The Effect of Discovery Learning Model Assisted by Live Worksheet on Students’ Learning Outcomes and Inference Skills in Elementary School Science Learning

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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.

Linguistic Factors Affecting English Speaking Skills among Second-Year English-Major Students: A Mixed-Methods Study

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This study investigated the relationships between vocabulary competence, grammatical competence, pronunciation competence, and self-perceived English-speaking skills among second-year English-major students at Nguyen Tat Thanh University (NTTU), Vietnam. An explanatory sequential mixed-methods design was employed. Quantitative data were collected through a questionnaire administered to 102 students, followed by semi-structured interviews with five selected participants. Descriptive statistics and Pearson correlation analysis were used to examine students’ self-assessments, while thematic analysis explored their reported speaking difficulties. The results revealed positive perceptions of linguistic competence and speaking skills overall. Vocabulary competence showed the strongest correlation with overall self-perceived speaking skills (r = .502, p < .001), followed by grammatical competence (r = .492, p < .001) and pronunciation competence (r = .397, p < .001). Interview findings provided further insights into difficulties with lexical retrieval, grammatical processing, final consonant production, stress, intonation, and speaking confidence. These findings highlight the interconnected roles of linguistic resources in students’ perceptions of oral communication. The study suggests that EFL instruction should integrate vocabulary development, communicative grammar practice, pronunciation training, and supportive speaking activities. However, because the quantitative measures were based on self-report, the findings indicate associations among perceived competencies rather than causal effects on objectively measured speaking performance.

Robust Optimal Power Flow under Industrial Cyberattacks and Renewable Uncertainty

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The digitalization of electric-power operation couples optimal power flow (OPF) with measurement systems, communication networks and increasingly variable renewable generation. Power system operators may have to make dispatch decisions using load measurements that have been altered by false-data injection attacks. At the same time, actual renewable power generation may differ from what was forecast. When these two problems occur together, the system may need more balancing capacity than would be expected if each uncertainty were considered separately. This paper examines both effects through a scenario-based robust direct-current optimal power flow (DC-OPF) approach. The proposed model determines generator schedules and upward and downward reserves with ensuring that the system can respond to bounded combinations of corrupted load measurements and renewable forecast errors. The approach focuses on reducing their operational consequences. It assumes that the operator does not know the exact amount of corruption measurement but can define reasonable limits for measurement errors and renewable uncertainty. The study uses the publicly available PGLib-OPF v23.07 IEEE 14-bus and IEEE 30-bus networks, with additional renewable generation and cyberattack scenarios introduced for testing. The results show that the robust approach increases preventive operating costs by 0.98% for the 14-bus system and 1.97% for the 30-bus system compared with a deterministic OPF using a standard 10% balancing-reserve rule. In 3,000 out-of-sample scenarios for each network, the robust schedule avoided emergency load shedding within the defined uncertainty limits. By comparison, the deterministic approach required load shedding in 62.77% of the IEEE 30-bus scenarios, with an average of 2.56 MW and a maximum of 18.93 MW of unserved power. These results suggest that the benefit of robust OPF is not simply a change in how generation is scheduled. More importantly, it helps place reserve capacity where it can be used effectively, reducing the risk that corrupt measurements and unexpected renewable fluctuations will prevent the power system from operating within its physical limits.

Taste Over Looks: How Product and Store Attributes Drive Satisfaction and Loyalty among Generation Z Coffee Shop Consumers

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Coffee shops targeting Generation Z increasingly compete on visually appealing beverages, on the assumption that this digitally native generation cares most about how products look. This study examined what actually satisfies Generation Z coffee shop customers and keeps them coming back, comparing the role of visual presentation with that of taste consistency, store ambience and value for money. A survey using a four-point Likert questionnaire was conducted in December 2025 among 87 undergraduate students at the Indralaya campus of Universitas Sriwijaya, Indonesia, who were selected by purposive sampling. The data were analysed in SPSS using descriptive statistics, the McNemar test, the Mann–Whitney U test, Cronbach’s alpha, Spearman’s rank correlation, multiple linear regression and bootstrapped mediation analysis with the PROCESS macro (Model 4). Respondents chose coffee shops mainly because the place was comfortable and conveniently located, whereas taste was mentioned far more often as a reason for being satisfied than as a reason for choosing a coffee shop. Although most respondents said that the presentation of a beverage matters to their satisfaction, the importance they attached to presentation was unrelated to how satisfied they actually were. Instead, satisfaction was driven mainly by consistent taste and, to a lesser extent, by a comfortable store environment. Satisfied customers were more willing to return and to recommend the coffee shop, and taste and ambience strengthened loyalty by first increasing satisfaction. Value for money did not raise satisfaction but directly encouraged customers to return. These findings challenge the assumption that visual appeal is decisive for Generation Z: whatever role presentation plays in attracting customers, consistent taste and a comfortable environment sustain their satisfaction, and fair prices bring them back.

Strategy for Optimizing Idle Land to Increase Non-Aeronautical Revenue: A SWOT and VRIO Approach

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The decline in air traffic at Adisutjipto Airport, Yogyakarta, following the opening of Yogyakarta International Airport calls for revenue sources that do not depend on passenger volume. This study analyzes the existing condition of idle land, the internal and external factors influencing its optimization, and the company’s resource advantages, and then formulates a strategy for optimizing idle land to increase non-aeronautical revenue. A descriptive qualitative approach was employed in a single case study of the 4,945 m² Babarsari idle land owned by PT Angkasa Pura Indonesia, Adisutjipto Yogyakarta Branch Office. Primary data were obtained through semi-structured interviews with nine purposively selected informants; secondary data came from the partner selection document and the highest and best use (HBU) study. The data were analyzed through reduction, display, and conclusion drawing using weighted strengths, weaknesses, opportunities, and threats (SWOT) analysis, value, rarity, imitability, and organization (VRIO) analysis, and a value creation assessment. Data trustworthiness was tested through triangulation, member checking, and an audit trail. The results show that the land has clean and clear legal status, that the company’s strategic position lies in SWOT Quadrant I (+0.88; +1.68), and that four of the six resources generate sustained competitive advantage. Corporate reputation and the stakeholder network have not yet been utilized because organizational readiness, particularly specific regulations for land outside the Airport Master Plan (AMP) and communication with the community, is still being developed. The sports center alternative with integrated commercial facilities ranks highest on four of the five value creation indicators, although its net present value is lower than that of office space. These findings indicate that strategy selection depends not only on financial performance but also on organizational readiness and stakeholder relationships. Actual revenue realization will be evaluated once the business activities are in operation. The study recommends strengthening internal regulations, accelerating the cooperation process, and developing an asset utilization strategy that considers economic potential, implementation readiness, and business sustainability.

Piezoelectric Materials for Piezocatalysis and Piezo-Photocatalysis: Fundamentals, Mechanisms, Materials and Environmental Applications

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Piezocatalysis and piezo-photocatalysis have emerged as promising approaches for environmental remediation by utilizing mechanical energy alone or in combination with light to drive redox reactions. This review systematically summarizes the fundamental principles and mechanisms of piezoelectricity, piezocatalysis, photocatalysis, and piezo-photocatalysis, with particular emphasis on charge separation and reactive species generation. Recent advances in piezoelectric materials, including conventional and emerging materials, transition-metal chalcogenides, perovskites, and layered bismuth-based materials, are discussed together with strategies for improving catalytic performance. Their applications in pollutant degradation, heavy-metal removal, water purification, disinfection, and microbial inactivation are further reviewed. Finally, current challenges and future perspectives related to material design, energy utilization, mechanistic understanding, stability, and practical application are highlighted. This review provides an integrated perspective on piezoelectric catalytic systems and their potential for sustainable environmental remediation.

“Balatro Madness” Exploring Addictive Game Elements in Indie Hit Through Octalysis Framework and Flow Theory

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This study explores the addictive elements of the hit indie game Balatro using the Octalysis Framework and Flow Theory. This study employed an explanatory mixed-method approach, combining quantitative survey data with qualitative open-ended responses. The questionnaire was answered by 59 players from the Balatro Game community on Facebook and Discord. Data were collected through a questionnaire structured based on the Octalysis Framework and the Flow model. The findings indicate that Balatro scored 66.78 out of 80 on the Octalysis scale, indicating strong addictive potential. The average Flow score was 28.5 out of 35, indicating high player engagement and an optimal FLOW state. Key addictive elements include: a balanced challenge-skill progression, objectives that adapt to players’ skill levels, collecting Joker cards, unpredictable strategy combinations, and a collectible card system. These elements are effective because Balatro gradually increases in difficulty as players’ skills increase, with eight Stake levels and an unlimited score cap (Naneinf). Players are rewarded with rare cards and encouraged to share achievements socially, which strengthens a sense of ownership and social influence. This research shows that the addictive mechanics in Balatro, developed by a single indie developer, can serve as a replicable model for designing educational and commercial games with high engagement potential.