Search results for: English learning strategies

Authors: Ruthanne Tobin

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As our data-driven, cloud-based, knowledge-centric lives become ever more global, mobile, and digital, educational systems everywhere are struggling to keep pace. Schools need to prepare students to become critical-thinking, tech-savvy, life-long learners who are engaged and adaptable enough to find their unique calling in a post-industrial world of work. Recognizing that no nation can afford poor achievement or high dropout rates without jeopardizing its social and economic future, the thirty-two nations of the OECD are launching initiatives to redesign schools, generally under the banner of Personalized Learning or 21st Century Learning. Their intention is to transform education by situating students as co-enquirers and co-contributors with their teachers of what, when, and how learning happens for each individual. In this focused review of the 2007-2017 literature on personalized learning, the author sought answers to two main questions: “What are the theoretical frameworks that guide personalized learning?” and “What is the conceptual understanding of the model?” Ultimately, the review reveals that, although the research area is overly theorized and under-substantiated, it does provide a significant body of knowledge about this potentially transformative educational restructuring. For example, it addresses the following questions: a) What components comprise a PL model? b) How are teachers facilitating agency (voice & choice) in their students? c) What kinds of systems, processes and procedures are being used to guide the innovation? d) How is learning organized, monitored and assessed? e) What role do inquiry based models play? f) How do teachers integrate the three types of knowledge: Content, pedagogical and technological? g) Which kinds of forces enable, and which impede, personalizing learning? h) What is the nature of the collaboration among teachers? i) How do teachers co-regulate differentiated tasks? One finding of the review shows that while technology can dramatically expand access to information, expectations of its impact on teaching and learning are often disappointing unless the technologies are paired with excellent pedagogies in order to address students’ needs, interests and aspirations. This literature review fills a significant gap in this emerging field of research, as it serves to increase conceptual clarity that has hampered both the theorizing and the classroom implementation of a personalized learning model.

Keywords: curriculum change, educational innovation, personalized learning, school reform

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Authors: Rashedul Islam

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A firmly-validated aim of teaching science is to support student enthusiasm for science learning with an outspread interest in scientific issues in future life. This is in keeping with the recent development in Gifted and Talented Education statement which instructs that gifted students have a renewed interest and natural aptitude in science. Yet, the practice of science teaching leaves many students with the feeling that science is difficult and compared to other school subjects, students interest in science is declining at the final years of the primary school. As a curriculum guides the teaching-learning activities in school, where significant consequences may result from the context of the curricula and syllabi, are a major feature of certain educational jurisdictions in NSW, Australia. The purpose of this study was an exploration of the curriculum sets the context to identify how science education is practiced through primary schools in Sydney, Australia. This phenomenon was explored through document review from two publicly available documents namely: the NSW Science Syllabus K-6, and Australian Curriculum: Foundation - 10 Science. To analyse the data, this qualitative study applied themed content analysis at three different levels, i.e., first cycle coding, second cycle coding- pattern codes, and thematic analysis. Preliminary analysis revealed the phenomenon of teaching-learning practices drawn from eight themes under three phenomena aligned with teachers’ practices and gifted student’s learning characteristics based on Gagné’s Differentiated Model of Gifted and Talent (DMGT). From the results, it appears that, overall, the two documents are relatively well-placed in terms of identifying the context of teaching and learning primary science to gifted students. However, educators need to make themselves aware of the ways in which the curriculum needs to be adapted to meet gifted students learning needs in science. It explores the important phenomena of teaching-learning context to provide gifted students with optimal educational practices including inquiry-based learning, problem-solving, open-ended tasks, creativity in science, higher order thinking, integration, and challenges. The significance of such a study lies in its potential to schools and further research in the field of gifted education.

Keywords: teaching primary science, gifted student learning, curriculum context, science syllabi, Australia

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Authors: Leila Anjomshoa, Firooz Sadighi

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This study investigated the effects of three types of pre-reading activities (vocabulary definitions, text summary and pre-passage questions) on EFL learners’ English reading comprehension. On the basis of the results of a placement test administered to two hundred and thirty English students at Kerman Azad University, 200 subjects (one hundred intermediate and one hundred advanced) were selected.Four texts, two of them at intermediate level and two of them at advanced level were chosen. The data gathered was subjected to the statistical procedures of ANOVA. A close examination of the results through Tukey’s HSD showed the fact that the experimental groups performed better than the control group, highlighting the effect of the treatment on them. Also, the experimental group C (text summary), performed remarkably better than the other three groups (both experimental & control). Group B subjects, vocabulary definitions, performed better than groups A and D. The pre-passage questions group’s (D) performance showed higher scores than the control condition.

Keywords: pre-reading activities, text summary, vocabulary definition, and pre-passage questions, reading comprehension

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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Authors: Penn P. Wu

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Recent advances in virtual reality (VR) technologies have made it possible for students to experience a virtual on-the-scene or virtual in-person observation of an educational event. In an experimental class, the author uses VR, particularly 360° videos, to virtually engage students in an event, through a wide spectrum of educational resources, such s a virtual “bystander.” Students were able to observe the event as if they were physically on site, although they could not intervene with the scene. The author will describe the adopted equipment, specification, and cost of building them as well as the quality of VR. The author will discuss (a) feasibility, effectiveness, and efficiency of using VR as a supplemental technology to teach college students and criteria and methodologies used by the authors to evaluate them; (b) barriers and issues of technological implementation; and (c) pedagogical practices learned through this experiment. The author also attempts to explore (a) how VR could provide an interactive virtual in-person learning experience; (b) how VR can possibly change traditional college education and online education; (c) how educators and balance six critical factors: cost, time, technology, quality, result, and content.

Keywords: learning with VR, virtual experience of learning, virtual in-person learning, virtual reality for education

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Authors: T. Pastraporn, J. Panida, P. Gasamapong, N. Jintana

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The study of inclusive educational environment of exceptional and normal children at the regional centre for special education aimed to establish guidelines for creating an environment for inclusive education. Buildings utilization of thirty-five elementary schools providing inclusive educational program in Bangkok were analyzed to study the following aspects: 1) The environment of exceptional and normal students’ inclusive classes at the regional centre for special education 2) The patterns of the environment suited to the exceptional and normal students’ inclusive classes 3) Environmental management policies for the inclusive classes of exceptional and normal students. Information was gathered from surveys, observations, questionnaires, document analysis, interviews, and non-experimental research. The findings showed that the usable spaces in school buildings were designated to enhance the three kinds of social learning experience: 1) Support class control 2) Help developing students’ personality consisting of physical, verbal and emotional expressions that are socially accepted 3) Recognition and learning, which are needed for the increasing of learning experience, were caused by having an interaction with the environment. Thus, the school buildings’ space designation positively affected the environmental management of exceptional and normal students’ inclusive classes.

Keywords: learning environment, inclusive education, school buildings, exceptional and normal children

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Authors: Van Thien NGO

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The purpose of the study is to examine the effect of student response systems in computer-based formative assessment on learning outcomes. The backward design course is a tool to be applied for collecting necessary assessment evidence. The quasi-experimental research design involves collecting pre and posttest data on students assigned to the control group and the experimental group. The sample group consists of 150 college students randomly selected from two of the eight classes of electrical and electronics students at Cao Thang Technical College in Ho Chi Minh City, Vietnam. Findings from this research revealed that the experimental group, in which student response systems were applied, got better results than the controlled group, who did not apply them. Results show that using student response systems for technology-based formative assessment is vital and meaningful not only for teachers but also for students in the teaching and learning process.

Keywords: student response system, computer-based formative assessment, learning outcome, backward design course

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Authors: Klara Królewiak-Detsi, Anna Orylska, Anna Gorgolewska, Marta Boczkowska, Agata Graczykowska

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This study investigates the communication between students and teachers in inclusive education in Poland. Specifically, we examine the communication and interaction of students with special educational needs during online learning compared to traditional face-to-face instruction. Our research questions are (1) how children with special educational needs communicate with their teachers and peers during online learning, and (2) what strategies can improve their communication skills. We conducted five focus groups with: (1) 55 children with special educational needs, (2) 65 typically developing pupils, (3) 28 professionals (psychologists and special education therapists), (4) 16 teachers, and (5) 16 parents of children with special educational needs. Our analysis focused on primary schools and used thematic analysis according to the 6-step procedure of Braun and Clarke. Our findings reveal that children with disabilities faced more difficulties communicating and interacting with others online than in face-to-face lessons. The online tools used for education were not adapted to the needs of children with disabilities, and schools lacked clear guidelines on how to pursue inclusive education online. Based on the results, we offer recommendations for online communication training and tools that are dedicated to children with special educational needs. Additionally, our results demonstrate that typically developing pupils are better in interpersonal relations and more often and effectively use social support. Children with special educational needs had similar emotional and communication challenges compared to their typically developing peers. In conclusion, our study highlights the importance of providing adequate support for the online education of children with special educational needs in inclusive classrooms.

Keywords: Inclusive education, Special educational needs, Social skills development, Online communication

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Authors: Jordan Putra Cahyono, Tiara Ayu Kusumaningtyas, Mohtar Rasyid

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This article aims to map the potential and strategy of digital economy develop-ment in Indonesia by using literature study and secondary data analysis. In the Indonesian context, the digital economy is attracting attention, especially amid the COVID-19 pandemic, which has brought substantial changes in economic activi-ties. This research aims to provide new insights into the potential and develop-ment strategies of the digital economy in Indonesia. This article also evaluates the effectiveness and efficiency of digital economic development strategies imple-mented in Indonesia. A literature review concluded that Indonesia has great po-tential to develop the digital economy with favorable conditions, including a large population, improved ICT infrastructure, and relatively liberalized regulations. Using qualitative and quantitative approaches, this research covers the subject of the potential and strategies for developing a digital economy in Indonesia. This article presents the research results, which are then discussed in the context of the potential and strategy of digital economy development in Indonesia. This article is expected to contribute to understanding Indonesia's digital economy and stimulate further discussion to formulate a robust development strategy and appropriate regulatory framework.

Keywords: indonesia's digital economy, ICT infrastructure, development strategy, potential

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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: A. Mohamed Mydeen, Pallapa Venkataram

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The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.

Keywords: knowledge representation, pervasive computing, agent technology, ECA rules

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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: Chaich Hamza Walid

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The primary goal of this paper is to question the situation of men’s place in D.H Lawrence’s Sons and Lovers. Our question is what is the role of each man in the novel? And how a mother’s possessiveness had changed the life of all men in the family? David Herbert Lawrence was an important and controversial English writer of the 20th century. He wrote many great works, one of his most popular novels, Sons and Loves, is an autobiographical account of his youth. This novel is about the life of the Morels. The author develops the story by portraying the relationships between many characters, especially the male ones we focus on. ‘Sons and Lovers’ seems to be written especially to women, all what Lawrence wrote is about women but when we go deeper, we see that Lawrence was also interested in men. This work will approach the question in two ways. The first chapter will deal with men’s place in D.H Lawrence’s Sons and Lovers, more exactly with Paul and his father Walter Morel, and with Baxter Dawes. We will focus on each man’s behavior with one another. In the second chapter, we will analyze possessiveness, that is to say, the desire of holding or having someone as one’s own or under one’s control. We will try to prove this view from the spiritual and symbolic possession of different relationships. Our study will be through an intensive psychological analysis of a wife’s possessiveness to her husband, and a mother’s possessiveness to her son’s; William and Paul. The conclusion will review all the important aspects of this analysis. It is very important to know about men’s relationships in D.H Lawrence’s Sons and Lovers this will give us another vision of the novel, and where we can situate Paul’s true relationships, that is to say, his relationships with his father and the other men in the novel.

Keywords: language, literature, English, civilisation

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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: Liberto Pombal, Christian Dieter Jaekel

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The objective of this work is to establish theoretical and numerical conditions for Solving Extended Linear Complementarity Problems (XLCP), with emphasis on the Horizontal Linear Complementarity Problem (HLCP). Two new strategies for solving complementarity problems are presented, using differentiable and penalized functions, which resulted in a natural formalization for the Linear Horizontal case. The computational results of all suggested strategies are also discussed in depth in this paper. The implication in practice allows solving and optimizing, in an innovative way, the (forestry) problems of the value chain of the industrial wood sector in Angola.

Keywords: complementarity, box constrained, optimality conditions, wood and environment

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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: Dzunisani Sibuyi

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This article demonstrates how corruption is revealed in Mandla Langa’s Memory of Stones (2000) through the deployment of narrational strategies by applying narrative theories by Gerard Genette’s Narrative Discourse and Narrative Discourse Revisited, as well as Mikhail Bakhtin’s Dialogic Imagination to the text. This is accomplished by analysing Langa’s use of extradiegetic-heterodiegetic and intradiegetic-homodiegetic narrational strategies respectively employed by the anonymous narrator and character narrator Mpanza. The narration provided by these narrators is multi-voiced in its approach to the events depicting corruption from various completing and explanatory perspectives. In addition, Langa also employs narrative techniques of narrating times such as simultaneous, subsequent, and interpolated narration to highlight corruption taking place, which is highlighted by situating the story in its presentness moments coinciding with the corruption action. As a result, by emphasising the events portraying the plight of the main characters and their struggle to resist and defeat corrupt leaders, the narration strategically reveals corruption.

Keywords: narrational strategies, narrating voice, dialogism, corruption, Gérard Genette, Mandla Langa, Mikhail Bakhtin, time(s) of the narration

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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: 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: Soheila Sadeghi

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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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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: Arshia Khan, Hans-Dietrich Haasis

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Different tools of the supply chain should be managed very efficiently in mass customization. In the automobile industry, there are different strategies to manage these tools. We need to investigate which strategies among the different ones are successful and which are not. There is lack in literature regarding such analysis. Keeping this in view, the purpose of this paper is to construct a framework and model which can help to analyze the supply chain of mass customized automobiles quantitatively for future studies. Furthermore, we will also consider that which type of data can be used for the suggested model and where it can be taken from. Such framework can help to bring insight for future analysis.

Keywords: mass customization, supply chain, inventory, distribution, automobile industry

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Authors: Betty Makena, Tsegaye Tadesse, Mark Svoboda

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Global warming has intensified the frequency and intensity of extreme climate disasters and led to unpredictable weather conditions. Consequently, rapid shifts between drought and floods, known as Drought-Flood Abrupt Alteration (DFAA), have become increasingly common. DFAA results in superimposed impacts of drought and floods within a short period, exacerbating the effects of the floods or drought event. Current disaster management plans often overlook DFAA events, as they primarily focus on either floods or drought. Therefore, effectively identifying DFAA events is crucial for developing effective mitigation strategies. This study aims to identify historical DFAA events in Kenya using the Long Cycle Drought-Flood Abrupt Alteration Index (LDFAI). The research will analyze the spatial distribution, temporal variation, and intensity of DFAA events from 1990 to 2023, as well as their socio-economic impacts. Understanding these events is important to develop more effective strategies to address the impacts of DFAA events. Findings from this study will inform decision making to develop coping strategies to mitigate the adverse effects of DFAA in Kenya.

Keywords: abrupt, alteration, drought, floods

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Authors: Adetoun Adedotun Amubode

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Nigeria's Textile Industry was the second largest in Africa after Egypt, with above 250 vibrant factories and over 50 percent capacity utilization contributing to foreign exchange earnings and employment generation. Currently, multifaceted challenges such as epileptic power supply, inconsistent government policies, growing digitalization, smuggling of foreign textiles, insecurity and the inability of the local industries to compete with foreign products, especially Chinese textile, has created a hostile environment for the sector. This led to the closure of most of the textile industries. China's textile industry has experienced institutional change and industrial restructuring, having 30% of the world's market share. This paper examined the strategies adopted by China in transforming her textile and clothing industries and designed a model for the integration of these strategies to improve the competitive strength and growth of the Nigerian textile and clothing industries in a dynamic and changing market. The paper concludes that institutional support, regional production, export-oriented policy, value-added and branding cultivation, technological upgrading and enterprise resource planning be integrated into the Nigerian clothing and textile industries.

Keywords: clothing, industry, integration, Nigerian, textile, transformation.

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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

Abstract:

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: Andres Diaz Garcia, Ana Maria Ceballos Rojas, Duvan Albeiro Millan Montano

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This paper describes the initial technological development stages in the area of liquid fermentation required to reach the quantities of biomass of the biofertilizer microorganism Rhizobium sp. strain B02, for the application of the unitary stages downstream at laboratory scale. In the first stage, the adjustment and standardization of the fermentation process in conventional batch mode were carried out. In the second stage, various fed-batch and continuous fermentation strategies were evaluated in 10L-bioreactor in order to optimize the yields in concentration (Colony Forming Units/ml•h) and biomass (g/l•h), to make feasible the application of unit operations downstream of process. The growth kinetics, the evolution of dissolved oxygen and the pH profile generated in each of the strategies were monitored and used to make sequential adjustments. Once the fermentation was finished, the final concentration and viability of the obtained biomass were determined and performance parameters were calculated with the purpose of select the optimal operating conditions that significantly improved the baseline results. Under the conditions adjusted and standardized in batch mode, concentrations of 6.67E9 CFU/ml were reached after 27 hours of fermentation and a subsequent noticeable decrease was observed associated with a basification of the culture medium. By applying fed-batch and continuous strategies, significant increases in yields were achieved, but with similar concentration levels, which involved the design of several production scenarios based on the availability of equipment usage time and volume of required batch.

Keywords: biofertilizer, liquid fermentation, Rhizobium sp., standardization of processes

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Authors: Alberto Mora-Vazquez, Nelly Paulina Trejo Guzmán

Abstract:

This study examines the learning trajectories of twelve language teachers who were former students of a BA in applied linguistics at a Mexican state university. In particular, the study compares the social, academic and professional trajectories of two groups of teachers, six locally raised and educated ones and six repatriated ones from the U.S. Our interest in undertaking this research lies in the wide variety of students’ backgrounds we as professors in the BA program have witnessed throughout the years it has been around. Ever since the academic program started back in 2006, the student population has been made up of students whose backgrounds are highly diverse in terms of English language proficiency level, professional orientations and degree of cross-cultural awareness. Such diversity is further evidenced by the ongoing incorporation of some transnational students who have lived and studied in the United States for a significant period of time before their enrolment in the BA program. This, however, is not an isolated event as other researchers have reported this phenomenon in other TESOL-related programs of Mexican universities in the literature. Therefore, this suggests that their social and educational experiences are quite different from those of their Mexican born and educated counterparts. In addition, an informal comparison of the participation in formal teaching activities of the two groups at the beginning of their careers also suggested that significant differences in teacher training and development needs could also be identified. This issue raised questions about the need to examine the life and learning trajectories of these two groups of student teachers so as to develop an intervention plan aimed at supporting and encouraging their academic and professional advancement based on their particular needs. To achieve this goal, the study makes use of a combination of retrospective life-history research and the analysis of academic documents. The first approach uses interviews for data-collection. Through the use of a narrative life-history interview protocol, teachers were asked about their childhood home context, their language learning and teaching experiences, their stories of studying applied linguistics, and self-description. For the analysis of participants’ educational outcomes, a wide range of academic records, including reports of language proficiency exams results and language teacher training certificates, were used. The analysis revealed marked differences between the two groups of teachers in terms of academic and professional orientations. The locally educated teachers tended to graduate first, to look for further educational opportunities after graduation, to enter the language teaching profession earlier, and to expand their professional development options more than their peers. It is argued that these differences can be explained by their identities, which are made up of the interplay of influences such as their home context, their previous educational experiences and their cultural background. Implications for language teacher trainers and applied linguistics academic program administrators are provided.

Keywords: beginning language teachers, life-history research, Mexican context, transnational students

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Authors: Anam Gopi

Abstract:

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

Procedia PDF Downloads 569