Engineering Tools Research Articles

The Evolution of EFL and ELL (2000-2024): Impact of Culture, Technology, and Innovative Pedagogies on Language Learning

For nearly a century, English language has consistently remained a global phenomenon with a continued business relevance; the mandatory inclusion of English Language Learning (ELL) in Asian, African and other non-native English-speaking countries is proof of the same. Consequently, research about English as a Foreign Language (EFL) has continued too. Despite ample empirical studies in the past that have examined the role of culture, linguistics, technology or digital tools in EFL, there are limited studied that holistically investigate and review the learning and successful implementation of EFL and its influencing factors. The current study is an attempt to systematically synthesize the findings from empirical studies undertaken between early 2000 and 2024 in the domains of EFL and ELL for a sample of 53 journal articles. The research also aims to draw a scientific relationship between the most relevant concepts surrounding ELL and EFL. To achieve this, the study conducted a systematic literature review coupled with Bibliometric mapping analysis. The study concluded that the upward surge of technological advancements and World Wide Web has transformed learning EFL. Cultural diversity, and technological or digital tools are key influencing factors and innovative teaching/learning pedagogies in EFL and ELL that can enhance the success rates in EFL and ELL in non-native English-speaking countries.

Digitally Driven Urban Governance: Framework and Evaluation in China

With the rapid development of digital technology, the role of digitalisation in urban governance continues to emerge. Building a theoretical analysis framework and evaluation system of digitally driven urban governance has important theoretical and practical significance for stimulating the efficiency of digital technology tools and improving the energy level of urban digital governance. This paper aims to explore the mechanism of urban governance enabled by digital technology, innovatively change the previous thinking mode that only attaches importance to facility construction and e-government platforms, adopt ecological thinking, and comprehensively consider the role of “soft elements” such as strategic support, industrial support, the security environment, talent support, and the market environment. Then, the extreme value variance method and the coefficient of variation method are used to calculate the overall capacity and secondary index scores of each city, and the standard deviation of secondary index scores is used to represent the sub-environmental balance of the cross-sectional data of China’s provinces. In order to further explore which indicators restrict the improvement of China’s urban digital governance capacity, this study also constructs an obstacle degree model. The results show the following: (1) The overall capability of China’s digitally driven urban governance is low, with a total score of 27.25, indicating that China’s digitally driven urban governance is in its infancy. (2) There is a significant development imbalance among Chinese provinces, with Beijing ranking first with a score of 81.16, and Tibet, Qinghai, Xinjiang, Heilongjiang, and Ningxia scoring less than 13.30 points, ranking as the bottom 5 among the 31 provinces. (3) The shortcomings of talent support, industrial support, and the security environment restrict the improvement of the entire digital ecological governance ability.

Factors influencing EFL learners’ speaking fluency: A case study at a high school in Vietnam

This study investigates how four key factors - English exposure, learning environment, motivation, and teaching pedagogy - affect English speaking fluency among high school students, using both qualitative and quantitative research methods. The findings indicate that frequent exposure to English, an engaging learning environment, and effective teaching pedagogy significantly enhance students' speaking fluency and motivation. Qualitative results show that students who interact with English regularly, whether through classroom activities or extracurricular engagement, demonstrate better fluency and enthusiasm. A dynamic and supportive learning environment, combined with interactive teaching strategies, fosters higher levels of student participation and motivation. However, the study acknowledges several limitations. The small sample size used in the qualitative phase may not fully represent the broader student population, potentially impacting the generalizability of the findings. The reliance on self-reported data in the quantitative analysis introduces the possibility of bias, which could affect the accuracy of the results. The study also notes that focusing on a limited set of factors might overlook other influential elements such as individual learning styles or external pressures. Future research should aim to include a larger and more diverse sample, explore a broader range of factors affecting English fluency, and incorporate various activities and technological tools to address these limitations. By expanding the scope of research and incorporating these suggestions, more comprehensive strategies can be developed to improve English speaking fluency among students. This approach will provide valuable insights for educators and policymakers, assisting them in designing more effective language programs and interventions that enhance students' communicative competence and overall language proficiency.

Impact of prior experience and gender on cognitive load during initial drone use

The purpose of this demonstration study was to determine the effect of prior experiences and gender on cognitive demands at the initial educational technology experience. The task of drone operation was selected as a novel educational technological tool and videogame use was determined to be a tangential prior experience. Through the framework of embodied cognition, the NASA Task Load Index was used to measure cognitive demand. Practicing middle- and high-school science teachers were recruited to participate in this study. Participants operated drones at three instances over two weeks. An additional challenging task was also presented. A mixed ANOVA suggested a significant interaction between videogame use and time: F(2, 28) = 3.77, p<\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p<$$\\end{document} 0.05. A significant interaction between gender and time was also observed: F(2, 29) = 3.72, p<\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p<$$\\end{document} 0.05. For both prior experience and gender, the differences were observed at the first instance of drone operation and not at subsequent trials. Results suggest prior experience and gender may only affect cognitive load at the initial experience and leveling of cognitive load occurs with continued practice. These findings can support an educator’s planning for drone-based activities and help to mitigate the stigma of gender differences regarding technology use. Additionally, these findings support the need to examine and enhance related and transferable skills, such as hand–eye coordination and spatial thinking, to lessen cognitive load at the initial educational experience.

Design and Technical-Economic-Environmental Evaluation of a Biorefinery Using Non-Marketable Edible Mushroom Waste

Edible mushrooms are gaining popularity as functional foods, not only for their distinctive taste and subtle flavor but also for their potential health benefits. They are rich in essential nutrients, including carbohydrates, proteins, fiber, minerals, and vitamins. However, it is estimated that up to 30% of total mushroom production generates non-marketable waste, which is currently used as animal feed, fertilizer, or compost. From a circular economy perspective, the objective of this work is to propose a conceptual design for a biorefinery to produce high-value-added products from non-marketable edible mushroom waste and to conduct a comprehensive assessment using modeling and simulation tools for process engineering. The general approach first involves identifying high-potential products, then determining the best processing routes, followed by developing a process flowsheet diagram for a case study (A. bisporus), and ultimately conducting a comprehensive assessment of the biorefinery to evaluate its sustainability. As a result, the proposed biorefinery may produce chitin, citric acid, and fertilizer, demonstrating the technical feasibility of waste valorization in terms of product yields, with positive profitability in terms of the rate of return on investment and payback period, and low environmental impact in terms of water and energy consumption as well as CO2 emissions.

A Critical Analysis of Social Engineering Theory in the Context of Legal Development in Indonesia

The theory of Social Engineering is a legal theory that views law as a tool for social engineering. However, the concept of Social Engineering in the context of legal development in Indonesia faces gaps in its implementation, often clashing with social, economic, political, and cultural realities. This research aims to analyze the concept of Social Engineering, as proposed by Roscoe Pound, within the framework of modern law. It also seeks to evaluate the relevance of this theory to legal development in Indonesia. This study adopts a normative juridical method with a conceptual approach. The data used is secondary in nature, derived from primary, secondary, and tertiary legal sources. Data collection is conducted through a literature review, while data analysis is performed qualitatively. Roscoe Pound's Social Engineering theory views law as a tool to create a balance of interests within society, aiming to meet its ever-evolving needs. In a modern context, this theory aligns with an approach that considers the impact of legal policies on social welfare. In Indonesia, the application of this theory is evident in legal reforms focused on social justice and public welfare. However, challenges such as weak law enforcement and discrepancies between policies and social realities need to be addressed in order to achieve effective legal development. Keywords: Theory; Law; Social Engineering.

Developing the KATAKU Mobile Application to Enhance Vocabulary Acquisition for Deaf Students

This study presents the development of the KATAKU (Kata untuk Tunarungu Interaktif dan Unik) application as an educational tool designed to support vocabulary learning for deaf students. Deaf students, who have the same educational rights as their hearing peers, often attend Special Schools (SLB). The integration of visual aids and technology in learning has proven effective in increasing their engagement and interest. This study employed a mixed-methods approach, including vocabulary assessments for deaf students, classroom observations, and teacher interviews for a needs analysis to identify the specific requirements of schools and students. Results from the vocabulary assessments revealed that deaf students face significant challenges, particularly with academic terms and word categorization. Classroom observations at three SLB schools in Jombang highlighted engaging but challenging learning dynamics, reinforcing the need for accessible and efficient teaching tools for educators. Teacher interviews indicated that using the paper dictionary provided by the Ministry of Education can be time-consuming and lacks efficiency. This study concludes that deaf students in Jombang face substantial obstacles in vocabulary comprehension, especially with academic vocabulary. The findings underscore the need for targeted vocabulary interventions using modern technological tools to better prepare students for advanced educational demands.

Evaluating Advanced Machine Learning Models for Histopathological Diagnosis of Hansen Disease.

Leprosy is a neglected infectious disease caused by Mycobacterium leprae and Mycobacterium lepromatosis and remains a public health challenge in tropical regions. Therefore, the development of technological tools such as machine learning (ML) offers an opportunity to innovate strategies for improving the diagnosis of this complex disease. To validate the utility of different ML models for the histopathological diagnosis of Hansen disease. An observational study was conducted where 55 H&E-stained tissue slides from leprosy patients and 51 healthy skin controls were analyzed using microphotographs captured at various magnifications. These images were categorized based on histopathological findings and processed using the Cross-Industry Standard Process for Data Mining methodology for designing and training ML models. Five types of ML models were evaluated using standard metrics such as accuracy, sensitivity, and specificity, emphasizing data normalization as a fundamental step in optimizing model performance. The artificial neural network (ANN) model demonstrated an accuracy of 70%, sensitivity of 74%, and specificity of 65%, demonstrating its ability to identify leprosy cases with moderate precision. The receiver operating characteristic curve of the ANN model showed an area under the curve of 0.71. Conversely, models such as decision trees, logistic regression, and random forests showed similar accuracy results but with slightly lower sensitivity, potentially indicating a higher risk of false negatives in detecting leprosy-positive cases. The ANN model emerges as a promising alternative for leprosy detection. However, further refinement of these models is necessary to enhance their adaptability across different clinical settings and participation in patient care.

The Role of Nursing in Reducing Medical Errors: Best Practices and Systemic Solutions

Medical errors remain a significant challenge in healthcare, contributing to patient harm and increased costs. As frontline caregivers, nurses play a pivotal role in minimizing these errors by implementing best practices and advocating for systemic improvements. This article explores the various types of medical errors and emphasizes the critical role of nursing interventions in error prevention. Key best practices discussed include effective communication strategies such as SBAR, medication management protocols, and the use of technological tools like Electronic Health Records (EHR) and Barcode Medication Administration (BCMA). Additionally, the article addresses the importance of continuous training, fatigue management, and interdisciplinary collaboration in reducing error rates. Systemic solutions are also reviewed, including fostering a culture of safety, ensuring adequate staffing, and implementing evidence-based protocols. The findings suggest that while nurses are integral to preventing errors, healthcare institutions must provide the necessary support and resources to optimize their efforts in promoting patient safety. Ultimately, the article highlights the need for both individual and organizational commitment to reducing medical errors.

Seeking the optimal SPOC-based blended learning approach to enhance deep learning from the community of inquiry perspective

To equip students with 21&lt;sup&gt;st&lt;/sup&gt; century skills to be competent global citizens and succeed academically and professionally, information and communication technology tools are being utilized to facilitate deep learning in higher education. This study integrated a small private online course (SPOC) with face-to-face (F2F) classroom learning to design and implement a blended English as a foreign language (EFL) course for deep learning. A mixed-method design was employed to investigate the learning experiences and perceptions of EFL students in the SPOC-based blended learning (BL) environment. The primary objective was to examine whether and how the teaching, social and cognitive presences were established from the perspective of the community of inquiry (CoI) model. Participants were 60 students enrolled in an eight-week English communicative course in a Chinese college. Quantitative data was obtained from the CoI and BL surveys, while qualitative data was gathered through individual interviews with 10 students. The results showed that a CoI was established, and deep learning happened in both SPOC and F2F learning areas with a more salient teaching presence in the SPOC area, a stronger social presence and a higher frequency of resolution phase reached in the F2F area. Furthermore, learners expressed satisfaction with the BL course, perceiving it as effective for English language acquisition. Pedagogical implications were offered to assist educators and institutions in optimizing the use of SPOC-based BL to enhance deep learning.

Mobile Applications and Artificial Intelligence for Nutrition Education: A Narrative Review

Mobile applications, websites and social media networks are now widely used communication tools. With the emergence of communication-related technologies in our lives and, consequently, the rise of social media networks and mobile applications, nutrition-related applications have become popular. Smartphones and other artificial intelligence technologies have become very useful tools for delivering nutrition-related interventions because they are very accessible and cost-effective. Digital interventions are also able to serve a larger number of communities than traditional interventions. Nutrition is not a field that has remained on the sidelines of these technological advances, and numerous mobile applications and technological tools have emerged that are intended to provide dietary advice or guidelines on the process of recovering from a disease. However, many of these applications have limitations and barriers that are important to consider. The aim of this review was to analyze the most current and widely used mobile applications related to nutrition, as well as their complementary tools (activity bracelets and smart scales, among others), highlighting their importance in improving lifestyle habits. In addition, their advantages and disadvantages are discussed and future directions are proposed.

Integration of Gamification and Mobile Applications to Promote Inclusive Education: a Techno Pedagogical Approach

Objective: The aim of this study is to analyze, through a document-based synthesis of existing literature, the integration of gamification and mobile applications in inclusive education, focusing on their potential to support the academic development of students. Theoretical Framework: The research presents key concepts and theories that underpin the implementation of gamification and mobile applications in the context of inclusive education, providing a solid theoretical framework that aids in understanding the study's context. Method: Through the review of 20 scientific articles, several effective strategies for implementing various technological tools (mobile applications) in the teaching-learning process are identified, with a special focus on inclusive education. Results and Discussion: It was shown that the use of playful elements and technological resources enhances active student participation, particularly for those with special educational needs, facilitating the development of soft skills such as collaboration, problem-solving, and self-efficacy. Research Implications: The implications of this research span various areas of education, highlighting the need to integrate innovative pedagogical approaches that promote equitable access and inclusion. Originality/Value: This study contributes to the literature by analyzing innovative approaches to the integration of gamification and mobile applications in emerging educational models. Its value lies in the need to develop projects that break educational monotony, promoting interactive experiences that empower both learners and educators.

A machine learning approach for analyzing sexual satisfaction based on psychological features

AbstractThe emergence of machine learning techniques has revolutionized various fields, helping to shed light into the complexities of human sexuality and address sexuality-related problems. The present study aimed to classify sexual satisfaction in both women (n = 503) and men (n = 342), who completed a digital survey aimed at Colombian adults based on a snowball sampling. Collected data were analyzed using several supervised learning algorithms where inputs included marital status, sociosexuality, sexual drive, sexual functioning, and personality traits. The results showed that the XGBoost model provided best classification results for sexual satisfaction in women, while the Artificial Neural Networks (ANN) had the best performance in classifying sexual satisfaction in men. In both groups, sexual functioning and sexual drive were the most significant predictors of sexual satisfaction. Traits such as extraversion, narcissism, machiavellianism, and sociosexual behavior had a lesser importance. Lastly, psychopathy emerged as a significant predictor of men's sexual satisfaction, whereas conscientiousness emerged as a significant predictor of women's satisfaction. This study provides a technological tool to classify sexual satisfaction using Machine Learning models, in addition, provide, in terms of entropy, variables with the greatest influence based on the data and predictions.

PKM Increasing Creativity and Economy in the Production of Digital Storytelling Videos on Social Media Platforms at the Kindergarten Teacher Activity Center (PKG) Biringkanaya District, Makassar

PKM to improve the creativity of teachers of the Cluster Activity Center (PKG) of Biringkanaya District, Makassar City will be an alternative for teachers in fulfilling the improvement of professionalism as educators in providing creative and innovative learning with the method of using social media. The technological tools applied in this PKM are the website which is the domain of PKG Kec. Biringkanaya and the YouTube link of PKG Kec. Biringkanaya. The website and YouTube of PKG Kec. Biringkanaya will help the cluster activity center in developing its activities in education management, increasing teacher creativity, and making this social media a place for self-development as well as income for PKG Kec. Biringkanaya in producing visual works on social media. This PKM is carried out in five stages of implementation, namely the first socialization, training to improve teacher creativity in making digital videos using the Canva and Capcut applications, training in using the PKG Kec. Biringkanaya website, mentoring stage, stage of implementing appropriate technology, and evaluation and sustainability stage. With this PKM activity, PKG Kec. partners. Biringkanaya has enthusiasm and commitment in increasing creativity and seeking income from the visual works of partners that are applied in social media, websites, and YouTube partners. This activity is the result of community service funded by the Directorate General of Higher Education, Ministry of Education and Culture of the Republic of Indonesia as the recipient of the Second Phase of Community Service Program Funding for the 2024 Fiscal Year.

Integration of Technological Tools in English Literature Pedagogy: Enhancing the Teaching-Learning Experience

Digital technology has transformed English Language anad Literature pedagogy. The use of digital technology in English Literature pedagogy represents a significant advancement in Literature and Language learning, significantly enhancing both teaching and learning processes. Technology helps students learn more effectively, which helps educators improve their instruction. The method keeps developing to help teachers acquire a language more quickly for their students. Teachers choose software-based instructional systems that enhance students' positive interactions with their instructors and promote the acquisition of the English language in its entirety. This research aims to explore the integration of digital technological tools in English Literature and Language teaching and it endorses various methods to encourage the best possible instruction. It also investigates a variety of facets of teaching and technological resources that gives educators access to cutting-edge tools for effective and high-quality instruction. For this study, an explanatory qualitative methodod is opted (Creswell &amp; Poth, 2018). For the survey of the literature, a linguistic and traditional description of the technology, and a thorough analysis of its relevance to currently used teaching techniques have all been conducted. The findings address key challenges by emphasizing the potential of digital and contemporary tools to enhance language education. The study advocates for the use of digital technological tools tools to improve Enlish language learning.

Logic of internship learning in hybrid engineering workplace settings: a sociomaterial assemble of digital tools, humans and activities

ABSTRACT During the recent pandemic, established modes of organising internships in engineering were disrupted; Internships often transitioned into hybrid formats with extensive online activity. But, empirical research on the quality of learning in engineering during these exceptional circumstances is limited. This study therefore examines internship experiences among engineering undergraduates (N = 39) in Singapore through semi-structured interviews conducted at two different time points. Thematic analysis revealed four challenges encountered by interns when access to engineering sites was disrupted. These included changes to processes of learning through the reorganisation of work routines requiring interns to adeptly utilise diverse technological tools and digital platforms for remote collaboration. Interns faced difficulties in gaining insights into the logic of engineering work through disrupted workflow. This was not helped when their learning experiences were also contingent upon the availability of meaningful work tasks. Finally, interns had to adapt to virtual and on-demand networking as a means of integrating into the engineering practice. Thus, the shift presented both challenges and opportunities for interns to learn about engineering in unprecedented ways. This research sheds light on how interns adapt during severe disruptions to engineering work environments, emphasising the importance of considering the sociomaterial context for supporting interns in hybrid workplaces.

TECHNOLOGIES FOR DEVELOPING STUDENTS' PHRASEOLOGICAL COMPETENCE IN ENGLISH LANGUAGE LESSONS (BASED ON EXAMPLES FROM GRADES 5-9)

This article explores the significance of developing phraseological competence in English language lessons for students in grades 5-9. It highlights the importance of idiomatic expressions, collocations, and fixed phrases in achieving effective communication and language proficiency. The article presents various technological tools, including interactive learning platforms, digital storytelling tools, online phraseology resources, video and multimedia resources, and mobile applications, that can enhance students’ understanding and use of phraseological units. Practical classroom examples illustrate how these technologies can be integrated into lesson plans to foster engagement and collaboration among students. Ultimately, the article underscores the role of educators in equipping students with the necessary skills to navigate the complexities of the English language, preparing them for success in diverse contexts.

Markerless deletion of the putative type I and III restriction-modification systems in the cellulolytic bacterium Clostridium cellulovorans using a codBA-based counterselection technique

Cellulose from lignocellulosic biomass (LB) is of increasing interest for the production of commodity chemicals. However, its use as substrate for fermentations is a challenge due to its structural complexity. In this context, the highly cellulolytic Clostridium cellulovorans has been considered an interesting microorganism for the breakdown of LB. C. cellulovorans does not naturally produce solvents in useful concentrations, but this could be achieved by metabolic engineering. Unfortunately, this is hampered by the lack of tools for genetic engineering. We describe a genetic system that allows strain engineering by the allelic-coupled exchange method. First, the Gram-positive origin of pUB110 was identified as a suitable clostridial 'pseudo-suicide' origin of replication for the construction of deletion vectors. Second, an efficient counterselection strategy based on a codBA cassette and the use of 5-fluorocytosine as the counterselective compound was employed. Third, since the prevention of DNA transfer by host restriction-modification (RM) systems is a critical barrier to genome engineering, deletion plasmids containing flanking regions for the putative type I (Clocel_1114) and III (Clocel_2651) RM systems were constructed and transferred into C. cellulovorans. The restriction-less strains C. cellulovorans ΔClocel_1114 and C. cellulovorans ΔClocel_2651 exhibit high conjugation efficiency and can be easily used for further metabolic engineering.

Statistical Analysis of Periodic MHD Chemically Radiative Casson Flow Over an Inclined Cylinder with Entropy Optimization

Statistical analysis (SA) stands as an indispensable tool in materials science and engineering, aiding in the understanding and optimization of heat and mass transport processes. This study delves into the interplay between periodic magneto-hydrodynamics (MHD) and chemical reactions concerning entropy generation over an inclined porous cylinder (IPC). We employ a statistical approach, amalgamating the robust 6th order Runge-Kutta (R-K) integration algorithm with the Nachtsheim-Swigert (N-S) shooting iteration method, subsequent to converting the governing equations into Ordinary Differential Equation (ODE) form. The primary objective of this study is to analyze the behavior of entropy generation, unveiling the intricate relationship between entropy dynamics, radiative periodic MHD on IPC, and chemical processes. The numerical findings encapsulate the dynamics of temperature, velocity, and entropy generation, visually portrayed across various dimensionless parameters. The primary findings of this investigation indicate that Casson fluid flow generates 18.99% more entropy in comparison to Newtonian fluid flow. Furthermore, entropy is 9.87% larger in an inclined cylinder than in a level cylinder. In contrast, entropy production falls by 3.34% in the presence of periodic MHD as opposed to non-periodic MHD. Regression study reveals a genuine and significant interaction between variables inside the entropy-generating systems, as well, with a correlation value (R2) of 99.82% at a 95% confidence level. The correlation study shows that there is a significant 98.13% relationship between entropy generation and chemical processes. Understanding the heightened entropy associated with Casson fluid flow benefits tissue engineering, drug delivery systems, and renewable energy. Increased entropy in inclined cylinders aids in optimizing drainage systems, pipeline design, and aerodynamic efficiency in aerospace engineering.

Versatile Xylose and Arabinose Genetic Switches development for Yeasts

Inducible transcription systems are essential tools in genetic engineering, where tight control, strong inducibility and fast response with cost-effective inducers are highly desired. However, existing systems in yeasts are rarely used in large-scale fermentations due to either cost-prohibitive inducers or incompatible performance. Here, we developed powerful xylose and arabinose induction systems in Saccharomyces cerevisiae, utilizing eukaryotic activators XlnR and AraRA from Aspergillus species and bacterial repressors XylR and AraRR. By integrating these signals into a highly-structured synthetic promoter, we created dual-mode systems with strong outputs and minimal leakiness. These systems demonstrated over 4000- and 300-fold regulation with strong activation and rapid response. The dual-mode xylose system was fully activated by xylose-rich agricultural residues like corncob hydrolysate, outperforming existing systems in terms of leakiness, inducibility, dynamic range, induction rate, and growth impact on host. We validated their utility in metabolic engineering with high-titer linalool production and demonstrated the transferability of the XlnR-based xylose induction system to Pichia pastoris, Candida glabrata and Candida albicans. This work provides robust genetic switches for yeasts and a general strategy for integrating activation-repression signals into synthetic promoters to achieve optimal performance.