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1.
Gerontol Geriatr Educ ; : 1-11, 2022 Nov 09.
Article in English | MEDLINE | ID: covidwho-2106859

ABSTRACT

Online activities have spiked due to the COVID-19 pandemic, including language learning activities. As the world is aging, this affects senior citizens too. Yet, few studies have been conducted studying online (language) learning in this age-group. Moreover, no concrete pointers exist on how to go about such an online language learning course. This paper examines what should be considered when designing and implementing online language learning courses for seniors. To that end we present data from 73 senior language learners from two independent language learning contexts: the Netherlands and Scotland. The data were collected between May 2020 and August 2021. Data includes spoken and written samples from lessons, focus groups, interviews and questionnaires. Given the qualitative nature of the data and the aim of identifying patterns of meaning across the respective datasets, a reflexive thematic analysis (TA) approach was adopted. We employed an inductive approach to coding, using both semantic (explicit or overt) and latent (implicit, underlying) coding frameworks, in order to inform two overarching themes: "Navigating the digital highway" and "Camera ready for new friends." We discuss these themes and their sub-themes and arrive at concrete recommendations for the third-age language learning classroom.

2.
Revista Medica Clinica Las Condes ; JOUR(5):450-457, 33.
Article in English | Web of Science | ID: covidwho-2105844

ABSTRACT

Developmental language disorder is a diagnostic challenge in early stages of development, so its adequate approach and intervention improves the prognosis of this group of patients who are often diagnosed late, especially recently in the context of the COVID-19 pandemic. This article seeks to provide tools that promote understanding its importance, as well as allowing parents to be given strategies that promote language and communication skills in the early stages of their children's development.

3.
J Med Internet Res ; 24(11): e34067, 2022 Nov 02.
Article in English | MEDLINE | ID: covidwho-2098982

ABSTRACT

BACKGROUND: Evidence from peer-reviewed literature is the cornerstone for designing responses to global threats such as COVID-19. In massive and rapidly growing corpuses, such as COVID-19 publications, assimilating and synthesizing information is challenging. Leveraging a robust computational pipeline that evaluates multiple aspects, such as network topological features, communities, and their temporal trends, can make this process more efficient. OBJECTIVE: We aimed to show that new knowledge can be captured and tracked using the temporal change in the underlying unsupervised word embeddings of the literature. Further imminent themes can be predicted using machine learning on the evolving associations between words. METHODS: Frequently occurring medical entities were extracted from the abstracts of more than 150,000 COVID-19 articles published on the World Health Organization database, collected on a monthly interval starting from February 2020. Word embeddings trained on each month's literature were used to construct networks of entities with cosine similarities as edge weights. Topological features of the subsequent month's network were forecasted based on prior patterns, and new links were predicted using supervised machine learning. Community detection and alluvial diagrams were used to track biomedical themes that evolved over the months. RESULTS: We found that thromboembolic complications were detected as an emerging theme as early as August 2020. A shift toward the symptoms of long COVID complications was observed during March 2021, and neurological complications gained significance in June 2021. A prospective validation of the link prediction models achieved an area under the receiver operating characteristic curve of 0.87. Predictive modeling revealed predisposing conditions, symptoms, cross-infection, and neurological complications as dominant research themes in COVID-19 publications based on the patterns observed in previous months. CONCLUSIONS: Machine learning-based prediction of emerging links can contribute toward steering research by capturing themes represented by groups of medical entities, based on patterns of semantic relationships over time.


Subject(s)
COVID-19 , Humans , Machine Learning , Semantics , Supervised Machine Learning
4.
J Clin Nurs ; 2022 Nov 01.
Article in English | MEDLINE | ID: covidwho-2097823

ABSTRACT

AIMS AND OBJECTIVES: This study aimed (a) to identify the communication issues and problems faced by individuals with hearing impairment (HI)/deafness during the COVID-19 pandemic and (b) to describe strategies to overcome the issues/problems and/or prevent their negative impact. BACKGROUND: Individuals with mild or severe HI face everyday communication problems, which have been worsened during the COVID-19 pandemic. However, no studies have summarised the available evidence to better understand the communication challenges faced by them and strategies allowing better interactions. The long duration of the outbreak-more than 2 years, with policies that have just been lifted in some countries-and the possible return of restrictions in the next Winter suggest the need to summarise evidence in the field. DESIGN AND METHODS: A rapid review is reported here in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Medline, CINAHL and Scopus databases were searched, including (a) primary or secondary studies published from January 2020 to 12 January 2022, (b) involving individuals with HI/deafness, (c) during the COVID-19 pandemic and (d) written in English. Data were extracted and summarised by using a content analysis approach. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution. RESULTS: Fourteen studies were included as follows: three non-systematic reviews, seven cross-sectional, three quasi- experimental and one qualitative study, performed mainly in the US and the UK. Face mask covering use; physical and social distancing; and information, education, rehabilitation, and healthcare accessibility have emerged as the main challenges triggering consequences such as social isolation, loneliness, poor knowledge regarding the prevention and mental health issues. Strategies mitigating these challenges are as follows: (a) adopting transparent face masks, (b) using basic skills while interacting (e.g. maintaining eye contact), (c) improving the availability of sign language interpreters, (d) allowing the presence of family members and (e) teaching basics of sign language to healthcare professionals. CONCLUSIONS AND RELEVANCE TO CLINICAL PRACTICE: Individuals with HI/deafness live with several challenges, suggesting that their vulnerability has increased tremendously during the COVID-19 pandemic. The effectiveness of strategies to overcome these difficulties should be scrutinised by conducting more research. Moreover, there should be increased awareness among all citizens by equipping them with simple strategies to communicate effectively with individuals with HI, an approach that may increase inclusiveness and prevent further negative consequences and burden.

5.
JMIR Hum Factors ; 8(2): e26043, 2021 Jun 09.
Article in English | MEDLINE | ID: covidwho-2098981

ABSTRACT

BACKGROUND: As COVID-19 poses different levels of threat to people of different ages, health communication regarding prevention measures such as social distancing and isolation may be strengthened by understanding the unique experiences of various age groups. OBJECTIVE: The aim of this study was to examine how people of different ages (1) experienced the impact of the COVID-19 pandemic and (2) their respective rates and reasons for compliance or noncompliance with social distancing and isolation health guidance. METHODS: We fielded a survey on social media early in the pandemic to examine the emotional impact of COVID-19 and individuals' rates and reasons for noncompliance with public health guidance, using computational and content analytic methods of linguistic analysis. RESULTS: A total of 17,287 participants were surveyed. The majority (n=13,183, 76.3%) were from the United States. Younger (18-31 years), middle-aged (32-44 years and 45-64 years), and older (≥65 years) individuals significantly varied in how they described the impact of COVID-19 on their lives, including their emotional experience, self-focused attention, and topical concerns. Younger individuals were more emotionally negative and self-focused, while middle-aged people were other-focused and concerned with family. The oldest and most at-risk group was most concerned with health-related terms but were lower in anxiety (use of fewer anxiety-related terms) and higher in the use of emotionally positive terms than the other less at-risk age groups. While all groups discussed topics such as acquiring essential supplies, they differentially experienced the impact of school closures and limited social interactions. We also found relatively high rates of noncompliance with COVID-19 prevention measures, such as social distancing and self-isolation, with younger people being more likely to be noncompliant than older people (P<.001). Among the 43.1% (n=7456) of respondents who did not fully comply with health orders, people differed substantially in the reasons they gave for noncompliance. The most common reason for noncompliance was not being able to afford to miss work (n=4273, 57.3%). While work obligations proved challenging for participants across ages, younger people struggled more to find adequate space to self-isolate and manage their mental and physical health; middle-aged people had more concerns regarding childcare; and older people perceived themselves as being able to take sufficient precautions. CONCLUSIONS: Analysis of natural language can provide insight into rapidly developing public health challenges like the COVID-19 pandemic, uncovering individual differences in emotional experiences and health-related behaviors. In this case, our analyses revealed significant differences between different age groups in feelings about and responses to public health orders aimed to mitigate the spread of COVID-19. To improve public compliance with health orders as the pandemic continues, health communication strategies could be made more effective by being tailored to these age-related differences.

6.
J Exp Child Psychol ; 226: 105580, 2022 Nov 05.
Article in English | MEDLINE | ID: covidwho-2095613

ABSTRACT

Face mask wearing was an important preventative strategy for the transmission of the COVID-19 virus. However, the effects that occluding the mouth and nose area with surgical masks could have on young children's language processing and emotion recognition skills have received little investigation. To evaluate the possible effects, the current study recruited a sample of 74 children from the North West of England (aged 4-8 years). They completed two computer-based tasks with adults wearing or not wearing surgical face masks to assess (a) language processing skills and (b) emotion recognition ability. To control for individual differences, age, sex, receptive vocabulary, early reading skills, and parent-reported social-emotional competence were included in analyses. The findings from the study highlighted that although younger children were less accurate than older children, face masks did not significantly impair basic language processing ability. However, they had a significant effect on the children's emotion recognition accuracy-with masked angry faces more easily recognized and masked happy and sad faces less easily recognized. Children's age and social-emotional skills also played a role. The findings suggest that the effects of face masks should continue to be evaluated.

7.
20th EURALEX International Congress, 2022 ; JOUR: 113-128,
Article in English | Scopus | ID: covidwho-2092621

ABSTRACT

Not only professional lexicographers, but also people without a professional background in lexicography, have reacted to the increased need for information on new words or medical and epidemio-logical terms being used in the context of the COVID-19 pandemic. In this study, corona-related glossaries published on German news websites are presented, as well as different kinds of responses from professional lexicography. They are compared in terms of the amount of encyclopaedic information given and the methods of definition used. In this context, answers to corona-related words from a German question-answer platform are also presented and analyzed. Overall, these different reactions to a unique challenge shed light on the importance of lexicography for society and vice versa. © 2022, European Association for Lexicography. All rights reserved.

8.
J Med Internet Res ; 24(11): e42261, 2022 Nov 17.
Article in English | MEDLINE | ID: covidwho-2089646

ABSTRACT

BACKGROUND: Since the first COVID-19 vaccine appeared, there has been a growing tendency to automatically determine public attitudes toward it. In particular, it was important to find the reasons for vaccine hesitancy, since it was directly correlated with pandemic protraction. Natural language processing (NLP) and public health researchers have turned to social media (eg, Twitter, Reddit, and Facebook) for user-created content from which they can gauge public opinion on vaccination. To automatically process such content, they use a number of NLP techniques, most notably topic modeling. Topic modeling enables the automatic uncovering and grouping of hidden topics in the text. When applied to content that expresses a negative sentiment toward vaccination, it can give direct insight into the reasons for vaccine hesitancy. OBJECTIVE: This study applies NLP methods to classify vaccination-related tweets by sentiment polarity and uncover the reasons for vaccine hesitancy among the negative tweets in the Serbian language. METHODS: To study the attitudes and beliefs behind vaccine hesitancy, we collected 2 batches of tweets that mention some aspects of COVID-19 vaccination. The first batch of 8817 tweets was manually annotated as either relevant or irrelevant regarding the COVID-19 vaccination sentiment, and then the relevant tweets were annotated as positive, negative, or neutral. We used the annotated tweets to train a sequential bidirectional encoder representations from transformers (BERT)-based classifier for 2 tweet classification tasks to augment this initial data set. The first classifier distinguished between relevant and irrelevant tweets. The second classifier used the relevant tweets and classified them as negative, positive, or neutral. This sequential classifier was used to annotate the second batch of tweets. The combined data sets resulted in 3286 tweets with a negative sentiment: 1770 (53.9%) from the manually annotated data set and 1516 (46.1%) as a result of automatic classification. Topic modeling methods (latent Dirichlet allocation [LDA] and nonnegative matrix factorization [NMF]) were applied using the 3286 preprocessed tweets to detect the reasons for vaccine hesitancy. RESULTS: The relevance classifier achieved an F-score of 0.91 and 0.96 for relevant and irrelevant tweets, respectively. The sentiment polarity classifier achieved an F-score of 0.87, 0.85, and 0.85 for negative, neutral, and positive sentiments, respectively. By summarizing the topics obtained in both models, we extracted 5 main groups of reasons for vaccine hesitancy: concern over vaccine side effects, concern over vaccine effectiveness, concern over insufficiently tested vaccines, mistrust of authorities, and conspiracy theories. CONCLUSIONS: This paper presents a combination of NLP methods applied to find the reasons for vaccine hesitancy in Serbia. Given these reasons, it is now possible to better understand the concerns of people regarding the vaccination process.

9.
Community Health Equity Res Policy ; : 2752535X221133140, 2022 Oct 25.
Article in English | MEDLINE | ID: covidwho-2089024

ABSTRACT

In this community-partnered study we conducted focus groups with non-English speaking immigrant and refugee communities of color in 4 languages to understand their perspectives on COVID-19 vaccines, barriers to accessing vaccines, and recommendations for healthcare providers. We used a mixed deductive-inductive thematic analysis approach and human centered design to guide data analysis. 66 individuals participated; 85% were vaccinated. The vaccination experience was often positive; however, participants described language inaccessibility, often relying on family members for interpretation. Community-based organizations played a role in connecting participants to vaccines. Unvaccinated participants expressed fear of side effects and belief in natural immunity. Participants shared recommendations to providers around increasing vaccine access, improving language accessibility, and building trust. Results from our study show numerous barriers immigrant and refugee communities of color faced getting their COVID-19 vaccine, but also highlights opportunities to engage with community partners. Future implications for research, policy, and practice are described.

10.
Augment Altern Commun ; : 1-12, 2022 Oct 26.
Article in English | MEDLINE | ID: covidwho-2087511

ABSTRACT

The closure of schools and healthcare facilities across the United States due to COVID-19 has dramatically changed the way that services are provided to children with disabilities. Little is known about how children who use augmentative and alternative communication (AAC), their families and their service providers have been impacted by these changes. This qualitative study sought to understand the perspectives of parents and speech-language pathologists (SLPs) on how COVID-19 has affected children, families, services providers and the delivery of AAC-related communication services. For the study, 25 parents and 25 SLPs of children who used aided AAC participated in semi-structured interviews, with data analyzed using qualitative thematic analysis. Parents and SLPs highlighted wide disparities in how children have been impacted, ranging from views of children making more progress with communication and language than before the pandemic to worries about regression. A complex system of factors and processes may explain these differences. COVID-19 will have lasting impacts on the lives of children with complex communication needs. This research highlights the crucial role of family-service provider partnerships and access to quality AAC services for children during the pandemic and into the future.

11.
Pravention und Gesundheitsforderung ; JOUR
Article in German | Scopus | ID: covidwho-2085545

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) pandemic has underscored the importance of real world data in everyday clinical practice and has highlighted some long-standing problems of our healthcare system such as gaps in primary data collection, hurdles in the evaluation of patient data, and complexity regarding the data exchange between different institutions. In addition, changes in physician–patient relationships such as transitions from a paternalistic to a partnership-based relationship model as well as increasing digitalization have shaped our modern understanding of healthcare, emphasizing the issue of patient autonomy and self-efficacy and highlighting the need for innovative, patient-centered approaches. Methods: Using the patient journey as a theoretical construct, we describe the collection of different types of real world data, their meaning and handling. Conclusion: Mapping the patient journey process combined with a widely used data standard can lead to the acquisition of primary data in the healthcare sector which can be used by all medical treatment institutions. This will lead to an exchange of valuable data between institutions and circuit the current problem of proprietary formats. Furthermore, the evaluation of patient-reported outcomes as a standard in the clinical routine could enhance patients’ autonomy and optimize treatment. Thus, the overall treatment effectiveness and survival of patients can be improved by creating a common data language and using a holistic, human-centered care approach through integrating perspectives of patients and their loved ones. © 2022, The Author(s).

12.
Turkish Online Journal of Distance Education ; JOUR(4), 23.
Article in English | Scopus | ID: covidwho-2083355

ABSTRACT

The coronavirus disease 2019 (Covid-19) outbreak has forced a sudden transition from face-to-face learning to online learning in higher education. This circumstance challenges university students to be more selfdirected in learning with relatively minimum assistance from their lecturers or peers. Therefore, it is becoming increasingly important to conduct a study on the issue of learner agency which remains little explored. The present study aimed at investigating the agency of first-year university students in online learning of Arabic as a foreign language. In particular, this study examines their intention, motivation, self-regulation and selfefficacy in online learning of Arabic delivered synchronously by using Google Meet and asynchronously by using Edmodo. An exploratory research method was employed in the study with the participation of 76 firstyear university students at an Islamic public university in Jakarta, Indonesia. Results of the study reveal that first-year university students have a relatively high intention, motivation, self-regulation and self-efficacy in Arabic online learning. Looking these findings into more detail, however, the students seem to have limited information and preparation to achieve their goals, are undermotivated to speak with native Arabic speakers, have shallow learning commitments, and are less likely to believe their performance. One of the practical implications that emerge from this study is to introduce first-year university students to a variety of strategies for learning Arabic in more self-directed ways, and this may be supported by lecturers as to not only delivering content but also promoting skills during their teaching practices. © 2022, Turkish Online Journal of Distance Education. All Rights Reserved.

13.
Estudios De Linguistica-Universidad De Alicante-Elua ; JOUR(38): 281-300,
Article in Spanish | Web of Science | ID: covidwho-2083198

ABSTRACT

The evolution of Terminology is joined to new technologies and the development of work platforms or interfaces that allow creating a technical glossary semi-automatically or even automatically. Terms and their properties are connected formally to the expression of knowledge of specialized fields in which they occur, so automatic approaches are not only faced with the task of determining which are the terminological units of a given field, but to express how such information is structured in their technical field. Most of the terms occurring in a scientific domain are also found in other disciplines and even in everyday language. Terms are often present on the lexical stock of languages and share with lexical units a complex set of relationships. Frame Semantics is a particularly attractive model for the terminological work, interested in accounting for the connection between the conceptual structure of a specialized field and the elements used to transmit this knowledge. This has led to many researchers to use FrameNet as a way of representing terminology. FrameNet is an online resource for English based on Frame Semantics and supported by corpus evidence. A frame is founded on the basis that certain words evoke certain situations in which particular participants take place. These situations or frames are stereotyped structures representing areas of sociocultural experience and knowledge. We present a statistical approach based on corpus able to select most representative FrameNet frames that best represent a set of electronic texts on COVID-19 and show which of their lexical units work as terminological units. Results confirm that this methodology can be a good support for terminographic work, since it not only allows the extraction of terminological units, but also the use of the FrameNet framework to structure this knowledge.

14.
International Journal of Bilingualism ; JOUR
Article in English | Web of Science | ID: covidwho-2082891

ABSTRACT

Aims and objectives/purpose/research questions: Very little is known to date about the long-term dynamics of balancing home and dominant languages by adult immigrants. Russian-speaking immigrants in Canada remain an underrepresented group with no available studies of their language development. To address these gaps, this article describes a linguistic journey experienced by Russian-speaking immigrants in Canada as they adapt to the life in the host country. The major objective of the study is to examine the importance of learning the host country's majority languages (English and French) vis-a-vis maintenance of the home language as seen by the participants in the beginning and after a few years of immigration. Design/methodology/approach: The article reports the results of a mixed-methods study involving an online survey and written narratives about language dynamics in immigration. Data and analysis: One hundred Russian-speaking immigrants from nine countries residing in seven Canadian provinces participated in the study. The analysis involves quantitative comparisons of responses involving correlation and chi-square tests as well as qualitative descriptions of the participants' linguistic experiences. Findings/conclusions: The results indicate that over the time since immigration, the importance of the English language learning decreases, and the importance of Russian language maintenance increases for the participants, whereas the salience of acquiring French remains unchanged. Originality: The new finding is the trajectory of the relationship between the participants' interest in the home language and culture maintenance and host languages and cultures learning over the years of immigration. Significance/implications: These results align with the authors' linguistic equilibrium hypothesis of language dynamics in immigration. The implications of the study involve long-term support of linguacultural needs of immigrant communities. Limitations: The research conducted during COVID-19 was limited in methods and would benefit from in-person interviews in future. Expanding the project to other immigrant groups for comparison is another direction for future research.

15.
Embase; 25.
Preprint in English | EMBASE | ID: ppcovidwho-346621

ABSTRACT

Background: Since the first year of the COVID-19 global pandemic, a hypothesis concerning the possible protection/immunity of beta-thalassemia carriers remains in abeyance. Method(s): Three databases (Pubmed Central, Scopus and Google Scholar) were screened and checked in order to extract all studies about incidence of confirmed COVID-19 cases OR mortality rate OR severity assessment OR ICU admission among patients with beta-thalassemia minor, were included in this analysis. The language was limited to English. Studies such as case reports, review studies, and studies that did not have complete data for calculating incidences were excluded. Results and discussion: Three studies upon 2265 were selected. According to our systematic-review meta-analysis, beta-thalassemia carriers could be less COVID-19 affected than general population [IRR= 0.9250(0.5752;1.4877)], affected by COVID-19 with a worst severity [OR=1.5933(0.4884;5.1981)], less admissible into ICU [IRR=0.3620(0.0025;51.6821)] and more susceptible to die from COVID-19 or one of its consequences [IRR=1.8542(0.7819;4.3970)]. However, all of those results stay insignificant with a bad p-value (respectively 0.7479, 0.4400, 0.6881, 0.1610). Other large case-control or registry studies are needed to confirm these trends. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.

16.
JMIR Med Inform ; 10(11): e37945, 2022 Nov 10.
Article in English | MEDLINE | ID: covidwho-2079974

ABSTRACT

BACKGROUND: The increasing availability of "real-world" data in the form of written text holds promise for deepening our understanding of societal and health-related challenges. Textual data constitute a rich source of information, allowing the capture of lived experiences through a broad range of different sources of information (eg, content and emotional tone). Interviews are the "gold standard" for gaining qualitative insights into individual experiences and perspectives. However, conducting interviews on a large scale is not always feasible, and standardized quantitative assessment suitable for large-scale application may miss important information. Surveys that include open-text assessments can combine the advantages of both methods and are well suited for the application of natural language processing (NLP) methods. While innovations in NLP have made large-scale text analysis more accessible, the analysis of real-world textual data is still complex and requires several consecutive steps. OBJECTIVE: We developed and subsequently examined the utility and scientific value of an NLP pipeline for extracting real-world experiences from textual data to provide guidance for applied researchers. METHODS: We applied the NLP pipeline to large-scale textual data collected by the Swiss Multiple Sclerosis (MS) registry. Such textual data constitute an ideal use case for the study of real-world text data. Specifically, we examined 639 text reports on the experienced impact of the first COVID-19 lockdown from the perspectives of persons with MS. The pipeline has been implemented in Python and complemented by analyses of the "Linguistic Inquiry and Word Count" software. It consists of the following 5 interconnected analysis steps: (1) text preprocessing; (2) sentiment analysis; (3) descriptive text analysis; (4) unsupervised learning-topic modeling; and (5) results interpretation and validation. RESULTS: A topic modeling analysis identified the following 4 distinct groups based on the topics participants were mainly concerned with: "contacts/communication;" "social environment;" "work;" and "errands/daily routines." Notably, the sentiment analysis revealed that the "contacts/communication" group was characterized by a pronounced negative emotional tone underlying the text reports. This observed heterogeneity in emotional tonality underlying the reported experiences of the first COVID-19-related lockdown is likely to reflect differences in emotional burden, individual circumstances, and ways of coping with the pandemic, which is in line with previous research on this matter. CONCLUSIONS: This study illustrates the timely and efficient applicability of an NLP pipeline and thereby serves as a precedent for applied researchers. Our study thereby contributes to both the dissemination of NLP techniques in applied health sciences and the identification of previously unknown experiences and burdens of persons with MS during the pandemic, which may be relevant for future treatment.

17.
Russian Journal of Linguistics ; 26(3):701-720, 2022.
Article in English | Scopus | ID: covidwho-2081323

ABSTRACT

Urban communication studies is a growing field of research aiming to reveal the regularities of human interaction in an urban context. The goal of the present study is to examine the semiotics of a big Chinese city as a complex communicative system and its effect on the social development of urban community. The material includes over 700 units (toponyms, street signs, advertisements, memorials, local foods and souvenirs, mass media, etc.) mostly collected in Tianjin, China’s fourth biggest city with a population of almost 14 million people. The research methodology is based on critical discourse analysis, ethnographic and semiotic methods, and narrative analysis. The study reveals the structure of communication in a big Chinese city and the integration of language into the city landscape. It indicates that urban historical memories are manifested in the form of memorials, symbols, historic and contemporary narratives. The physical context is associated with names of streets and other topological objects. Verbal and visual semiotic signs are used to ensure people’s psychological and physical safety. Social advertising predominantly deals with the propaganda of Chinese governmental policy, traditional values and ‘civilized behaviour’. Chinese urban subcultures, such as ‘ant tribe, ‘pendulums’, ‘shamate’, etc., reflect new social realities. Food and foodways are defined by cultural values and different aspects of social identity. The image of a big Chinese city is also affected by globalization tendencies and the COVID-19 pandemic. The research framework presented in the study provides an opportunity to show a wide panorama of modern urban life. It can be extrapolated to the investigation of other big cities and their linguistic landscapes. © Olga Leontovich & Nadezhda Kotelnikova, 2022.

18.
Acta Medica Iranica ; 60(8):521-525, 2022.
Article in English | Scopus | ID: covidwho-2081192

ABSTRACT

Since the outbreak of the COVID-19 pandemic, online education has gained more momentum. Despite its advantages, virtual learning has some drawbacks. To compensate for these shortcomings, the application of some innovative approaches has obtained more importance;one of them is Project-Based Learning (PBL). The present study aimed to investigate the effect of PBL on students' performance in a general English course. The participants were 55 Iranian freshmen medical students who registered in the General English Course at the Birjand University of Medical Sciences. They were selected based on convenience sampling. The classes were held virtually twice a week for 24 sessions during the spring semester of 2020. All the students in the class were asked to do a term project in the form of making English language videos about a medical topic. The recorded classes, observations, and semi-structured interviews with the students about the advantages of doing projects were the sources of data. The collected data were analyzed through thematic analysis and validated through member checking. The data analyses resulted in five main themes about the advantages of PBL in the areas of students' "autonomy," "engagement," "learning," "motivation," and "evaluation." PBL helped the students to be more autonomous and improved their engagement. Furthermore, it helped them learn new words about the diseases and improve their knowledge of their major. It also made the students more motivated and helped the teacher figure out how well they did during the term instead of just relying on the final exam. © 2022 Tehran University of Medical Sciences.

19.
European Journal of Educational Research ; 11(4):2043-2055, 2022.
Article in English | Scopus | ID: covidwho-2080987

ABSTRACT

Translanguaging enables students to communicate in multiple languages in an English-dominant classroom. It has received considerable attention from scholars in content and language integrated learning (CLIL). Its implementation in primary schools in European countries has been adopted in Asian countries, including Indonesia. This study employed a narrative inquiry investigating a teacher who taught first graders both content matter and English during the COVID-19 forced-remote learning. Furthermore, data were gathered using semi-structured interviews to guide the participant in narrating CLIL science teaching experiences. Virtual observations were carried out eight times to obtain evidence of translanguaging practiced. Due to forced-remote learning, the results indicated that the teacher had to find the most convenient ways to instruct the young students without adding to their burden. Furthermore, it was reported that scaffolding by translanguaging was planned systematically by valuing the students’ L1 and alternating it with English as the target language. The findings also discussed the practical implications of this study to maintain young learners' (YLs) engagement through translanguaging strategies. © 2022 The Author(s).

20.
Frontiers in Education ; 7, 2022.
Article in English | Scopus | ID: covidwho-2080120

ABSTRACT

The COVID-19 pandemic has become a focus on reforming teaching, learning models and strategies, particularly in online teaching and learning tools. Based on the social cognitive career theory and the constructivist learning theory, the purpose of this study was to understand and explore the learning preference and experience of students’ online courses during the COVID-19 pandemic and the management after the COVID-19 pandemic from the students’ perspective. The study was guided by the following two research questions: (1) After the COVID-19 pandemic, why do the students want to continue their foreign language courses via an online platform and model? What are the motivations and reasons? (2) How would the students describe their experience of a foreign language course via an online platform and model? With the general inductive approach and sharing from 80 participants, the participants indicated that flexibilities and convenience, same outcomes and learning rigorousness, and interactive experiences with classmates from different parts of the world were the three main key points. The results of this study may provide recommendations to university leaders, department heads, and teachers to reform and upgrade their online teaching curriculum and course delivery options after the COVID-19 pandemic. Copyright © 2022 Dos Santos.

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