The developmental and advancement of engineering vis-à-vis scientific and technological research and development (R&D) has contributed immensely to sustainable development (SD) initiatives, but our future survival and development are hampered by this developmental and advancement mechanism. The threat posed by current engineering vis-à-vis scientific and technological practices is obvious, calling for a paradigm change that ensures engineering as well as scientific and technological practices are focused on SD initiatives. In order to promote sound practices that result in SD across all economic sectors, it is currently necessary to concentrate on ongoing sustainable engineering vis-à-vis scientific and technological education. Hence, this perspective review article will attempt to provide insight from Sub-Saharan Africa (Nigeria to be specific) about how engineering vis-à-vis scientific and technological R&D should incorporate green technologies in order to ensure sustainability in the creation of innovations and practices and to promote SD and a green economy. Furthermore, the study highlights the importance as well as prospects and advancements of engineering vis-à-vis scientific and technological education from the in Sub-Saharan Africa context.

This research presents a novel approach utilizing a self-enhanced chimp optimization algorithm (COA) for feature selection in crowdfunding success prediction models, which offers significant improvements over existing methods. By focusing on reducing feature redundancy and improving prediction accuracy, this study introduces an innovative technique that enhances the efficiency of machine learning models used in crowdfunding. The results from this study could have a meaningful impact on how crowdfunding campaigns are designed and evaluated, offering new strategies for creators and investors to increase the likelihood of campaign success in a rapidly evolving digital funding landscape.

The purpose of this study was to assess rural students’ computational thinking abilities. The following proofs were observed: (1) Students’ abstraction affected algorithmic thinking skills; (2) Students’ decomposition influenced algorithmic thinking skills; (3) Students’ abstraction impacted evaluation skills; (4) Students’ algorithmic thinking affected evaluation skills; (5) Students’ abstraction impacted generalization skills; (6) Students’ decomposition impacted generalization skills; (7) Students’ evaluation affected generalization skills. Gender differences were observed in the relationship among the computational thinking factors of junior high school students. This included the abstraction-generalization skills; evaluation-generalization skills; and decomposition-generalization skills relationships, which were moderated by the gender of the students. 258 valid surveys were collected, and they were utilized in the study. Conducting the descriptive, reliability, and validity analyses used SPSS software, and the structural equation modeling (SEM) was also conducted through Smart PLS software to assess the hypothetical relationships. There were gender disparities in the correlation among computational thinking components of the junior high school students’ studying in rural areas. Research has shown that male and female students may have different abstractions, evaluations, and generalizations related to computational thinking, with females being more strongly associated than males in non-programming learning contexts. These results are expected to provide relevant information in subsequent analyses and implement a computational thinking curriculum to overcome the still-existing gender gaps and promote computational thinking skills.

The use of green bonds as a financial instrument to support sustainable development has become a major focus in Indonesia. However, the success of green bond implementation not only depends on market willingness but also on public policies that support and regulate its use. Therefore, this research aims to analyze the impact of public policies on the use of green bonds in Indonesia and how these policies can influence sustainable development. Public policy theory and sustainable development theory are the basis of analysis in this research. Public policy theory is used to understand how public policies are formed, implemented, and evaluated. Meanwhile, sustainable development theory is used to evaluate the impact of public policies on sustainable development. This research uses a qualitative approach with public policy analysis as the main method. Data are collected from various sources, including policy documents, government reports, and interviews with relevant stakeholders. The analysis results show that public policies have a significant impact on the use of green bonds in Indonesia. These policies cover various aspects, such as regulation, incentives, and government support. Additionally, these policies also influence how green bonds are used to support sustainable development in Indonesia. In order to promote sustainable development, it is important for the Indonesian government to continue developing and strengthening public policies that support the use of green bonds. This will help improve the success.

This study proposes a fuzzy analytic hierarchy process (FAHP) method to support strategic decision-makers in choosing a project management research agenda. The analytical hierarchy process (AHP) model is the basic tool used in this study. It is a mathematical tool for evaluating decisions with multiple alternatives by decomposing them into successive levels according to their degree of importance. The Sustainable Development Goals (SDG) oriented theme of project management was chosen from among four themes that emerged from a strategic monitoring study. The FAHP method is an effective decision-making tool for multiple aspects of project management. It eliminates subjectivity and produces decisions based on consistent judgment.