Search results for: learning management systems

Authors: Kadidiatou Toure

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Mali has started experimentation of teaching the national languages at school through the convergent pedagogy in 1987. Then, it is in 1994 that it will become widespread with eleven of the thirteen former national languages used at primary school. The aim was to improve the Malian educational system because the use of French as the only medium of instruction was considered a contributing factor to the significant number of student dropouts and the high rate of repetition. The Convergent pedagogy highlights the knowledge acquired by children at home, their vision of the world and especially the knowledge they have of their mother tongue. That pedagogy requires the use of a specific medium only during classroom practices and teachers have been trained in this sense. The specific medium depends on the learning content, which sometimes is French, other times, it is the national language. Research has shown that bilingual learners do not only use the required medium in their learning activities, but they code switch. It is part of their learning processes. Currently, many scholars agree on the importance of CS in bilingual classes, and teachers have been told about the necessity of integrating it into their classroom practices. One of the challenges of the Malian bilingual education curriculum is the question of ‘effective languages management’. Theoretically, depending on the classrooms, an average have been established for each of the involved language. Following that, teachers make use of CS differently, sometimes, it favors the learners, other times, it contributes to the development of some linguistic weaknesses. The present research tries to fill that gap through a tentative model of didactization of CS, which simply means the practical management of the languages involved in the bilingual classrooms. It is to know how to use CS for effective learning. Moreover, the didactization of CS tends to sensitize the teachers about the functional role of CS so that they may overcome their own weaknesses. The overall goal of this research is to make code switching a real tool for bilingual education. The specific objectives are: to identify the types of CS used during classroom activities to present the functional role of CS for the teachers as well as the pupils. to develop a tentative model of code-switching, which will help the teachers in transitional classes of bilingual schools to recognize the appropriate moment for making use of code switching in their classrooms. The methodology adopted is a qualitative one. The study is based on recorded videos of teachers of 3rd year of primary school during their classroom activities and interviews with the teachers in order to confirm the functional role of CS in bilingual classes. The theoretical framework adopted is the typology of CS proposed by Poplack (1980) to identify the types of CS used. The study reveals that teachers need to be trained on the types of CS and the different functions they assume and on the consequences of inappropriate use of language alternation.

Keywords: bilingual curriculum, code switching, didactization, national languages

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Authors: Wiem Zemzem, Moncef Tagina

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In this work, we are addressing the problem of an autonomous mobile robot navigating in a large, unknown and dynamic environment using reinforcement learning abilities. This problem is principally related to the exploration/exploitation dilemma, especially the need to find a solution letting the robot detect the environmental change and also learn in order to adapt to the new environmental form without ignoring knowledge already acquired. Firstly, a new action selection strategy, called ε-greedy-MPA (the ε-greedy policy favoring the most promising actions) is proposed. Unlike existing exploration/exploitation policies (EEPs) such as ε-greedy and Boltzmann, the new EEP doesn’t only rely on the information of the actual state but also uses those of the eventual next states. Secondly, as the environment is large, an exploration favoring least recently visited states is added to the proposed EEP in order to accelerate learning. Finally, various simulations with ball-catching problem have been conducted to evaluate the ε-greedy-MPA policy. The results of simulated experiments show that combining this policy with the Qlearning method is more effective and efficient compared with the ε-greedy policy in stationary environments and the utility-based reinforcement learning approach in non stationary environments.

Keywords: autonomous mobile robot, exploration/ exploitation policy, large, dynamic environment, reinforcement learning

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Authors: R. Malisa, E. Schwella, K. I. Theletsane

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Due to climate change, population growth and rapid urbanization, the demand for water in South Africa is inevitably surpassing supply. To address similar challenges globally, there has been a paradigm shift from conventional urban waste water management “government” to a “governance” paradigm. From the governance paradigm, Integrated Urban Water Management (IUWM) principle emerged. This principle emphasizes efficient urban waste water treatment and production of high-quality recyclable effluent. In so doing mimicking natural water systems, in their processes of recycling water efficiently, and averting depletion of natural water resources.  The objective of this study was to investigate drivers of shifting the current urban waste water management approach from a “government” paradigm towards “governance”. The study was conducted through Interactive Management soft systems research methodology which follows a qualitative research design. A case study methodology was employed, guided by realism research philosophy. Qualitative data gathered were analyzed through interpretative structural modelling using Concept Star for Professionals Decision-Making tools (CSPDM) version 3.64.  The constructed model deduced that the main drivers in shifting the Stellenbosch municipal urban waste water management towards IUWM “governance” principles are mainly social elements characterized by overambitious expectations of the public on municipal water service delivery, mis-interpretation of the constitution on access to adequate clean water and sanitation as a human right and perceptions on recycling water by different communities. Inadequate public participation also emerged as a strong driver. However, disruptive events such as draught may play a positive role in raising an awareness on the value of water, resulting in a shift on the perceptions on recycled water. Once the social elements are addressed, the alignment of governance and administration elements towards IUWM are achievable. Hence, the point of departure for the desired paradigm shift is the change of water service authorities and serviced communities’ perceptions and behaviors towards shifting urban waste water management approaches from “government” to “governance” paradigm.

Keywords: integrated urban water management, urban water system, wastewater governance, wastewater treatment works

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Authors: Yi Ding

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With the rapid development of educational technologies, higher education institutions are facing the challenge of creating an inclusive learning environment for students from diverse backgrounds. Academic libraries, the hubs of research, instruction, and innovation at higher educational institutions, are facing the same challenge. While academic librarians worldwide have been working hard to provide services for emerging information technology such as information literacy education, online learning support, and scholarly communication advocacy, the problem of digital exclusion remains a difficult one at higher education institutions. Information services provided by academic libraries can result in the digital exclusion of students from diverse backgrounds, such as students with various digital readiness levels, students with disabilities, as well as English-as-a-Second-Language learners. This research study shows how academic librarians can design digital learning objects that are cognizant of differences in learner traits and student profiles through the lens of design thinking. By demonstrating how the design process of digital learning objects can take into consideration users’ needs, experiences, and engagement with different technologies, this research study explains design principles of accessibility, connectivity, and scalability in creating inclusive digital learning objects as shown in various case studies. Equipped with the mindset and techniques to be mindful of diverse student learning traits and profiles when designing information services, academic libraries can improve the digital inclusion and ultimately student success at higher education institutions.

Keywords: academic librarians, digital inclusion, information services, digital learning objects, student success

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Authors: Aishatu Ibrahim Birma, Aminu Tukur, Abdulkarim Abbass Gora

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Machine translation plays a vital role in the Field of Natural Language Processing (NLP), breaking down language barriers and enabling communication across diverse communities. In the context of Hausa, a widely spoken language in West Africa, mainly in Nigeria, effective translation systems are essential for enabling seamless communication and promoting cultural exchange. However, due to the unique linguistic characteristics of Hausa, accurate translation remains a challenging task. The research proposes an approach to improving the machine learning translation of Hausa by integrating Named Entity Recognition (NER) techniques. Named entities, such as person names, locations, organizations, and dates, are critical components of a language's structure and meaning. Incorporating NER into the translation process can enhance the quality and accuracy of translations by preserving the integrity of named entities and also maintaining consistency in translating entities (e.g., proper names), and addressing the cultural references specific to Hausa. The NER will be incorporated into Neural Machine Translation (NMT) for the Hausa to English Translation.

Keywords: machine translation, natural language processing (NLP), named entity recognition (NER), neural machine translation (NMT)

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Authors: Şirin Küçük, Ayşe Kök, İsmail Şahin

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Mobile devices are very popular and useful tools for assisting people in daily life. With the advancement of mobile technologies, the issue of mobile learning has been widely investigated in education. Many researches consider that it is important to integrate pedagogical and technical strengths of mobile technology into learning environments. For this reason, the purpose of this research is to examine the effect of mobile technology use in education with meta-analysis method. Meta-analysis is a statistical technique which combines the findings of independent studies in a specific subject. In this respect, the articles will be examined by searching the databases for researches which are conducted between 2005 and 2014. It is expected that the results of this research will contribute to future research related to mobile technology use in education.

Keywords: mobile learning, meta-analysis, mobile technology, education

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Authors: Andrew Nowlan

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During the Coronavirus pandemic, collaborative online international learning (COIL) emerged as an alternative to overseas sojourns. However, now that face-to-face classes have resumed and students are studying abroad, the rationale for doing COIL is not always clear amongst educators and students. Also, the logistics of COIL become increasingly complicated when participants involved in a potential collaboration have different second language (L2) learning goals. In this paper, the researcher will report on a study involving two bilingual, cross-cultural COIL courses between students at a university in Japan and those studying in North America, from April to December, 2022. The students in Japan were enrolled in an intercultural communication class in their L2 of English, while the students in Canada and the United States were studying intermediate Japanese as their L2. Based on a qualitative survey and journaling data received from 31 students in Japan, and employing a transcendental phenomenological research design, the researcher will highlight the students’ essence of experience during COIL. Essentially, students benefited from the experience through improved communicative competences and increased knowledge of the target culture, even when the L2 learning goals between institutions differed. Students also reported that the COIL experience was effective in preparation for actual study abroad, as opposed to a replacement for it, which challenges the existing literature. Both educators and administrators will be exposed to the perceptions of Japanese university students towards COIL, which could be generalized to other higher education contexts, including those in Southeast Asia. Readers will also be exposed to ideas for developing more effective pre-departure study abroad programs and domestic intercultural curriculum through COIL, even when L2 learning goals may differ between participants.

Keywords: collaborative online international learning, study abroad, phenomenology, EdTech, intercultural communication

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Authors: Catherine Omole

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Examination malpractice includes acts that temper with collecting accurate results during the conduct of an examination, thereby giving undue advantage to a student over his colleagues. Even though examination malpractice has been a lingering problem, examinations may not be easy to do away with completely as it is an important feedback tool in the learning process with several other functions e.g for the purpose of selection, placement, certification and promotion. Examination malpractice has created a lot of problems such as a relying on a weak work force based on false assessment results. The question is why is this problem still persisting, despite measures that have been taken to curb this ugly trend over the years? This opinion paper has identified modifications that could help relieve the student of the examination stress and thus increase the student’s effort towards effective learning and discourage examination malpractice in the long run.

Keywords: assessment, examination malpractice, learning, science classroom

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Authors: Gaurav Kumar Sinha

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In an era marked by increasing concerns about energy sustainability, this research endeavors to address the pressing challenge of energy consumption in buildings and industries. This study delves into the transformative potential of AWS services in optimizing energy efficiency. The research is founded on the recognition that effective management of energy consumption is imperative for both environmental conservation and economic viability. Buildings and industries account for a substantial portion of global energy use, making it crucial to develop advanced techniques for analysis and reduction. This study sets out to explore the integration of AWS services with big data analytics to provide innovative solutions for energy consumption analysis. Leveraging AWS's cloud computing capabilities, scalable infrastructure, and data analytics tools, the research aims to develop efficient methods for collecting, processing, and analyzing energy data from diverse sources. The core focus is on creating predictive models and real-time monitoring systems that enable proactive energy management. By harnessing AWS's machine learning and data analytics capabilities, the research seeks to identify patterns, anomalies, and optimization opportunities within energy consumption data. Furthermore, this study aims to propose actionable recommendations for reducing energy consumption in buildings and industries. By combining AWS services with metrics-driven insights, the research strives to facilitate the implementation of energy-efficient practices, ultimately leading to reduced carbon emissions and cost savings. The integration of AWS services not only enhances the analytical capabilities but also offers scalable solutions that can be customized for different building and industrial contexts. The research also recognizes the potential for AWS-powered solutions to promote sustainable practices and support environmental stewardship.

Keywords: energy consumption analysis, big data analytics, AWS services, energy efficiency

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Authors: Kittipong Tissayakorn, Fumio Akagi, Yu Song

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Manufacturers have been exploring innovative strategies to achieve and sustain competitive advantages as they face a new era of intensive global competition. Such strategy is known as Supply Chain Management (SCM), which has gained a tremendous amount of attention from both researchers and practitioners over the last decade. Supply chain management (SCM) is considered as the most popular operating strategy for improving organizational competitiveness in the twenty-first century. It has attracted a lot of attention recently due to its role involving all of the activities in industrial organizations, ranging from raw material procurement to final product delivery to customers. Well-designed supply chain systems can substantially improve efficiency and product quality, and eventually enhance customer satisfaction and profitability. In this paper, a manufacturing engineering perspective on supply chain integration is presented. Research issues discussed include the product and process design for the supply chain, design evaluation of manufacturing in the supply chain, agent-based techniques for supply chain integration, intelligent information for sharing across the supply chain, and a development of standards for product, process, and production data exchange to facilitate electronic commerce. The objective is to provide guidelines and references for manufacturing engineers and researchers interested in supply chain integration.

Keywords: supply chain, supply chain management, supply chain integration, manufacturing industries

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Authors: Haneen Alrawashdeh, Naciye Kunt

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Intercultural communicative competence or (ICC), is an extension of communicative competence that takes into account the intercultural aspect of learning a foreign language. Accordingly, this study aimed at investigating the intercultural interaction impact on English as a foreign language learners' academic achievement of language as a scholastic subject and their motivation towards learning it. To achieve the aim of the study, a qualitative research approach was implemented by means of semi-structured interviews. Interview sessions were conducted with eight teachers of English as well as ten English language learners who work in the tourism industry in a variety of career paths, such as selling antiques and traditional costumes. An analysis of learners' grades of English subjects from 2014 to 2019 academic years was performed by using the Open Education Management Information System Database in Jordan to support the findings of the study. The results illustrated that due to the fact that they work in the tourism sector, students gain skills and knowledge that assist them in better academic achievement in the subject of English by practicing intercultural communication with different nationalities on a daily basis; intercultural communication enhances students speaking skills, lexicon, and fluency; however, despite that their grades showed increasing, from teachers perspectives, intercultural communicative competence reduces their linguistic accuracy and ability to perform English academic writing in academic contexts such as exams.

Keywords: intercultural communicative competence, Jordan, language learning motivation, language academic achievement

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Authors: Maria Janet, Anita David, P. Vijayasamundeeswarimaria

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Introduction: The main purpose of this study is to compare the effectiveness of web-based and blended learning on Paediatric Basic Life Support on competency among undergraduate nursing students in selected nursing colleges in Chennai. Materials and methods: A descriptive pre-test and post-test study design were used for this study. Samples of 100 Fourth year B.Sc., nursing students at Sri Ramachandra Faculty of Nursing SRIHER, Chennai, 100 Fourth year B.Sc., nursing students at Apollo College of Nursing, Chennai, were selected by purposive sampling technique. The instrument used for data collection was Knowledge Questionnaire on Paediatric Basic Life Support (PBLS). It consists of 29 questions on the general expansion of Basic Life Support and Cardiopulmonary Resuscitation, Prerequisites of Basic Life Support, and Knowledge on Paediatric Basic Life Support in which each question has four multiple choices answers, each right answer carrying one mark and no negative scoring. This questionnaire was formed with reference to AHA 2020 (American Heart Association) revised guidelines. Results: After the post-test, in the web-based learning group, 58.8% of the students had an inadequate level of objective performance score, while 41.1% of them had an adequate level of objective performance score. In the blended learning group, 26.5% of the students had an inadequate level of an objective performance score, and 73.4% of the students had an adequate level of an objective performance score. There was an association between the post-test level of knowledge and the demographic variables of undergraduate nursing students undergoing blended learning. The age was significant at a p-value of 0.01, and the performance of BLS before was significant at a p-value of 0.05. The results show that there was a significant positive correlation between knowledge and objective performance score of undergraduate nursing students undergoing web-based learning on paediatric basic life support.

Keywords: basic life support, paediatric basic life support, web-based learning, blended learning

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Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

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Authors: Gertrude Nkechi Okenwa

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Higher institutions, especially the universities that are saddled with the responsibilities of teaching, learning, research, publications and social services for the production of graduates that are worthy in learning and character, and the creation of up-to-date knowledge and innovations for the total socio-economic and even political development of a given nation. Therefore, the purpose of the study was to identify the teaching, learning techniques used in the Enugu State University of Science and Technology to ensure or ascertain students’ perception on these techniques. To guide the study, survey research method was used. The population for the study was made up of second and final year students which summed up to one hundred and twenty-six students in the faculty of education. Stratified random sampling technique was adopted. A sample size of sixty (60) students was drawn for the study. The instrument used for data collection was questionnaire. To analyze the data, mean and standard deviation were used to answers the research questions. The findings revealed that direct instruction and construction techniques are used in the university. On the whole, it was observed that the students perceived constructivist techniques to be more useful and effective than direct instruction technique. Based on the findings recommendations were made to include diversification of teaching techniques among others.

Keywords: Strategies, Teaching and Learning, Constructive Technique, Direct Instructional Technique

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Authors: Siyao Zhu, Yifang Xu

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After natural and man-made disasters, robots can bypass the danger, expedite the search, and acquire unprecedented situational awareness to design rescue plans. The hands-free requirement from the first responders excludes the use of tedious manual control and operation. In unknown, unstructured, and obstructed environments, natural-language-based supervision is not amenable for first responders to formulate, and is difficult for robots to understand. Brain-computer interface is a promising option to overcome the limitations. This study aims to test the feasibility of using electroencephalography (EEG) signals to decode human intentions and detect the level of consensus on robot-provided information. EEG signals were classified using machine-learning and deep-learning methods to discriminate search intentions and agreement perceptions. The results show that the average classification accuracy for intention recognition and consensus assessment is 67% and 72%, respectively, proving the potential of incorporating recognizable users’ bioelectrical responses into advanced robot-assisted systems for emergency response.

Keywords: consensus assessment, electroencephalogram, emergency response, human-robot collaboration, intention recognition, search and rescue

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Authors: Sobhy Fathy A. Hashesh

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The study was carried out in the Elementary Classes of Andalus Private Schools, girls section using control and experimental groups formed by Random Assignment Strategy. The study aimed at investigating the effect of Al-Andalus Fused Curriculum (AFC) model of learning and the effect of separate subjects’ approach on the development of students’ conceptual learning and skills acquiring. The society of the study composed of Al-Andalus Private Schools, elementary school students, Girls Section (N=240), while the sample of the study composed of two randomly assigned groups (N=28) with one experimental group and one control group. The study followed the quantitative and qualitative approaches in collecting and analyzing data to investigate the study hypotheses. Results of the study revealed that there were significant statistical differences between students’ conceptual learning and skills acquiring for the favor of the experimental group. The study recommended applying this model on different educational variables and on other age groups to generate more data leading to more educational results for the favor of students’ learning outcomes.

Keywords: AFC, STEAM, lego education, Al-Andalus fused curriculum, mechatronics

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Authors: Ellie Abdi

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This paper is a review of a recently published book (April 2018) by Dr. Ellie Abdi. The book divides into two sections of 1) leadership in school organization and 2) pragmatic research in physical education professional development. The first part of the book explores school organizational development in terms of 1) communication development, 2) community development, and 3) decision making development. It concludes to acknowledge that decision making is the heart of educational management. This is while communication and community are essential to the development of the school organization. The role of a leader in a professional learning community (PLC) is acknowledged with the organizational development plan and moves onto 5 overall objectives of a professional development plan. It clarifies that professional learning community (PLC) benefits both students and professionals in education. Furthermore, professional development needs to be involved in opportunities to value diversity and foundations of learning, in addition to search for veteran teachers who offer a rich combination of experience and perspective. School educational platform in terms of teacher training in physical education is discussed in the second part. The book reviews that well-designed programs are powerful and constructive ways to identify the strength and weaknesses of teachers. Post-positivism, constructivism, advocacy/participatory, and pragmatism in teacher education are also disclosed. The book specifically unfolds pragmatic research in professional development of physical education. It provides researchers, doctoral, and masters level students with defined examples. In summary, the book shows how appropriate it is when many different traditions are displayed in a pragmatic way, following the stages of research from development to dissemination.

Keywords: leadership, physical education, pragmatic, professional development

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Authors: Yi-Hsiang Pan, Chen-Hui Huang, Ching-Hsiang Chen, Wei-Ting Hsu

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The purposes of the study were to explore the students' learning effect of physical education curriculum between merging Teaching Personal and Social Responsibility (TPSR) with sport education model and TPSR with traditional teaching model, which these learning effects included sport self-efficacy, sport enthusiastic, group cohesion, responsibility and game performance. The participants include 3 high school physical education teachers and 6 physical education classes, 133 participants with experience group 75 students and control group 58 students, and each teacher taught an experimental group and a control group for 16 weeks. The research methods used questionnaire investigation, interview, focus group meeting. The research instruments included personal and social responsibility questionnaire, sport enthusiastic scale, group cohesion scale, sport self-efficacy scale and game performance assessment instrument. Multivariate Analysis of covariance and Repeated measure ANOVA were used to test difference of students' learning effects between merging TPSR with sport education model and TPSR with traditional teaching model. The findings of research were: 1) The sport education model with TPSR could improve students' learning effects, including sport self-efficacy, game performance, sport enthusiastic, group cohesion and responsibility. 2) The traditional teaching model with TPSR could improve students' learning effect, including sport self-efficacy, responsibility and game performance. 3) the sport education model with TPSR could improve more learning effects than traditional teaching model with TPSR, including sport self-efficacy, sport enthusiastic,responsibility and game performance. 4) Based on qualitative data about learning experience of teachers and students, sport education model with TPSR significant improve learning motivation, group interaction and game sense. The conclusions indicated sport education model with TPSR could improve more learning effects in physical education curriculum. On other hand, the curricular projects of hybrid TPSR-Sport Education model and TPSR-Traditional Teaching model are both good curricular projects of moral character education, which may be applied in school physical education.

Keywords: character education, sport season, game performance, sport competence

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Authors: Daniel A. Walzer

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As the options for course delivery and development expand, plenty of misconceptions still exist concerning e-learning and online course delivery. Classroom instructors often discuss pedagogy, methodologies, and best practices regarding teaching from a singular, traditional in-class perspective. As more professors integrate online, blended, and hybrid courses into their dossier, a clearly defined rubric for gauging online course delivery is essential. The transition from a traditional learning structure towards an updated distance-based format requires careful planning, evaluation, and revision. This paper examines how new media stimulates reflective practice and guided inquiry to improve pedagogy, engage interdisciplinary collaboration, and supply rich qualitative data for future research projects in media arts disciplines.

Keywords: action research, inquiry, new media, reflection

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Authors: D. Moser, D. Pinto, A. Cipriano

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A Disaster Management System (DMS) for countries with different disasters is very important. In the world different disasters like earthquakes, tsunamis, volcanic eruption, fire or other natural or man-made disasters occurs and have an effect on the population. It is also possible that two or more disasters arisen at the same time, this means to handle multi-risk situations. To handle such a situation a Decision Support System (DSS) based on multiagents is a suitable architecture. The most known DMSs deal with one (in the case of an earthquake-tsunami combination with two) disaster and often with one particular disaster. Nevertheless, a DSS helps for a better realtime response. Analyze the existing systems in the literature and expand them for multi-risk disasters to construct a well-organized system is the proposal of our work. The here shown work is an approach of a multi-risk system, which needs an architecture, and well-defined aims. In this moment our study is a kind of case study to analyze the way we have to follow to create our proposed system in the future.

Keywords: decision support system, disaster management system, multi-risk, multiagent system

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Authors: Monette S. De Castro, Veneranda A. Magpantay, Christine B. Adiova, Mark D. Arboleda

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One-hundred-layer chicken farmers were randomly selected and interviewed using structured questionnaires to assess the production system and management practices in layer chicken farms. The respondents belonged to the commercial scale operation. Results showed that the predominant rearing and housing systems were intensive/complete confinement and open-sided, while slatted was the common type of flooring used during the brood-grow period. Dekalb and Lohmann were the common chicken layer strains reared by farmers. The majority of commercial chicken layer farms preferred ready-to-lay (RTL) pullets as their replacement stocks. Selling was the easiest way for farmers to dispose of and utilize poultry manure, while veterinary waste and mortality were disposed of in pits. Biosecurity practices employed by the farmers conformed with the ASEAN Biosecurity Management Manual for Commercial Poultry Farming. Flies and odor were the major problems in most layer farms that are associated with their farm wastes. Therefore, the application of new technologies and husbandry practices through training and actual demonstrations could be implemented to further improve the layer chicken raising in the province.

Keywords: layer chicken farms, marketing, production system, waste management

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Authors: Ruchika Malhotra, Megha Khanna

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The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics

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Authors: Karthik Mittal

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This study performs an unsupervised machine learning analysis to find clusters of related SNPs which highlight biological pathways that are important for the biological mechanisms of breast cancer. Studying genetic variations in isolation is illogical because these genetic variations are known to modulate protein production and function; the downstream effects of these modifications on biological outcomes are highly interconnected. After extracting the SNPs and their effect on different types of breast cancer using the MRBase library, two unsupervised machine learning clustering algorithms were implemented on the genetic variants: a k-means clustering algorithm and a hierarchical clustering algorithm; furthermore, principal component analysis was executed to visually represent the data. These algorithms specifically used the SNP’s beta value on the three different types of breast cancer tested in this project (estrogen-receptor positive breast cancer, estrogen-receptor negative breast cancer, and breast cancer in general) to perform this clustering. Two significant genetic pathways validated the clustering produced by this project: the MAPK signaling pathway and the connection between the BRCA2 gene and the ESR1 gene. This study provides the first proof of concept showing the importance of unsupervised machine learning in interpreting GWAS summary statistics.

Keywords: breast cancer, computational biology, unsupervised machine learning, k-means, PCA

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Authors: Anam Gopi

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The undesired torque and flux ripple may occur in conventional direct torque control (DTC) induction motor drive. DTC can improve the system performance at low speeds by continuously tuning the regulator by adjusting the Kp, Ki values. In this Teaching Learning Based Optimization (TLBO) is proposed to adjust the parameters (Kp, Ki) of the speed controller in order to minimize torque ripple, flux ripple, and stator current distortion. The TLBO based PI controller has resulted is maintaining a constant speed of the motor irrespective of the load torque fluctuations.

Keywords: teaching learning based optimization, direct torque control, PI controller

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Authors: Agis Andriani

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To create an effective teaching condition, the teacher requests the students as the instruction to guide the them interactively in the learning activities in the classroom. This study involves 160 Indonesian students who study English in the university, as participants in the discourse completion test, and ten of them are interviewed. The result shows that when the students response the teacher’s request, it realizes assertives, directives, commisives, expressives, and declaratives. These indicate that the students are active, motivated, and responsive in the learning process, although in the certain condition these responses are to prevent their faces from the shyness of their silence in interaction. Therefore, it needs the teacher’s creativity to give the conducive atmosphere in order to support the students’ participation in learning English.

Keywords: discourse completion test, effective teaching, request, teacher’s creativity

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Authors: Guo Haonan, Chen Peiyu, Zhao Hanyu, Burra Venkata Durga Kumar

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Unix and Unix-like operating systems are widely used due to their high stability but are limited by the parent-child process structure, and the child process depends on the parent process, so the crash of a single process may cause the entire process group or even the entire system to fail. Another possibility of unexpected process termination is that the system administrator inadvertently closed the terminal or pseudo-terminal where the application was launched, causing the application process to terminate unexpectedly. This paper mainly analyzes the reasons for the problems and proposes two solutions.

Keywords: process management, daemon, login-bash and non-login bash, process group

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Authors: Haci Mehmet Guzey, Levent Acar

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In this paper, a novel decentralized controller is developed for linear systems with nonlinear unknown interconnections. A model linear decoupled system is assigned for each system. By using the difference actual and model state dynamics, the problem is formulated as inverse problem. Then, the interconnected dynamics are approximated by using Galerkin’s expansion method for inverse problems. Two different sets of orthogonal basis functions are utilized to approximate the interconnected dynamics. Approximated interconnections are utilized in the controller to cancel the interconnections and decouple the systems. Subsequently, the interconnected systems behave as a collection of decoupled systems.

Keywords: decentralized control, inverse problems, large scale systems, nonlinear interconnections, basis functions, system identification

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Authors: Ágoston Nagy

Abstract:

This paper introduces a method of using unsupervised machine learning to visualize the feature space of a dataset in 2D, in order to find most characteristic segments in the set. After dimension reduction, users can select clusters by manual drawing. Selected clusters are recorded into a data model that is used for later predictions, based on realtime data. Predictions are made with supervised learning, using Gesture Recognition Toolkit. The paper introduces two example applications: a semantic audio organizer for analyzing incoming sounds, and a gesture database organizer where gestural data (recorded by a Leap motion) is visualized for further manipulation.

Keywords: gesture recognition, machine learning, real-time interaction, visualization

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Authors: Nahid Tavakoli, Asghar Ehteshami, Akbar Hassanzadeh, Fatemeh Amini

Abstract:

Introduction: The Information security incident management guidelines was been developed to help hospitals to meet their information security event and incident management requirements. The purpose of this Study was to investigate on Information Security Incident Management in Isfahan’s educational hospitals in accordance to ISO/IEC 27002 standards. Methods: This was a cross-sectional study to investigate on Information Security Incident Management of educational hospitals in 2014. Based on ISO/IEC 27002 standards, two checklists were applied to check the compliance with standards on Reporting Information Security Events and Weakness and Management of Information Security Incidents and Improvements. One inspector was trained to carry out the assessments in the hospitals. The data was analyzed by SPSS. Findings: In general the score of compliance Information Security Incident Management requirements in two steps; Reporting Information Security Events and Weakness and Management of Information Security Incidents and Improvements was %60. There was the significant difference in various compliance levels among the hospitals (p-valueKeywords: information security incident management, information security management, standards, hospitals

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Authors: Akram Hashemi

Abstract:

This study provided an empirical evidence for learners of elementary level of language proficiency to investigate the potential role of contextualization in vocabulary learning. Prior to the main study, pilot study was performed to determine the reliability and validity of the researcher-made pretest and posttest. After manifesting the homogeneity of the participants, the participants (n = 90) were randomly assigned into three equal groups, i.e., two experimental groups and a control group. They were pretested by a vocabulary test, in order to test participants' pre-knowledge of vocabulary. Then, vocabulary instruction was provided through three methods of visual instruction, the use of context and the use of conventional techniques. At the end of the study, all participants took the same posttest in order to assess their vocabulary gain. The results of independent sample t-test indicated that there is a significant difference between learning vocabulary visually and learning vocabulary contextually. The results of paired sample t-test showed that different teaching strategies have significantly different impacts on learners’ vocabulary gains. Also, the contextual strategy was significantly more effective than visual strategy in improving students’ performance in vocabulary test.

Keywords: vocabulary instruction, explicit instruction, implicit instruction, strategy

Procedia PDF Downloads 315