seek to devise a framework that is able to take the uncertainty regarding policy preferences into account. Empirically, we focus on the effects of COVID-19 on agriculture. First, we propose a multi-criteria decision-making framework following the Pugh matrix approach for group decision-making. The Monte Carlo simulation is used to check the effects of the perturbations in the criteria weights. Then, we identify the factors behind agricultural resilience and organize them into the three groups (food security, agricultural viability, decent jobs). The expert survey is carried out to elicit the ratings in regard to the expected effects of the policy measures with respect to dimensions of agricultural resilience. The case of Lithuania is considered in the empirical analysis. The existing and newly proposed agricultural policy measures are taken into account. The measures related to alleviation of the financial burden (e.g., credit payment deferral) appear to be the most effective in accordance with the expert ratings.

Policies for Rapid Mitigation of the Crisis’ Effects on Agricultural Supply Chains: A Multi-Criteria Decision Support System with Monte Carlo Simulation

This research proposes a well-being analytical framework using social media chatter data. The proposed framework infers analytics and provides insights into the public’s well-being relevant to education throughout and post the COVID-19 pandemic through a comprehensive Emotion and Aspect-based Sentiment Analysis (ABSA). Moreover, this research aims to examine the variability in emotions of students, parents, and faculty toward the e-learning process over time and across different locations. The proposed framework curates Twitter chatter data relevant to the education sector, identifies tweets with the sentiment, and then identifies the exact emotion and emotional triggers associated with those feelings through implicit ABSA. The produced analytics are then factored by location and time to provide more comprehensive insights that aim to assist the decision-makers and personnel in the educational sector enhance and adapt the educational process during and following the pandemic and looking toward the future. The experimental results for emotion classification show that the Linear Support Vector Classifier (SVC) outperformed other classifiers in terms of overall accuracy, precision, recall, and F-measure of 91%. Moreover, the Logistic Regression classifier outperformed all other classifiers in terms of overall accuracy, recall, an F-measure of 81%, and precision of 83% for aspect classification. In online experiments using UAE COVID-19 education-related data, the analytics show high relevance with the public concerns around the education process that were reported during the experiment’s timeframe. 

https://www.mdpi.com/2504-2289/6/3/99/pdf?version=1663479578

Triggers and Tweets: Implicit Aspect-Based Sentiment and Emotion Analysis of Community Chatter Relevant to Education Post-COVID-19

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The Problems and Opinions of School Administrators during COVID-19 Pandemic: A Qualitative Study from Turkey.

Educational practices and strategies have been changed due to the COVID-19 pandemic. Universities nowadays are adopting online education systems to ensure delivering of their educational information and knowledge. This study aims to evaluate the experience of the agricultural sciences students during the COVID-19 pandemic in Jordan with focus on their preparedness, attitude and barriers. Online survey was distributed to 559 students among four different majors at the College of Agriculture Sciences at Jerash University in Jordan. Data were collected via google forms. The results’ showed no gender differences in any of these domains. However, there was statistical significance difference barrier score, attitude score, and preparedness scores between different age groups. The results showed no statistical difference throughout our four departments in different levels of study. The results indicated that about 76 % of the students were satisfied with the quality of services offered from Jerash University during the COVID-19 lockdown. Student expressed negative impression with the practical session being online instead of being in the field. Finally, students mentioned the availability and the quality of network as a barrier for them to perform better and get higher grades. This new experience for students during pandemic lockdown identified areas for improvement that can done. Sharing the study results could help to enhance online education with similar settings in colleges throughout the country.

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Distance Online Learning during the COVID-19 Crisis from the Perspective of Agricultural Sciences Students in Jordan: Survey Study

The official announcement of COVID-19 as a global pandemic on 11 March 2020 by WHO, the world economy has abruptly declined, billions of people are in lockdown, maintaining self-isolation.
In this survey, 150 respondents were selected randomly and this survey intends to highlight the impact of lockdown in agriculture Students on their education along with their response towards pros and cons.
This survey shows that maximum respondent, around 52% of them found lockdown beneficial in the sense that it has helped to neutralize the gravity of viral infection and 48% of them doesn’t found it beneficial as their educational schedule has been halted. The practical education of a student is disturbed due to lockdown and now they are utilizing this period involving in online courses, training, and webinars.
Many of them couldn’t have access to the internet to catch the session, thus the government should initiate policy in education through a long term perspective so that no pandemic could interfere with the educational institution in digital world.

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Neha Sotang

Papers

Impact of COVID-19 Lockdown on Agriculture Education in Nepal: An Online survey