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Underlying thematic analysis are a few fundamental human cognitive processes, such as categorizing, prototyping and metaphorical mapping. By unpacking these basic processes of human cognition, this paper hopes to provide a cognitive basis for thematic analysis as a foundational method in data analysis for qualitative research. In particular, it hopes to address the gap between qualitative methodologists' assumption of thematic analysis as a subjective, creative and flexible process and editors/reviewers' expectation that thematic analysis shall be objective, reliable and rigorous. By consciously and purposefully applying these cognitive processes, thematic analysis can be subjective and yet disciplined, creative and yet rigorous, flexible and yet reliable. The ultimate goal of this paper is to demystify, delineate and further demarcate the thematic analysis process for young and novice qualitative researchers.

In today's university era, reforming the English teaching model has become a major research topic for researchers. Based on this, this paper adopts a hierarchical and progressive model construction method to further explore the reform model of university English teaching in the context of educational ecology. First, this paper discusses the development of the layered progressive approach in various countries and the current status of the layered progressive approach. By allowing the use of the model of the layered progressive approach, the data related to the reform of university English teaching were analyzed and organized. The combination of internal optimization, data-theoretic learning algorithms, and data federation algorithms for the model of the hierarchical incremental approach are also investigated. The results of the study show that the layered progressive model of college English teaching reform has good results through specific practical applications in a strengthened educational ecosystem.

The higher education efficiency evaluation model using the data envelopment analysis method has interested many researchers. This paper uses bibliometric analysis on publications extracted from the Scopus database to provide a comprehensive overview of research publications on the measurement of higher education efficiency based on data envelopment analysis: its growth rate, major collaboration networks, the most important and popular research topic. A total of 169 related publications were collected and analyzed from 1988 to 2021. The analysis results show that: Publications published every year have increased sharply in the last six years; The quality of publications is relatively high as publications tend to be published in journals with high-ranking indexes; Countries with the most influence in studies on this topic are: Italy, China, Spain, the USA, and the United Kingdom; Authors with the most influence in this research direction are Agasisti T., Abbott M., Doucouliagos C., Avkiran N.K., and Johnes J.; The research cooperation among countries and among affiliations is not strong. Finally, the paper has provided recommendations for future studies based on the findings.

The severity of plastic pollution is increasing, and delaying sustainable development is not an option. China is a large consumer of plastic, so it is essential to encourage the use of eco-friendly shopping bags there. The paper focuses on the recognition and use of eco-friendly shopping bags among young people in Guangdong Province, China, and determines what factors can lead to a rise in the use of these bags. A questionnaire was utilized to gather data from 392 young people in Guangdong Province using a quantitative research approach. According to the data from the questionnaire, they generally are supportive of eco-friendly shopping bags. Ultimately, the paper's data emphasize the positive effects of materials (paper material), function (internal compartment), and design (green label). For the purpose of advocating sustainable development, this paper provides helpful guidance for the design of eco-friendly shopping bags. [ABSTRACT FROM AUTHOR]

Improving the efficiency of factor allocation, breaking the resource curse, and achieving high-quality economic development are an urgent concern in resource-based cities. Using the panel data of 116 prefecture-level resource-based cities in China from 2005 to 2020, this paper constructs the data envelopment analysis-Malmquist index model to measure the level of high-quality economic development; to construct a resource misallocation growth accounting model based on the total production function to measure the distortion coefficient, the threshold panel model is employed to explore the threshold effect of factor market distortion on high-quality economic development. The results yielded three important findings: (1) The green total factor productivity of resource-based cities in China presents spatial heterogeneity and type heterogeneity. (2) Factor market distortion gradient standards are proposed innovatively, and the factor market distortion level shows the spatial heterogeneity and type heterogeneity. (3) The influence of factor market distortion on high-quality economic development in resource-based cities presents a double threshold effect. According to the above research conclusions, this paper gives several policy recommendations to promote the factor marketization allocation and high-quality economic development of resource-based cities., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In the last three decades, a networked global system has emerged in the natural-science-based disciplines, sustained by collegial epistemic relations in universities. Nationally ordered and funded science has expanded alongside the global science system. The common global pool of papers, defined by bibliometric collections, nevertheless excludes large components of knowledge. In the global system, four tendencies are apparent: (1) rapid growth of papers, (2) diversification of scientific capacity to many more countries, (3) expansion of networked international and national collaboration as measured by co-authorship, (4) growing multi-polarity of capacity, outputs and quality, with the rise of China and several middle-sized national systems outside the Euro-American bloc. The paper critiques the interpretation of global science dominant in scientometrics, in which positivist data analyses are applied to performative national comparisons. It argues for a historical-synthetic explanation of the global system that combines data and theorisation, and accounts for relations of power.

The development of efficient and reliable online assessments has become increasingly important in the digital era. We developed a 10-min online word reading assessment of global English based on the existing paper-and-pencil version of our English silent word reading test. The test includes two parts, namely, random word recognition and contextual word reading. A total of 889 participants (437 children and 392 adults; 62.7% female) took part in the study. They were from various regions including mainland China, Hong Kong SAR, Macau SAR, Poland, the United States, and the Philippines. Reliability and validity analyses on various demographics samples (by age and country/region of origin) demonstrated that the WordSword Test is highly reliable and valid (e.g., the correlation of this test with other English reading measures were above.80). Education level was positively correlated with test performance, while the correlations between age and test performance were not consistent. Ninety-seven children participants also took the paper-and-pencil version of the WordSword Test. The correlation between performances on the online and paper-and-pencil versions of the test was.879, one year apart. With more children and adults taking the WordSword Test, we ultimately hope to establish norms by area, grade level, and age. [ABSTRACT FROM AUTHOR]

In response to the problem of inaccurate classification of big data information in traditional English teaching ability evaluation algorithms, this paper proposes an English teaching ability estimation algorithm based on big data fuzzy K-means clustering. Firstly, the article establishes a constraint parameter index analysis model. Secondly, quantitative recursive analysis is used to evaluate the capabilities of big data information models and achieve entropy feature extraction of capability constrained feature information. Finally, by integrating big data information fusion and K-means clustering algorithm, the article achieves clustering and integration of indicator parameters for English teaching ability, prepares corresponding teaching resource allocation plans, and evaluates English teaching ability. The experimental results show that using this method to evaluate English teaching ability has good information fusion analysis ability and improves the accuracy of teaching ability evaluation and the efficiency of teaching resource application.

Data mining (DM) is an in-depth approach to data analysis by mining useful information from large amounts of data, and this technique is now being used in an increasing number of fields. In this paper, the authors present the design of a real-time data analysis system for sports training based on DM technology and use the corresponding mining tools of DM technology to discover relevant patterns or laws hidden in the data. Therefore, using the real-time data analysis system for sports training based on DM technology, useful information and patterns for improving examination performance can be obtained, which can improve targeted teaching methods and help students overcome learning difficulties, providing rational teaching, synchronizing courses, establishing preparation, effectively guiding students in course selection, and improving course quality and educational effectiveness.

With the advent of the big data internet era, the corresponding multimedia technology is also developing. At the same time, as an important place for students to improve their cognitive level and expand their knowledge coverage, the construction of knowledge and information in university libraries will have an important impact on the growth of students and the development of the library itself. Big data not only brings specific challenges to the intelligent information construction of libraries, but also provides opportunities for the further development of intelligent information construction. Therefore, this paper aims to analyze the intelligent informatization construction of university libraries in the multimedia big data environment, make suggestions for the further development of library intelligent informatization construction, and provide reference materials for library intelligent informatization construction.

For those receiving funding from the UK HEFCE-funded Open Educational Resource Programme (2009-2012), the sustainability of project outputs was one of a number of essential goals. Our approach for the hosting and distribution of health and life science open educational resources (OER) was based on the utilisation of the WordPress.org blogging platform and search engine optimisation (SEO) techniques to curate content and widen discovery. This paper outlines the approaches taken and tools used at the time, and reflects upon the effectiveness of web strategies several years post-funding. The paper concludes that using WordPress.org as a platform for sharing and curating OER, and the adoption of a pragmatic approach to SEO, offers cheap and simple ways for small-scale open education projects to be effective and sustainable.

This paper provides an overall picture of women's representation and gender parity in the field of Agricultural Economics by constructing and analyzing a database of agricultural economists in China. We find that female scholars "occupy half the sky" in number, but not all the way up to the higher‐ranking academic positions. Women lag behind men in terms of research performance and academic promotion; even more so, gender disparity becomes more prominent when moving up the ranking ladder. A closer examination of agricultural economists of different age cohorts indicates that the gender gap, both in numbers engaged in the profession and academic performance measured by Chinese paper publications and nation‐level projects chaired, is narrowing. However, gaps in the number of high‐quality paper publications and the time span before promotion, alongside the phenomenon of a "leaky pipeline" in academia, are growing significantly over time. The representation of "star scientists" shows similar, yet steeper trends. In the absence of detailed studies, the paper explores possible explanations of the converging gender gap in scale but increasing gender disparity that is termed a "leaky pipeline." It concludes that the Policy of Enrollment Expansion in Higher Education provides vulnerable young females with more opportunities to access higher education, which increases both the number and proportion of women in the profession. [ABSTRACT FROM AUTHOR]

This article describes how the Sichuan University - Pittsburgh Institute has embraced new methods and new technologies to ensure high-quality laboratory teaching during the COVID-19 pandemic. Taking Mechanical Measurements 1 course as an example, this paper introduces two lab projects that were successfully transferred into online experiments through remote-control platform and virtual simulation software, as well as three lab projects which were transformed into "pocket labs" where cheap and easy-access equipment was mailed to enable students to conduct experiments at home. Meanwhile, video demos, online Q&A sessions, feedback collection were employed to deliver a realistic lab experience to students.

The rise of big data technology provides direction and support for the reform and development of education. Big data technology can realize the inventory management and effective dynamic monitoring of schools, students, and teachers. It is conducive to comprehensively and accurately controlling the development of teaching activities, injecting new ideas and working ideas into teaching activities, and providing essential guidance for personalized teaching. This paper reviewed the detailed process of applying big data in education to teaching practice based on the case of a middle school in China. Furthermore, it pointed out the factors hindering the large-scale development of big data in the education field, aiming to provide directions for applying big data in education.

Substantial amount of research regarding L2 learners' beliefs has been conducted in recent years. However, not enough attention has been paid to investigating the nature of learners' beliefs; hence our understanding of the construct is contradictory in the sense that early research studies report stability in beliefs, while more recent studies provide evidence of change in learners' beliefs. This paper reports on a case study aiming at contributing to a deeper understanding of the nature of language learners' beliefs. Data were gathered longitudinally over an 18-week period using a number of tools. The findings reveal the complexity of learners' beliefs. The beliefs that the learners held were not always in harmony and some of them can be self-contradictory. Furthermore, while some beliefs may evolve and change over time and across situation, others may remain relatively stable, suggesting the complex and dual nature of learners' beliefs. Drawing on these findings, the paper concludes that learner beliefs can best be perceived as an inter-related construct that has dual features and sometimes can be paradoxical.

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As an important way to expand financing channels, the listing can significantly improve the enterprises' comprehensive competitiveness. However, few studies pay attention to the continuous impact of listing years on enterprise innovation. Based on the sample data of Chinese enterprises before and after listing from 2004 to 2017, this paper discusses the relationship between the listing years and dual innovation. And analyzes the moderating effect of slack. The research shows that the listing years are related to the quantity and quality of innovation in the inverted U-shaped, but the inflection point of the innovation quantity is later than the innovation quality. Before listing, the innovation quantity and quality increased; after listing, the innovation quantity first increased and then decreased, while the innovation quality declined. High slack makes the inverted U-shaped relationship between the listing years and innovation quality steeper. [ABSTRACT FROM AUTHOR]

To recover the global economy, China in 2013 called for a new global strategy, namely, "One Belt and One Road Initiative" (BRI), which aims at reinforcing regional economic cooperation, enhancing regional collaboration of economic policy, and realizing the goal of rapid economic development of member countries. Accelerating industrialization not only has been recognized as an effective way to stimulate economic development, but also lead to the serious issue of environmental pollution, which challenges the environmental sustainability. In this study, we focus on the industrializing region as a study area to investigate the driving factors of environmental pollution. Technically, we utilized satellite observation technique to obtain NO 2 columns data to denote environmental pollution and then applied dynamic spatial panel data models to evaluate what affects NO 2 pollution levels. The findings are the following. (1) NO 2 pollution exhibits significant and positive spatial autocorrelation, indicating spatial spillovers of NO 2 pollution. (2) Lebanon, Bangladesh, Kyrgyzstan, and India experienced the largest increase of NO 2 pollution while NO 2 pollution in Singapore, Hungary, Greece, and Ukraine was substantially reduced. (3) The results of the dynamic spatial panel data models show that both the time dynamics effects and the spatial spillover effects are found to be significant and positive. In other words, both effects should be considered. Population is the foremost contributor to increase NO 2 pollution while urbanization is an effective way to reduce pollution. An EKC relationship between NO 2 pollution and per capita income was verified. Besides, industrialization, foreign direct investment, and trade openness have positive impacts on NO 2 pollution.

Learning analytics is a domain that has been constantly evolving throughout recent years due to the acknowledgement of its importance by those using intelligent data, learner-produced data, and analysis models to discover information and social connections for predicting and advising people's learning [1]. Learning analytics may be applied in a variety of different cases, but their role in understanding the multilingual requirements of users of learning portals is of an outstanding significance. As the adaptation of existing portals in multilingual environments is a cost- and time-consuming aspect of the development of a portal, the outcomes of learning analytics may provide the requirements on which further multilingual services of a portal will be built, ensuring their efficiency. This paper aims to identify and interpret the behavior of users from developing countries in a multilingual learning portal using the log files of the portal by applying the methodology defined in a previous work by Stoitsis et al. [2] The paper also aims to identify the aspects that should be studied by future related works by focusing on specific regions and countries that exhibit special interest for further adaptation of the portal to additional multilingual environments.

From the connotation of bilingual education in higher education in China, this paper analyzes the factors that may affect the quality and result of bilingual education, such as faculty and students' English level, teaching materials, curriculum system, classroom instruction, teaching quality control, as well as incentives and other factors. The paper focuses on Fuzzy-AHP model as a university bilingual education quality evaluation system, and build an evaluation index system for quality control of bilingual teaching. It also conducts quantitative analysis using analytic hierarchy process and fuzzy comprehensive evaluation on the degree of the bilingual education of business courses in Guangdong University of Foreign Studies (GDUFS), China. By selecting evaluation indicators and using analytic hierarchy process, the paper determines corresponding weight of the indicators. It also establishes sets of standard on evaluation and fuzzy relationship matrix, and conducts an empirical study on the degree of bilingual education of business courses in GDUFS. The paper has certain theoretical and practical significance for bilingualism in higher education in China.

Unbalanced and insufficient development is a prominent problem in China's period of economic transformation, and an accurate grasp of the current situation and evolutionary trend of innovation and economic development is of great significance in finding a solution and promoting regional coordinated development. This paper introduces the framework of functional data analysis to the study of both innovation and economic development in China, examining its spatial dynamic distribution and convergence characteristic in greater depth. Empirical results revealed the following. (1) Significant regional differences exist in the absolute level of China's innovation development, with a balanced improvement in the development speed and growth potential. Significant differences exist in the absolute level and speed of economic development, but not in the potential energy of development as reflected by acceleration. (2) The σ(t) function of nationwide and regional innovation development shows a downward trend. There is σ(t) convergence in economic development nationwide and in the northeastern, eastern, and western regions, but the regional disparities in economic development within the six central provinces have not yet been effectively mitigated. (3) Nationwide and regional innovation development are in a state of β(t) convergence. There is significant β(t) convergence in the nationwide economic development, with a transition point from divergence to convergence in the northeastern, eastern, and western regions. However, the β(t) function of economic development in the central region shows a region-wide divergence. The findings of this paper have important policy implications for recognizing the balance and disparities in innovation and economic development among regions in China and promoting coordinated regional development. [ABSTRACT FROM AUTHOR]

Background This analysis estimates the association between smoking-related knowledge and smoking behaviour in a Chinese context. To identify the specific knowledge most directly related to smoking status, we used a novel latent variable analysis approach to adjust for the high correlations between different measures of knowledge about tobacco smoking. Method Data are from the Global Adult Tobacco China Survey, a nationally representative sample of 13 354 household-dwelling individuals 15 years of age or older. Multinomial logistic regressions estimated the association between smoking status (ie, never smoked, current smoker or past smoker) and four smoking-related beliefs: whether or not smoking causes lung cancer, heart attack and stroke, and whether or not low-tar cigarettes are less harmful. A latent variable approach reassessed these associations while taking into account the general level of knowledge about smoking. Results After demographic variables and general knowledge about smoking had been controlled for, the belief that low-tar cigarettes are not less harmful was more prevalent in persons who had never smoked than in current smokers (OR=1.3 (95% CI 1.0 to 1.7) in men and OR=2.8 (95% CI 1.3 to 5.9) in women); this association was even stronger when past smokers and current smokers were compared (OR=2.1 (95% CI 1.5 to 3.0) in men and OR=5.0 (95% CI 1.3 to 20.1) in women). Conclusions Compared with those who have never smoked and those who have ceased smoking, current smokers in China are more likely to believe that low-tar cigarettes are less harmful than regular cigarettes. [ABSTRACT FROM AUTHOR]

In recent years, in order to address climate change and energy depletion, countries around the world have been constantly promoting energy transformation and structural upgrading. The effectiveness of RCEP has broadened the international east Asian new energy market. The development of renewable energy trade in the context of RCEP has attracted significant economic, environmental, and technical attention. Based on the background of RCEP in this study, the constant market share (CMS) model and the weighted dominant comparative advantage (IRCA) index are used to assess the export competitiveness of renewable energy products from 2006 to 2021. The data in this paper were obtained from the UN comtrade database according to the categorical statistics of HS codes. The results show that: (1) the overall competitiveness of Chinese renewable energy products shows an upward trend; (2) the comparative advantages of Chinese renewable energy products are strong, with some differences among different industries; (3) the growth effect is the main reason for the fluctuation of Chinese renewable energy product exports; and (4) the signing of RCEP has injected new vitality into Chinese renewable energy trade. Finally, based on the research conclusions, the paper puts forward corresponding policy proposal. [ABSTRACT FROM AUTHOR]

Conducting public opinion surveys on sensitive topics like NIMBY ("Not in My Backyard") facilities among China's rural population (often voiceless) is challenging. To advance relevant research, a new mixed-method approach is proposed in this paper based on fieldwork in Huizhou, China, concerning the T Nuclear Power Plant. The approach combines the paper-and-pencil interviewer-administered questionnaires (PAPIAQ) and bystanding interviews (BI). While PAPIAQ prioritizes researcher neutrality, potentially creating a barrier for less educated respondents, BI fosters deeper interaction and clarifies responses. This strengthens both data reliability (through PAPIAQ illustration) and BI text validity (through deeper understanding). Coded BI texts and statistically analysed PAPIAQ data (via elaboration procedure) ultimately generate a more valid and reliable understanding of rural sentiments on sensitive issues. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to develop a preliminary model of instructional leadership in the Chinese educational context and explore the ways in which Chinese school principals locate their instructional-leadership practices in response to traditional expectations and the requirements of recent reforms. Design/methodology/approach: In-depth interviews were conducted with 22 selected primary school principals in Shenzhen and Guangzhou. A qualitative analysis was conducted to categorize the major leadership practices enacted by these principals. Findings: An initial model of instructional leadership in China with six major dimensions is constructed. The paper also illustrates and elaborates on three dimensions with the greatest context-specific meanings for Chinese principals. Originality/value: The paper explores the ways in which Chinese principals enact their instructional leadership in a context in which "the west wind meets the east wind"; that is, when they are required to accommodate both imported reform initiatives and traditional expectations. The paper contributes to the sparse existing research on principals' instructional leadership in non-western cultural and social contexts.

Interaction is critical for successful teaching and learning in a virtual learning environment (VLE). This paper presents a web-based interaction-aware VLE--WebIntera-classroom--which aims to augment learning interactions by increasing the learner-to-content and learner-to-instructor interactions. We design a ubiquitous interactive interface that integrates a pen-and-paper interface with a web-based whiteboard to promote effective learner-to-content interactions. We develop a learning analytics tool that instantly shows learners' learning interactions, with which instructors can supervise learner-to-instructor interactions. We implement a high-granularity Learning Analytics Engine (hgLAE) to broadcast, record and play a lecture recording. The hgLAE identifies hotspots in a lecture recording and raises students' awareness of the hotspots when they watch the recording. WebIntera-classroom has been deployed in 11 universities in China. The system obtained high satisfaction in the questionnaires (N = 464) and face-to-face interviews (N = 60) conducted with the users from China Jiliang University. We compared the students' performance, respectively, achieved in traditional classroom and in WebIntera-classroom at China Jiliang University during 2012-2013. The result demonstrates that the students could gain performance improvement by using WebIntera-classroom.

This case study analyzed data from an asynchronous written mediated exchange between a native speaker and nonnative speaker of English. Three methods of analysis-error analysis, propositional complexity (idea units), and qualitative analysis were used to analyze learner performance over time. The results from these methods were visualized and interpreted according from Complex Dynamic Systems Theory (CDST) perspective, which allows longitudinal language production data to be interpreted from multiple perspectives so that change can be understood at both the micro and macro levels. Results from the analysis revealed patterns of linguistic change both within and between participants as they interacted over time. Several instances of continuity in language production were observed between the participants, including a drop in error rate that coincided with an increase in minor idea units during one turn of the exchange. Results from a qualitative analysis offer several explanations for this finding and are related to the implications this holds for CDST.

Background: The condition and correlation of fatigue, sleep and physical activity in postoperative patients with pituitary adenomas remain unclear. This survey aimed to evaluate the current status and influencing factors of fatigue, sleep and physical activity in postoperative patients with pituitary adenomas. Methods: Patients undergoing pituitary adenoma resection in two tertiary hospitals from November 2019 to November 2021 were included. The general data questionnaire, Multidimensional Fatigue Inventory (MFI‐20), Pittsburgh Sleep Quality Index (PSQI) and international physical activity questionnaire were used for data analysis. Results: In total, 184 patients with pituitary adenomas were included. The postoperative patients with pituitary adenomas had a high level of fatigue. In total, 34 (18.5%) patients had low level of physical activity, 76(41.3%) patients had medium level of physical activity and 74 (40.2%) had high level of physical activity. Postoperative time, PSQI, physical activity level and gender were the influencing factors of fatigue in patients with pituitary adenomas (all P < 0.05). Conclusions: Postoperative patients with pituitary adenomas have a higher level of fatigue, and it is related to reduced sleep quality and activity. Relevant nursing measures should be taken according to the influencing factors of fatigue to reduce the fatigue of postoperative patients with pituitary adenomas. Summary statement: What is already known about this topic? The postoperative nursing care of patients is very important to the quality of life in patients with pituitary adenomas.Fatigue, sleep and physical activity in postoperative patients with pituitary adenomas remain unclear. What this paper adds? There is a high level of fatigue in patients with pituitary adenomas within 1 year after operation.The degree of fatigue is negatively correlated with the course of disease and the level of physical activity. The implications of this paper: Interventions and nursing care strategies targeted on the factors affecting postoperative fatigue of patients with pituitary adenomas are needed. [ABSTRACT FROM AUTHOR]

Qualitative research strategy has been widely adopted by educational researchers in order to improve the quality of their empirical studies. This paper aims to introduce a generic inductive approach, pragmatic and flexible in qualitative theoretical support, by describing its application in a study of non-English major undergraduates' English learning transition from school to university in China. Through an analysis of how this case study was conducted, the main features of the generic inductive approach are discussed in detail. Subsequently, some suggestions for its effective use are put forward so that this approach can help to provide meaningful interpretive power to make sense of the findings in educational research.

Purpose: The purpose of this paper is to develop a framework for studying organizational learning, firm innovation and firm financial performance. Design/methodology/approach: This paper examines the effects of organizational learning on innovation and performance among 287 listed Chinese companies. Findings: The results indicate a positive association between organizational learning dimensions and firm performance (both objective financial performance and perceptual innovation measure). Research limitations/implications: The sample includes only firms for which secondary data are available. Different results might have been obtained if we include smaller, private firms into the sample. This paper only includes a limited number of measures of financial performance to assess the relationship between organization learning dimensions and firm performance. Therefore, researchers are encouraged to test the proposed propositions further with different performance measures. Practical implications: The results showed that it is the combination of several learning characteristics and not a single dimension that influenced the variance of firm performance. The findings reinforce the notion that systemic interventions that address a variety and different combinations of learning organization characteristics will be more likely to be successful than interventions that solely focus on singular or a limited number of dimensions. Originality/value: The integration of objective measures of firms' financial performance with perceptual survey data represents a unique methodology that has not been widely used in the organizational learning literature. The positive correlations between the eight learning dimensions and the measures of firms' performance lend credence to the efficacy of the organizational learning concepts.

With the massive use of lithium-ion batteries in electric vehicles and energy storage, the environmental and resource problems faced by used lithium-ion batteries are becoming more and more prominent. In order to better resource utilization and environmental protection, this paper employs bibliometric and data analysis methods to explore publications related to waste lithium-ion battery recycling from 1984 to 2021. The Web of Science core set from the SCIE online database was used for this article. These findings demonstrate a considerable increase trend in the number of publications published in the subject of recycling used lithium-ion batteries, with a natural-sciences-centric focus. Argonne National Lab, Chinese Academy of Sciences, and China Academic and Scientific Research Center are the top three institutions in terms of quantity of papers published. The affiliated journals corresponding to these three institutions also have high impact factors, which are 106.47, 44.85, and 58.69, respectively. In comparison to comparable institutes in other nations, the American Argonne National Laboratory supports 223 research articles in this area. China and the US make up the majority of the research's funding. The two key aspects of current lithium-ion battery recycling research are material structure research and environmentally friendly recycling. Nevertheless, high-capacity lithium-ion batteries, waste lithium-ion integrated structures, and gentle recycling of spent lithium-ion batteries will be the major aspects of study in the future. It is hoped that the above analysis can bring new ideas and methods to the field of waste lithium-ion battery recycling and provide a basis for the subsequent research and application of waste lithium-ion battery recycling. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable energy resources, their variable, intermittent and unpredictable characteristics bring new challenges to the power system. These challenges require micro-meteorological data and techniques to provide more support for the power systems, including planning, dispatching, operation, and so on. This paper aims to provide readers with insights into the effects of micro-meteorology on power systems, as well as the actual improvement brought by micro-meteorology in some power system scenarios. This paper provides a review including the relevant micro-meteorological techniques such as observation, assimilation and numerical techniques, as well as artificial intelligence, presenting a relatively complete overview of the most recent and relevant micro-meteorology-related literature associated with power systems. The impact of micro-meteorology on power systems is analyzed in six different forms of power generation and three typical scenarios of different stages in the power system, as well as integrated energy systems and disaster prevention and reduction. Finally, a case study in China is provided. This case takes wind power prediction as an example in a power system to compare the performance when applying micro-meteorological data or not. The experimental results demonstrated that using the micro-meteorological reanalysis dataset with high spatial--temporal resolution for wind power prediction performed better, verifying the improvement of micro-meteorology to the power system to some extent. [ABSTRACT FROM AUTHOR]

This systematic review is built on the seminal work by the New London Group in 1996. Few endeavours have synthesized findings of empirical studies pertaining to the effects and challenges of multiliteracies practices in various schooling and geographical contexts. Through a five-point Likert scale and a deductive and inductive thematic analysis, we conducted a systematic review of 66 multiliteracies articles from the ProQuest® database. These studies were empirical, qualitative/mixed-method, and ranged from 2006 to 2015. Findings show a burgeoning number of multiliteracies studies occurring in 15 countries, with Canada being the most prominently involved. Our evaluation of the reviewed studies was generally favourable with strengths identified in researchers' articulation of pertinent theoretical frameworks and connections to existent literature. Our findings refer to insufficient information of data collection and data analysis in a certain number of papers. We also elaborate on major affordances, challenges, and oversights of the multiliteracies practices as reported by the reviewed studies and discuss implications for future multiliteracies research, policies on literacy education, and teacher education in diverse contexts.

With the development of online learning, LMSs accumulated huge amounts of students' interaction data. Unfortunately, with the support of LMSs data, few researchers put a sight on interaction research in MPOCs. Particularly, comparing interaction activity patterns of different achievement student groups and in different course processes in MPOCs has been paid less attention. This paper generates hidden Markov models to identify frequently occurring interaction activity sequence patterns of High/Low achievement groups in the Learning/Exam processes under MPOCs settings. The results demonstrate that High-achievement students especially focused on content learning, assignments, and quizzes to consolidate their knowledge construction in both Learning and Exam processes, while Low-achievement students extremely did not perform the same. Further, High-achievement students adjusted their learning strategies based on the goals of different course processes; Low-achievement students were inactive in the learning process and opportunistic in the exam process. In sum, the comparative analysis implies that certain interaction patterns may distinguish the High-achievement students from the Low-achievement ones, and students change their patterns more or less based on different course processes. It is also helpful for students, instructors to adjust their strategies and make decisions, and for developers, and administrators to build recommendation systems based on objective and comprehensive information.

Nowadays, China is faced with increasing downward pressure on its economy, along with an expanding business risk on listed companies in China. Listed companies, as the solid foundation of the national economy, once they face a financial crisis, will experience hazards from multiple perspectives. Therefore, the construction of an effective financial crisis early warning model can help listed companies predict, control and resolve their risks. Based on textual data, this paper proposes a web crawler and textual analysis, to assess the sentiment and tone of financial news texts and that of the management discussion and analysis (MD&A) section in annual financial reports of listed companies. The emotional tones of the two texts are used as external and internal information sources for listed companies, respectively, to measure whether they can improve the prediction accuracy of a financial crisis early warning model based on traditional financial indicators. By comparing the early warning effects of thirteen machine learning models, this paper finds that financial news, as external texts, can provide more incremental information for prediction models. In contrast, the emotional tone of MD&A, which can be easily modified by the management, will distort predictions. Comparing the early warning effect of machine learning models with different input feature variables, this paper also finds that DBGT, AdaBoost, random forest and Bagging models maintain stable and accurate sample recognition ability. This paper quantifies financial news texts, unraveling implied information hiding behind the surface, to further improve the accuracy of the financial crisis early warning model. Thus, it provides a new research perspective for related research in the field of financial crisis warnings for listed companies. [ABSTRACT FROM AUTHOR]

Aims: This study aims to examine the prevalence of anxiety symptoms and identify predictors of anxiety among pregnant women with gestational diabetes mellitus and their partners and explore the mediating role of marital satisfaction between maternal and paternal anxiety. Design: A cross‐sectional study was conducted in Guangzhou, China, from July 2021 to May 2022. Methods: A total of 306 dyads of pregnant women with gestational diabetes mellitus and their partners completed the State–Trait Anxiety Inventory, Locke–Wallace Marital Adjustment Test and the socio‐demographic and clinical data sheet. Results: The prevalence of anxiety symptoms was 32.4% and 36.6% in pregnant women with gestational diabetes mellitus and their partners, respectively. The predictors of maternal anxiety were paternal anxiety, maternal marital satisfaction, maternal monthly salary, fasting glucose value and 1‐h glucose value. By contrast, the predictors of paternal anxiety were maternal anxiety, paternal marital satisfaction and paternal monthly salary. Moreover, the relationship between maternal and paternal anxiety was mediated by marital satisfaction. Conclusions: The anxiety symptoms of pregnant women with gestational diabetes mellitus and their partners influence each other, and this relationship was mediated by marital satisfaction. Every couple should be screened for anxiety symptoms and treated as a team rather than focusing solely on the pregnant woman. Summary statement: What is already known about this topic? Gestational diabetes mellitus is strongly associated with various short‐ and long‐term adverse maternal and neonatal outcomes.The diagnosis of gestational diabetes mellitus is stressful for pregnant women and their partners.No studies have been conducted to examine and compare the anxiety symptoms among pregnant women with GDM and their partners in mainland China. What this paper adds? The anxiety symptoms of pregnant women with gestational diabetes mellitus and their partners influence each other.The prevalence of anxiety symptoms was high in both pregnant women with gestational diabetes mellitus and their partners.Marital satisfaction played a mediating role between maternal and paternal anxiety. The implications of this paper: Study findings provide important information to guide future practice for nurses and other health‐care professionals.For the future, routine screening for anxiety symptoms is necessary for both pregnant women with gestational diabetes mellitus and their partners; mental health support should be delivered in a timely fashion for couples.Pregnant women with gestational diabetes mellitus and their partners should be treated as a team rather than focusing solely on pregnant women, with couples given training on enhancing marital satisfaction skills to prevent and reduce their anxiety symptoms. [ABSTRACT FROM AUTHOR]

In the context of the continuous promotion of China's big data development strategy, this paper quantitively analyses China's existing national-level big data policies from the perspective of policy instruments and coword networks, discusses the rationality of existing policies, explores ways to improve policies, and provides a reference for the innovation of China's big data policies. This paper carries out a quantitative textual analysis of China's national big data policy from the perspective of policy instruments using word frequency analysis to obtain a keyword coword matrix and visualization analysis tools to obtain a coword network. This paper further studies the network node characteristics and structure using social network analysis methods, including degree centrality, clustering analysis, and multidimensional scale analysis, to identify the policy structure and characteristics. Improving big data policy requires improvements in policy instruments on the supply side, resolving existing policy gaps, and strengthening coordination with other policies. [ABSTRACT FROM AUTHOR]

During the Ming Dynasty, China and Korea exchanged frequently and recorded a large amount of written information, which is of great value for understanding the culture of that time. The large amount of data makes it difficult to conduct quantitative analysis by researchers, which makes the analysis limited. This paper carries out a research on the cognition and analysis method of Chinese and Korean envoys to foreign cultures in Ming Dynasty based on big data analysis technology. Based on the literature research, this paper determines the ontology model establishment method to efficiently detect the written records of Chinese and Korean envoys in Ming Dynasty. The established ontology model and the improved clustering analysis method can improve the efficiency of data detection, reduce the error of data detection, and provide data basis for the research of this paper. According to the technology of big data analysis, this paper analyzes the focus and status class of Chinese and Korean envoys in Ming Dynasty and analyzes cognition of the Chinese and Korean envoys for the foreign culture. The results show that the envoys of the Chinese and Korean pay different attention to the foreign culture due to their different cognition of the foreign culture, compared with Ming Dynasty envoys, Korean envoys paid 15.3 percent less attention to geography, 19.7 percent more to history, 11.7 percent more to people, and 16 percent less to customs. This reflects the two envoys' different perceptions of the foreign culture. And the status class of the envoys exacerbates this difference. In the early Ming Dynasty, the creative diversity of Ming envoys was far lower than that of Korean envoys. As time went by, the creative diversity of Ming envoys increased. The results provide support for further understanding of Chinese and Korean culture and their relationship in Ming Dynasty. [ABSTRACT FROM AUTHOR]

This paper proposes the concept of green institutional environment, and constructs China's green institutional environmental system from the three dimensions of green supervision and public institution, green standardized institution and green accounting institution. Based on the relevant data from 2007 to 2017, this paper simulates China's green institutional environmental index through the Functional Data Analysis method and the functional entropy weight method. The results show that, first, there is a general upward trend in China's green institutional environmental index, with a range of [0.2–0.8]; the minimum value of this index is 0, and there is no maximum value. The larger the value, the higher the level of green institutional environment. Second, at the present stage, China's green standardized institution is relatively well-developed, accounting for the largest weight (i.e., [0.932–0.940]) in the green institutional environmental index system; the green accounting institution plays a supporting role, with a weight of [0.030–0.040], due to the fact that the Chinese government has made great efforts to implement policies at this level; the development of green supervision and public institution is under-developed and has little influence on the green institutional environmental index, with a weight of [0.0285–0.0305]. Finally, the proposed green institutional environmental index remains robust when equalizing the weights of the three dimensions. [ABSTRACT FROM AUTHOR]

Background: Painting is the foundational expression across all art forms and is one of the key creative practices for fostering students' aesthetic ability and creativity within fine arts courses. Collaborative painting in the form of socially shared regulation of learning (SSRL) can be recognized as an effective strategy for enhancing creativity in both individual and group work. However, the absence of contextual experiences and collaborative spaces poses challenges for students in cultivating their creativity in painting. Objectives: The present study explores students' creativity, socially shared regulation (SSR) and positive painting behaviours using an SSRL‐based collaborative painting approach in the metaverse (Meta‐CP). Methods: Via a quasi‐experimental design, a total of 40 Chinese students in fifth grade were recruited and were randomly divided into an experimental group and a control group, with 20 students utilizing the Meta‐CP approach, while the remaining 20 students followed the conventional SSRL‐based paper‐and‐brush collaborative painting (C‐CP) approach. The Meta‐CP approach not only offers an authentic painting context and a collaborative space but also facilitates the collaborative process through the SSRL framework. The data collection included students' creative tendency, painting works and painting process. Results and Conclusions: The Meta‐CP approach effectively enhances students' creativity concerning adventure, curiosity and imagination, as well as results in the creation of more distinctive and logical artistic works. Furthermore, the approach significantly improved the quality of students' SSR. Additionally, students utilizing the Meta‐CP approach displayed more positive painting behaviours compared with those employing the C‐CP approach. Lay Description: What is already known about this topic:Collaborative painting is an effective strategy for enhancing creativity.Socially shared regulation of learning (SSRL) fosters collaborative learning.Students in collaborative painting may lack a contextual and synchronized painting space.The metaverse benefits in terms of contextual experiences and collaborative spaces. What this paper adds:Using an SSRL‐based collaborative painting approach in the metaverse (Meta‐CP) is effective in improving students' creativity.The Meta‐CP approach has the potential to improve students' quality of socially shared regulation (SSR), and positive painting behaviours. Implications for practice and/or policy:The metaverse provides an immersive synchronized painting space for art education to stimulate students' creative potential.The metaverse with proper learning strategies (e.g., SSRL) provides an effective collaborative learning environment for creation. [ABSTRACT FROM AUTHOR]

Drawing on conversation analysis, this paper explores how medical encounters are closed in China's mainland. Based on a collection of 75 naturally occurring cases, we observe two dominant conversational practices oriented to closing Chinese medical encounters: a stand-alone 'okay?' as a generic preclosing initiation, and a gratitude-expressing action as the initiation of the closing sequence. Through a further examination of salient closing patterns in our data, we propose that Chinese doctors prefer fishing for patients' initiation of the terminal exchange to closing the medical interaction by themselves. The ways of and reasons for eliciting a patient-initiated closure are also discussed. This study may provide a frame of reference for studying medical closures in other cultures and have implications for cross-cultural comparison. [ABSTRACT FROM AUTHOR]

Aims: The present study aimed to explore the effects of a guided self‐help mindfulness intervention on psychological resilience and job burnout among psychiatric nurses. Background: Psychiatric nurses work in challenging and potentially high stress settings. Mindfulness interventions can improve psychological resilience and reduce job burnout of nurses. However, face‐to‐face delivery of mindfulness interventions may be inconvenient for individuals. Guided self‐help interventions may be more accessible. Methods: This randomized controlled trial was conducted from January to August 2022. One hundred and eighteen psychiatric nurses were randomized into the intervention and control groups. The individuals in the intervention group received an 8‐week guided self‐help mindfulness intervention, while the individuals in the control group received a psycho‐educational brochure. The Five Facet Mindfulness Questionnaire, the Connor‐Davidson Resilience Scale and the Maslach Burnout Inventory‐Human Services Survey were used to evaluate the levels of mindfulness, psychological resilience and job burnout, respectively. Results: After an 8‐week intervention, compared with the control group, the levels of mindfulness and psychological resilience were higher, while the level of job burnout was lower in the intervention group. Conclusions: The guided self‐help mindfulness intervention can improve psychological resilience and reduce job burnout among psychiatric nurses. Summary statement: What is already known about the topic? Mindfulness‐based interventions can improve psychological resilience and reduce job burnout of nurses.A growing body of studies has begun incorporating self‐help strategies with mindfulness‐based interventions.There are few studies exploring the use of the guided self‐help mindfulness interventions for Chinese psychiatric nurses and the associated effects on psychological resilience and job burnout. What this paper adds? The guided self‐help mindfulness intervention reduced job burnout and improved psychological resilience compared with psycho‐education intervention. Implications of this research Self‐guided mindfulness interventions can be used to improve psychological resilience and reduce job burnout among psychiatric nurses.In the future, the impact of self‐help mindfulness interventions on the mental health of nurses in other specialties can be trialled. [ABSTRACT FROM AUTHOR]

Aim: To analyse the risk factors and incidence of falls in geriatric outpatients in a university hospital ward in Hangzhou, China. Methods: From May 2020 to August 2022, 1712 geriatric outpatients in a university hospital ward in Hangzhou, China, were screened using a socio‐demographic questionnaire (e.g. gender, age, living arrangement, etc.) and assessment scales. The correlation between each factor and falls was preliminarily analysed by chi‐squared tests. Finally, binary logistic regression analysis was conducted to further analyse the risk factors of falls. The STROBE checklist was used in reporting this study. Results: Of the 1712 geriatric outpatients recruited, 1626 participants (60–79 and ≥ 80 years old) with complete questionnaire and assessment data were included. The occurrence of falls for those in the 60–79 age group was 8.4%, and for those in the ≥80 age group it was 13.4%. Age (p =.007), use of a walking assistance device (p <.001), the Stay Independent Brochure Questionnaire (SIB) (OR = 7.751, 95% CI = 5.089–11.806, p <.001), living arrangement (p =.004), timed up and go test (TUGT) (p =.007) and three diseases or above (OR = 2.496, 95% CI = 1.358–11.4.586, p =.003) reached statistical significance. Conclusions: Older people have a high incidence of falls. In this study, age, disease history, SIB scores (≥4 points), living arrangement, TUGT and walking assistance device increased the probability of falls in older Chinese adults. Personalised interventions should be carried out according to the specific situation of older people to effectively reduce their incidence of falls and improve their quality of life. Relevance to Clinical Practice: The basic characteristics and fall risk factors of the older can help nurses identify fall risk, and early intervention by caregivers can reduce fall‐related injuries, which has practical significance for promoting healthy aging. Patient or Public Contribution: The subjects of this study were older patients ≥60 years old, and the demographic characteristics and fall‐related information of patients were obtained by questionnaire. The team worked closely with a team of experts in the field of health care. Some researchers collect data and rewrite them, while other researchers analyse the information and write a paper. All authors read and approved the final manuscript. [ABSTRACT FROM AUTHOR]