Environment-Behaviour Proceedings Journal (E-BPJ)
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Generative AI in Academic Writing: Exploring ESL students’ strategies and performance
Full text linkEasy access to Generative Artificial Intelligence (GenAI) technologies has enabled tertiary students to accomplish writing tasks in the English language regardless of their competencies. However, the lack of formal instructions in higher education curricula leaves many unanswered questions regarding how effectively students use the tools to their advantage. To identify how tertiary students incorporate GenAI into their academic writing and the effects on their output, this exploratory case study investigated GenAI-assisted writing strategies among 13 university students in Malaysia. A thematic analysis of their self-reported usage of ChatGPT revealed six key strategies that influence their writing performance
Landscape Optimization Design based on the Concept of "Ming Tang" in Geomancy Science
Full text linkThis paper discusses the application of the concept of "Ming Tang" in modern landscape optimization in Chinese geomancy science. Through literature review and case analysis, the application principles of this concept in modern landscape design are extracted, and the project is implemented. It is found that the concept of "Ming Tang" can guide the order of environmental space, increase cultural significance, optimize functional layout, and improve comfort. In addition, this paper also discusses the limitations of the concept of "Ming Tang" in modern landscape design, such as lack of quantitative data support, cultural background differences, etc
Integration of Aesthetics and Creative Design: The influence of traditional Ru porcelain on product design
Full text linkThis study reviews the historical background of Ru porcelain aesthetics, emphasizing its natural and minimalist qualities. It proposes the application of Ru porcelain aesthetics to modern product design, focusing on material selection, craftsmanship, incorporation of natural elements, and combining cultural heritage with innovation. The research deepens the understanding of the value of Ru porcelain aesthetics and its role in product integration and innovation, providing practical guidance and methodologies for its application in contemporary design practices
Information Management Monitoring System for Fish Cage Farming
Full text linkThis study investigates the integration of Internet of Things (IoT) technologies within an Information Management Monitoring System (IMMS) to improve water quality monitoring, operational efficiency, and decision-making in fish cage farming on the Semantan River, Temerloh. Employing mixed methods, the research targets 117 fish cage farmers, sampling 30 to 50 participants. The IoT-powered IMMS enables real-time monitoring and data-driven management, enhancing aquaculture resilience against environmental challenges. This approach supports sustainable seafood production by optimizing water quality and farm operations, contributing to the aquaculture industry’s adaptation and sustainability goals
Application of Fuzzy Delphi Technique for Developing a Higher Education Competency Model: Insights from HR practitioners
Full text linkThis study employs the Fuzzy Delphi Technique to develop a higher education competency model, addressing the significant gap between academic curricula and industry requirements. A panel of 15 experts, including academic professionals and HR practitioners, participated in a structured process to evaluate and prioritize essential skills. The expert consensus identified communication, technical proficiency, time management, and teamwork as top priorities, each with over 90% agreement. The integration of HR insights ensures the model aligns precisely with workforce demands. The findings provide actionable guidance for curriculum development, enhancing graduate employability by bridging the gap between academic preparation, and evolving employer expectations
Preserving and Promoting Malaysia's Regional Culinary Traditions: Governmental Roles and Challenges
Full text linkThis research examined the role of Malaysia's culinary heritage in driving tourism and fostering economic development, focusing on government interventions. It unravelled the nuances of effective marketing strategies and their long-term economic implications by incorporating regional cuisine into promoting tourism. The study addressed the government's emphasis on preserving culinary traditions but noted challenges in promotional efforts affecting sustainable development. Using quantitative methodologies it elucidated the government's responsibilities on integrating local food in tourism. The findings contribute to knowledge on tourism, local gastronomy dynamics, and cultural inclusion, recommended a framework in future research for sustainable and culturally enriched tourism in Malaysia
Blockchain Technology in the Halal Supply Chain: Comparative insights from Malaysian micro, small, and medium enterprises
Full text linkThis study explores blockchain adoption in the Halal supply chain, focusing on Malaysian micro, small, and medium enterprises (MSMEs). Blockchain technology enhances transparency, traceability, and trust in Halal certification processes. Through in-depth interviews with MSME representatives, the research identifies technological readiness and vendor support as critical factors influencing adoption. Findings emphasize the need for robust infrastructure and reliable vendor services to drive blockchain integration. The study contributes to technology adoption literature and offers practical insights for improving Halal supply chain efficiency. Future research should further examine these determinants and develop frameworks for blockchain implementation in Halal industries
Enhancing Speaking Proficiency through Task-Based Activities: A systematic literature review in the TVET context
Full text linkSpeaking proficiency is important to TVET learners as they prepare for workplace communication. This systematic literature review explores the use of task-based language teaching (TBLT) for improving speaking in TVET context. Following the PRISMA framework, we included and analyzed twelve studies in the from Scopus and Web of Science. Three themes were identified in the review: (1) task-based speaking activity design, (2) learners’ communicative competence and (3) trends and gaps in TBLT research. The results emphasize the need for real tasks, learner interaction and more research in digital tools and teacher preparedness in TVET contexts
Change Management Practices' Survey in Implementing Education Policy from Teacher Perspective
Full text linkEmploying change management at school level could enhance teacher acceptance and preparedness, subsequently reduce any hindrance of education policy implementation. This paper examines the validity and reliability of Change Management Practices' Survey as a tool for evaluating change management practices in school through Exploratory Factor Analysis and Cronbach's Alpha test. Study of the instrument gives communalities ranging from 0.83 to 0.57, and factor loading values varying between 0.89 and 0.63, meanwhile Cronbach Alpha value stood at 0.97. These indicate the instrument's high validity and reliability, rendering it suitable for further comprehensive investigations into assessing change management practices within school
Deep Learning Architectures for ECG Classification in Cardiac Arrhythmia Detection: A review
Full text linkCardiac arrhythmias are irregular heartbeats that may cause severe complications, including stroke and heart failure. Early detection is essential for diagnosis and treatment. This study examines deep learning models for ECG classification, evaluating CNNs, RNNs, and LSTMs. Results indicate LSTMs achieve the highest accuracy: 97.3% (PTB), 93.11% (ECG-ID), and 96.81% (MIT-BIH). Hybrid CNN-LSTM models enhance performance, particularly on imbalanced datasets. These findings demonstrate deep learning’s effectiveness, especially LSTMs, in improving ECG classification. Enhanced accuracy in arrhythmia detection can support cardiologists in diagnosing conditions more efficiently, leading to better patient outcomes and automated diagnostic advancements