Search results for: joint mediation learning

Authors: María González Alriols, Itziar Egües, María A. Andrés, Mirari Antxustegi

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Several collaborative learning proposals were prepared to be applied in the laboratory sessions of chemistry in the first course of engineering studies. The aim was to engage the students from the beginning and to avoid absenteeism as well as to reach a more homogeneous level in the class. The students, divided into small groups of four or five mates, were asked to do an exercise before having the practical session in the lab. Precisely, each one of the groups was asked to study the theoretical fundamentals and the practical aspects of one lab session and to prepare a didactical video with this content, including the materials, equipment and reactants required, and the detailed experimental procedure. Furthermore, they should include the performance of the experiment step by step, indicating the faced difficulties and the obtained results and conclusions. After watching the video of this precise activity, the other groups of students would go to the lab to put into practice the session following the commands explained in the video. The evaluation of the video activity that is worth the 50% of the total mark of the laboratory sessions, is done depending on the success that the other groups of students had while doing the practical session that was explained in the video. This means that the successful transmission of knowledge to the rest of the mates in the class through the video was compulsory to pass the practical sessions and the subject. The other 50% of the mark depended on the understanding of the other students’ explanations and the success in the corresponding practical sessions. The experience was found to be very positive, as the engagement level was considerably higher, the absenteeism lower and the attitude in the laboratory much more responsible. The materials, reactants and equipment were used carefully, and no incidents were registered. Furthermore, the fact of having peer experts was useful to encourage critical thinking in a more relaxed way, with the teacher figure in a secondary position. Finally, the academic achievements were satisfactory as well, with a high percentage of students over the level required for passing the subject.

Keywords: collaborative learning, engineering instruction, chemistry, laboratory sessions

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Authors: Mohan Li

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Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

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Authors: Asiful Islam, Ahmed Al Muzaddid, Ikram Efaz

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Concrete, the most widely used construction material globally, is valued for its versatility and strength. However, accurately predicting its compressive strength—a critical parameter for structural durability and safety—remains a persistent challenge due to its complex composition, diverse applications, and sensitivity to environmental conditions. Recent advancements in other scientific domains, such as the development of transformer models in computer science, which have revolutionized fields like natural language processing, biomedicine, and drug discovery, offer promising opportunities to address this challenge. Consequently, this study leverages a large-scale dataset to develop a transformer-based machine learning model that effectively exploits the underlying relationships among input parameters, such as total cementitious material, water-cement ratio, slump, percentage of air, and fly ash. Specifically, A dataset of 35,000 average compressive strength test results from the industry is introduced in this study. Each average compressive strength result is derived from two 4x8-inch cylinder tests, resulting in the analysis of 70,000 individual cylinder break results. This extensive dataset distinguishes the research, as no prior study has examined such a large sample size. The proposed model demonstrates superior accuracy through comprehensive experiments and analysis compared to traditional methods, including multiple linear regression, decision trees, random forests, and vanilla neural networks. Additionally, the transformer model’s attention mechanism provides valuable insights into the relative importance of input factors influencing compressive strength.

Keywords: concrete compressive strength, transformer model, machine learning, concrete strength prediction

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Authors: Chukwuemeka Daniel Ezeliora, Chukwuebuka Lawrence Ezeliora

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The research focused on the appraisal of impact strength on mild steel cladding weld metal geometry. Over the years, poor welding has resulted in failures in engineering components, poor material quality, the collapse of welded materials, and failures in material strength. This is as a result of poor selection and combination of welding input process parameters. The application of the Tungsten Inert Gas (TIG) welding method with weld specimen of length 60; width 40, and thickness of 10 was used for the experiment. A butt joint method was prepared for the welding, and tungsten inert gas welding process was used to perform the twenty (20) experimental runs. A response surface methodology was used to model and to analyze the system. For an adequate polynomial approximation, the experimental design was used to collect the data. The key parameters considered in this work are welding current, gas flow rate, welding speed, and voltage. The range of the input process parameters was selected from the literature and the design. The steps followed to achieve the experimental design and results is the use of response surface method (RSM) implemented in central composite design (CCD) to generate the design matrix, to obtain quadratic model, and evaluate the interactions in the factors as well as optimizing the factors and the response. The result expresses that the best impact strength of the mild steel cladding weld metal geometry is 115.419 Joules. However, it was observed that the result of the input factors is; current 180.4 amp, voltage 23.99 volt, welding speed 142.7 mm.s and gas flow rate 10.8 lit/min as the optimum of the input process parameters. The optimal solution gives a guide for optimal impact strength of the weldment when welding with tungsten inert gas (TIG) under study.

Keywords: mild steel, impact strength, response surface, bead geometry, welding

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Authors: Mohammad Hassanzadeh

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As far as incidental vocabulary learning is concerned, the basic contention of the Involvement Load Hypothesis (ILH) is that retention of unfamiliar words is, generally, conditional upon the degree of involvement in processing them. This study examined input modality and incidental vocabulary uptake in a task-induced setting whereby three variously loaded task types (marginal glosses, fill-in-task, and sentence-writing) were alternately assigned to one group of students at Allameh Tabataba’i University (n=2l) during six classroom sessions. While one round of exposure was comprised of the audiovisual medium (TV talk shows), the second round consisted of textual materials with approximately similar subject matter (reading texts). In both conditions, however, the tasks were equivalent to one another. Taken together, the study pursued the dual objectives of establishing a litmus test for the ILH and its proposed values of ‘need’, ‘search’ and ‘evaluation’ in the first place. Secondly, it sought to bring to light the superiority issue of exposure to audiovisual input versus the written input as far as the incorporation of tasks is concerned. At the end of each treatment session, a vocabulary active recall test was administered to measure their incidental gains. Running a one-way analysis of variance revealed that the audiovisual intervention yielded higher gains than the written version even when differing tasks were included. Meanwhile, task 'three' (sentence-writing) turned out the most efficient in tapping learners' active recall of the target vocabulary items. In addition to shedding light on the superiority of audiovisual input over the written input when circumstances are relatively held constant, this study for the most part, did support the underlying tenets of ILH.

Keywords: Keywords— Evaluation, incidental vocabulary learning, input mode, Involvement Load Hypothesis, need, search.

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Authors: Taiebe Shokri, Shahram Yazdani, Leila Afshar, Soleiman Ahmadi

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Introduction: The importance of professionalism in higher education not only determines the appropriate and inappropriate behaviors and guides faculty members in the implementation of professional responsibilities, but also guarantees faculty members' adherence to professional principles and values, ensures the quality of teaching and facilitator will be the teaching-learning process in universities and will increase the commitment to meet the needs of students as well as the development of an ethical culture based on ethics. Therefore, considering the important role of medical education teachers to prepare teachers and students in the future, the need to determine the concept of professional teacher and teacher, and the characteristics of teacher professionalism, we have explained the concept of professionalism in teachers in this study. Methods: The concept analysis method used in this study was Walker and Avant method which has eight steps. Walker and Avant state the purpose of concept analysis as follows: The process of distinguishing between the defining features of a concept and its unrelated features. The process of concept analysis includes selecting a concept, determining the purpose of the analysis, identifying the uses of the concept, determining the defining features of the concept, identifying a model, identifying boundary and adversarial items, identifying the precedents and consequences of the concept, and defining empirical references. is. Results: Professionalism in its general sense, requires deep knowledge, insight, creating a healthy and safe environment, honesty and trust, impartiality, commitment to the profession and continuous improvement, punctuality, criticism, professional competence, responsibility, and Individual accountability, especially in social interactions, is an effort for continuous improvement, the acquisition of these characteristics is not easily possible and requires education, especially continuous learning. Professionalism is a set of values, behaviors, and relationships that underpin public trust in teachers.

Keywords: concept analysis, medical education, professionalism, faculty members

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Authors: T. Goldstein, E. Serok, J. D. Kark

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Background and Aim: The prevalence of obesity is increasing worldwide and in Israel. To meet this challenge, our study tests a new educational approach through a controlled school-based trial to achieve an improvement in eating habits, aerobic activity, and reduced obesity in Grades 2-3. Methods and Design: A cluster randomized controlled trial allocated 4 elementary schools (3rd and 2nd-grade classes each) to intervention or control groups. This allocation was switched with the next cohort of children. Recruitment was in first grade, randomization at the beginning of second grade, evaluation of results at the end of second grade and the beginning of third grade — intervention: 5 joint parent-children classroom activities on health topics and 5 educational workshops for parents only. Alfred Adler's concepts were guiding principles. Subjects: Of 743 children in 23-second grade classes, parents provided informed consent for 508 (68%). Information of retention health habits continued for third grade. Additional parental approvals were required. Parents provided informed consent for third-grade follow-up for 432. Results: At the end of 2nd grade, the amount of aerobic activity increased in the intervention group in comparison with the control group, the difference being marginally statistically significant (p=0.061). There is a significant difference between the groups in the percentage of "no activity being done" reported at the end of second grade when in the experimental group, the percentage is lower than the control. There are differences between genders in the percentage of aerobic activity at the end of second grade (p=0.044) and in the third grade (p < 0.0001). Height increased significantly (p=0.030 ), and waist circumference declined significantly (p=0.021) in the intervention compared with the control group. There were no significant between-group differences in BMI and weight. Conclusion: There were encouraging changes in aerobic activity and in anthropometric measurements. To maintain changes over longer periods, refreshing these nutrition and activity themes annually in school using the model is required.

Keywords: aerobic activity, child obesity, Alfred Adler, schoolchildren

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Authors: Parsa Keyvani, Alistair Phillips, David Warwick

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Background: The current process for gaining patient consent for hand and wrist surgery at University Hospital Southampton (UHS) is paper-based and makes use of generic forms provided by the NHS and no patient information leaflet is available relating to hand and wrist surgery. Aims: To evaluate the process of obtaining clinical consent and suggest ways in which the service can be improved. Methods: A log-book review of four orthopaedic surgeons at UHS was carried out over a three-month period in order to identify the 10 most common types of elective hand and wrist surgeries performed. A literature review was carried out to identify the complications of these surgeries. The surgeries were then divided into 6 types: nerve, bone, ligament, joint, tendon and dupuytren’s surgery. A digitised consent form was created covering the complications of all 6 surgery types. Finally, the surgeons at the orthopaedic department of UHS were asked whether they prefer the old paper-based or the digitised consent form. Results: All of the surgeons felt that the procedure type-based form was easier to read, use and understand. Conclusion: This research highlights a number of problems related to the use of current NHS consent forms. The proposed solution is to use a set of digitised, procedure type-based consent forms. Digital consent forms can be filled in in advance and sent to the patient electronically along with any relevant information leaflets, thus giving them time to absorb the information and come up with any questions before they have their pre-procedure discussion with their doctor. This would allow the doctor to focus the consultation on the patient rather than writing out the consent form and would ultimately be a step forward in making the NHS a global digital leader and fully embrace the opportunity offered by technology.

Keywords: digitised consent form, elective surgery, hand surgery complications, informed consent, procedure type-based consent form

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Authors: A.H.Y. Lai, C. Teyra

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In Taiwan, there are 16 official indigenous groups, accounting for 2.3% of the total population. Like other indigenous populations worldwide, indigenous peoples in Taiwan have poorer mental health because of their history of oppression and colonisation. Amid the negative narratives, the ethnic identity of cultural minorities is their unique psychological and cultural asset. Moreover, positive socialisation is found to be related to strong ethnic identity. Based on Phinney’s theory on ethnic identity development and social support theory, this study adopted a strength-based approach conceptualising ethnic identity as the central organising principle that linked perceived social support and mental health among indigenous adults in Taiwan. Aims. Overall aim is to examine the effect of ethnic identity and social support on mental health. Specific aims were to examine : (1) the association between ethnic identity and mental health; (2) the association between perceived social support and mental health ; (3) the indirect effect of ethnic identity linking perceived social support and mental health. Methods. Participants were indigenous adults in Taiwan (n=200; mean age=29.51; Female=31%, Male=61%, Others=8%). A cross-sectional quantitative design was implemented using data collected in the year 2020. Respondent-driven sampling was used. Standardised measurements were: Ethnic Identity Scale(6-item); Social Support Questionnaire-SF(6 items); Patient Health Questionnaire(9-item); and Generalised Anxiety Disorder(7-item). Covariates were age, gender and economic satisfaction. A four-stage structural equation modelling (SEM) with robust maximin likelihood estimation was employed using Mplus8.0. Step 1: A measurement model was built and tested using confirmatory factor analysis (CFA). Step 2: Factor covariates were re-specified as direct effects in the SEM. Covariates were added. The direct effects of (1) ethnic identity and social support on depression and anxiety and (2) social support on ethnic identity were tested. The indirect effect of ethnic identity was examined with the bootstrapping technique. Results. The CFA model showed satisfactory fit statistics: x^2(df)=869.69(608), p<.05; Comparative ft index (CFI)/ Tucker-Lewis fit index (TLI)=0.95/0.94; root mean square error of approximation (RMSEA)=0.05; Standardized Root Mean Squared Residual (SRMR)=0.05. Ethnic identity is represented by two latent factors: ethnic identity-commitment and ethnic identity-exploration. Depression, anxiety and social support are single-factor latent variables. For the SEM, model fit statistics were: x^2(df)=779.26(527), p<.05; CFI/TLI=0.94/0.93; RMSEA=0.05; SRMR=0.05. Ethnic identity-commitment (b=-0.30) and social support (b=-0.33) had direct negative effects on depression, but ethnic identity-exploration did not. Ethnic identity-commitment (b=-0.43) and social support (b=-0.31) had direct negative effects on anxiety, while identity-exploration (b=0.24) demonstrated a positive effect. Social support had direct positive effects on ethnic identity-exploration (b=0.26) and ethnic identity-commitment (b=0.31). Mediation analysis demonstrated the indirect effect of ethnic identity-commitment linking social support and depression (b=0.22). Implications: Results underscore the role of social support in preventing depression via ethnic identity commitment among indigenous adults in Taiwan. Adopting the strength-based approach, mental health practitioners can mobilise indigenous peoples’ commitment to their group to promote their well-being.

Keywords: ethnic identity, indigenous population, mental health, perceived social support

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Authors: Paul Lam, Kevin Wong, Chi Him Chan

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Constant practicing and accurate, immediate feedback are the keys to improving students’ speaking skills. However, traditional oral examination often fails to provide such opportunities to students. The traditional, face-to-face oral assessment is often time consuming – attending the oral needs of one student often leads to the negligence of others. Hence, teachers can only provide limited opportunities and feedback to students. Moreover, students’ incentive to practice is also reduced by their anxiety and shyness in speaking the new language. A mobile app was developed to use artificial intelligence (AI) to provide immediate feedback to students’ speaking performance as an attempt to solve the above-mentioned problems. Firstly, it was thought that online exercises would greatly increase the learning opportunities of students as they can now practice more without the needs of teachers’ presence. Secondly, the automatic feedback provided by the AI would enhance students’ motivation to practice as there is an instant evaluation of their performance. Lastly, students should feel less anxious and shy compared to directly practicing oral in front of teachers. Technically, the program made use of speech-to-text functions to generate feedback to students. To be specific, the software analyzes students’ oral input through certain speech-to-text AI engine and then cleans up the results further to the point that can be compared with the targeted text. The mobile app has invited English teachers for the pilot use and asked for their feedback. Preliminary trials indicated that the approach has limitations. Many of the users’ pronunciation were automatically corrected by the speech recognition function as wise guessing is already integrated into many of such systems. Nevertheless, teachers have confidence that the app can be further improved for accuracy. It has the potential to significantly improve oral drilling by giving students more chances to practice. Moreover, they believe that the success of this mobile app confirms the potential to extend the AI-assisted assessment to other language skills, such as writing, reading, and listening.

Keywords: artificial Intelligence, mobile learning, oral assessment, oral practice, speech-to-text function

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Authors: Boubacar Niang, Denis Raulin

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This paper presents the design of a dedicated board for learning and programming with ATMEL AVR new generation micro controller’s family. This board designed as a "shield" for the Arduino Uno allows us to focus on the design and programming of basic micro controller functionalities in high level language with a considerable time saving because of dealing with additional components is not required.

Keywords: Arduino, microcontroller, programming, language

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Authors: Sima Modirkhameneh, Mohammad Mohammadpanah

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In the process of EFL teachers’ development, self-led reflection (SLR) is thought to have an imperative role because it may help teachers analyze, evaluate, and contemplate what is happening in their classes. Such contemplations can not only enhance the quality of their instruction and provide better learning environments for learners but also improve the quality of their classroom management (CM). Accordingly, understanding the effect of teachers’ SLR practices may help us gain valuable insights into what possible modifications SLR may bring about in all aspects of EFL teachers' practitioners, especially their CM. The main purpose of this case study was, thus, to investigate the impact of SLR practices of 12 Iranian EFL teachers on their CM based on the universal classroom management checklist (UCMC). In addition, another objective of the current study was to have a clear image of EFL teachers’ perceptions of their own SLR practices and their possible outcomes. By conducting repeated reflective interviews, observations, and feedback of the participants over five teaching sessions, the researcher analyzed the outcomes qualitatively through the process of meaning categorization and data interpretation based on the principles of Grounded Theory. The results demonstrated that EFL teachers utilized SLR practices to improve different aspects of their language teaching skills and CM in different contexts. Almost all participants had positive comments and reactions about the effect of SLR on their CM procedures in different aspects (expectations and routines, behavior-specific praise, error corrections, prompts and precorrections, opportunity to respond, strengths and weaknesses of CM, teachers’ perception, CM ability, and learning process). Otherwise stated, results implied that familiarity with the UCMC criteria and reflective practices contributes to modifying teacher participants’ perceptions about their CM procedure and utilizing the reflective practices in their teaching styles. The results are thought to be valuably beneficial for teachers, teacher educators, and policymakers, who are recommended to pay special attention to the contributions as well as the complexity of reflective teaching. The study concludes with more detailed results and implications and useful directions for future research.

Keywords: classroom management, EFL teachers, reflective practices, self-led reflection

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Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

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Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

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Authors: Sara T. K. Li, Belinda H. J. Chung, Jeffery C. N. Yip, Janet H. Hsiao

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Music notation and text reading both involve statistical learning of music or linguistic structures. However, it remains unclear how music reading expertise influences text reading behavior. The present study examined this issue through an eye-tracking study. Chinese-English bilingual musicians and non-musicians read English sentences, Chinese sentences, musical phrases, and sentences in Tibetan, a language novel to the participants, with their eye movement recorded. Each set of stimuli consisted of two conditions in terms of structural regularity: syntactically correct and syntactically incorrect musical phrases/sentences. They then completed a sentence comprehension (for syntactically correct sentences) or a musical segment/word recognition task afterwards to test their comprehension/recognition abilities. The results showed that in reading musical phrases, as compared with non-musicians, musicians had a higher accuracy in the recognition task, and had shorter reading time, fewer fixations, and shorter fixation duration when reading syntactically correct (i.e., in diatonic key) than incorrect (i.e., in non-diatonic key/atonal) musical phrases. This result reflects their expertise in music reading. Interestingly, in reading Tibetan sentences, which was novel to both participant groups, while non-musicians did not show any behavior differences between reading syntactically correct or incorrect Tibetan sentences, musicians showed a shorter reading time and had marginally fewer fixations when reading syntactically correct sentences than syntactically incorrect ones. However, none of the musicians reported discovering any structural regularities in the Tibetan stimuli after the experiment when being asked explicitly, suggesting that they may have implicitly acquired the structural regularities in Tibetan sentences. This group difference was not observed when they read English or Chinese sentences. This result suggests that music reading expertise facilities reading texts in a novel language (i.e., Tibetan), but not in languages that the readers are already familiar with (i.e., English and Chinese). This phenomenon may be due to the similarities between reading music notations and reading texts in a novel language, as in both cases the stimuli follow particular statistical structures but do not involve semantic or lexical processing. Thus, musicians may transfer their statistical learning skills stemmed from music notation reading experience to implicitly discover structures of sentences in a novel language. This speculation is consistent with a recent finding showing that music reading expertise modulates the processing of English nonwords (i.e., words that do not follow morphological or orthographic rules) but not pseudo- or real words. These results suggest that the modulation of music reading expertise on language processing depends on the similarities in the cognitive processes involved. It also has important implications for the benefits of music education on language and cognitive development.

Keywords: eye movement behavior, eye-tracking, music reading expertise, sentence reading, structural regularity, visual processing

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Authors: Thi Phuong Pham

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This paper explores the intricate relationships between Sustainable Supply Chain Management (SSCM) practices, digital transformation (DT), and enterprise performance within the context of Vietnam. Over the past two decades, there has been a paradigm shift in supply chain management, with sustainability gaining prominence due to increasing concerns about climate change, labor practices, and the environmental impact of business operations. In the ever-evolving realm of global business, sustainability and digital transformation (DT) intersecting dynamics have become pivotal catalysts for organizational success. This research investigates how integrating SSCM with DT can enhance enterprise performance, a subject of significant relevance as Vietnam undergoes rapid economic growth and digital transformation. The primary objectives of this research are twofold: (1) to examine the effects of SSCM practices on enterprise performance in three critical aspects: economic, environmental, and social performance in Vietnam and (2) to explore the mediating role of DT in this relationship. By analyzing these dynamics, the study aims to provide valuable insights for policymakers and the academic community regarding the potential benefits of aligning SSCM principles with digital technologies. To achieve these objectives, the research employs a robust mixed-method approach. The research begins with a comprehensive literature review to establish a theoretical framework that underpins the empirical analysis. Data collection was conducted through a structured survey targeting Vietnamese enterprises, with the survey instrument designed to measure SSCM practices, DT, and enterprise performance using a five-point Likert scale. The reliability and validity of the survey were ensured by pre-testing with industry practitioners and refining the questionnaire based on their feedback. For data analysis, structural equation modeling (SEM) was employed to quantify the direct effects of SSCM on enterprise performance, while mediation analysis using the PROCESS Macro 4.0 in SPSS was conducted to assess the mediating role of DT. The findings reveal that SSCM practices positively influence enterprise performance by enhancing operational efficiency, reducing costs, and improving sustainability metrics. Furthermore, DT acts as a significant mediator, amplifying the positive impacts of SSCM practices through improved data management, enhanced communication, and more agile supply chain processes. These results underscore the critical role of DT in maximizing the benefits of SSCM practices, particularly in a developing economy like Vietnam. This research contributes to the existing body of knowledge by highlighting the synergistic effects of SSCM and DT on enterprise performance. It offers practical implications for businesses that enhance their sustainability and digital capabilities, providing a roadmap for integrating these two pivotal aspects to achieve competitive advantage. The study's insights can also inform governmental policies designed to foster sustainable economic growth and digital innovation in Vietnam.

Keywords: sustainable supply chain management, digital transformation, enterprise performance, Vietnam

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Authors: Lik Hang Gary Wong

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Background: Practice learning is crucial for preparing the healthcare profession to meet the real challenge upon graduation. Students are required to demonstrate their competence in managing interpersonal challenges, such as teamwork with other professionals and communicating well with the service users, during the placement. Such competence precedes clinical practice, and it may eventually affect students' actual performance in a clinical context. Unfortunately, there were limited studies investigating how such competence affects students' performance in practice learning. Objectives: The aim of this study is to investigate how self-rated interpersonal competence affects students' actual performance during clinical placement. Methods: 40 occupational therapy students from Hong Kong were recruited in this study. Prior to the clinical placement (level two or above), they completed an online survey that included the Interpersonal Communication Competence Scale (ICCS) measuring self-perceived competence in interpersonal communication. Near the end of their placement, the clinical educator rated students’ performance with the Student Practice Evaluation Form - Revised edition (SPEF-R). The SPEF-R measures the eight core competency domains required for an entry-level occupational therapist. This study adopted the cross-sectional observational design. Pearson correlation and multiple regression are conducted to examine the relationship between students' interpersonal communication competence and their actual performance in clinical placement. Results: The ICCS total scores were significantly correlated with all the SPEF-R domains, with correlation coefficient r ranging from 0.39 to 0.51. The strongest association was found with the co-worker communication domain (r = 0.51, p < 0.01), followed by the information gathering domain (r = 0.50, p < 0.01). Regarding the ICCS total scores as the independent variable and the rating in various SPEF-R domains as the dependent variables in the multiple regression analyses, the interpersonal competence measures were identified as a significant predictor of the co-worker communication (R² = 0.33, β = 0.014, SE = 0.006, p = 0.026), information gathering (R² = 0.27, β = 0.018, SE = 0.007, p = 0.011), and service provision (R² = 0.17, β = 0.017, SE = 0.007, p = 0.020). Moreover, some specific communication skills appeared to be especially important to clinical practice. For example, immediacy, which means whether the students were readily approachable on all social occasions, correlated with all the SPEF-R domains, with r-values ranging from 0.45 to 0.33. Other sub-skills, such as empathy, interaction management, and supportiveness, were also found to be significantly correlated to most of the SPEF-R domains. Meanwhile, the ICCS scores correlated differently with the co-worker communication domain (r = 0.51, p < 0.01) and the communication with the service user domain (r = 0.39, p < 0.05). It suggested that different communication skill sets would be required for different interpersonal contexts within the workplace. Conclusion: Students' self-perceived interpersonal communication competence could predict their actual performance during clinical placement. Moreover, some specific communication skills were more important to the co-worker communication but not to the daily interaction with the service users. There were implications on how to better prepare the students to meet the future challenge upon graduation.

Keywords: interpersonal competence, clinical education, healthcare professional education, occupational therapy, occupational therapy students

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Authors: Obasa Joshua Ifeoluwa

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Phonetics is the foundation and most important part of language learning. This article, through an acoustic experiment as well as using Praat software, uses Yoruba students’ Chinese consonants, vowels, and tones pronunciation to carry out a visual comparison with that of native Chinese speakers. This article is aimed at Yoruba native speakers learning Chinese phonetics; therefore, Yoruba students are selected. The students surveyed are required to be at an elementary level and have learned Chinese for less than six months. The students selected are all undergraduates majoring in Chinese Studies at the University of Lagos. These students have already learned Chinese Pinyin and are all familiar with the pinyin used in the provided questionnaire. The Chinese students selected are those that have passed the level two Mandarin proficiency examination, which serves as an assurance that their pronunciation is standard. It is discovered in this work that in terms of Mandarin’s consonants pronunciation, Yoruba students cannot distinguish between the voiced and voiceless as well as the aspirated and non-aspirated phonetics features. For instance, while pronouncing [ph] it is clearly shown in the spectrogram that the Voice Onset Time (VOT) of a Chinese speaker is higher than that of a Yoruba native speaker, which means that the Yoruba speaker is pronouncing the unaspirated counterpart [p]. Another difficulty is to pronounce some affricates like [tʂ]、[tʂʰ]、[ʂ]、[ʐ]、 [tɕ]、[tɕʰ]、[ɕ]. This is because these sounds are not in the phonetic system of the Yoruba language. In terms of vowels, some students find it difficult to pronounce some allophonic high vowels such as [ɿ] and [ʅ], therefore pronouncing them as their phoneme [i]; another pronunciation error is pronouncing [y] as [u], also as shown in the spectrogram, a student pronounced [y] as [iu]. In terms of tone, it is most difficult for students to differentiate between the second (rising) and third (falling and rising) tones because these tones’ emphasis is on the rising pitch. This work concludes that the major error made by Yoruba students while pronouncing Chinese sounds is caused by the interference of their first language (LI) and sometimes by their lingua franca.

Keywords: Chinese, Yoruba, error analysis, experimental phonetics, consonant, vowel, tone

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Authors: Folasade R. Sulaiman

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Pupils’ health and nutrition are basically important to their schooling. The preponderance of avoidable deaths among children in Africa (WHO, 2000) may not be unconnected with the nutritional and health education status of families and communities that have their children as school clients. This study adopted a descriptive survey design focusing on the assessment of the level of nutritional and health education of families and community members in the rural riverine areas of Ogun State. Two research questions were raised. The Nutritional and Health Education of Families and Communities Inventory (NHEFCI) was used to collect data from 250 rural child-bearing aged women, and 0.73 test-retest reliability coefficient was established to determine the strength of the instrument. Data collected were analysed using descriptive statistics of frequency counts, percentages and mean in accordance with research questions raised in the study. The findings revealed amongst others: that 65% of the respondents had low level of nutritional and health education among the families and community members; while 72% had low level of awareness of the possible influence of nutritional and health education on the learning outcomes of the children. Based on the findings, it was recommended among others that government should intensify efforts on sensitization, mass literacy campaign etc.; also improve upon the already existing School Feeding Programme in Nigerian primary schools to provide at least one balanced diet for children while in school; community health workers, social workers, Non-Governmental Organizations (NGO) should collaborate with international Organizations like UNICEF, UNESCO, WHO etc. to organize sensitization programmes for members of the rural riverine communities on the importance of meeting the health and nutritional needs of their children in order to attain their educational potentials.

Keywords: nutritional and health education, learning capacities, school-age children, universal basic education, rural riverine areas

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Authors: Aikaterini Amanatidou

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We describe the case of a 20-year-old female patient diagnosed with Ehlers-Danlos Syndrome (EDS) who was scheduled to undergo a wisdom teeth extraction in outpatient surgery. EDS is a hereditary connective tissue disorder characterized by joint hypermobility, skin hyper-extensibility, and vascular and soft tissue fragility. There are six subtypes of Ehlers-Danlos, and in our case, the patient had EDS hyper-mobility (HT) type disorder. One important clinical feature of this syndrome is chronic pain, which is often poorly understood and treated. Our patient had a long history of articular and lumbar pain when she was diagnosed. She was prescribed analgesic treatment for acute and neuropathic pain and had multiple sessions of psychotherapy and physiotherapy to ease the pain. Unfortunately, her extensive medical history was underrated by our anesthetic team, and no further measures were taken for the operation. Despite an uneventful intra-operative phase, the patient experienced several episodes of hyperalgesia during the immediate post-operative care. Management of pain was challenging for the anesthetic team: initial opioid treatment had only a temporary effect and a paradoxical reaction after a while. Final pain relief was eventually obtained with psycho-physiologic treatment, high doses of ketamine, and patient-controlled analgesia infusion of morphine-ketamine-dehydrobenzperidol. We suspected an episode of Opioid-Induced hyperalgesia. This case report supports the hypothesis that anti-hyperalgesics such as ketamine as well as lidocaine, and dexmedetomidine should be considered intra-operatively to avoid opioid-induced hyperalgesia and may be an alternative solution to manage complex chronic pain like others in neuropathic pain syndromes.

Keywords: Ehlers-Danlos, post-operative management, hyperalgesia, opioid-induced hyperalgesia, rare disease

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Authors: Y. Zhang, J. Perez, S. Marnier

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To date, no study on goaltending butterfly motion has been completed in real conditions, during an ice hockey game or training practice, to the author's best knowledge. This motion, performed to save score, is unnatural, intense, and repeated. The target of this research activity is to identify representative biomechanical criteria for this goaltender-specific movement pattern. Determining specific physical parameters may allow to will identify the risk of hip and groin injuries sustained by goaltenders. Four professional or academic goalies were instrumented during ice hockey training practices with five inertial measurement units. These devices were inserted in dedicated pockets located on each thigh and shank, and the fifth on the lumbar spine. A camera was also installed close to the ice to observe and record the goaltenders' activities, especially the butterfly motions, in order to synchronize the captured data and the behavior of the goaltender. Each data recorded began with a calibration of the inertial units and a calibration of the fully equipped goaltender on the ice. Three butterfly motions were recorded out of the training practice to define referential individual butterfly motions. Then, a data processing algorithm based on the Madgwick filter computed hip and knee joints joint range of motion as well as angular specific angular velocities. The developed algorithm software automatically identified and analyzed all the butterfly motions executed by the four different goaltenders. To date, it is still too early to show that the analyzed criteria are representative of the trauma generated by the butterfly motion as the research is only at its beginning. However, this descriptive research activity is promising in its ecological assessment, and once the criteria are found, the tools and protocols defined will allow the prevention of as many injuries as possible. It will thus be possible to build a specific training program for each goalie.

Keywords: biomechanics, butterfly motion, human motion analysis, ice hockey, inertial measurement unit

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Authors: Joyce Joas Kahembe

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The implementation of education assessment reforms in developing countries has been claimed to be problematic and difficult. The socio-economic teaching and learning environment has pointed to constraints in the education reform process. Nevertheless, there are existing assessment practices that if enhanced, can have potential to foster formative assessment practices in those contexts. The present study used the sociocultural perspective to explore teachers’ assessment practices and factors influencing them in Tanzania. Specifically, the sociocultural perspective helped to trace social, economic and political histories imparted to teachers’ assessment practices. The ethnographic oriented methods like interviews, observations and document reviews was used in this exploration. Teachers used assessment practices, such as questioning and answering, tests, assignments and examinations, for evaluating, monitoring and diagnosing students’ understanding, achievement and performance and standards and quality of instruction practices. The obtained assessment information functioned as feedback for improving students’ understanding, performance, and the standard and quality of teaching instruction and materials. For example, teachers acknowledged, praised, approved, disapproved, denied, graded, or marked students’ responses to give students feedback and aid learning. Moreover, teachers clarified and corrected or repeated students’ responses with worded/added words to improve students’ mastery of the subject content. Teachers’ assessment practices were influenced by the high demands of passing marks in the high stakes examinations and the contexts of the social economic teaching environment. There is a need to ally education assessment reforms with existing socio-economic teaching environments and society and institutional demands of assessment to make assessment reforms meaningful and sustainable. This presentation ought to contribute on ongoing strategies for contextualizing assessment practices for formative uses.

Keywords: assessment, feedback, practices, formative assessment

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Authors: Muneeb Ullah, Daishihan, Xiadong Young

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Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

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Authors: Talar Agopian

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Teaching English as a Second Language (ESL) is a common practice in many Lebanese schools. However, ESL teaching is done in traditional ways. Methods such as constructivism are seldom used, especially in villages. Here lies the significance of this research which joins constructivism and Piaget’s theory of cognitive development in ESL classes in Lebanese villages. The purpose of the present study is to explore the effects of applying constructivist student-centered strategies in teaching grammar, reading comprehension, and poetry on students in elementary ESL classes in two villages in Lebanon, Zefta in South Lebanon and Boqaata in Mount Lebanon. 20 English teachers participated in a training titled “Teaching English with Fun”, which focused on strategies that create a student-centered class where active learning takes place and there is increased learner engagement and autonomy. The training covered three main areas in teaching English: grammar, reading comprehension, and poetry. After participating in the training, the teachers applied the new strategies and methods in their ESL classes. The methodology comprised two phases: in phase one, practice-based research was conducted as the teachers attended the training and applied the constructivist strategies in their respective ESL classes. Phase two included the reflections of the teachers on the effects of the application of constructivist strategies. The results revealed the educational benefits of constructivist student-centered strategies; the students of teachers who applied these strategies showed improved engagement, positive attitudes towards poetry, increased motivation, and a better sense of autonomy. Future research is required in applying constructivist methods in the areas of writing, spelling, and vocabulary in ESL classrooms of Lebanese villages.

Keywords: active learning, constructivism, learner engagement, student-centered strategies

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Authors: Anika Chebrolu

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Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Karolina Wieczorek, Zofia Przypaśniak

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Climate change is a rapidly growing threat to global health, and part of the responsibility to combat it lies within the healthcare sector itself, including adequate education of future medical professionals. To mitigate the consequences, the General Medical Council (GMC) has equipped medical schools with a list of outcomes regarding sustainability teaching. Students are expected to analyze the impact of the healthcare sector’s emissions on climate change. The delivery of the related teaching content is, however, often inadequate and insufficient time is devoted for exploration of the topics. Teaching curricula lack in-depth exploration of the learning objectives. This study aims to assess the extent and characteristics of climate change and sustainability subjects teaching in the curriculum of a chosen UK medical school (Barts and The London School of Medicine and Dentistry). It compares the data to the national average scores from the Climate Change and Sustainability Teaching (C.A.S.T.) in Medical Education Audit to draw conclusions about teaching on a regional level. This is a single-center audit of the timetabled sessions of teaching in the medical course. The study looked at the academic year 2020/2021 which included a review of all non-elective, core curriculum teaching materials including tutorials, lectures, written resources, and assignments in all five years of the undergraduate and graduate degrees, focusing only on mandatory teaching attended by all students (excluding elective modules). The topics covered were crosschecked with GMC Outcomes for graduates: “Educating for Sustainable Healthcare – Priority Learning Outcomes” as gold standard to look for coverage of the outcomes and gaps in teaching. Quantitative data was collected in form of time allocated for teaching as proxy of time spent per individual outcomes. The data was collected independently by two students (KW and ZP) who have received prior training and assessed two separate data sets to increase interrater reliability. In terms of coverage of learning outcomes, 12 out of 13 were taught (with the national average being 9.7). The school ranked sixth in the UK for time spent per topic and second in terms of overall coverage, meaning the school has a broad range of topics taught with some being explored in more detail than others. For the first outcome 4 out of 4 objectives covered (average 3.5) with 47 minutes spent per outcome (average 84 min), for the second objective 5 out of 5 covered (average 3.5) with 46 minutes spent (average 20), for the third 3 out of 4 (average 2.5) with 10 mins pent (average 19 min). A disproportionately large amount of time is spent delivering teaching regarding air pollution (respiratory illnesses), which resulted in the topic of sustainability in other specialties being excluded from teaching (musculoskeletal, ophthalmology, pediatrics, renal). Conclusions: Currently, there is no coherent strategy on national teaching of climate change topics and as a result an unstandardized amount of time spent on teaching and coverage of objectives can be observed.

Keywords: audit, climate change, sustainability, education

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Authors: Łukasz Bis

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The author is going to discuss virtual reality and its importance for new didactic methods. It has been known for years that experience-based education gives much better results in terms of long-term memory than theoretical study. However, practice is expensive - virtual reality allows the use of an empirical approach to learning, with minimized production costs. The author defines what makes a given VR experience appropriate (adequate) for the didactic and cognitive process. The article is a kind of a list of guidelines and their importance for the VR experience under development.

Keywords: virtual reality, education, universal design, guideline

Procedia PDF Downloads 112

Authors: Michael Amankwaa Adu

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Effective communication in the classroom plays a vital role in ensuring successful teaching and learning. In particular, the types of language and speech acts teachers use shape classroom interactions and influence student engagement. This study aims to analyze the speech acts employed by a Career Technology teacher in a junior high school. While much research has focused on speech acts in language classrooms, less attention has been given to how these acts operate in non-language subject areas like technical education. The study explores how different types of speech acts—directives, assertives, expressives, and commissives—are used during three classroom encounters: lesson introduction, content delivery, and classroom management. This research seeks to fill the gap in understanding how teachers of non-language subjects use speech acts to manage classroom dynamics and facilitate learning. The study employs a mixed-methods design, combining qualitative and quantitative approaches. Data was collected through direct classroom observation and audio recordings of a one-hour Career Technology lesson. The transcriptions of the lesson were analyzed using John Searle’s taxonomy of speech acts, classifying the teacher’s utterances into directives, assertives, expressives, and commissives. Results show that directives were the most frequently used speech act, accounting for 59.3% of the teacher's utterances. These speech acts were essential in guiding student behavior, giving instructions, and maintaining classroom control. Assertives made up 20.4% of the speech acts, primarily used for stating facts and reinforcing content. Expressives, at 14.2%, expressed emotions such as approval or frustration, helping to manage the emotional atmosphere of the classroom. Commissives were the least used, representing 6.2% of the speech acts, often used to set expectations or outline future actions. No declarations were observed during the lesson. The findings of this study reveal the critical role that speech acts play in managing classroom behavior and delivering content in technical subjects. Directives were crucial for ensuring students followed instructions and completed tasks, while assertives helped in reinforcing lesson objectives. Expressives contributed to motivating or disciplining students, and commissives, though less frequent, helped set clear expectations for students’ future actions. The absence of declarations suggests that the teacher prioritized guiding students over making formal pronouncements. These insights can inform teaching strategies across various subject areas, demonstrating that a diverse use of speech acts can create a balanced and interactive learning environment. This study contributes to the growing field of pragmatics in education and offers practical recommendations for educators, particularly in non-language classrooms, on how to utilize speech acts to enhance both classroom management and student engagement.

Keywords: classroom interaction, pragmatics, speech acts, teacher communication, career technology

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Authors: Bumjo Kim, Hyun Jin Kim, Joon Ha Kim

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The separate sewer system is that collects the wastewater as a sewer pipe and rainfall as a stormwater pipe separately, and then sewage is treated in the wastewater treatment plant, the stormwater is discharged to rivers or lakes through stormwater drainage pipes. Unfortunately, even for separate sewer systems, it is not possible to prevent Rainfall Driven Inflow/Infiltration(RDII) completely to the sewer pipe. Even if the sewerage line is renovated, there is an ineluctable RDII due to the combined sewer system in the house or the difficulty of sewage maintenance in private areas. The basic statistical analysis was performed using environmental data including rainfall, sewage, water qualities and groundwater level in the strict of Gwangju in ​South Korea. During rainfall in the target area, RDII showed an increased rate of 13.4 ~ 53.0% compared to that of a clear day and showed a rapid hydrograph response of 0.3 ~ 3.0 hr. As a result of water quality analysis, BOD5 concentration decreased by 17.3 % and salinity concentration decreased by 8.8 % at the representative spot in the project area compared to the sunny day during rainfall. In contrast to the seasonal fluctuation range of 0.38 m ~ 0.55 m in groundwater in Gwangju area and 0.58 m ~ 0.78 m in monthly fluctuation range, while the difference between groundwater level and the depth of sewer pipe laying was 2.70 m on average, which is larger than the range of fluctuation. Comprehensively, it can be concluded that the increasing of flowrate at sewer line is due to not infiltration water caused by groundwater level rise, construction failure, cracking due to joint failure or conduit deterioration, rainfall was directly inflowed into the sewer line rapidly. Acknowledgements: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: ground water, rainfall, rainfall driven inflow/infiltration, separate sewer system

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