Search results for: online learning management system

Authors: Armita Ghobadi, Samantha Emerson, Seyda Ozcaliskan

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Being a bilingual involves mastery of both speech and gesture patterns in a second language (L2). We know from earlier work in first language (L1) production contexts that speech and co-speech gesture form a tightly integrated system: co-speech gesture mirrors the patterns observed in speech, suggesting an online effect of language on nonverbal representation of events in gesture during the act of speaking (i.e., “thinking for speaking”). Relatively less is known about the online effect of language on gesture in bilinguals speaking structurally different languages. The few existing studies—mostly with small sample sizes—suggests inconclusive findings: some show greater achievement of L2 patterns in gesture with more advanced L2 speech production, while others show preferences for L1 gesture patterns even in advanced bilinguals. In this study, we focus on advanced bilingual speakers of two structurally different languages (Spanish L1 with English L2) in comparison to L1 English speakers. We ask whether bilingual speakers will follow target L2 patterns not only in speech but also in gesture, or alternatively, follow L2 patterns in speech but resort to L1 patterns in gesture. We examined this question by studying speech and gestures produced by 23 advanced adult Spanish (L1)-English (L2) bilinguals (Mage=22; SD=7) and 23 monolingual English speakers (Mage=20; SD=2). Participants were shown 16 animated motion event scenes that included distinct manner and path components (e.g., "run over the bridge"). We recorded and transcribed all participant responses for speech and segmented it into sentence units that included at least one motion verb and its associated arguments. We also coded all gestures that accompanied each sentence unit. We focused on motion event descriptions as it shows strong crosslinguistic differences in the packaging of motion elements in speech and co-speech gesture in first language production contexts. English speakers synthesize manner and path into a single clause or gesture (he runs over the bridge; running fingers forward), while Spanish speakers express each component separately (manner-only: el corre=he is running; circle arms next to body conveying running; path-only: el cruza el puente=he crosses the bridge; trace finger forward conveying trajectory). We tallied all responses by group and packaging type, separately for speech and co-speech gesture. Our preliminary results (n=4/group) showed that productions in English L1 and Spanish L1 differed, with greater preference for conflated packaging in L1 English and separated packaging in L1 Spanish—a pattern that was also largely evident in co-speech gesture. Bilinguals’ production in L2 English, however, followed the patterns of the target language in speech—with greater preference for conflated packaging—but not in gesture. Bilinguals used separated and conflated strategies in gesture in roughly similar rates in their L2 English, showing an effect of both L1 and L2 on co-speech gesture. Our results suggest that online production of L2 language has more limited effects on L2 gestures and that mastery of native-like patterns in L2 gesture might take longer than native-like L2 speech patterns.

Keywords: bilingualism, cross-linguistic variation, gesture, second language acquisition, thinking for speaking hypothesis

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Authors: Slava Kalyuga

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There are two opposing major points of view on the optimal degree of initial instructional guidance that is usually discussed in the literature by the advocates of the corresponding learning approaches. Using unguided or minimally guided problem-solving tasks prior to explicit instruction has been suggested by productive failure and several other instructional theories, whereas an alternative approach - using fully guided worked examples followed by problem solving - has been demonstrated as the most effective strategy within the framework of cognitive load theory. An integrated approach discussed in this paper could combine the above frameworks within a broader theoretical perspective which would allow bringing together their best features and advantages in the design of learning tasks for STEM education. This paper represents a systematic review of the available empirical studies comparing the above alternative sequences of instructional methods to explore effects of several possible moderating factors. The paper concludes that different approaches and instructional sequences should coexist within complex learning environments. Selecting optimal sequences depends on such factors as specific goals of learner activities, types of knowledge to learn, levels of element interactivity (task complexity), and levels of learner prior knowledge. This paper offers an outline of a theoretical framework for the design of complex learning tasks in STEM education that would integrate explicit instruction and inquiry (exploratory, discovery) learning approaches in ways that depend on a set of defined specific factors.

Keywords: cognitive load, explicit instruction, exploratory learning, worked examples

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Authors: Andrzej Poszewiecki

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The presented paper contributes to the experimental current of research on privacy. The question of privacy is being discussed at length at present, primarily among lawyers and politicians. However, the matter of privacy has been of interest for economists for some time as well. The valuation of privacy by people is of great importance now. This article is about how people valuate their privacy. An experimental method has been utilised in the conducted research – the survey was carried out among customers of an online store, and the studied issue was whether their readiness to sell their data (WTA) was different from the willingness to buy data back (WTP). The basic aim of this article is to analyse whether people shopping on the Internet differentiate their privacy depending on whether they protect or sell it. The achieved results indicate the presence of major differences in this respect, which do not always come up with the original expectations. The obtained results have supported the hypothesis that people are more willing to sell their data than to repurchase them. However, the hypothesis that the value of proposed remuneration affects the willingness to sell/buy back personal data (one’s privacy) has not been supported.

Keywords: privacy, experimental economics, behavioural economics, internet

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Authors: Jonathan Frank, Michelle Salmona

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We conducted quantitative and qualitative analyses of nurses’ perceived ease of use of electronic medical records and telemedicine in the Cook Islands. We examined antecedents of perceived ease of use through the lens of social construction of learning, and cultural diffusion. Our findings confirmed expected linkages between PEOU, attitudes and intentions. Interviews with nurses suggested infrastructural barriers to engaged learning. We discussed managerial implications of our findings, and areas of interest for future research.

Keywords: health information technology, ICT4D, TAM, developing countries

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Authors: Fiseha M. Guangul, Annissa Muhammed, Aja O. Chikere

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Group task is one method to create the conducive environment for the active teaching-learning process. Performing group task with active involvement of students will benefit the students in many ways. However, in most cases all students do not participate actively in the group task, and hence the intended benefits are not acquired. This paper presents the improvements of students’ participation in the group task and learning from the group task by introducing different techniques to enhance students’ participation. For the purpose of this research Carpentry and Joinery II (WT-392) course from Wood Technology Department at Adama Science and Technology University was selected, and five groups were formed. Ten group tasks were prepared and the first five group tasks were distributed to the five groups in the first day without introducing the techniques that are used to enhance participation of students in the group task. On another day, the other five group tasks were distributed to the same groups and various techniques were introduced to enhance students’ participation in the group task. The improvements of students’ learning from the group task after the implementation of the techniques. After implementing the techniques the evaluation showed that significant improvements were obtained in the students’ participation and learning from the group task.

Keywords: group task, students participation, active learning, the evaluation method

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Authors: Ritwik Dutta, Marylin Wolf

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This paper describes the trade-offs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The back-end consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.

Keywords: flask, Java, JavaScript, health monitoring, long-term care, Mongo, Python, smart home, software engineering, webserver

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Authors: Beulah Rani Inbanathan

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In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

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Authors: Ahmad Haidar

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This research paper investigates the concept of modern management, concentrating on the development of managerial practices and the adoption of innovative strategies in response to the fast-changing business landscape caused by Artificial Intelligence (AI). The study begins by examining the historical context of management theories, tracing the progression from classical to contemporary models, and identifying key drivers of change. Through a comprehensive review of existing literature and case studies, this paper provides valuable insights into the principles and practices of modern management, offering a roadmap for organizations aiming to navigate the complexities of the contemporary business world. The paper examines the growing role of digital technology in modern management, focusing on incorporating AI, machine learning, and data analytics to streamline operations and facilitate informed decision-making. Moreover, the research highlights the emergence of new principles, such as adaptability, flexibility, public participation, trust, transparency, and digital mindset, as crucial components of modern management. Also, the role of business leaders is investigated by studying contemporary leadership styles, such as transformational, situational, and servant leadership, emphasizing the significance of emotional intelligence, empathy, and collaboration in fostering a healthy organizational culture. Furthermore, the research delves into the crucial role of environmental sustainability, corporate social responsibility (CSR), and corporate digital responsibility (CDR). Organizations strive to balance economic growth with ethical considerations and long-term viability. The primary research question for this study is: "What are the key principles, practices, and innovations that define modern management, and how can organizations effectively implement these strategies to thrive in the rapidly changing business landscape?." The research contributes to a comprehensive understanding of modern management by examining its historical context, the impact of digital technologies, the importance of contemporary leadership styles, and the role of CSR and CDR in today's business landscape.

Keywords: modern management, digital technology, leadership styles, adaptability, innovation, corporate social responsibility, organizational success, corporate digital responsibility

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Authors: Paul Koffitse Agobia

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In 2020 the Ministry of Education in Ghana and the National Council for Curriculum and Assessment (NaCCA) rolled out a new curriculum, Common Core Programme (CCP) for Basic 7 to 10, that lays emphasis on character building and values which are important to the Ghanaian society by providing education that will produce character–minded learners, with problem solving skills, who can play active roles in dealing with the increasing challenges facing Ghana and the global society. Therefore, learning and teaching approaches that prioritise the use of digital learning resources and active learning are recommended. The new challenge facing Ghanaian teachers is the ability to use new technologies together with the appropriate content pedagogical knowledge to help learners develop, aside the communication skills in French, the essential 21st century skills as recommended in the new curriculum. This article focusses on the pedagogical approaches that are recommended by NaCCA. The study seeks to examine French language teachers’ understanding of the recommended pedagogical approaches and how they use digital learning resources in class to foster the development of these essential skills and values. 54 respondents, comprised 30 teachers and 24 head teachers, were selected in 6 Junior High schools in rural districts (both private and public) and 6 from Junior High schools in an urban setting. The schools were selected in three regions: Volta, Central and Western regions. A class observation checklist and an interview guide were used to collect data for the study. The study reveals that some teachers adopt teaching techniques that do not promote active learning. They demonstrate little understanding of the core competences and values, therefore, fail to integrate them in their lessons. However, some other teachers, despite their lack of understanding of learning and teaching philosophies, adopted techniques that can help learners develop some of the core competences and values. In most schools, digital learning resources are not utilized, though teachers have smartphones or laptops.

Keywords: active learning, core competences, digital learning resources, pedagogical approach, values.

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Om Viroje

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Quantum machine learning represents a frontier in computational technology, promising significant advancements in data processing capabilities. This study explores the significance of data encoding techniques, specifically amplitude and phase encoding, in this emerging field. By employing a comparative analysis methodology, the research evaluates how these encoding techniques affect the accuracy, efficiency, and noise resilience of quantum algorithms. Our findings reveal that amplitude encoding enhances algorithmic accuracy and noise tolerance, whereas phase encoding significantly boosts computational efficiency. These insights are crucial for developing robust quantum frameworks that can be effectively applied in real-world scenarios. In conclusion, optimizing encoding strategies is essential for advancing quantum machine learning, potentially transforming various industries through improved data processing and analysis.

Keywords: quantum machine learning, data encoding, amplitude encoding, phase encoding, noise resilience

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Authors: Yi-Cheng Tian, Miin-Shen Yang

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The mixture likelihood approach to clustering is a popular clustering method where the expectation and maximization (EM) algorithm is the most used mixture likelihood method. In the literature, the EM algorithm had been used for mixture regression models. However, these EM mixture regression algorithms are sensitive to initial values with a priori number of clusters. In this paper, to resolve these drawbacks, we construct a learning-based schema for the EM mixture regression algorithm such that it is free of initializations and can automatically obtain an approximately optimal number of clusters. Some numerical examples and comparisons demonstrate the superiority and usefulness of the proposed learning-based EM mixture regression algorithm.

Keywords: clustering, EM algorithm, Gaussian mixture model, mixture regression model

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Authors: Ali Montazar

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California and the Colorado River Basin are facing increasing uncertainty concerning water supplies. The Colorado River is the main source of irrigation water in the low desert of California. Currently, due to an increasing water-use competition and long-term drought at the Colorado River Basin, efficient use of irrigation water is one of the highest conservation priorities in the region. This study aims to present some of current irrigation technologies and management approaches in the low desert and assess the viability and potential of these water management practices. The results of several field experiments are used to assess five water conservation practices of sub-surface drip irrigation, automated surface irrigation, sprinkler irrigation, tail-water recovery system, and deficit irrigation strategy. The preliminary results of several ongoing studies at commercial fields are presented, particularly researches in alfalfa, sugar beets, kliengrass, sunflower, and spinach fields. The findings indicate that all these practices have significant potential to conserve water (an average of 1 ac-ft/ac) and enhance the efficiency of water use (15-25%). Further work is needed to better understand the feasibility of each of these applications and to help maintain profitable and sustainable agricultural production system in the low desert as water and labor costs, and environmental issues increase.

Keywords: automated surface irrigation, deficit irrigation, low desert of California, sprinkler irrigation, sub-surface drip irrigation, tail-water recovery system

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Authors: Nurazean Maarop, Noorjan Mohd Mustapha, Rasimah Yusoff, Roslina Ibrahim, Norziha Megat Mohd Zainuddin

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The goal of this study is to identify success factors that could influence the ISMS self-implementation in government sector from qualitative perspective. This study is based on a case study in one of the Malaysian government agency. Semi-structured interviews involving five key informants were conducted to examine factors addressed in the conceptual framework. Subsequently, thematic analysis was executed to describe the influence of each factor on the success implementation of ISMS. The result of this study indicates that management commitment, implementer commitment and implementer competency are part of the success factors for ISMS self-implementation in Malaysian Government Sector.

Keywords: ISMS success factors, IT project management, IS success, information security

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Authors: Polycarpe Feussi

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Globalization, technological and customer increasing changes, amongst other drivers, result in higher levels of uncertainty and unpredictability for organizations. In order for organizations to cope with the uncertain and fast-changing economic and business environment, these organizations need to innovate in order to achieve flexibility. In simple terms, the organizations must develop strategies leading to the ability of these organizations to provide horizontal information connections across the supply chain to create and deliver products that meet customer needs by synchronization of customer demands with product creation. The generated information will create efficiency and effectiveness throughout the whole supply chain regarding production, storage, and distribution, as well as eliminating redundant activities and reduction in response time. In an integrated supply chain, spanning activities include coordination with distributors and suppliers. This paper explains how through postponement strategies, flexibility can be achieved in an organization. In order to achieve the above, a thorough literature review was conducted via the search of online websites that contains material from scientific journal data-bases, articles, and textbooks on the subject of postponement and flexibility. The findings of the research are found in the last part of the paper. The first part introduces the concept of postponement and its importance in supply chain management. The second part of the paper provides the methodology used in the process of writing the paper.

Keywords: postponement strategies, supply chain management, flexibility, logistics

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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Authors: Francisco M. Silva

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Technology is evolving, creating an impact on our everyday lives and the telehealth industry. Telehealth encapsulates the provision of healthcare services and information via a technological approach. There are several benefits of using web-based methods to provide healthcare help. Nonetheless, few health and psychological help approaches combine this method with wearable sensors. This paper aims to create an online platform for users to receive self-care help and information using wearable sensors. In addition, researchers developing a similar project obtain a solid foundation as a reference. This study provides descriptions and analyses of the software and hardware architecture. Exhibits and explains a heart rate dynamic and efficient algorithm that continuously calculates the desired sensors' values. Presents diagrams that illustrate the website deployment process and the webserver means of handling the sensors' data. The goal is to create a working project using Arduino compatible hardware. Heart rate sensors send their data values to an online platform. A microcontroller board uses an algorithm to calculate the sensor heart rate values and outputs it to a web server. The platform visualizes the sensor's data, summarizes it in a report, and creates alerts for the user. Results showed a solid project structure and communication from the hardware and software. The web server displays the conveyed heart rate sensor's data on the online platform, presenting observations and evaluations.

Keywords: Arduino, heart rate BPM, microcontroller board, telehealth, wearable sensors, web-based healthcare

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Authors: Peyman Sindareh Esfahani, Jeffery Kurt Pieper

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In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l₂-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem.

Keywords: linear fractional transformation, linear matrix inequality, robust model predictive control, state feedback control

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Authors: Ferhat Demir

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Even if strategic management is highly critical for all types of organizations, only a few maturity models have been proposed in business literature for the area of strategic management activities. This paper updates previous studies and presents a new conceptual model for assessing the maturity of strategic management in any organization. Strategic management maturity model (S-3M) is basically composed of 6 maturity levels with 7 dimensions. The biggest contribution of S-3M is to put innovation into agenda of strategic management. The main objective of this study is to propose a model to align innovation with business strategies. This paper suggests that innovation (breakthrough new products/services and business models) is the only way of creating sustainable growth and strategy studies cannot ignore this aspect. Maturity models should embrace innovation to respond dynamic business environment and rapidly changing customer behaviours.

Keywords: strategic management, innovation, business model, maturity model

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Authors: Y. T. Gee, I. N. Umar

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Students’ achievement and motivation in learning English in Malaysia is a worrying trend as it is lagging behind several other countries in Asia. Thus, necessary actions have to be taken by the parties concerned to overcome this problem. The purpose of this research was to study the effects of drill and practice courseware on students’ achievement and motivation in learning English language. A multimedia courseware was developed for this purpose. The independent variable was the drill and practice courseware while the dependent variables were the students’ achievement and motivation. Their achievement was measured using pre-test and post-test scores, while motivation was measured using a questionnaire adapted from Keller’s (1979) Instructional Materials Motivation Scale. A total of 60 students from three vernacular primary schools in a northern state in Malaysia were randomly selected in this study. The findings indicate: (1) a significant difference between the students’ pre-test and post-test scores after using the courseware, (2) no significant difference in the achievement score between male and female students after using the courseware, (3) a significant difference in motivation score between the female and the male students, and (4) while the female students scored significantly higher than the male students in the aspects of relevance, confidence and satisfaction, no significant difference in terms of attention was observed between them. Overall, the findings clearly indicate that although the female students are significantly more motivated than their male students, they are equally good in terms of achievement after learning from the courseware. Through this study, the drill and practice courseware is proven to influence the students’ learning and motivation.

Keywords: courseware, drill and practice, English learning, motivation

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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Authors: Silvia Hvozdíková, Eva Stranovská

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The purpose of the article is to discuss the results of the research conducted during the period of two semesters paying attention to selected factors of foreign language reading comprehension through the means of Linguistic Intervention Program. The Linguistic Intervention Program was designed for the purpose of the current research. It refers to such method of foreign language teaching which emphasized active social learning, creative drama strategies, self-directed learning. The research sample consisted of 360 respondents, foreign language learners ranging from 13 – 17 years of age. Specifically designed questionnaire and a standardized foreign language reading comprehension tests were applied to serve the purpose. The outcomes of the research recorded significant results towards significant relationship between selected elements of the Linguistic Intervention Program and the academic achievements in the factors of reading comprehension.

Keywords: foreign language learning, linguistic intervention program, reading comprehension, social learning

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Authors: Reyhaneh Saeedi

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Iran is one of the regions which are most prone for earthquakes annually having a large number of financial and mortality and financial losses. Every year around the world, a large number of people lose their home and life due to natural disasters such as earthquakes. It is necessary to provide and specify some suitable places for settling the homeless people before the occurrence of the earthquake, one of the most important factors in crisis planning and management. Some of the natural disasters can be Modeling and shown by Geospatial Information System (GIS). By using GIS, it would be possible to manage the spatial data and reach several goals by making use of the analyses existing in it. GIS has a determining role in disaster management because it can determine the best places for temporary resettling after such a disaster. In this research QuantumGIS software is used that It is an OpenSource software so that easy to access codes and It is also free. In this system, AHP method is used as decision model and to locate the best places for temporary resettling, is done based on the related organizations criteria with their weights and buffers. Also in this research are made the buffer layers of criteria and change them to the raster layers. Later on, the raster layers are multiplied on desired weights then, the results are added together. Eventually, there are suitable places for resettling of victims by desired criteria by different colors with their optimum rate in QuantumGIS platform.

Keywords: disaster management, temporary resettlement, earthquake, QuantumGIS

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Authors: Siti Anis Nadia Abu Bakar, Vani Tanggamani

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Over recent years, the quality and environmental management practices are the necessary tasks in hospitality industry in order to provide high quality services, a comfortable and safe environment for occupants as well as innovative nature and shareholders' satisfaction, its environmental and social added value sustainable. Numerous studies have observed and measured quality management program (QMProg) and environmental management practices (EMPrac) independently. This paper analyzed the level of QMProg, and EMPrac in hospitality industry, particularly on hotel performance, specifically in the context of Malaysia as hotel industry in Malaysia has contributed tremendously to the development in the Malaysia tourism industry.The research objectives are; (1) to analyze how the level of QMProg influences on firm performance; (2) to investigate the level of EMPrac and its influence on firm performance. This paper contributes to the literature by providing added-value to the service industry strategic decision-making processes by helping to predict the varying impacts of positive and negative corporate social responsibility (CSR) activities on financial performance in their respective industries. Further, this paper also contributes to develop more applicable CSR strategies. As a matter of fact, the findings of this paper has contributed towards an integrated management system that will assist a firm in implementation of their environmental strategy by creating a higher level of accountability for environmental performance. The best results in environmental systems have instigated managers to explore more options when dealing with problems, especially problems involving the reputation of their hotel. In conclusion, the results of the study infer that the best CSR strategies of the quality and environmental management practices influences hotel performance.

Keywords: corporate social responsibility (CSR), environmental management practices (EMPrac), performance (PERF), quality management program (QMProg)

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Authors: Vishnu Pratap Singh Kirar

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Artificial Neural Network (ANN) can be trained using backpropagation (BP). It is the most widely used algorithm for supervised learning with multi-layered feed-forward networks. Efficient learning by the BP algorithm is required for many practical applications. The BP algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a two-term algorithm consisting of a learning rate (LR) and a momentum factor (MF). The major drawbacks of the two-term BP learning algorithm are the problems of local minima and slow convergence speeds, which limit the scope for real-time applications. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and criteria for evaluating convergence are required to facilitate the application of the three terms BP algorithm. Although these two seem to be closely related, as described later, we summarize various improvements to overcome the drawbacks. Here we compare the different methods of convergence of the new three-term BP algorithm.

Keywords: neural network, backpropagation, local minima, fast convergence rate

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Authors: Yoones Tavoosy

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This present study concentrates on the organizational implication the Iranian students with learning difficulties (LD) experience when they write an English essay. Particularly, the present study aims at exploring students' structural problems in EFL essay writing. A mixed method research design was employed including a questionnaire and a semi-structured in-depth interview. Technical Data Analysis of findings exposed that students experience a number of difficulties in the structure of EFL essay writing. Discussion and implications of these findings are presented respectively.

Keywords: Iranian students, learning difficulties, organizational implication, writing

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Authors: Bruna Azzari Puga, Richard Roe, Andre Pagani de Souza

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abstract outlines a proposed study to examine how and to what extent interactive, experiential, learner centered methodology develops learning of basic civic and democratic competencies among young children. It stems from the Literacy and Law course taught at Georgetown University Law Center in Washington, DC, since 1998. Law students, trained in best literacy practices and legal cases affecting literacy development, read “law related” children’s books and engage in interactive and extension activities with emerging readers. The law students write a monthly journal describing their experiences and a final paper: a conventional paper or a children’s book illuminating some aspect of literacy and law. This proposal is based on the recent adaptation of Literacy and Law to Brazil at Mackenzie Presbyterian University in São Paulo in three forms: first, a course similar to the US model, often conducted jointly online with Brazilian and US law students; second, a similar course that combines readings of children’s literature with activity based learning, with law students from a satellite Mackenzie campus, for young children from a vulnerable community near the city; and third, a course taught by law students at the main Mackenzie campus for 4th grade students at the Mackenzie elementary school, that is wholly activity and discourse based. The workings and outcomes of these courses are well documented by photographs, reports, lesson plans, and law student journals. The authors, faculty who teach the above courses at Mackenzie and Georgetown, observe that literacy, broadly defined as cognitive and expressive development through reading and discourse-based activities, can be influential in developing democratic civic skills, identifiable by explicit civic competencies. For example, children experience justice in the classroom through cooperation, creativity, diversity, fairness, systemic thinking, and appreciation for rules and their purposes. Moreover, the learning of civic skills as well as the literacy skills is enhanced through interactive, learner centered practices in which the learners experience literacy and civic development. This study will develop rubrics for individual and classroom teaching and supervision by examining 1) the children’s books and students diaries of participating law students and 2) the collection of photos and videos of classroom activities, and 3) faculty and supervisor observations and reports. These rubrics, and the lesson plans and activities which are employed to advance the higher levels of performance outcomes, will be useful in training and supervision and in further replication and promotion of this form of teaching and learning. Examples of outcomes include helping, cooperating and participating; appreciation of viewpoint diversity; knowledge and utilization of democratic processes, including due process, advocacy, individual and shared decision making, consensus building, and voting; establishing and valuing appropriate rules and a reasoned approach to conflict resolution. In conclusion, further development and replication of the learner centered literacy and law practices outlined here can lead to improved qualities of democratic teaching and learning supporting mutual respect, positivity, deep learning, and the common good – foundation qualities of a sustainable world.

Keywords: democracy, law, learner-centered, literacy

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Authors: Melvin Chan, Chew Lee Teo

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There has been a growing emphasis in elevating the teachers’ proficiency and competencies through continuing professional development (CPD) opportunities. In this era of a Volatile, Uncertain, Complex, Ambiguous (VUCA) world, teachers are expected to be collaborative designers, critical thinkers and creative builders. However, many of the CPD structures are still revolving in the model of transmission, which stands in contradiction to the cultivation of future-ready teachers for the innovative world of emerging technologies. This article puts forward the framing of CPD through a Principle-Based, Technological-Driven Knowledge Building Approach grounded in the essence of andragogy and progressive learning theories where growth is best exemplified through an authentic immersion in a social/community experience-based setting. Putting this Knowledge Building Professional Development Model (KBPDM) in operation via a Professional Learning Team (PLT) situated in a Secondary School in Singapore, research findings reveal that the intervention has led to a fundamental change in the learning paradigm of the teachers, henceforth equipping and empowering them successfully in their pedagogical design and practices for a 21^st century classroom experience. This article concludes with the possibility in leveraging the Learning Analytics to deepen the CPD experiences for educators.

Keywords: continual professional development, knowledge building, learning paradigm, principle-based

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Authors: Donald C. Lantu, Henndy Ginting, M. Yorga Permana, Dany M. A. Ramdlany

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We constructed a training program for top-talents of a Bank with Scharmer Theory-U as the model. In this training program, we implemented the action learning perspective, as it is claimed to be the most effective one currently available. In the process, participants were encouraged to be more involved, especially compared to traditional lecturing. The goal of this study is to assess the effectiveness of this particular training. The program consists of six days non-residential workshop within two months. Between each workshop, the participants were involved in the works of action learning group. They were challenged by dealing with the real problem related to their tasks at work. The participants of the program were 30 best talents who were chosen according to their yearly performance. Using paired difference statistical test in the behavioral assessment, we found that the training was not effective to increase participants’ leadership competencies. For the future development program, we suggested to modify the goals of the program toward the next stage of development.

Keywords: action learning, behavior, leadership development, Theory-U

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Authors: A. Ishag, E. Witruk, C. Altmayer

Abstract:

Motivation and attitudes are considered as hypothetical psychological constructs in explaining the process of second language learning. Gardner (1985) – who first systematically investigated the motivational factors in second language acquisition – found that L2 achievement is related not only to the individual learner’s linguistic aptitude or general intelligence but also to the learner’s motivation and interest in learning the target language. Traditionally language learning motivation can be divided into two types: integrative motivation – the desire to integrate oneself with the target culture; and instrumental motivation – the desire to learn a language in order to meet a specific language requirement such as for employment. One of the Gardner’s main ideas is that the integrative motivation plays an important role in second language acquisition. It is directly and positively related to second language achievement more than instrumental motivation. However, the significance of integrative motivation reflects a rather controversial set of findings. On the other hand, Students’ attitudes towards the target language, its speakers and the learning context may all play some part in explaining their success in learning a language. Accordingly, the present study aims at exploring the significance of motivational and attitudinal factors in learning foreign languages, namely English and German among Sudanese undergraduate students from a psycholinguistic and interdisciplinary perspective. The sample composed of 221 students from the English and German language departments respectively at the University of Khartoum in Sudan. The results indicate that English language’s learners are instrumentally motivated and that German language’s learners have positive attitudes towards the German language community and culture. Furthermore, there are statistical significant differences in the attitudes toward the two languages due to gender; where female students have more positive attitudes than their male counterparts. However, there are no differences along the variables of academic grade and study level. Finally, the reasons of studying the English or German language have also been indicated.

Keywords: motivation and attitudes, foreign language learning, english language, german language

Procedia PDF Downloads 683