The purpose of this paper is to discuss the innovative research on the instructional design and development of courses based on digital platforms. Firstly, the importance of digital platforms in the field of education and the current status of their application are introduced. Secondly, the concepts and key elements of course instructional design and development are analysed, and the role of digital platforms in course instructional design and development is discussed. Then, the innovative practices and methods of course instructional design and development based on digital platforms are described, including the integration and personalised customisation of learning resources, the construction and interactive communication of learning communities, and the improvement of evaluation and feedback.

The young Muslim generation’s embracing digital platforms for Zakat payments represents a dynamic fusion of enduring religious values with the modern digital landscape, heralding a new era in Islamic charitable practices. This trend illustrates a profound transformation within the Islamic world, where the pillars of faith are being reimagined and revitalized through the lens of technological advancement. The present study delved into the factors influencing the young Muslim generation’s preference for digital platforms in Zakat transactions across Indonesia and Malaysia. We examined variables such as Performance Expectancy, Effort Expectancy, Social Influence, Trust, Zakat Literacy, and Digital Infrastructure, aiming to discern their impact on the propensity for digital Zakat contributions with the extension of Unified Theory of Acceptance and Use of Technology (UTAUT) model. The research encompassed a diverse sample of 382 participants and utilized advanced methodologies, specifically Partial Least Squares Structural Equation Modeling (PLS-SEM) and PLS Multi Group Analysis (PLS-MGA), for rigorous data analysis. The results indicated that Effort Expectancy, Social Influence, Digital Infrastructure, and Zakat Literacy notably influenced the use of digital platforms for Zakat. Furthermore, PLS-MGA uncovered significant cross-country differences where Digital Infrastructure showed a more pronounced positive impact in Malaysian context, whereas Social Influence had a greater effect in Indonesia. These findings offer critical insights into the young Muslim community’s digital engagement for religious financial obligations, underscoring the need for tailored digital Zakat solutions that cater to the unique preferences of this demographic. This research not only enriches the understanding of digital adoption in religious practices but also challenges the notion of a universal approach, advocating for context-specific strategies in the realm of digital religious financial services. Future researchers are suggested to consider longitudinal investigations as well as examining cross-regional contexts in this realm of research.

This paper discusses the use of workforce ecosystems to manage human intellectual capital. The need for work ecosystems has emerged in the digital age because of the rapid growth in the number of engaged partners and freelancers in the digitalization of enterprises. It is shown that this growth is directly related to the use of agile management systems in design and development: agile, DevOps, microservice architecture, turquoise practices, etc. The information systems needed to manage workforce ecosystems should have competency-based metrics to link business needs, recruitment and training, and finding new partners. At the same time, training should be prioritized over recruitment and the search for new partners in the context of staff shortages. When automating workforce ecosystems, a platform approach should be used to integrate both corporate HR, time and business process management systems, and similar systems from partners.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.