With society’s continuous development and progress, artificial intelligence (AI) technology is increasingly utilized in higher education, garnering increased attention. The current application of AI in higher education impacts teachers’ instructional methods and students’ learning processes. While acknowledging that AI advancements offers numerous advantages and contribute significantly to societal progress, excessive reliance on AI within education may give rise to various issues, students’ over-dependence on AI can have particularly severe consequences. Although many scholars have recently conducted research on artificial intelligence, there is insufficient analysis of the positive and negative effects on higher education. In this paper, researchers examine the existing literature on AI’s impact on higher education to explore the opportunities and challenges presented by this super technology for teaching and learning in higher educational institutions. To address our research questions, we conducted literature searches using two major databases—Scopus and Web of Science—and we selected articles using the PRISMA method. Findings indicate that AI plays a significant role in enhancing student efficiency in academic tasks and homework; However, when considering this issue from an ethical standpoint, it becomes apparent that excessive use of AI hinders the development of learners’ knowledge systems while also impairing their cognitive abilities due to an over-reliance on artificial technology. Therefore, our research provides essential guidance for stakeholders on the wise use of artificial intelligence technology.

This research article examines the relationship between the level of social welfare expenditure and economic growth rates, based on unbalanced panel data from 38 OECD countries covering the period from 1985 to 2022. Four hypotheses are formulated regarding the impact of social expenditure on economic growth rates. Through multiple iterations of regression model building, employing various combinations of dependent and independent variables, and conducting tests for stationarity and causality, compelling empirical evidence was obtained on the negative influence of social welfare spending on economic growth rates. The study takes into account both government and non-governmental expenditures on social welfare, a novelty in this field. This approach allows for a detailed examination of the effects of different components on economic growth and provides a more comprehensive understanding of the relationships. The findings indicate that countries with high levels of social welfare spending experience a slowdown in economic growth rates. This is associated with increasing demands on social security systems, their growing inclusivity, and the escalating required levels of financing, which are increasingly covered by debt sources. The research highlights the need to strike a balance between social expenditures and economic growth rates and proposes a set of measures to ensure economic growth outpaces the indexing of social expenditures. The abstract underscores the relevance of the study in light of the widespread recognition of the necessity to combat inequality, poverty, and destitution, and calls on OECD countries’ governments to pay increased attention to social policy in order to achieve sustainable and balanced economic growth.

The development of entrepreneurship in fisheries operations is an important component of eliminating poverty. Fisherman obviously produce fishery goods, despite the broad recognition of the positive role that entrepreneurship can play in the reduction of poverty. Integration into one’s society and economy are increasingly beginning to be seen as an essential component of entrepreneurial success. This study aims to investigate the cultural and entrepreneurial attitudes of fishermen involved in the production of fishery products in the Province of West Sumatra, Indonesia, accordingly with a particular focus on marine resource conservation areas in village development. In this development, the descriptive design of capitals was utilized. This design included interviews, a questionnaire survey, and a review of the relevant body of literature. As a result, the purpose of the study was to propose an alternative model for the development of villages that would be considered novel in Indonesia. The findings demonstrated that the model makes a contribution to enhancing the socio-economic, cultural, and social capabilities of a group of fishermen. In conclusion, tourism that is focused on social entrepreneurship has the potential to boost entrepreneurial attitudes as well as the atmosphere surrounding community understanding of creative village development. We came to the conclusion that implementing tourism with a focus on social entrepreneurship could increase entrepreneurial attitudes and create an atmosphere that is more conscious of the needs of the community in village development.

In the context of establishing businesses in a new region, neglecting environmental orientation may lead to the omission of crucial motives for entrepreneurs’ migration and the subsequent course of their businesses. This present study aims to investigate the effect of green space quality (GSQ), green campaign (GC), and green attitude (GA) on green entrepreneurship pioneering intention (GEPI). Further, national pride (NP) was added as a moderator. This study utilized a cross-sectional approach using a survey method targeting small and medium-sized enterprise (SME) owners who will be relocated to the new capital city. Partial least square structural equation modeling was employed in the data analysis. The results revealed that GSQ, GC, and GA positively influence GEPI. Also, NP moderates the positive influences of GC and GA on GEPI. Entrepreneurs were motivated to pioneer green entrepreneurship in the new region due to environmental factors. Furthermore, their nationalism reinforces the connection between environmental motivations and the aspirations to undertake such pioneering endeavors. The findings present valuable insights for governments to formulate policies that encourage entrepreneurs to migrate internally and establish new economic nodes. Further, the results demonstrate how nationalism encourages green business pioneering endeavors in an untapped market.

Oil spills (OS) in waters can have major consequences for the ecosystem and adjacent natural resources. Therefore, recognizing the OS spread pattern is crucial for supporting decision-making in disaster management. On 31 March 2018, an OS occurred in Balikpapan Bay, Indonesia, due to a ship’s anchor rupturing a seafloor crude oil petroleum pipe. The purpose of this study is to investigate the propagation of crude OS using coupled three-dimensional (3D) model from DHI MIKE software and remote sensing data from Sentinel-1 SAR (Synthetic Aperture Radar). MIKE3 FM predicts and simulates the 3D sea circulation, while MIKE OS models the path of oil’s fate concentration. The OS model could identify the temporal and spatial distribution of OS concentration in subsurface layers. To validate the model, in situ observations were made of oil stranded on the shore. On 1 April 2018, at 21:50 UTC, Sentinel-1 SAR detected an OS on the sea surface covering 203.40 km². The OS model measures 137.52 km². Both methods resulted in a synergistic OS exposure of 314.23 km². Wind dominantly influenced the OS propagation on the sea surface, as detected by the SAR image, while tidal currents primarily affected the oil movement within the subsurface simulated by the OS model. Thus, the two approaches underscored the importance of synergizing the DHI MIKE model with remote sensing data to comprehensively understand OS distribution in semi-enclosed waters like Balikpapan Bay detected by SAR.