Performance of the World Health Organisation suspected COVID-19 case definition in cluster-associated and sporadic SARS-CoV-2 transmission in Malaysia.

INTRODUCTION: Cluster-associated transmission has contributed to the majority of COVID-19 cases in Malaysia. Although widely used, the performance of the World Health Organization (WHO) case definition for suspected COVID19 in environments with high numbers of such cases has not been reported. MATERIALS AND METHODS: All suspected cases of COVID-19 that self-presented to hospitals or were cluster screened from 1st April to 31st May 2020 were included. Positive SARS-CoV-2 rRT-PCR was used as the diagnostic reference for COVID-19. RESULTS: 540 individuals with suspected COVID-19 were recruited. Two-third of patients were identified through contact screening, while the rest presented sporadically. Overall COVID-19 positivity rate was 59.4% (321/540) which was higher in the cluster screened group (85.6% vs. 11.6%, p<0.001). Overall, cluster-screened COVID-19 cases were significantly younger, had fewer comorbidities and were less likely to be symptomatic than those present sporadically. Mortality was significantly lower in the cluster-screened COVID-19 cases (0.3% vs. 4.5%, p<0.05). A third of all chest radiographs in confirmed COVID-19 cases were abnormal, with consolidation, ground-glass opacities or both predominating in the peripheral lower zones. The WHO suspected case definition for COVID-19 accurately classified 35.4% of all COVID-19 patients, a rate not improved by the addition of baseline radiographic data. Misclassification rate was higher among the cluster-associated cases (80.6%) compared to sporadic cases (35.3%). CONCLUSION: COVID-19 cases in Malaysia identified by active tracing of community cluster outbreaks had lower mortality rate. The WHO suspected COVID-19 performed poorly in this setting even when chest radiographic information was available, a finding that has implications for future spikes of the disease in countries with similar transmission characteristics.

Synchronising Online Resource (Penzu) and Computer Application for Language Instructions: A Pakistani Post Covid-19 Pandemic Context

Pakistan is going through a period of transition after Covid-19 pandemic situation which created a dire need to use computer as a tool and other online resources in the classrooms. To contribute to this situation, the present study investigated the effects of using computer as a tool and Penzu software as online source for language instructions. The study used experimental design and conducted a classroom experiment of 40 higher secondary school students ( 20 experimental & 20 in control group) through pre/post-tests over different period of time to examine development in students' writing skills. On post-test-I, it was observed that students in the control group showed sudden rise in the development of writing skills compared to experimental group. But, on post-test-II and III, students in the experimental group showed consistency in the development in writing skills while control group could not maintain their consistency of development in writings. Hence, findings of the study revealed that using computer as a tool for instructions and Penzu as online resource to conduct writing activities proved more useful in improving students' writing skills compared to the students in the control group. Finally, findings also revealed that students became more independent in self-corrections in the experimental group and continued to expand their learning outside the classroom while control group was dependent on teacher and could only find time in the classroom for corrective feedback which limited students' learning to their classroom. In addition to this, the study recommends that further computer applications and other online resources can be more useful in language instructions apart from teaching writing skills. Besides, findings of this study have significant theoretical and practical implications pertaining to EFL teachers' professional development, teaching skills and students' learning environment.

Lawful Instruction of Using Cali for Higher Secondary Level Students in Pakistan: The Post Covid-19 Context

Post-Covid-19 pandemic situation has created a dire need to use computer in the instructional methodology synchronising with other online resources in the classrooms. The present study was conducted to examine the effects of using computer synchronised by Penzu software as online source for teaching English to the higher secondary school students in Punjab, Pakistan. The study used experimental design and conducted a classroom experiment of 40 higher secondary school students (20 experimental & 20 in control group) through pre/post-tests over different period of time to examine development in students' writing skills. On post-test-I, it was observed that students in the control group showed sudden rise in the development of writing skills compared to experimental group. But, on post-test-II and III, students in the experimental group showed consistency in the development in writing skills while control group could not maintain their consistency of development in writings. Hence, findings of the study revealed that using computer as a tool for instructions and Penzu as online resource to conduct writing activities proved more useful in improving students' writing skills compared to the students in the control group. Finally, findings also revealed that students became more independent in self-corrections in the experimental group and continued to expand their learning outside the classroom while control group was dependent on teacher and could only find time in the classroom for corrective feedback which limited students' learning to their classroom. In addition to this, the study recommends that further computer applications and other online resources can be more useful in language instructions apart from teaching writing skills. Besides, findings of this study have significant theoretical and practical implications pertaining to EFL teachers' professional development, teaching skills and students' learning environment.

Anosmia Association with Covid-19 Risk Level among Staff: Validating the Covid-19 Health Risk Assessment System in A Malaysian University

Introduction: Anosmia has been increasingly recognized as one of the most important clinical symptom to be screened for the COVID-19 Objective: This study was conducted to determine the prevalence of anosmia and its association with COVID-19 risk level among staff in a higher education institution in Malaysia. Method(s): The data was obtained from COVID-19 risk assessment system implemented in the institution within four-month surveillance period from May to September 2020. The risk level was categorised into three levels namely low, moderate, and high depending on the staff reported symptoms and presence of epidemiological link. Pearson Chi Square analysis and Binary Logistic Regression were applied to assess possible association between anosmia and COVID-19 risk level. Result(s): A total of 1787 staff were involved in the analysis;1455 (81.4%) were categorized as low risk, 316 (17.7%) were medium risk and 16 (0.9%) were at high risk of contracting COVID-19. Out of 1787, 65 (3.6%) staff presented with anosmia. There was a statistically significant association between anosmia and COVID-19 risk level. Those with anosmia were 8.31 times more likely to be categorised under higher risk group (medium and high risk) compared to those without anosmia (Odds Ratio (OR): 8.31, beta =2.117, 95% Confidence Interval (CI): 4.94-13.99, p < 0.001). Conclusion(s): The COVID-19 risk assessment system is proven to be valid as it demonstrated anosmia association with higher COVID-19 risk level which is consistent the current epidemiological evidence on anosmia. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Development of Android-Controlled Ultraviolet Floor Sanitizer Robot

Ultraviolet (UV) light radiation is very dangerous as it can irritate human skin and eyes in which long and direct exposure can lead to skin and eyes cancer. However, Ultraviolet C (UVC) light with a wavelength between 207nm-222nm could sanitize in which inactivate the bacteria such as superbug (the pathogen that already built immunity against chemical sanitizer) and contribute to the fight against Covid-19 viruses. Therefore, this development of UV sanitizer is to sanitize surface area effectively with a human alert system in which will activate the buzzer, turn off the UV light and stop moving when human motion is detected. The notification also will be sent to the user whenever a human motion is detected as a 360° sanitization area to inactivate pathogens. The precaution to avoid any accident. The device is equipped with one UVC light which provides, the body has ultrasonic sensors to detect obstacles and provide autonomous movement to the device while the PIR sensor is used to detect human motion and activate the human alert system. As the result, the UVC light effectiveness is determined based on the bacteria growth in the petri dish. After the sanitization process, the bacteria are significantly reduced and killed effectively in low areas such as floors but reduce their efficiency to the high area. Thus, this device is time efficient and able to reduce the cost of sanitization compared to chemical sanitizer. © 2022 IEEE.

Towards Managing Covid-19 Using Artificial Intelligence and Big Data Analytics

Coronavirus Diseases (COVID-19) is an infectious disease caused by a newly discovered coronavirus that becomes world pandemic with 200 countries recorded affected, and nearly 1 million people died. Starting from Wuhan in December 2019, within three months, the spread across global with high reproduction rates (R Rates). There is evidence in one case, it spread to more than 100 people and creates his pandemic cluster. As the pandemic contributes to a large volume of data, Artificial Intelligence (AI) and Big Data Analytics (BDA) play a huge role in understanding the pan-demic to help necessary action can be deployed. Researchers and developers are increasingly using artificial intelligence, machine learning, and natural language processing to track and contain coronavirus and gain a more comprehensive understanding of the disease. So far, due to new diseases, there is a limited study to cover how AI and BDA will help in fighting COVID-19. Therefore, we provide a comprehensive analysis of the existing and potential of using AI and BDA to manage the COVID-19 outbreak based on COVID-19 Outbreak Life Cycle phases;detection, spread, management, recovery. We also presented the challenges needed to be overcome for BI in BDA in the fighting. To conclude, these findings show the necessity of AI and BDA as a critical tool to understand COVID-19 and there a lot of ongoing intensive works have been carried out to cope with COVID-19. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Disseminating Information Through Social Media During Covid-19 Pandemic Among University Students

The current rate of technological innovation makes it easier to convey data from one person to another. As technology progresses, it becomes easier for everyone to access social media, to the point where some news organisations seek to exploit it as a news source. Meanwhile, in order to avoid public panic, it is critical to educate society at a young age about the impact of fake news on social media. The purpose of this study is to explain the purpose of social media usage and to investigate whether the use of social media platforms to disseminate information has increased the spread of fake news in Malaysia, as well as the effect of information disseminated among university students during the COVID pandemic. Social media is well-known for its ease of use, particularly among young people, in sharing and expressing their opinions on domestic and international topics. Using social media has become second nature to us, particularly during the COVID-19 pandemic. Because of the strength of social media, the public's opinion of finding information during a lockdown is quite positive. The study was carried out in a qualitative manner. The researcher gathered all of the data by asking the participants general research questions. The method employed to obtain the results was an in-depth interview. The findings revealed that information disseminated via social media was successful in raising awareness during the pandemic, particularly among university students. According to the findings, certain scientific and technical advancements should benefit the global community rather than be manipulated in order to obtain accurate and true knowledge;society must be astute. False knowledge would have negative repercussions, and society would inevitably exist in a state of deception. Obtaining reliable information during the COVID-19 pandemic is critical to ensuring that individuals become social media literate in the future. © 2022, Penerbit Universiti Kebangsaan Malaysia. All rights reserved.

A Detecting Technique for the Climatic Factors that Aided the Spread of COVID-19 using Deep and Machine Learning Algorithms

Novel Coronavirus (COVID-19) is viewed as one of the main general wellbeing theaters on the worldwide level all over the planet. Because of the abrupt idea of the flare-up and the irresistible force of the infection, it causes individuals tension, melancholy, and other pressure responses. The avoidance and control of the novel Covid pneumonia have moved into an imperative stage. It is fundamental to early foresee and figure of infection episode during this troublesome opportunity to control of its grimness and mortality. The entire world is investing unimaginable amounts of energy to fight against the spread of this lethal infection. In this paper, we utilized machine learning and deep learning techniques for analyzing what is going on utilizing countries shared information and for detecting the climate factors that effect on spreading Covid-19, such as humidity, sunny hours, temperature and wind speed for understanding its regular dramatic way of behaving alongside the forecast of future reachability of the COVID-2019 around the world. We utilized data collected and produced by Kaggle and the Johns Hopkins Center for Systems Science. The dataset has 25 attributes and 9566 objects. Our Experiment consists of two phases. In phase one, we preprocessed dataset for DL model and features were decreased to four features humidity, sunny hours, temperature and wind speed by utilized the Pearson Correlation Coefficient technique (correlation attributes feature selection). In phase two, we utilized the traditional famous six machine learning techniques for numerical datasets, and Dense Net deep learning model to predict and detect the climatic factor that aide to disease outbreak. We validated the model by using confusion matrix (CM) and measured the performance by four different metrics: accuracy, f-measure, recall, and precision.

Telafer University’s Experiment in E-learning as Vague Neutrosophic Experiment

This paper is dedicated to studying the stages that Telafer University has gone through at using E-learning. The challenges of converting traditional learning (i.e. classical learning with realistic student attendance in their teaching programs) to E-learning over google classrooms. The efforts to maintain the quality teaching and their outcomes were a very ambiguous experiment that led the authors after more than two years for spreading the Covid-19 Pandemic to evaluate the University's performance using the most modern mathematical tools in uncertainty systems that called the Neutrosophic theory and logic. Finally, the flexibility of the neutrosophic mathematical methods has been applied to analyze the recorded issued data of E-learning in the University. © 2022, Neutrosophic Sets and Systems.All Rights Reserved.

CORONAVIRUS EXACERBATES XENOPHOBIA: DECONSTRUCTING OTHERNESS IN THE TWITTER

Free speech is not a licence for racists to spread racist propaganda. However, the outbreak of COVID-19 and its subsequent dissemination through social media has left a shock wave of disbelief resulting xenophobia in society. By looking from the lens of 'Othering,' this study tries to delve into revealing the representation of xenophobia resulting otherness amidst Twitter during the COVID-19 pandemic. This study considers a set of tweets related to #clustertabligh and several types related to the tabligh cluster to represent the otherness. The data were collected through a random sampling technique using machine learning tools Twitter API and processed using JSON format. The results lead to a discussion of power between social networks by intertwining the machine learning tools in social science and humanities studies. This study also looks at blame allotting, a typical social reaction to an outbreak, and an even more typical general media system. Malaysia needs to take actions by recognizing the distinctive levels of hateful racial online content brewing and addressing it systematically and proportionately. (C) 2021 Published by European Publisher.

Identification of warning signs in Malaysian patients having COVID-19 infection who progress to severe form of the illness

INTRODUCTION: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by a novel coronavirus, now widely known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has caused 3 major pandemic waves in Malaysia. We aimed to identify the warning signs as indicators that predict the progression of disease. MATERIALS AND METHODS: This is a retrospective cohort study of adult patients more than 12 years of age presenting with laboratory-confirmed COVID-19 admitted in three separate hospitals around the country. RESULTS: Of the 228 patients initially admitted with mild illness, 47 had progressed requiring oxygen. The median time from admission to deterioration was 3 days (IQR 2 - 5). Age more than ≥50years old (median age = 42.5, IQR = 28.8 - 57.0), higher temperature (mean = 37.3, IQR 36.8 - 38.0), MEWS score >3 (9, 19.1%), Neutrophil-to-lymphocyte ratio (NLR) >3.13 , (18, 38.3%) C-reactive protein (CRP) >5. (12, 27.3%), multiple zonal involvement on the chest radiography on admission (2, IQR 1-3) were more common in the deteriorated group on admission. On multivariate analysis, multiple comorbidities (HR = 7.40, 95 percent CI 2.58-21.2, p0.001), presence of persistent fever (HR = 2.88, 95 percent CI 1.15 - 7.2, p = 0.024), MEWS scoring >3 (HR of 6.72 ;95 percent CI 2.81-16.0, p0.001) were associated with progression to severe illness. CONCLUSION: In our cohort, we found that several factors were associated with the severity of COVID19. Early detection of these factors could correctly identify patients who need more intensive monitoring, and early referral for ICU care.

Covid-19 Pandemic: Strategies to Improve Daylighting and Visual Comfort for Building Occupants

Sufficient lighting has a substantial impact on the health, comfort, and performance of building occupants. Researchers frequently focus on daylighting for its psychological, physiological, and economic benefits to human well-being. However, the COVID-19 pandemic demonstrated that these wellness considerations are no longer optional features of a building, but rather a necessary component of providing a comfortable and healthy living environment. Everyone must adhere to the stay-at-home order to mitigate pandemic transmission. This study aims to review the literature and recommends strategies that will improve building occupants’ daylighting and visual comfort. For the review, this study identified 41 peer-reviewed journal articles using a keyword search followed by a filter based on SCOPUS and Web of Science inclusion criteria. However, once the inclusion and exclusion criteria were applied, only 31 papers were chosen for evaluation. Thematic analysis of these 31 publications revealed eight tentative criteria for effective daylighting in buildings, categorised into three clusters: passive design, active design, and projected ideal daylighting based on daylight simulation tests. The results demonstrate that a passive design strategy provides improved illumination and is a more cost-effective way to achieve appropriate daylight and visual comfort in a facility. Despite its limitations, the study recommends the hybrid technique of passive and active design as a helpful experimental tool for future research targeted to increase the interior environment’s quality. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Coronavirus exacerbates xenophobia: Consciousness of Twitter posting during the pandemic

Free speech is not a license for racists to spread propaganda. However, the outbreak of COVID-19 and its subsequent spread across the globe has left a shocking wave of disbelief resulting in an upsurge of xenophobia in the society. Racism is a system of dominance and power designed to uphold the racially privileged. This study delves into the consciousness of Twitter postings during the COVID-19 pandemic and deconstructs the power dynamics in the hashtags used. The study's data was analysed using Twitter Application Programming Interface (API) to identify the representation within tweet sample sets. The study concludes that social interactions on Twitter constructs power dynamics and these shared values create a new form of power resistance and subjugated knowledge. This leads to a discussion of power between social media intertwined with the machine learning tools in social science and humanities studies. This study contributes to the academic debates about the public sphere and social media's role in constructing meaning in cultural and social change. It also suggests that Twitter develops policies to prohibit hate speech and impose regulations to ensure that online spaces remain civil, safe, and democratic.

Analysing Trends and Forecasting of COVID-19 Pandemic in Malaysia using Singular Spectrum Analysis

The Singular Spectrum Analysis (SSA) is a powerful non-parametric time series analysis that has demonstrated its capability in forecasting different time series in various disciplines. SSA falls in the framework of data-driven modelling of dynamical system which does not rely on any underlying assumption except the inherent dynamics which are captured over time. The capabilities of SSA are mainly aff orded by its direct connection to the singular value decomposition (SVD). It is generally accepted that SVDbased methods are very affective for the noise reduction in deterministic time series and consequently for forecasting, as well as for extracting trends and structures. Despite its strength, several shortcomings of SSA in the analysis of COVID-19 time series have been reported in the literature. The aim of this paper is to determine the scope of this limitation and we confine our investigation in the analysis and forecasting of COVID-19 Pandemic in Malaysia. We scrutinize the results fromthe SSA analysis of the number of daily confirmed cases to gain further insight into the intrinsic trends of the pandemic. Groupings of the singular spectra that contributes to different features of the pandemic time series are identified using analysis of the singular value spectrum, periodogram analysis and analysis of the weighted correlation matrix. It was revealed that under stationary conditions, the principal eigentriple is sufficient to produce reliable forecast. However, in non-stationary conditions, for example during a movement control order, it is useful to also study the minor eigentriples which could contain transient dynamics that may persist.

Emerging themes in facebook and twitter before movement control order (MCO) in Malaysia

Social media’s potential to directly interact with the public and stakeholders is huge and pertinent, especially during a health crisis. This research applied the phenomenological approach to explore themes related to COVID-19 that emerged on Facebook and Twitter before the Movement Control Order (MCO)(1 January-17 March 2020). For this purpose, the top 10 influencers/pages from Facebook and Twitter, including The Ministry of Health’s social account were selected, pooling around 51 million Malaysian Facebook and Twitter users and engaging around 6,068 mentions. The thematic analysis reveals that a number of health, politics, economic and policy issues emerged before the Malaysian government enforced the MCO on 18 March 2020. The themes that emerged varied according to the situation and the early impact of the COVID-19 pandemic. The findings enable us to understand better public sentiment and the possible different points of view regarding the dissemination of COVID-19 related information on social media platforms. These insights can help government health agencies to connect effectively with the public about health and relevant preventive measures. Specifically, this can support public health stakeholders in developing tailored strategies to monitor and prevent the COVID-19 spread. © SEARCH Journal 2021.

Risk factors associated with severe covid19 illness in kidney transplant recipients

Purpose: COVID19 is an acute respiratory infection that is caused by the SARSCOV-2 that has been shown to be highly contagious and poses a significant mortality risk. Kidney transplant recipients are shown to be at increased risk of acquiring and developing a severe form of the disease compared to the general population. There is limited evidence to guide the transplant community on methods to reduce disease severity. We aim to evaluate risk factors associated with severe [requiring hospitalization] or critical [requiring ICU care] COVID-19 illness in kidney transplant recipients. Methods: We evaluated kidney transplant recipients with COVID19 between February to August 2020. Among 748 recipients followed at our center, 43 recipients (5.7%) were diagnosed with COVID19 infection through nasopharyngeal swab PCR. Of those, 9 patients were treated within an isolation facility, 25 patients admitted to the hospital and 9 patients were admitted to the intensive care unit (ICU). We evaluated demographic, clinical and laboratory factors to evaluate severity of illness by using Kruskal-Wallis for continuous variables and chi square test for categorical. Results: Older age was associated with ICU admission (57 vs. 53 vs. 45 P=0.03) while gender, ethnicity and type of transplant were similar between the three groups (Table 1). In addition, CNI level, MMF dose or base line creatinine was not significantly different between the three groups. Presentation with fever, shortness of breath and hypoxia were more frequent in ICU group. Laboratory findings of lymphopenia, low Albumin, high CRP and high procalcitonin at presentation were also more frequent in ICU group. Treatment with hydroxychloroquine, Oseltamivir, Ritonavir, Azithromycin, and reduction of immunosuppression were more frequent in ICU (table 2). We observed 14 patients with graft dysfunction and majority were in ICU group. Furthermore, in the ICU group, 3 recipients required renal replacement therapy and of those there was a single death. Conclusions: Severity of COVID19 infection is variable among our transplant population. Prognostication of COVID19 severity in kidney transplant recipient is crucial for early recognition of critical illness and may offer the benefit of early therapy such as antiviral or immunosuppression reduction in this high-risk group.

Practice Of Proper Handwashing And Its Associated Factors Among Staff In A Malaysian University

In higher education setting throughout the world, the practise of handwashing among staff is essential, particularly in the period of COVID-19 pandemic. Despite the overwhelming evidence on the effectiveness of proper handwashing, the knowledge, attitude and practice of handwashing among the staff of higher education have not been well investigated. Consequently, a cross-sectional study among staff in a university in Malaysia was conducted to identify the prevalence of proper handwashing and its associated factors. The data was collected using questionnaires in Google form from 18th June to 21st June 2020. Statistical analyses involved simple and multiple logistic regression with backward likelihood ratio method. Out of 349 participants, 31.8% (95% CI: 26.9,36.7) had proper handwashing practice. The results of the multivariable analysis revealed that the total knowledge scores (OR: 1.04, 95% CI: 1.001, 1.071) and the total attitude scores (OR: 1.23, 95% CI: 1.152, 1.321) were found to be significantly associated with proper handwashing practice among staff. Our study suggests that having the right knowledge and favourable attitudes are crucial towards achieving the proper handwashing practise. Additional supports for promoting a conducive ecosystem may also likely be needed to sustain a long-term practice of proper handwashing. © 2021, Malaysian Journal of Public Health Medicine. All Right Reserved.

Learning about English language lecturers' resilience: Identification of stress and coping strategies of open and distance learning (ODL)

The sudden shift of tertiary teaching and learning environment due to the Covid-19 pandemic outbreak has provided great challenges to educators globally. The purpose of this case study is to identify the source of stress and its consequences among English language lecturers of a Malaysian public university teaching in the ODL environment during the Movement Control Order period as well as their coping strategies to overcome occupational stress. The lived experiences of the participants were explored through in-depth semi-structured interviews. The data gleaned were thematically analysed for gaining insights into the phenomenon under study. Results indicate that even though the participants are familiar with the integration of technology in blended learning model, the stress is sourced from inadequate preparation time and teaching materials for the full implementation of ODL, and the struggle of maintaining work-life balance due to managing other commitments in work-from-home mode. The present study identified personal, social and professional coping strategies were utilised by participants to cope with the stress and solve arisen issues during ODL sessions. The results have given insights into the participants' resilience in ODL practices and could offer recommendations to in-service professional development programmes, training and stress management courses for lecturers. The limitations and recommendations for future studies were also discussed. © 2021 Author(s).

English lecturers' self-efficacy beliefs in open and distance learning (ODL): Substantive implications

The enforcement of Movement Control Order (MCO) in Malaysia due to COVID-19 pandemic has affected the education sector where the teaching and learning process is instructed to practice open and online distance learning (ODL). The purpose of this qualitative case study is to explore the English language lecturers in one Malaysian public university describe their self-efficacy beliefs in ODL practice. Purposive sampling method was used to recruit prospective participants. Semi-structured interviews were used as the primary data collection method. The data gathered were then analysed using thematic data analysis. The results indicate that despite having the compulsory implementation of ODL within a short notice, the participants disclosed that their sense of self-efficacy beliefs varied depending on context-specific nature based on several domains including self-assurance, technological pedagogical content knowledge (TPCK), teaching preparation, intrinsic motivation and administration support. The present study also reveals that participants utilised emotion-driven self-efficacy beliefs to overcome ODL challenges and eventually developed social-emotional rewards for staying positive in ODL practices. It was also found that self-efficacy beliefs contributed to students' positive performance, and this has become a factor in heightening participants' self-efficacy beliefs. The results have provided enlightenment on participants' self-efficacy beliefs in ODL practices and offer recommendations for improvement in tertiary educational practices to bring positive impacts on teaching and learning. © 2021 Author(s).

Exploring the impacts of covid-19 on oil and electricity industry

The COVID-19 Pandemic has dramatically influenced the global market of energy production and consumption. This influence could be noticed obviously by the latest drop in crude oil prices. Furthermore, coronavirus has affected the supply chains and delayed the development of sustainable energy worldwide. Due to its relevance, academics have begun to study the associations regarding this crisis. The COVID-19 Pandemic offers a new chance to investigate the impacts of prolonged landscape-scale confusion on sustainability change paths in real-time. How the global renewable energy flexibility sector will respond to the COVID-19 Pandemic is a critical question. This crisis could inspire governance structures to plan adequately for other varieties of crises in the future. These improvements can drive research by spouting the generation of new disciplines stemming from the COVID-19 outbreak to expedite sustainability transitions and improve the recognition of governance's main role in changes. Smart policies could transform COVID-19 threats into great opportunities for the world's sustainable energy scenario towards green energy generation and use in the coming years. In this paper, the impacts of COVID-19 in terms of the energy sector, especially the electricity and oil sectors, will be explained. The major objective of this research is to shed light on future research on renewable energy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.