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Jul 28, 2023

Current Situation of English Language and Literature in English Teaching in Higher Vocational Colleges

With the gradual acceleration of China's adaptation to the global environment, the country's demand for English talents is growing. In recent years, with the continuous innovation of the education system, English education in higher vocational colleges is also undergoing optimization and innovation. Language and literature are closely related. English language and literature education in higher vocational colleges aims to cultivate high-quality talents who can flexibly use English language and literature for communication. It can be seen that teachers in higher vocational colleges need to focus on cultivating students' application ability of English language and literature in the teaching process. By analyzing the current situation of English language and literature teaching in higher vocational colleges, this paper expounds its significance and puts forward corresponding countermeasures, hoping to promote the development and progress of English language and literature education in higher vocational colleges.

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Jul 24, 2024

School or home: Exploring the impact of digital infrastructure on digital literacy of school-age young people in a developing economy

Digital literacy plays a very important role for a developing innovative economy, since one of the global trends significantly affecting the dynamics of open innovation is strengthening of the influence of digital technologies on all spheres of society. This paper seeks to study the impact of digital infrastructure on digital literacy of school-age young people, which starts and develops both at school and/or at home. This paper uses a balanced panel of statistical data that includes 18 regions of Kazakhstan surveyed for the period between 2016 and 2022 on four indicators: the level of digital literacy in Kazakhstan, the share of households with Internet access, the share of Internet users aged 6-15, and the number of students per PC in public schools. Methods of correlation, variance, and structural model analysis proposed hereby consist of successive stages and include five hypotheses for verification. The results have shown that (a) the literature has not accumulated a unified methodology for assessing digital literacy yet; (b) digital infrastructure in Kazakhstan’s public schools has been found to have a negligible impact on formation of digital literacy, as well as on the increase in the number of school-age Internet users; (c) the number of young school-age Internet users have been found to have a positive effect on formation of digital literacy in Kazakhstan; (d) access to the Internet at home has been found to have a significant stable impact on digital literacy in Kazakhstan and an increase in the share of young school-age Internet users. This paper is intended for decision makers, researchers, education and open innovation experts interested in opportunities for the development of citizens’ digital skills and competencies and the implementation of an open innovation economy strategy.

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Dec 23, 2024

International education programme and career expectations in an emerging country

This study investigates the career expectations of individuals in Thailand’s emerging economy, emphasizing the critical factors that shape these expectations within the context of a rapidly evolving labour market in the digital era. A quantitative approach was employed, collecting data from 1230 Thai respondents through convenience sampling, utilizing a structured survey as the primary research instrument. Data analysis involved the use of percentages, means and logistic regression to provide a comprehensive understanding of the findings. The results indicate that factors such as gender, age, monthly income, professional identity, values, culture and technology usage (including devices like laptops, social media platforms, home internet access and usage hours) significantly influence career expectations. Understanding these influential factors is crucial for developing targeted strategies to enhance career satisfaction, preparedness and overall competitiveness in an increasingly globalized and digital economy. By addressing the unique needs and aspirations of the Thai workforce, particularly in this digital age, stakeholders can cultivate a more responsive and adaptive professional environment, ultimately contributing to national economic growth in the digital era.

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Nov 10, 2023

Study on the Optimal Design of Rural Wisdom Pension in the Context of Rural Revitalization

With the implementation of the rural revitalization strategy, rural wisdom pension gradually becomes an important direction for the development of rural society. The purpose of this paper is to study the optimization path of rural smart pension in the context of rural revitalization. By analyzing the definition, development status and dilemma of rural wisdom pension, key factors for optimizing rural wisdom pension are proposed, and the paths for enhancing rural wisdom pension are discussed. The research results show that strengthening infrastructure construction, improving service quality, and promoting information technology application are the key paths to realize rural smart aging. This study provides theoretical guidance and policy recommendations for the implementation of rural smart aging.

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May 7, 2024

Examination of the position of cruise shipping in the post-season period at Lake Balaton

Water-based, waterfront tourism has always played an important role in the development of the tourism sector, water has been and still is an important attraction and contributes to regional development. In Hungary, Lake Balaton is the primary destination for waterfront tourism, offering a wide range of opportunities in this sector. Water-based, waterfront tourism is mainly concentrated in the high summer season, but there is an increasing range of opportunities in both the low and high season. In our research, we investigated the development of cruise tourism in Lake Balaton in the off-season, in the months of September-October 2023, by conducting in-depth interviews and questionnaire research. Our research has confirmed that this service is also in demand outside the high season. In the autumn, cruises add a special value to the experience, they can help to reduce seasonal fluctuations in tourism by offering attractive activities and also increase income for local businesses during the off-season.

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Jan 14, 2025

An insight from machine learning perspective for COVID-19 survival prediction in Malaysia based on demographic factor

Malaysia reported its first imported COVID-19 case on 23 January 2020, which marked the country's first confirmed positive case. The first case in Malaysia was from eight close contacts in Johor. The global health landscape has been significantly impacted by the COVID-19 pandemic, with mortality or survival being critical outcomes of interest. This study aims to predict COVID-19 survival occurrences in Malaysia by utilizing machine learning approaches based on demographic factors. The dataset used in this study comprises demographic information of 2,151,315 COVID-19 patients, including nationality, regions, age groups, gender, medical history, vaccine brands, and the number of vaccine doses received between 2020 and 2022. Four machine learning algorithms, namely Logistic Regression, Naïve Bayes, Support Vector Machine, and Artificial Neural Network were employed to assess the relationship between demographic factors and COVID-19 survival. To evaluate the model performance, the datasets are categorized into imbalanced and balanced (down-sampling). The results indicate that the balanced dataset (down-sampling) outperforms the imbalanced dataset in terms of overall accuracy, sensitivity, specificity, precision, and Area Under the Curve (AUC). Based on the analysis, the Artificial Neural Network (ANN) classifier exhibited the highest performance with a specificity 95.2% on a balanced dataset. The model excels in accurately identifying survivors, thereby minimizing false mortality predictions and is selected as the best model for predicting COVID-19 survival. Its capacity to process larger sample sizes, combined with numerous interconnected nodes, enables it to identify complex patterns and extract meaningful insights from diverse datasets, such as demographic factors. Additionally, the optimization of parameters, including the number of layers, learning rate, and activation functions, significantly contributed to its superior accuracy. The study identifies that those of chronic diseases, male, and aged 45 and above as the notable factors associated with lower survival rates among COVID-19 patients. The findings underscore the importance of completing the vaccination series by obtaining at least the second dose, as the first dose alone may not offer sufficient protection. In conclusion, this study successfully achieves its objectives by identifying the optimal dataset configuration and predictive model for forecasting COVID-19 survival based on demographic factors. This network could serve as a benchmark model classifier, offering a valuable tool to predict and promote vaccinations, as well as optimize the general healthcare system during the pandemic outbreak. The study not only contributes to the theoretical understanding of effective COVID-19 prediction but also emphasizes the practical implications of integrating advanced machine learning techniques into pandemic management strategies. Future research can build upon these findings by exploring additional machine learning techniques and considering geographical and environmental factors to further enhance the accuracy of long-term predictions.

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