The accelerating pressures of population growth, industrial expansion, climate variability, and urbanization have rendered water quality monitoring and management one of the most critical challenges of the twenty-first century. Traditional water monitoring frameworks, largely reliant on periodic sampling and centralized laboratory analysis, are increasingly inadequate to address the spatial and temporal complexity of contemporary water systems. In response, a convergence of emerging technologies—biosensors, Internet of Things architectures, artificial intelligence, and blockchain—has begun to redefine how water quality data are generated, transmitted, analyzed, governed, and trusted. This article presents a comprehensive and theoretically grounded examination of integrated smart water quality monitoring systems, synthesizing insights from environmental science, information systems, and sustainability studies. Drawing strictly on the provided body of literature, the paper critically analyzes the principles and applications of biosensors for environmental monitoring, the evolution of water quality monitoring strategies, the role of IoT-enabled sensor networks in real-time data acquisition, and the transformative potential of artificial intelligence for predictive analytics and decision support in water governance (Huang et al., 2023; Behmel et al., 2016; Hoang et al., 2022). Particular emphasis is placed on blockchain technology as an institutional and technical mechanism for enhancing data integrity, transparency, and accountability in distributed water management systems, especially in contexts characterized by fragmented governance and trust deficits (Nofer et al., 2017; Xia et al., 2022).

Beyond technological integration, this article situates smart water monitoring within broader socio-economic and regulatory frameworks, including the Clean Water Act, national drinking water standards, and sustainable development imperatives (Keiser and Shapiro, 2019; BIS, 2012; Huang et al., 2023). The methodological approach adopts a critical interpretive synthesis of interdisciplinary literature to construct an integrated conceptual framework that elucidates how sensor-level innovations scale into system-level sustainability outcomes. Results are articulated through descriptive and interpretive analysis rather than quantitative modeling, highlighting patterns, alignments, and tensions across scholarly perspectives. The discussion advances a nuanced critique of techno-centric narratives by foregrounding issues of equity, governance, cybersecurity, and rural–urban disparities in water access and monitoring capacity (Pacheco et al., 2017; Yasin et al., 2021). The article concludes by identifying future research directions that prioritize socio-technical co-design, regulatory harmonization, and ethical data stewardship. Collectively, the study contributes a publication-ready, theoretically expansive, and policy-relevant foundation for advancing secure, intelligent, and sustainable water quality monitoring systems aligned with global development goals.

The 2021–2025 period has been a challenging yet highly impressive period for Vietnam’s economy. Amid complex global fluctuations—including the COVID-19 pandemic, geopolitical conflicts, and supply chain disruptions—Vietnam has maintained macroeconomic stability and promoted sustainable growth. This research report provides an in-depth analysis of results over the past five years, focusing on the implementation of 23 key socio-economic indicators and three strategic breakthroughs in institutions, infrastructure, and human resources. Data indicate a robust recovery in GDP growth; furthermore, administrative reform efforts have eliminated over 3,200 business regulations, resulting in annual savings of approximately 49 trillion VND. Vietnam also set a new record in import-export turnover, estimated at 920 billion USD, while attracting the highest realized Foreign Direct Investment (FDI) in five years. However, the report identifies bottlenecks in labor productivity and public investment disbursement that require resolution. Overall, the past five years provide a solid foundation for the nation to reach its goal of becoming a high-income developed country by 2045

Modular learning is the organization of the educational process in which educational information is divided into modules (complete and independent units, parts of information). A module is a block of information that includes a logically completed unit of educational material, a targeted program of action and methodological guidance that ensures the achievement of set goals. The concept of a module contains such a volume of educational material, thanks to which the primary acquisition of certain theoretical and practical skills for performing any specific work is ensured.

This article examines the differentiated approach to teaching Russian language lessons as an effective pedagogical technology within the modern educational process. The study highlights the importance of competency-based education and the necessity of adapting instructional methods to students’ individual abilities, cognitive activity, and learning pace. Special attention is given to grouping learners according to their academic preparedness and psychological characteristics. The article analyzes the criteria for differentiation, describes the pedagogical tasks of the teacher for each group, and outlines practical methods used at different stages of the lesson. The findings demonstrate that differentiated instruction contributes to improving educational quality, fostering learner autonomy, and developing communicative competence.

This article examines the prospects and challenges of integrating artificial intelligence (AI) technologies into the operations of higher education institutions in Uzbekistan. It analyzes both the potential benefits and the associated risks of AI adoption, drawing on the experiences of leading international universities that have successfully implemented AI-based solutions in their educational systems. Particular attention is given to the pedagogical application of the ChatGPT platform in teaching and learning processes. In addition, the study identifies a set of priority measures that higher education institutions should undertake to ensure the effective and responsible deployment of AI technologies. The article also explores practical approaches for maximizing the educational, administrative, and analytical potential of AI platforms within the higher education system.

Background: In the modern era, technological justice is one of its fundamental aspects since it helps to ensure that everyone has an equal chance to obtain education and use technology in a fair and efficient way. Justice, particularly in the area of education and the principle of equal educational opportunities, reflects the values of social justice and equality. Goal: By conducting an applied study on primary school teachers in Riyadh, Saudi Arabia, this study seeks to explore the opportunities and difficulties associated with attaining technological justice in education. The study concentrated on the degree of access to technology in schools, the digital proficiency of teachers in utilizing technology in the classroom, and the effect of technology on students' equal access to education. Methodology: A quantitative cross-sectional descriptive design was employed. Using Krejcie and Morgan's sample size formula, 402 primary school teachers were systematically selected through stratified random sampling. Data were collected using a validated 21-item questionnaire administered electronically. Statistical analysis included descriptive statistics, Pearson correlation coefficients, and internal consistency reliability testing using Cronbach's alpha. To produce results in the form of means, standard deviations, frequencies, and percentages, descriptive analysis was performed. Findings: In Riyadh's primary schools, the level of technological resource availability was largely average. When it came to using technology in the classroom, primary school teachers were highly proficient. According to primary school teachers, equal educational opportunities for all students in primary schools are greatly impacted by the use of technology. The low average accessibility of digital resources for all students highlights a potential gap in meeting their diverse needs, calling for a review of current policies and practices to ensure true inclusiveness in the use of educational technology. The degree of availability, teacher competence, and technological justice was average, which means that there is need for improvement especially in relation to investing in technological infrastructure and training primary school teachers in Riyadh to equip them with advanced technological skills.