This quasi-experimental study examined the effect of a mechanics course delivered through a Learning Management System (LMS) on the creativity of prospective physics teachers at a teacher training college in Mataram, Indonesia. The study was conducted in the post-pandemic era. Using a pretest-posttest one-group design, the researchers evaluated changes in creativity across three domains: figural, numeric, and verbal. The results showed significant improvements in overall creativity, with the most critical gains observed in the figural domain. Further analysis revealed that fluency was the creative indicator with the most enhancement. In contrast, other indicators displayed varying degrees of improvement. These findings highlight the potential of LMS-based instruction in fostering creativity among future physics educators, particularly in the figural, numeric, and verbal domains. This study adds to the growing body of evidence supporting technology integration into teacher education, especially during times of crisis. Future research should explore more targeted instructional strategies within LMS environments and utilize comprehensive creativity assessment methods further to enhance creative learning experiences for prospective physics teachers.

In June 2023, the European Union (EU) enacted the Regulation on Deforestation-Free Products (EUDR), which requires agricultural products to enter and leave its territory free from deforestation. The regulations apply to seven commodities: cattle, cocoa, coffee, oil palm, rubber, soya, wood, and their derivate products grown or raised on land subject to deforestation or forest degradation will be banned from entering the EU market. EUDR will have a significant impact on Vietnam’s Exports of Agricultural Products. Coffee, rubber, wood, and wood products are the main industries in Vietnam affected by this regulation, as the country exports a substantial portion of these products to EU markets. This article examines the impacts of the European Union Deforestation Regulation on Vietnam’s coffee supply chains, discusses possible unintended effects on coffee farmers and farming households, and explores strategies to mitigate these negative impacts while highlighting specific challenges that may arise. The results of this study contribute to a better understanding and management of Vietnam’s agricultural exports, particularly in the coffee sector. Additionally, the article gives some recommendations for improving Vietnam’s laws and policies on deforestation-free products.

This paper presents a quantitative exploration of the functionality of cost accounting systems and their determinants in social welfare organizations. We conducted a questionnaire survey of managers of social welfare organizations running special nursing homes for the elderly and conducted a cluster analysis based on the data collected. The questionnaire was created based on the scales used in previous studies, with some new scales developed. For data analysis, the statistical analysis environment R was used. The clValid package of R was used to assess the validity of the cluster analysis. Based on the results of the analysis in this paper, it is expected that social welfare organizations that pursue cost leadership strategies and have a strong public interest orientation will benefit greatly by being able to utilize a highly functional cost accounting system. Such organizations will be able to improve their business efficiency by utilizing cost information, and their social contribution activities based on the resulting resources will truly be a contribution to public welfare. The findings from this study are of practical significance because they can be used by business managers of social welfare organizations to review the functionality of their cost accounting systems. We also focus on the degree to which nonprofit organizations focus on social contribution activities (in this paper, we call this public interest orientation). The public interest orientation of an organization is thought to affect the functionality of the cost accounting system in the same way as the organization’s strategy, but there has not been enough quantitative research on this point. By focusing on the public interest orientation of social welfare organizations, this study contributes to deepening our knowledge in this area.

The construction of researcher profiles is crucial for modern research management and talent assessment. Given the decentralized nature of researcher information and evaluation challenges, we propose a profile system for Chinese researchers based on unsupervised machine learning and algorithms. This system builds comprehensive profiles based on researchers’ basic and behavior information dimensions. It employs Selenium and Web Crawler for real-time data retrieval from academic platforms, utilizes TF-IDF and BERT for expertise recognition, DTM for academic dynamics, and K-means clustering for profiling. The experimental results demonstrate that these methods are capable of more accurately mining the academic expertise of researchers and performing domain clustering scoring, thereby providing a scientific basis for the selection and academic evaluation of research talents. This interactive analysis system aims to provide an intuitive platform for profile construction and analysis.

The Urabá region, known for its banana production, faces significant challenges due to seasonal droughts that affect crop productivity. The implementation of innovative technologies, such as efficient irrigation systems, is presented as a potential solution to improve the sustainability and profitability of plantations. This study validates the implementation of an irrigation system in a banana (Musa spp.) plantation located in the region of Urabá, in order to meet the water needs of the crop during periods of drought. A case study was carried out in a banana plantation in the region of Urabá, considering the maximum and minimum monthly losses due to drought, and a random sample was used to measure the weight before and after the implementation of the irrigation system, in order to carry out an economic analysis. The study shows that the implementation of a sprinkler irrigation system increases the average weight of the harvested bunches by 20%, which is reflected in an annual increase of 30.3% of exported boxes, obtaining satisfactory results in terms of internal rate of return, cost-benefit ratio and return on investment. The implementation of irrigation systems makes it possible to increase competitiveness in international markets, especially in regions such as Urabá, where the use of these technologies is still incipient.

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.