Mental Health Management of English Teachers in English Teaching Under the COVID-19 Era

Ding, Yiling; Wang, Tianhua

doi:10.3389/fpsyg.2022.916886

“…Under the positive influence of big data technology, many colleges and universities in our country have introduced the Internet and mobile phones into English classrooms, and a variety of online classes have been created to facilitate students to learn English anytime and anywhere, thus improving the efficiency of English teaching [11][12]. It is because of a series of changes that the role of college English teaching begins to change, and students change from passive recipients to active learners.…”

Section: Community Participation In Teachingmentioning

confidence: 99%

The Impact of Network Teaching Mode on Teaching Quality in The Context of Big Data: A Case Study of College Foreign Languages

Lin

2024

jes

0

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Under the heritage of massive data, community education has been extensively used in the area of education and has an essential effect on education quality. Taking university English education as an example, this paper analyzes the impact of community instructing mode on education quality. First of all, the paper introduces the influencing elements of community instructing fantastic below the heritage of massive data. Secondly, primarily based on regular differential equation (ODE), particle swarm optimization (PSO), and least square help vector computing device (LSSVM), a university English educating great assessment mannequin is constructed, and the impact of English educating in a positive college is tested. The effects exhibit that in contrast with different present comparison systems, the proposed assessment mannequin has benefits in pace and accuracy, and the contrasting impact is the best.

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“…Several works studied psychological effects of COVID-19 pandemic on students and the education sector. Ding et al [29] studied the mental health of English teachers during the outbreak of coronavirus. Huckins et al [30] investigated whether the behavioral patterns and mental health of students in college have changed in response to the pandemic of COVID-19 and whether these changes are associated with news related to COVID-19.…”

Section: Covid-19 and Psychological Healthmentioning

confidence: 99%

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses

Alswedani¹,

Mehmood²,

Katib³

et al. 2023

Preprint

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Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment, however, more important is to remove the root causes of mental illnesses because doing so can help prevent mental health problems from occurring or recurring. This requires a holistic approach to understanding mental health issues that are missing from the existing research. Mental health should be understood in the context of social and environmental factors. More research and awareness are needed, as well as interventions to address root causes. The effectiveness and risks of medications should also be studied. This paper proposes a big data and machine learning-based approach for the automatic discovery of parameters related to mental health from Twitter data. The parameters are discovered from three different perspectives, Drugs & Treatments, Causes & Effects, and Drug Abuse. We used Twitter to gather 1,048,575 tweets in Arabic about psychological health in Saudi Arabia. We built a big data machine learning software tool for this work. A total of 52 parameters were discovered for all three perspectives. We defined 6 macro-parameters (Diseases & Disorders, Individual Factors, Social & Economic Factors, Treatment Options, Treatment Limitations, and Drug Abuse) to aggregate related parameters. We provide a comprehensive account of mental health, causes, medicines and treatments, mental health and drug effects, and drug abuse, as seen on Twitter, discussed by the public and health professionals. Moreover, we identify their associations with different drugs. The work will open new directions for social media-based identification of drug use and abuse for mental health, as well as other micro and macro factors related to mental health. The methodology can be extended to other diseases and provides a potential for discovering evidence for forensics toxicology from social and digital media.

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“…Several works studied psychological effects of COVID-19 pandemic on students and the education sector. Ding et al [30] studied the mental health of English teachers during the outbreak of coronavirus. Huckins et al [31] investigated whether the behavioral patterns and mental health of students in college have changed in response to the pandemic of COVID-19 and whether these changes are associated with news related to COVID-19.…”

Section: Covid-19 and Psychological Healthmentioning

confidence: 99%

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses

Alswedani¹,

Mehmood²,

Katib³

et al. 2023

Preprint

View full text Add to dashboard Cite

Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment, however, more important is to remove the root causes of mental illnesses because doing so can help prevent mental health problems from occurring or recurring. This requires a holistic approach to understanding mental health issues that are missing from the existing research. Mental health should be understood in the context of social and environmental factors. More research and awareness are needed, as well as interventions to address root causes. The effectiveness and risks of medications should also be studied. This paper proposes a big data and machine learning-based approach for the automatic discovery of parameters related to mental health from Twitter data. The parameters are discovered from three different perspectives, Drugs & Treatments, Causes & Effects, and Drug Abuse. We used Twitter to gather 1,048,575 tweets in Arabic about psychological health in Saudi Arabia. We built a big data machine learning software tool for this work. A total of 52 parameters were discovered for all three perspectives. We defined 6 macro-parameters (Diseases & Disorders, Individual Factors, Social & Economic Factors, Treatment Options, Treatment Limitations, and Drug Abuse) to aggregate related parameters. We provide a comprehensive account of mental health, causes, medicines and treatments, mental health and drug effects, and drug abuse, as seen on Twitter, discussed by the public and health professionals. Moreover, we identify their associations with different drugs. The work will open new directions for social media-based identification of drug use and abuse for mental health, as well as other micro and macro factors related to mental health. The methodology can be extended to other diseases and provides a potential for discovering evidence for forensics toxicology from social and digital media.

show abstract

Mental Health Management of English Teachers in English Teaching Under the COVID-19 Era

Cited by 4 publications

References 25 publications

The Impact of Network Teaching Mode on Teaching Quality in The Context of Big Data: A Case Study of College Foreign Languages

The Impact of Network Teaching Mode on Teaching Quality in The Context of Big Data: A Case Study of College Foreign Languages

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses

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