Under the developing trend of artificial intelligence (AI) technology gradually penetrating all aspects of society, the traditional language education industry is also greatly affected [1]. AI technology has had a positive impact on college English teaching, but it also presents challenges and negative impacts. On the positive side, AI technology can provide personalized learning experiences, real-time feedback, and autonomous learning opportunities, and so on. However, it may also lead to a lack of communication between students and humans, resulting in a decline in students’ interpersonal skills, and cause students’ dependence on online learning resources as well as possible risks to student data privacy and security, and other negative impacts. To address these challenges, teachers can adopt the following countermeasures: improving teachers’ skills in the use of AI technology incorporated in the classroom, offering personalized instruction to reduce students’ dependence on AI technologies, emphasizing the cultivation of students’ humanistic literacy and interpersonal communication ability. Additionally, colleges and technology providers should strengthen data security and privacy protection to ensure the safety and confidentiality of student data. By implementing comprehensive measures, we can maximize the advantages of AI technology in college English teaching while overcoming potential issues and challenges.
Using individual- and panel country-level data from 118 countries for the period 1981–2020, this study investigates the effects of national- and individual-level economic and environmental factors on subjective well-being (SWB). Two individual SWB indicators are selected: the feeling of happiness and life satisfaction. Additionally, two environmental factors are also considered: CO2 emissions by country level and personal perspective on environmental protection. The ordered probit estimation results show that CO2 emissions have a significant negative effect on SWB, and a higher perspective on environmental protection has a significant and positive effect. Compared with the average marginal effect of national income, CO2 emissions are a more important determinant of SWB when considering a personal perspective on protecting the environment. The estimation results are robust to various estimation model specifications: inclusion of additional air pollutants (CH4 and N2O), PM 2.5 and various sample groupings. This study makes a novel contribution by providing comprehensive insights into how both individual environmental attitudes and national pollution levels jointly influence subjective well-being.
This study examines the impact of parliamentary thresholds on the Indonesian political system through the lens of the Routine Policy Implementation Model and the Strategic Policy Implementation Model. The main objective is to evaluate the effectiveness of parliamentary thresholds in managing political fragmentation, assess their impact on stability and representation in the legislative system, and understand their implementation’s technical and strategic implications. Using a qualitative approach supported by interview studies and field observations, this research combines analysis of election data in the 2009, 2014, and 2019 elections with a qualitative assessment of policy changes and political dynamics. The Routine Policy Implementation Model focuses on the technical aspects of threshold implementation, including vote counting procedures and seat allocation efficiency. Meanwhile, the Strategic Policy Implementation Model examines the broader implications of these thresholds for political consolidation, government effectiveness, and the representation of minor parties. The results show that the parliamentary threshold has significantly reduced political fragmentation by consolidating the number of parties in Parliament, resulting in a legislative system that is cleaner and easier to administer. However, this consolidation has also marginalized small parties and limited political diversity. The novelty of this study lies in its comprehensive analysis of how parliamentary thresholds affect administrative efficiency and strategic political stability in Indonesia, compared to democratic countries in transition, such as Slovenia and Montenegro. In conclusion, although parliamentary thresholds have increased political stability and government effectiveness, they have also raised concerns about the reduced representation of small and regional parties. The study recommends maintaining balanced thresholds that ensure stability and diversity, implementing mechanisms to review thresholds periodically, and involving diverse stakeholders in adjusting policies to reflect evolving political dynamics. This approach will help balance the need for a stable legislative environment with broad representation.
This study investigates the impact of tourism and institutional quality on environmental preservation, utilizing principal component analysis to generate three composite indices of environmental sustainability for 134 countries from 2002 to 2020. The results reveal that environmental sustainability indices have generally improved in lower- and middle-income nations but have declined in certain high-income countries. The findings also underscore the critical role of institutional quality—particularly regulatory standards, government effectiveness, anti-corruption efforts, and adherence to legal frameworks—in promoting environmental sustainability. However, the study shows that both domestic and international tourism expenditures can have adverse effects on environmental sustainability. Notably, these negative effects are exacerbated in countries with well-developed institutions, which is an unexpected outcome. This highlights the need for careful, thoughtful policymaking to ensure that the tourism sector supports sustainable development, rather than undermining environmental objectives.
Since 2013, the state has introduced a number of policies to strictly control the number and scale of public hospitals and to control the rapid expansion of public hospitals. After the introduction of this series of policies, the number of public hospitals in China did not continue to grow, but the number of beds in public hospitals continued to grow. This paper uses difference-in-difference (DID) method to analyze the number of public hospitals with the corresponding data of the development of private hospitals after the introduction of the policy, and the results proves that the introduction of relevant policies has an impact on the number of public hospitals, but has a limited impact on the expansion of the scale of public hospitals. At the end of the article, positive policy suggestions are given to the development of hospitals in China, such as controlling the expansion of public hospitals, strictly controlling the number of beds in public hospitals, and vigorously developing private hospitals. Promoting the development of private hospitals is an important economic supplement to China’s health care.
While the healthcare landscape continues to evolve, rural-based hospitals face unique challenges in providing quality patient care amidst resource constraints and geographical isolation. This study evaluates the impact of big data analytics in rural-based hospitals in relation to service delivery and shaping future policies. Evaluating the impact of big data analytics in rural-based hospitals will assist in discovering the benefits and challenges pertinent to this hospital. The study employs a positivist paradigm to quantitatively analyze collected data from rural-based hospital professionals from the Information Technology (IT) departments. Through a comprehensive evaluation of big data analytics, this study seeks to provide valuable insights into the feasibility, infrastructure, policies, development, benefits and challenges associated with incorporating big data analytics into rural-based hospitals for day-to-day operations. The findings are expected to contribute to the ongoing discourse on healthcare innovation, particularly in rural-based hospitals and inform strategies for optimizing the implementation and use of big data analytics to improve patient care, decision-making, operations and healthcare sustainability in rural-based hospitals.
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