This study provides empirical data on the impact of generative AI in education, with special emphasis on sustainable development goals (SDGs). By conducting a thorough analysis of the relationship between generative AI technologies and educational outcomes, this research fills a critical gap in the literature. The insights offered are valuable for policymakers seeking to leverage new educational technologies to support sustainable development. Using Smart-PLS4, five hypotheses derived from the research questions were tested based on data collected from an E-Questionnaire distributed to academic faculty members and education managers. Of the 311 valid responses, the measurement model assessment confirmed the validity and reliability of the data, while the structural model assessment validated the hypotheses. The study’s findings reveal that New Approaches to Learning Outcome Assessment (NALOA) significantly contribute to achieving SDGs, with a path coefficient of 0.477 (p < 0.001). Similarly, the Use of Generative AI Technologies (UGAIT) has a notable positive impact on SDGs, with a value of 0.221 (p < 0.001). A Paradigm Shift in Education and Educational Process Organization (PSEPQ) also demonstrates a significant, though smaller, effect on SDGs with a coefficient of 0.142 (p = 0.008). However, the Opportunities and Risks of Generative AI in Education (ORGIE) study did not find statistically significant evidence of an impact on SDGs (p = 0.390). These findings highlight the potential opportunities and challenges of using generative AI technologies in education and underscore their key role in advancing sustainable development goals. The study also offers a strategic roadmap for educational institutions, particularly in Oman to harness AI technology in support of sustainable development objectives.

Introduction: Citizen insecurity is a complex, multidimensional and multi-causal social problem, defined as the spaces where people feel insecure mainly due to organized crime in all nations that suffer from it. Objective: To analyzes the sociodemographic factors associated with public insecurity in a Peruvian population. Methodology: The research employed a non-experimental, quantitative design with a descriptive and cross-sectional approach. A total of 11,116, citizens participated, ranging from 18 to 85 years old (young adults, adults, and the elderly), of both sexes, and with any occupation, education level, and marital status. The study employed purposive non-probability sampling to select the participants. Results: More than 50% of the population feels unsafe, in public and private spaces. All analyzed sociodemographic variables (p < 0.05), showing distinctions in the perception of citizen insecurity based on age, gender, marital status, occupation, area of residence, and education level. It was determined that young, single students, who had not experienced a criminal event and reside in urban areas, regardless of gender, perceive a greater sense of insecurity. Contribution: The study is relevant due to the generality of the results in a significant sample, demonstrating that the study contributes to understanding how various elements of the socioeconomic and demographic context can influence the way in which individuals perceive insecurity in their communities, likewise, the perception of citizen insecurity directly affects the general well-being and quality of life of residents, influencing their behaviors and attitudes towards coexistence and public policies; which will help implement more effective actions in the sector to reduce crime rates.

The root of the problem in this research is the fact that scientific writing with a national reputation is still low and the publication of scientific writing with a national reputation is also low, thus affecting the quality of lecturers at the University. To overcome this problem, this research developed a training management model that can improve the scientific writing skills of lecturers and familiarize lecturers to actively conduct nationally reputable scientific writing. The training management model in question is called the “National Reputable Scientific Writing Training Management” model. This type of research is development research or R&D to produce a valid, practical, and effective model, as well as all devices and research instruments related to the application of the model at the University. The results showed that: (1) the National Reputable Scientific Writing Training Management model is suitable for improving the scientific writing ability of lecturers; (2) the output of the National Reputable Scientific Writing Training Management model in the model group is significantly higher than the initial group (pre-model); (3) The average value of IP/IO from experts is 4.4 with a high category, from observers at stage I test is 4.0 with a high category, at stage II test is 4.7 with a high category and stage III test is 4.77 with a high category, so it is concluded that the National Reputable Scientific Writing Training Management model meets the criteria of effectiveness, practicality and implementation; (4) The response of university managers and respondents to the implementation of the model is quite satisfactory, both regarding the concept of the model, the application in technical implementation and their perception of the National Reputable Scientific Writing Training Management model; and (5) the National Reputable Scientific Writing Training Management model can be developed as an alternative implementation in training management at the university.

The objective of this study is to explore the relationship between changing weather conditions and tourism demand in Thailand across five selected provinces: Chonburi (Pattaya), Surat Thani, Phuket, Chiang Mai, and Bangkok. The annual data used in this study from 2012 to 2022. The estimation method is threshold regression (TR). The results indicate that weather conditions proxied by the Temperature Humidity Index (THI) significantly affect tourism demand in these five provinces. Specifically, changes in weather conditions, such as an increase in temperature, generally result in a decrease in tourism demand. However, the impact of weather conditions varies according to each province’s unique characteristics or highlights. For example, tourism demand in Bangkok is not significantly affected by weather conditions. In contrast, provinces that rely heavily on maritime tourism, such as Chonburi (Pattaya), Phuket, and Surat Thani, are notably affected by weather conditions. When the THI in each province rises beyond a certain threshold, the demand for tourism in these provinces by foreign tourists decreases significantly. Furthermore, economic factors, particularly tourists’ income, significantly impact tourism demand. An increase in the income of foreign tourists is associated with a decrease in tourism in Pattaya. This trend possibly occurs because higher-income tourists tend to upgrade their travel destinations from Pattaya to more upscale locations such as Phuket or Surat Thani. For Thai tourists, an increase in income leads to a decrease in domestic tourism, as higher incomes enable more frequent international travel, thereby reducing tourism in the five provinces. Additionally, the study found that the availability and convenience of accommodation and food services are critical factors influencing tourism demand in all the provinces studied.

Conspiracy theories during Covid-19 pandemic spread worldwide, including in Indonesia. What political and religious factors explain their spread in Indonesia with particular reference to the DKI Jakarta province, its surrounding municipalities, and West Sumatera province? This study aimed to answer the questions. It employed a qualitative approach with multi-data collection methods, including those from media, documents, and interviews. The spread of Conspiracy theories benefited from the democratic system that promotes the freedom of information in using social media. First, the government officials initially spread conspiracy theories to satisfy people’s anxiety about the obscured Pandemic. However, they resulted in the government’s ambiguous, controversial, and reckless policies leading to people’s distrust of the government. Jokowi-Makruf Amien, political opponents capitalized on the government’s poor policies to spread conspiracy theories which partly discredited the Jokowi-Amien administration. Both government officials and the opposition capitalized on politics and religious teaching or supra-natural pretexts to posit their conspiracy theories.

With the development of the times and changes in the environment of traditional martial arts, Choi Lei Fut (a Chinese martial arts system), a Chinese state-level intangible cultural heritage, is facing many difficulties in its inheritance and sustainable development. Especially in the context of COVID-19 pandemic prevention and control measures, the sustainable development of Choi Lei Fut is facing increasingly serious challenges. In order to understand the current situation of Choi Lei Fut’s survival and development in the new era, and to enhance the momentum and vitality of its sustainable development, this study combines questionnaire survey and field interviews to investigate and analyze the current situation. Based on this, it proposes strategies to promote the sustainable development of Choi Lei Fut. This study will not only provide methodological reference for the inheritance and development of Choi Lei Fut but also offer insights for the inheritance and sustainable development of other Chinese martial arts gyms and even martial arts practices elsewhere.