Q-methodology to understand stakeholder discourses on bat conservation and management in view of the COVID-19 pandemic

Human-bat interactions are becoming more frequent with growing proximity between people and wildlife. As such, it is important to understand the perspectives of human stakeholders in these interactions, especially considering how media coverage of bats' potential roles as the reservoirs of the ancestral virus to SARS-Cov2 has exacerbated negative perceptions of bats. We used Q-methodology to describe diverse viewpoints on bat conservation and management and identify areas of consensus among stakeholders in Singapore. We derived perspectives, problems, and priorities for bat conservation and management based on qualitative and quantitative analyses. The results reveal three distinct discourses. The ecocentric viewpoint advocates conserving bats for their intrinsic value. The anthropocentric viewpoint outright rejects the idea of conserving bats because of the perceived public-health threat that bats pose. The third discourse prioritizes educating citizens and enhancing general appreciation for biodiversity. All stakeholders agree on the need to reconsider COVID-19-related concerns about bats and address misconceptions that could hinder conservation. The top recommendation by stakeholders is to assess and improve bat-related attitudes and beliefs so that citizens become more supportive of conserving bats for their inherent value and roles in maintaining Singapore's ecosystems. Considering both diverging and consensus viewpoints and engaging various stakeholders in conservation and management decisions can yield both attitudinal change and more effective solutions while meeting the ecological and social needs of conservation. Copyright © 2022 Leong, Lebarbenchon, Zhang and Coleman.

Sentiment Analysis of COVID19 Reviews Using Hierarchical Version of d-RNN

In recent years understanding person's sentiments for catastrophic events has been a major subject of research. In recent times COVID19 has raised psychological issues in people's minds across world. Sentiment analysis has played significant role in analysing reviews across wide array of real-life situations. With constant development of deep learning based language models, this has become an active investigation area. With COVID19 pandemic different countries have faced several peaks resulting in lockdowns. During this time people have placed their sentiments in social media. As review data corpora grows it becomes necessary to develop robust sentiment analysis models capable of extracting people's viewpoints and sentiments. In this paper, we present a computational framework which uses deep learning based language models through delayed recurrent neural networks (d-RNN) and hierarchical version of d-RNN (Hd-RNN) for sentiment analysis catering to rise of COVID19 cases in different parts of India. Sentiments are reviewed considering time window spread across 2020 and 2021. Multi-label sentiment classification is used where more than one sentiment are expressed at once. Both d-RNN and Hd-RNN are optimized by fine tuning different network parameters and compared with BERT variants, LSTM as well as traditional methods. The methods are evaluated with highly skewed data as well as using precision, recall and F1 scores. The results on experimental datasets indicate superiority of Hd-RNN considering other techniques.

Work in Progress: Engaging First-year Students in Programming 1 during COVID-19

During the Fall 2020 semester, it became even more important than before to engage students in the “classroom” whether that be in-person, online, or a hybrid model. This paper will introduce various entrepreneurial mindset (EM) techniques to engage students that could be adapted to any engineering course. All the techniques have suggestions for adapting to a fully online course as well as working for an in-person or hybrid class. The first activity presented will be name signs with badges that will promote (1) setting, evaluating, and achieving goals, (2) self-reflection, (3) considering a problem from multiple viewpoints, and (4) seeing the values of others. Example badges include: Being Brave, Stump the Professor, Discussion Board Guru, Peer Tutor Extraordinary, and Nominator. The second activity presented will be Tik-Tok-ing the student's way into learning concepts. This activity focuses on students' creating course content via videos that will promote (1) being able to teach and learn from peers, (2) modifying a product based on feedback, and (3) connecting life experiences with class content. The third activity is using Play-Doh to make connections with material. In this activity students use the Play-Doh as a medium to present technical information effectively to a wide audience and make connections with life experiences and class content. Each activity will be explained with examples from introduction to programming along with methods to adapt to other engineering courses. © American Society for Engineering Education, 2021

Who are the "Real" Experts? The Debate Surrounding COVID-19 Health Risk Management: An Israeli Case Study.

BACKGROUND: The uncertainty surrounding the COVID-19 crisis and the different approaches taken to manage it have triggered scientific controversies among experts. This study seeks to examine how the fragile nature of Israeli democracy accommodated differences of opinion between experts during the COVID-19 crisis. OBJECTIVE: To map and analyze the discourse between experts surrounding issues that were the topic of scientific controversy. To examine the viewpoints of the public regarding the positions of the different experts. METHODS AND SAMPLE: A sequential mixed study design. The qualitative research was a discourse analysis of 435 items that entailed mapping the voices of different experts regarding controversial topics. In the quantitative study, a total of 924 participants answered a questionnaire examining topics that engendered differences of opinion between the experts. RESULTS: The results showed that there was no dialogue between opposition and coalition experts. Moreover, the coalition experts labeled the experts who criticized them as "coronavirus deniers" and "anti-vaxxers." The coalition changed its opinion on one issue only-the issue of lockdowns. When we asked the public how they see the scientific controversy between the coalition and the opposition experts, they expressed support for opposition policies on matters related to the implications of the lockdowns and to transparency, while supporting government policy mainly on topics related to vaccinations. The research findings also indicate that personal and socio-demographic variables can influence how the public responds to the debate between experts. The main differentiating variables were the personal attribute of conservatism, locus of control, age, and nationality. CONCLUSION: Controversy must be encouraged to prevent misconceptions. The internal discourse in the committees that advise the government must be transparent, and coalition experts must be consistently exposed to the views of opposition experts, who must be free to voice their views without fear.