A Correlational Study of Peer Social Support and Student Engagement Among Junior High School Students

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Student engagement is widely regarded as a key determinant of successful learning, yet preliminary observations at a state Islamic junior high school (Madrasah Tsanawiyah) in South Sumatra indicated that students’ affective, behavioral, and cognitive engagement had not yet developed optimally. One contextual factor thought to contribute to this pattern is peer social support, given that friendship relationships become increasingly important during early adolescence for meeting the psychological needs of belonging and relatedness. This study aimed to empirically examine the relationship between peer social support and student engagement among seventh- and eighth-grade students. A quantitative correlational design was employed, involving 205 students drawn from a population of 500 through simple random sampling based on the Isaac and Michael table at a 95% confidence level. Data were collected using two five-point Likert scales: a Student Engagement Scale developed from the affective, behavioral, and cognitive engagement dimensions proposed by Lam et al. (2014), and a Peer Social Support Scale based on the appraisal, tangible, belonging, and self-esteem support dimensions proposed by Cohen and Wills (as cited in Schonfeld, 1991). Data were analyzed using simple linear regression with SPSS version 27. The results revealed a positive and highly significant relationship between peer social support and student engagement (r = 0.329; R Square = 0.108; p = 0.000), with peer support accounting for 10.8% of the variance in engagement. These findings indicate that greater peer social support is associated with higher student engagement, although most of the variance in engagement is explained by factors beyond peer support alone.

The Application of a Problem-Based Learning Model Using The Experimental Method on The Learning Outcomes and Scientific Reasoning Skills of Elementary School Students in Science Education

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Science learning in elementary schools requires students to understand concepts through observation, investigation, and reasoning processes. However, students’ learning outcomes and inference skills are still relatively low because learning activities are often dominated by teacher explanations and have not fully involved students in scientific inquiry activities. This study aims to analyze the effect of the Discovery Learning model assisted by Live Worksheet on students’ learning outcomes and inference skills in science learning on the topic of changes in states of matter.

This study employed a quantitative approach with a quasi-experimental method using a Nonequivalent Control Group Design. The research subjects were fourth-grade students of SD Negeri Antirogo 01 and SD Negeri Antirogo 04, Jember Regency, consisting of 62 students. The experimental class received treatment through Discovery Learning assisted by Live Worksheet, while the control class received conventional learning. Data collection techniques used learning outcome tests and inference skill instruments. Data analysis was performed through prerequisite tests and hypothesis testing using inferential statistics.

The results showed that the Discovery Learning model assisted by Live Worksheet had a significant effect on students’ learning outcomes and inference skills. The learning process encouraged students to actively observe, collect information, process data, verify findings, and formulate conclusions based on evidence. The integration of interactive digital worksheets strengthened students’ involvement and supported meaningful learning experiences. Therefore, Discovery Learning assisted by Live Worksheet can be an effective alternative strategy to improve cognitive achievement and scientific thinking skills among elementary school students.

Transition From Free Bags to Eco-Friendly Alternatives: Economics, Greenwashing and Consumer Behavior in Veracruz, Mexico

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The replacement of free plastic bags with alternatives marketed as eco-friendly has transformed the economic and environmental relationships between businesses and consumers; however, charging for bags does not necessarily imply an effective reduction in their consumption and can encourage greenwashing strategies when environmental claims lack verifiable support. The objective of this research was to analyze the economic and environmental implications of changing from free bags to paid bags with an eco-label in businesses in Veracruz–Boca del Río. A descriptive-exploratory study was conducted through direct observation in 16 businesses in the Veracruz–Boca del Río metropolitan area, Veracruz, Mexico, during January and February 2024. The type of material, price, dimensions, delivery conditions, and observed consumer behavior were recorded. The information was systematized through a qualitative-interpretive analysis. Significant differences were identified in prices and marketing methods, noting that conventional bags ranged in price from $1.00 to $17.50 MXN, while those labeled as eco-friendly or reusable ranged from $3.00 to $25.00 MXN. Replacing free bags with paid alternatives eliminated an operating cost and generated a new potential revenue stream. Furthermore, commercial practices based on environmental attributes were observed without sufficient information on reuse or environmental performance. It is concluded that the analyzed transition presents a relevant economic dimension and characteristics consistent with greenwashing; therefore, the environmental effectiveness of these policies should be evaluated using verifiable indicators of reduced consumption and increased bag reuse.

Generative AI Empowering Chinese Language Teaching in Vietnam: Current Applications, Empirical Investigations, and Practical Pathways

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The iterative upgrading of generative artificial intelligence (AI) has profoundly reshaped the pedagogical forms and developmental models of international Chinese language education. As a core country for Chinese learning in Southeast Asia, Vietnam witnesses robust and growing demands for Chinese language education, yet it has long confronted structural dilemmas including insufficient teacher supply, inadequate localized teaching resources, and difficulties in implementing personalized instruction. To explore the adaptability and practical value of AI technology in Vietnamese Chinese teaching, this study adopts a mixed‑method research design. Based on questionnaires, semi‑structured interviews, and an eight‑week classroom action research involving 221 teachers and learners from universities, primary and secondary schools, and training institutions in Hanoi and Ho Chi Minh City, this paper systematically examines the application scenarios, practical effects, and localized challenges of generative AI in local Chinese pedagogy. The results indicate that generative AI functions as an effective digital pedagogical scaffold, alleviating shortages of teaching resources and professional teachers, reducing learners’ foreign language anxiety, and improving the efficiency of basic linguistic training. Nevertheless, current applications are constrained by insufficient Vietnamese‑Chinese bilingual corpus adaptation, inadequate teachers’ AI pedagogical literacy, learners’ technological dependence, and prominent regional digital divides. Grounded on the Technology Acceptance Model (TAM) and sociocultural constructivist theory, this study constructs a teacher‑led and AI‑assisted collaborative teaching paradigm and proposes targeted optimization pathways from four dimensions: localized resource development, teacher competency cultivation, classroom procedure reconstruction, and learner media literacy enhancement. This research fills the empirical research gap regarding intelligent Chinese language education in Vietnam and provides practical implications for the digital transformation of Chinese language education in ASEAN countries.

Business Analytics Capability and Organizational Cyber Resilience: The Roles of Data-Driven Risk Detection and Cybersecurity Governance

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This study examines the relationships among business analytics capability, data driven risk detection, and organizational cyber resilience while evaluating the moderating influence of cybersecurity governance maturity. Drawing on Dynamic Capabilities Theory and Organizational Information Processing Theory, it conceptualizes organizational cyber resilience as the outcome of organizational capabilities that transform integrated analytical resources and cyber risk information into timely, coordinated, and adaptive responses. Cybersecurity governance maturity serves as a boundary condition that determines whether analytical insights can be translated into stronger resilience outcomes. A quantitative cross-sectional design gathered responses through a five point Likert scale questionnaire from 385 Vietnamese professionals knowledgeable about business analytics, cybersecurity, information technology, risk management, digital operations, organizational governance, or business continuity. IBM SPSS version 26 supported reliability assessment, exploratory factor analysis, and multiple linear regression, while Hayes’ Process Macro Model 1 examined the moderating effect. The findings show that business analytics capability (β = 0.573) and data driven risk detection (β = 0.638) significantly improve organizational cyber resilience. Data driven risk detection produces the stronger direct effect, emphasizing the importance of continuous monitoring, anomaly identification, and actionable cyber risk warnings. Cybersecurity governance maturity further strengthens the positive relationship between business analytics capability and organizational cyber resilience through a significant interaction coefficient of 0.407. The results demonstrate that analytical technologies alone cannot guarantee cyber resilience. Organizations must combine integrated analytical resources and timely risk detection with clear accountability, formal escalation procedures, structured oversight, continuous governance improvement, and sufficient authority to coordinate responses.

Enhancing E-Commerce Customer Satisfaction: A Multi-Method Approach Using Sentiment Analysis, IPA, and PGCV

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The advancement of information technology has enabled rapid expansion in e-commerce, establishing one of the platforms as a leading company in Indonesia. Subsequently, the authors name the e-commerce platform as XZ to preserve the anonymity of the research subject. This research intends to evaluate consumer sentiment regarding XZ’s e-service quality utilizing opinion mining based in the Support Vector Machine (SVM) method, while also determining enhancement priorities through Importance Performance Analysis (IPA) and Potential Gain in Customer Value (PGCV). The dataset comprises 50,000 data from the Google Play Store, categorized into positive and negative comments. The findings reveal that factors including the promptness in addressing customer complaints, the effectiveness of refund procedures, and XZ’s reliability in delivering promotional commitments, including shipping discount vouchers, are primary customer concerns. The IPA technique indicated that key service components should be emphasized to improve customer satisfaction, particularly attributes such as P4, P13, and P14. The PGCV methodology strengthened these results by determining the enhancement opportunities that would most significantly elevate service value, particularly attribute P4 associated with the promptness of addressing customer complaints. Also, P13 regarding the effectiveness of refund procedures for incorrectly shipped or defective products, and lastly P14 pertaining to XZ’s reliability in delivering on promotional commitments such as shipping discount vouchers. The results of this study have the potential to provide a benchmark for the businesses in formulating more efficient service enhancement plans and assist in advancing the field of quality management within the e-commerce industry.

A Comparative Analysis of Advanced Nuclear Fuel and structural Design in Advanced Fission Reactor

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The rapid transition toward low-carbon energy systems and increasing global energy demand have renewed interest in advanced nuclear fission technologies, particularly Generation IV reactors and Small Modular Reactors. This study aims to comparatively evaluate advanced nuclear fuels and structural materials based on their thermal, neutronic, mechanical, chemical, irradiation, and safety performance. An analytical review of scientific and technical literature from academic databases and authoritative nuclear organizations was conducted. The literature was qualitatively synthesized according to fuel type, structural material, reactor concept, coolant, and neutron spectrum. The findings indicate that uranium nitride, uranium silicide, and tri-structural isotropic fuels provide important advantages over conventional uranium dioxide fuel, including higher thermal conductivity, greater fuel density, improved high-temperature performance, and enhanced fission-product retention. Among structural materials, iron-chromium-aluminum alloys, silicon carbide composites, and high-entropy alloys demonstrate promising oxidation resistance, thermal stability, mechanical strength, and irradiation tolerance. However, their performance is strongly dependent on reactor type, neutron spectrum, coolant chemistry, operating temperature, and irradiation conditions. The review further shows that integrating advanced fuels and structural materials with passive safety systems and modular reactor architectures can improve safety, thermal efficiency, sustainability, and economic potential. Major challenges remain in irradiation qualification, corrosion, manufacturing, regulatory approval, economic feasibility, and spent-fuel management. Overall, coordinated development of advanced fuels and structural materials represents a promising pathway toward safer, more efficient, sustainable, and economically viable nuclear energy systems.

The Role of Traditional Pottery Production in Sustainable Community Development in Uganda: (A Case Study of the Ankole Sub-Region)

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Traditional pottery production is a significant but not broadly researched area in sustainable community development in Uganda, especially in rural areas where the economy is generally based on the crafts industry. This study aimed at the investigating socio-economic, cultural, and environmental impacts of traditional pottery production in sustainable community development in the Ankole Sub-Region, Western Uganda. The study was guided by the sustainable livelihood framework and the perspectives of culture-based development. The study used a descriptive cross-sectional case study design. This study used a sample size of 20 respondents, comprising 8 master potters, 4 long-term traders, 2 elders, 4 clay extractors, and 2 transporters. The researcher used a multistage sampling technique in areas with concentrated, accessible pottery activity in the Ankole sub-region. Semi-structured interviews and observations, together with structured interviews, were employed in data collection. Thematic data analysis, as described by Braun and Clarke (2006), was employed in analyzing the qualitative data, while descriptive statistics summarized the basic livelihood and production data.

The findings showed that traditional pottery-making is an important economic activity for diversifying income and minimize poverty level by empowering women economically, passing on skills to the next generation, preserving cultural identity, heritage, and improve community ties through working together, and helping the development of the circular economy through the availability of local resources such as clay and organic matter for firing, and the simple technology for pottery-making.

However, the sustainability of the traditional pottery is also limited by factors such as less access to the market, insufficient production facilities and modern kilns, reduced access to suitable clay materials, health risks from inhaling smoke and dust, and less institutional backing for the value steam. These findings also confirm previous evidence suggesting that pottery production results in employment and alleviates poverty in Ankole, while also emphasizing environmental and technical concerns related to production methods. The study concludes that enhancing pottery value steams through technological innovations, collaborative marketing strategies, heritage tourism partnerships, and targeted support from local government can promote sustainable community development outcomes aligned with Uganda’s national development goals and the increasing recognition of crafts within Uganda’s creative economy.

From Magnesium Feedstocks to Reactive MgO: A Critical Review of Production Routes, Reactivity Control, Industrial Scalability, and Environmental Trade-Offs

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Reactive magnesium oxide (r-MgO) is often treated as a single material class, yet its performance is governed by a chain of coupled decisions extending from magnesium source and precursor chemistry to heat and mass transfer, calcination severity, atmosphere, particle size, purification, and post-calcination aging. This structured critical narrative review reframes reactive MgO production as a process–structure–reactivity engineering problem rather than a catalog of synthesis methods. A fixed core evidence corpus of 103 publications from 2020 through August 2026 was coded by production route, evidence scale, reactivity endpoint, and environmental/economic dimension; three pre-2020 foundational sources were used only for terminology and mechanistic context and were excluded from corpus counts. The review compares mineral-derived, brucite-derived, dolomitic, seawater/brine, waste-derived, sulfate-derived, and specialty precursors; conventional, flash, fluidized-bed, steam-assisted, solar/electrified, precipitation, carbonation, electrochemical, and hybrid routes; and the analytical methods used to describe reactivity. No single metric—calcination temperature, BET surface area, hydration rate, or CO₂ uptake—defines reactive MgO across applications. Instead, reactivity emerges from the preservation or destruction of accessible mesoporosity, surface defects, dissolution sites, crystallite-scale disorder, and pore connectivity, provided that sufficient precursor conversion and chemical purity are achieved. Fast thermal routes can reduce sintering exposure, whereas brine and residue routes can decouple purity from the original mineralogy but introduce reagent demand, washing, mother-liquor management, and scale-up penalties. Environmental advantage is likewise route-specific: avoiding magnesite decarbonation can reduce process CO₂, but upstream alkalis, electricity, solids handling, and unrealized carbonation can reverse apparent benefits. The industrially optimum product is therefore not the MgO with the highest nominal reactivity, but the product whose application-specific reactivity window is achieved at acceptable purity, energy demand, carbon footprint, cost, throughput, and consistency. The review concludes with a research agenda centered on standardized reporting, direct route-to-route experiments, impurity-tolerance maps, continuous pilot validation, and integrated mass–energy–carbon–cost assessment.

European Classification and Labelling of Hazardous Products

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By adopting the CLP Regulation, the European Union has aligned its classification and labelling system for hazardous substances with a globally accepted standard based on the United Nations’ Globally Harmonised System of Classification and Labelling of Chemicals (GHS). This article summarizes the key aspects of the current status of the CLP Regulation. It introduces the available labelling elements, such as hazard pictograms, signal words, hazard statements, and precautionary statements. This is followed by an overview of physical hazard classes, health hazards, environmental hazards, and an additional hazard class. The communication elements for each hazard class are presented in a tabular overview. Subsequently, general and specific criteria for the classification of mixtures are listed. The discussion section examines current legislative trends.