Search results for: learning management

Authors: Recep Yücel, Cihat Kartal, Mustafa Kara

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On the basis of strategic management, it is believed in the necessity of a number of innovations in the postmodern management approach in the management of universities in our country. In this sense, some of these requirements are the integration of public and private universities, international integration, R & D status and increasing young population will create a dynamic structure. According to the postmodern management approach, universities, in our country despite being governed by the classical approach autonomous universities; academically are thought solid, to be non-hierarchical and creative. In fact, studies that require a multidisciplinary academic environment, universities and there is a close cooperation between formal and non-formal sub-units. Moreover, terms of postmodern management approaches, the requirements specified in the direction of solving the problem of an increasing number of universities in our country is considered to be more difficult. Therefore, considering the psychological impact on the academic personnel the university organizational structure, the study are trying to aim to propose an appropriate model of university organization. In this context, the study sought to answer the question how to have an impact innovation and international integration on the academic achievement of the classical organizational structure. Finally, in the study, due to the adoption of the classical organizational structure of the university, integration is considered to be difficult, academic cooperation between universities at the international level and maintaining it. In addition, it was understood that block the efforts of this organization structure, academic motivation, development and innovation. In this study under these purposes; on the basis of the existing organization and management structure of the universities in the Marmara Region in Turkey, a study was conducted with qualitative research methods. The data have been analyzed using content analysis and assessment was based on the results obtained.

Keywords: university, strategic management, postmodern management approaches, multidisciplinary studies

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Authors: Arzu Firlarer, Duygu Gocmen, Gokhan Uysal

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There is currently a growing trend among universities towards blended learning. Blended learning is becoming increasingly important in higher education, with the aims of better accomplishing course learning objectives, meeting students’ changing needs and promoting effective learning both in a theoretical and practical dimension like interior architecture discipline. However, the practical dimension of the discipline cannot be supported in the university environment. During the undergraduate program, the practical training which is tried to be supported by two different internship programs cannot fully meet the requirements of the blended learning. The lack of education program frequently expressed by our graduates and employers is revealed in the practical knowledge and skills dimension of the profession. After a series of meetings for curriculum studies, interviews with the chambers of profession, meetings with interior architects, a gap between the theoretical and practical training modules is seen as a problem in all interior architecture departments. It is thought that this gap can be solved by a new education model which is formed by the cooperation of University-Industry in the concept of blended learning. In this context, it is considered that theoretical and applied knowledge accumulation can be provided by the creation of industry-supported educational environments at the university. In the application process of the Interior Architecture discipline, the use of materials and technical competence will only be possible with the cooperation of industry and participation of students in the production/manufacture processes as observers and practitioners. Wood manufacturing is an important part of interior architecture applications. Wood productions is a sustainable structural process where production details, material knowledge, and process details can be observed in the most effective way. From this point of view, after theoretical training about wooden materials, wood applications and production processes are given to the students, practical training for production/manufacture planning is supported by active participation and observation in the processes. With this blended model, we aimed to develop a training model in which theoretical and practical knowledge related to the production of wood works will be conveyed in a meaningful, lasting way by means of university-industry cooperation. The project is carried out in Ankara with Arcora Architecture and Furniture Company and Başkent University Department of Interior Design where university-industry cooperation is realized. Within the scope of the project, every week the video of that week’s lecture is recorded and prepared to be disseminated by digital medias such as Udemy. In this sense, the program is not only developed by the project participants, but also other institutions and people who are trained and practiced in the field of design. Both academicians from University and at least 15-year experienced craftsmen in the wood metal and dye sectors are preparing new training reference documents for interior architecture undergraduate programs. These reference documents will be a model for other Interior Architecture departments of the universities and will be used for creating an online education module.

Keywords: blended learning, interior design, sustainable training, effective learning.

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Carla Teixeira, Diana Azevedo, Jonatas Bessa, Maria Guilam

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The flipped classroom is a blended learning modality that combines face-to-face and virtual activities of self-learning, mediated by digital information and communication technologies, which reverses traditional teaching approaches and presents, as a presupposition, the previous study of contents by students. In the following face-to-face activities, the contents are discussed, producing active learning. This work aims to describe the systematization process of the use of flipped classrooms as a method to develop complementary national activities in PROFSAÚDE, a professional master's program in the area of public health, offered as a distance learning course, in the network, in Brazil. The complementary national activities were organized with the objective of strengthening and qualifying students´ learning process. The network gathers twenty-two public institutions of higher education in the country. Its national coordination conducted a survey to detect complementary educational needs, supposed to improve the formative process and align important content sums for the program nationally. The activities were organized both asynchronously, making study materials available in Google classrooms, and synchronously in a tele presential way, organized on virtual platforms to reach the largest number of students in the country. The asynchronous activities allowed each student to study at their own pace and the synchronous activities were intended for deepening and reflecting on the themes. The national team identified some professors' areas of expertise, who were contacted for the production of audiovisual content such as video classes and podcasts, guidance for supporting bibliographic materials and also to conduct synchronous activities together with the technical team. The contents posted in the virtual classroom were organized by modules and made available before the synchronous meeting; these modules, in turn, contain “pills of experience” that correspond to reports of teachers' experiences in relation to the different themes. In addition, activity was proposed, with questions aimed to expose doubts about the contents and a learning challenge, as a practical exercise. Synchronous activities are built with different invited teachers, based on the participants 'discussions, and are the forum where teachers can answer students' questions, providing feedback on the learning process. At the end of each complementary activity, an evaluation questionnaire is available. The responses analyses show that this institutional network experience, as pedagogical innovation, provides important tools to support teaching and research due to its potential in the participatory construction of learning, optimization of resources, the democratization of knowledge and sharing and strengthening of practical experiences on the network. One of its relevant aspects was the thematic diversity addressed through this method.

Keywords: active learning, flipped classroom, network education experience, pedagogic innovation

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Authors: Dauda Ibrahim Adagye

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Effective internal control system in the bursary unit of tertiary educational institutions is geared toward achieving quality teaching, learning, and research environment and as well assist the management of the institutions, particularly when decisions are to be made. While internal control system exists in all institutions, the outlined objectives above are far from being achieved. The paper; therefore, assesses the effectiveness of internal control system in tertiary educational institutions in Nasarawa State, Nigeria with the specific focus on the Nasarawa state Polytechnic, Lafia. The study is survey; hence, a simple closed-ended questionnaire was developed and administered to a sample of twenty-seven (27) member staff from the Bursary and the internal audit unit of the Nasarawa State Polytechnic, Lafia to obtain data for analysis purposes and to test the study hypothesis. Responses from the questionnaire were analyzed using a simple percentage and chi-square. Findings shows that the right people are not assigned to the right job in the department, budget, and management accounting were never used in the institution’s operations and checking of subordinate by their superior officers is not regular. This renders the current internal control structure of the Polytechnic as ineffective and weak. The paper therefore, recommends that: transparency should be seen as significant, as the institution work toward meeting its objectives, therefore, it means that the right staff is assigned to the right job and regular checking of the subordinates by their ensued superiors.

Keywords: internal control, tertiary educational intuitions, efficiency

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Authors: Kasun P. Wijayaratna, Lauren Gardner, Taha Hossein Rashidi

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Undergraduate students entering university across the last 2 to 3 years tend to be born during the middle years of the 1990s. This generation of students has been exposed to the internet and the desire and dependency on technology since childhood. Brains develop based on environmental influences and technology has wired this generation of student to be attuned to sophisticated complex visual imagery, indicating visual forms of learning may be more effective than the traditional lecture or discussion formats. Furthermore, post-millennials perspectives on career are not focused solely on stability and income but are strongly driven by interest, entrepreneurship and innovation. Accordingly, it is important for educators to acknowledge the generational shift and tailor the delivery of learning material to meet the expectations of the students and the needs of industry. In the context of transport engineering, effectively teaching undergraduate students the basic principles of transport planning, traffic engineering and highway design is fundamental to the progression of the profession from a practice and research perspective. Recent developments in technology have transformed the discipline as practitioners and researchers move away from the traditional “pen and paper” approach to methods involving the use of computer programs and simulation. Further, enhanced accessibility of technology for students has changed the way they understand and learn material being delivered at tertiary education institutions. As a consequence, blended learning approaches, which aim to integrate face to face teaching with flexible self-paced learning resources, have become prevalent to provide scalable education that satisfies the expectations of students. This research study involved the development of a series of ‘Blended Learning’ initiatives implemented within an introductory transport planning and geometric design course, CVEN2401: Sustainable Transport and Highway Engineering, taught at the University of New South Wales, Australia. CVEN2401 was modified by conducting interactive polling exercises during lectures, including weekly online quizzes, offering a series of supplementary learning videos, and implementing a realistic design project that students needed to complete using modelling software that is widely used in practice. These activities and resources were aimed to improve the learning environment for a large class size in excess of 450 students and to ensure that practical industry valued skills were introduced. The case study compared the 2016 and 2017 student cohorts based on their performance across assessment tasks as well as their reception to the material revealed through student feedback surveys. The initiatives were well received with a number of students commenting on the ability to complete self-paced learning and an appreciation of the exposure to a realistic design project. From an educator’s perspective, blending the course made it feasible to interact and engage with students. Personalised learning opportunities were made available whilst delivering a considerable volume of complex content essential for all undergraduate Civil and Environmental Engineering students. Overall, this case study highlights the value of blended learning initiatives, especially in the context of large class size university courses.

Keywords: blended learning, highway design, teaching, transport planning

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Authors: Ebrahim Mansoori, Datin Joriah Muhammad

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Recent studies in finance have focused on the effect of external variables on working capital management. This study investigates the effect of corruption indexes on firms' working capital management. A large data set that covers data from 2005 to 2013 from five ASEAN countries, namely, Malaysia, Indonesia, Singapore, Thailand, and the Philippines, was selected to investigate how the level of corruption in these countries affect working capital management. The results of panel data analysis include fixed effect estimations showed that a high level of countries' corruption indexes encourages managers to shorten the CCC length. Meanwhile, the managers reduce the level of investment in cash and cash equivalents when the levels of corruption indexes increase. Therefore, increasing the level of countries' corruption indexes encourages managers to select conservative working capital strategies by reducing the level of NLB.

Keywords: ASEAN, corruption indexes, panel data analysis, working capital management

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Authors: Rodrique Watong Tchounkeu

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This paper investigated the implementation and impact of inclusive education practices in early childhood settings (ages 3-6) with the overarching aim of fostering a diverse learning environment. The primary objectives were to assess the then-current state of inclusive practices, identify effective methodologies for accommodating diverse learning needs, and evaluate the outcomes of implementing inclusive education in early childhood settings. To achieve these objectives, a mixed-methods approach was employed, combining qualitative interviews with early childhood educators and parents, along with quantitative surveys distributed to a diverse sample of participants. The qualitative phase involved semi-structured interviews with 30 educators and 50 parents, selected through purposive sampling. The interviews aimed to gather insights into the challenges faced in implementing inclusive education, the strategies employed, and the perceived benefits and drawbacks. The quantitative phase included surveys administered to 300 early childhood educators across various settings, measuring their familiarity with inclusive practices, their perceived efficacy, and their willingness to adapt teaching methods. The results revealed a significant gap between the theoretical understanding and practical implementation of inclusive education in early childhood settings. While educators demonstrated a high level of theoretical knowledge, they faced challenges in effectively translating these concepts into practice. Parental perspectives highlighted the importance of collaboration between educators and parents in supporting inclusive education. The surveys indicated a positive correlation between educators' familiarity with inclusive practices and their willingness to adapt teaching methods, emphasizing the need for targeted professional development. The implications of this study suggested the necessity for comprehensive training programs for early childhood educators focused on the practical implementation of inclusive education strategies. Additionally, fostering stronger partnerships between educators and parents was crucial for creating a supportive learning environment for all children. By addressing these findings, this research contributed to the advancement of inclusive education practices in early childhood settings, ultimately leading to more inclusive and effective learning environments for diverse groups of young learners.

Keywords: inclusive education, early childhood settings, diverse learning, young learners, practical implementation, parental collaboration

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Authors: Agah Tuğrul Korucu, Handan Atun

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Diversity and usefulness of information that used in education are have increased due to development of technology. Web technologies have made enormous contributions to the distance learning system especially. Mobile systems, one of the most widely used technology in distance education, made much easier to access web technologies. Not bounding by space and time, individuals have had the opportunity to access the information on web. In addition to this, the storage of educational information and resources and accessing these information and resources is crucial for both students and teachers. Because of this importance, development and dissemination of web technologies supply ease of access to information and resources are provided by web technologies. Dynamic web technologies introduced as new technologies that enable sharing and reuse of information, resource or applications via the Internet and bring websites into expandable platforms are commonly known as Web 2.0 technologies. Cloud systems are one of the dynamic web technologies that defined as a model provides approaching the demanded information independent from time and space in appropriate circumstances and developed by NIST. One of the most important advantages of cloud systems is meeting the requirements of users directly on the web regardless of hardware, software, and dealing with install. Hence, this study aims at using cloud services in education and investigating the services provided by the cloud computing. Survey method has been used as research method. In the findings of this research the fact that cloud systems are used such studies as resource sharing, collaborative work, assignment submission and feedback, developing project in the field of education, and also, it is revealed that cloud systems have plenty of significant advantages in terms of facilitating teaching activities and the interaction between teacher, student and environment.

Keywords: cloud systems, cloud systems in education, online learning environment, integration of information technologies, e-learning, distance learning

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Authors: Odd Ivar Haugen

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This paper explores the relationship between assurance, risk, and risk management in the context of complex safety-related systems. It introduces a nuanced understanding of assurance and argues that the foundation for grounds for justified confidence in claims made about a complex system is related to the system behaviour. It emphasises the importance of knowledge as the cornerstone of assurance. The paper addresses the challenges of epistemic and aleatory uncertainties inherent in safety-critical systems. A systems approach is proposed to model emergent properties and complexity using the composition, environment, structure, mechanisms (CESM) metamodel, offering a structured framework for analysing system behaviour. The interplay between assurance and risk management is conceptualised through two models: the domain model and the control model. Assurance and risk management are mutually dependent on each other to reduce uncertainty and control risk levels. This work highlights the dual roles of assurance in risk management, acting as an epistemic actuator on the one side and providing feedback about the strength of the justification on the other. Assurance and risk management have inseparable roles in ensuring safety in complex systems.

Keywords: assurance, CESM metamodel, confidence, emergent properties, knowledge, objectivity, risk, system behaviour, system safety

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Authors: Michael Karnes, Alper Yilmaz

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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

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Authors: Michael Lousis

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The systematic identification of the most conspicuous and significant errors made by learners during three-years of testing of their progress in learning Arithmetic are presented in this article. How these errors have changed over three-years of school instruction of Arithmetic also is shown. The sample is comprised of two hundred (200) English students and one hundred and fifty (150) Greek students. These students were purposefully selected according to their participation in each testing session in the development of the three-year Kassel Project in England and Greece, in both domains simultaneously in Arithmetic and Algebra. The data sample includes six test-scripts corresponding to three testing sessions in both Arithmetic and Algebra respectively.

Keywords: arithmetic, errors, Kassel Project, progress of learning

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Authors: Milad Abbasi

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Carbon fiber-reinforced polymer (CFRP) composite structures are increasingly being utilized in the automotive industry due to their lightweight and specific energy absorption capabilities. Although it is impossible to predict composite mechanical properties directly using theoretical methods, various research has been conducted so far in the literature for accurate simulation of CFRP structures' energy-absorbing behavior. In this research, axial compression experiments were carried out on hand lay-up unidirectional CFRP composite tubes. The fabrication method allowed the authors to extract the material properties of the CFRPs using ASTM D3039, D3410, and D3518 standards. A neural network machine learning algorithm was then utilized to build a robust prediction model to forecast the axial compressive properties of CFRP tubes while reducing high-cost experimental efforts. The predicted results have been compared with the experimental outcomes in terms of load-carrying capacity and energy absorption capability. The results showed high accuracy and precision in the prediction of the energy-absorption capacity of the CFRP tubes. This research also demonstrates the effectiveness and challenges of machine learning techniques in the robust simulation of composites' energy-absorption behavior. Interestingly, the proposed method considerably condensed numerical and experimental efforts in the simulation and calibration of CFRP composite tubes subjected to compressive loading.

Keywords: CFRP composite tubes, energy absorption, crushing behavior, machine learning, neural network

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Authors: Sukanya Sripho

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The purpose of this research was to study the role of local administration management to promote culture based on philosophy of sufficiency economy to many communities in Thailand. The philosophy was given to the Thai people by their King and become one of the important policies from the Thai government. A total of 375 local people in main district, Amnadcharoen province were selected by random sampling. A questionnaire was used as the tool for collecting data. Descriptive statistics in this research included percentage, mean, and multiple regression analysis. The findings revealed that the role of facilitator was utilized the most from the management in order to promote culture based on philosophy of sufficiency economy to many communities in Thailand.

Keywords: administration, management, philosophy of sufficiency economy, facilitator

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Authors: Mary Jane B. Suarez

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Public speaking anxiety (PSA), also known as speech anxiety, is innumerably persistent in any traditional communication classes, especially for students who learn English as a second language. The speech anxiety intensifies when communication skills assessments have taken their toll in an online or a remote mode of learning due to the perils of the COVID-19 virus. Both teachers and students have experienced vast ambiguity on how to realize a still effective way to teach and learn speaking skills amidst the pandemic. Communication skills assessments like public speaking, oral presentations, and student reporting have defined their new meaning using Google Meet, Zoom, and other online platforms. Though using such technologies has paved for more creative ways for students to acquire and develop communication skills, the effectiveness of using such assessment tools stands in question. This mixed method study aimed to determine the factors that affected the public speaking skills of students in a communication class, to probe on the assessment gaps in assessing speaking skills of students attending online classes vis-à-vis the implementation of remote and blended modalities of learning, and to recommend ways on how to address the public speaking anxieties of students in performing a speaking task online and to bridge the assessment gaps based on the outcome of the study in order to achieve a smooth segue from online to on-ground instructions maneuvering towards a much better post-pandemic academic milieu. Using a convergent parallel design, both quantitative and qualitative data were reconciled by probing on the public speaking anxiety of students and the potential assessment gaps encountered in an online English communication class under remote and blended learning. There were four phases in applying the convergent parallel design. The first phase was the data collection, where both quantitative and qualitative data were collected using document reviews and focus group discussions. The second phase was data analysis, where quantitative data was treated using statistical testing, particularly frequency, percentage, and mean by using Microsoft Excel application and IBM Statistical Package for Social Sciences (SPSS) version 19, and qualitative data was examined using thematic analysis. The third phase was the merging of data analysis results to amalgamate varying comparisons between desired learning competencies versus the actual learning competencies of students. Finally, the fourth phase was the interpretation of merged data that led to the findings that there was a significantly high percentage of students' public speaking anxiety whenever students would deliver speaking tasks online. There were also assessment gaps identified by comparing the desired learning competencies of the formative and alternative assessments implemented and the actual speaking performances of students that showed evidence that public speaking anxiety of students was not properly identified and processed.

Keywords: blended learning, communication skills assessment, public speaking anxiety, speech anxiety

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Authors: Anne Öman

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Today in Sweden and in other countries, a variety of digital artefacts, such as laptops, tablets, interactive whiteboards, are being used at all school levels. From an educational perspective, digital artefacts challenge traditional teaching because they provide a range of modes for expression and communication and are not limited to the traditional medium of paper. Digital technologies offer new opportunities for representations and physical interactions with objects, which put forward the role of the body in interaction and learning. From a multimodal perspective the emphasis is on the use of multiple semiotic resources for meaning- making and the study presented here has examined the differential use of semiotic resources by pupils interacting in a digitally designed task in a primary school context. The instances analyzed in this paper come from a case study where the learning task was to create an advertising film in a film-software. The study in focus involves the analysis of a single case with the emphasis on the examination of the classroom setting. The research design used in this paper was based on a micro ethnographic perspective and the empirical material was collected through video recordings of small-group work in order to explore pupils’ communication within the group activity. The designed task described here allowed students to build, share, collaborate upon and publish the redesigned products. The analysis illustrates the variety of communicative modes such as body position, gestures, visualizations, speech and the interaction between these modes and the representations made by the pupils. The findings pointed out the importance of embodied communication during the small- group processes from a learning perspective as well as a pedagogical understanding of pupils’ representations, which were similar from a cultural literacy perspective. These findings open up for discussions with further implications for the school practice concerning the small- group processes as well as the redesigned products. Wider, the findings could point out how multimodal interactions shape the learning experience in the meaning-making processes taking into account that language in a globalized society is more than reading and writing skills.

Keywords: communicative learning, interactive learning environments, pedagogical issues, primary school education

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Authors: Laurence C. Hanes, Robert J. Stone

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Video games have reached a point of huge commercial success as well as wide familiarity with audiences both young and old. Much attention and research have also been directed towards serious games and their potential learning affordances. It is little surprise that the field of virtual heritage has taken a keen interest in using serious games to present cultural heritage information to users, with applications ranging from museums and cultural heritage institutions, to academia and research, to schools and education. Many researchers have already documented their efforts to develop and distribute virtual heritage serious games. Although attempts have been made to create classifications of the different types of virtual heritage games (somewhat akin to the idea of game genres), no formal taxonomy has yet been produced to define the different types of cultural heritage and historical information that can be presented through these games at a content level, and how the information can be manifested within the game. This study proposes such a taxonomy. First the informational content is categorized as heritage or historical, then further divided into tangible, intangible, natural, and analytical. Next, the characteristics of the manifestation within the game are covered. The means of manifestation, level of demonstration, tone, and focus are all defined and explained. Finally, the potential learning outcomes of the content are discussed. A demonstration of the taxonomy is then given by describing the informational content and corresponding manifestations within several examples of virtual heritage serious games as well as commercial games. It is anticipated that this taxonomy will help designers of virtual heritage serious games to think about and clearly define the information they are presenting through their games, and how they are presenting it. Another result of the taxonomy is that it will enable us to frame cultural heritage and historical information presented in commercial games with a critical lens, especially where there may not be explicit learning objectives. Finally, the results will also enable us to identify shared informational content and learning objectives between any virtual heritage serious and/or commercial games.

Keywords: informational content, serious games, taxonomy, virtual heritage

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Authors: Joseph Wolff, Jeffrey Eilbott

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Autism Spectrum Disorders (ASD) are a spectrum of social disorders characterized by deficits in social communication, verbal ability, and interaction that can vary in severity. In recent years, researchers have used magnetic resonance imaging (MRI) to help detect how neural patterns in individuals with ASD differ from those of neurotypical (NT) controls for classification purposes. This study analyzed the classification of ASD within males and females using functional MRI data. Functional connectivity (FC) correlations among brain regions were used as feature inputs for machine learning algorithms. Analysis was performed on 558 cases from the Autism Brain Imaging Data Exchange (ABIDE) I dataset. When trained specifically on females, the algorithm underperformed in classifying the ASD subset of our testing population. Although the subject size was relatively smaller in the female group, the manual matching of both male and female training groups helps explain the algorithm’s bias, indicating the altered sex abnormalities in functional brain networks compared to typically developing peers. These results highlight the importance of taking sex into account when considering how generalizations of findings on males with ASD apply to females.

Keywords: autism spectrum disorder, machine learning, neuroimaging, sex differences

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Authors: Bilal Haider, Farhan Aadil

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A Vehicular Ad hoc Network (VANET) provides various services to end-users traveling on the road at high speeds. However, this high-speed mobility of mobile nodes can cause frequent service disruptions. Various mobility management protocols exist for managing node mobility, but due to their centralized nature, they tend to suffer in the VANET environment. In this research, we proposed a distributed mobility management protocol using software-defined networks (SDN) for VANETs. Instead of relying on a centralized mobility anchor, the mobility functionality is distributed at multiple infrastructural nodes. The protocol is based on the classical Proxy Mobile IP version 6 (PMIPv6). It is evident from simulation results that this work has improved the network performance with respect to nodes throughput, delay, and packet loss.

Keywords: SDN, VANET, mobility management, optimization

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Authors: David F. Nettleton, Christian Wasiak, Jonas Dorissen, David Gillen, Alexandr Tretyak, Elodie Bugnicourt, Alejandro Rosales

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In this work, preliminary results are given for the modeling and calibration of two inline processes, pultrusion, and laser ablation, using machine learning techniques. The end product of the processes is the core of a medical guidewire, manufactured to comply with a user specification of diameter and flexibility. An ensemble approach is followed which requires training several models. Two state of the art machine learning algorithms are benchmarked: Kernel Recursive Least Squares (KRLS) and Support Vector Regression (SVR). The final objective is to build a precise digital model of the pultrusion and laser ablation process in order to calibrate the resulting diameter and flexibility of a medical guidewire, which is the end product while taking into account the friction on the forming die. The result is an ensemble of models, whose output is within a strict required tolerance and which covers the required range of diameter and flexibility of the guidewire end product. The modeling and automatic calibration of complex in-line industrial processes is a key aspect of the Industry 4.0 movement for cyber-physical systems.

Keywords: calibration, data modeling, industrial processes, machine learning

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Authors: Siti Nurma Hanim Hadie, Asma’ Hassan, Zul Izhar Ismail, Ahmad Fuad Abdul Rahim, Mohd. Zarawi Mat Nor, Hairul Nizam Ismail

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Anatomy is a medical subject, which contributes to high cognitive load during learning. Despite its complexity, anatomy remains as the most important basic sciences subject with high clinical relevancy. Although anatomy knowledge is required for safe practice, many medical students graduated without having sufficient knowledge. In fact, anatomy knowledge among the medical graduates was reported to be declining and this had led to various medico-legal problems. Applying cognitive load theory (CLT) in anatomy teaching particularly lecture would be able to address this issue since anatomy information is often perceived as cognitively challenging material. CLT identifies three types of loads which are intrinsic, extraneous and germane loads, which combine to form the total cognitive load. CLT describe that learning can only occur when the total cognitive load does not exceed human working memory capacity. Hence, managing these three types of loads with the aim of optimizing the working memory capacity would be beneficial to the students in learning anatomy and retaining the knowledge for future application.

Keywords: cognitive load theory, intrinsic load, extraneous load, germane load

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Authors: Nattida Wannaruk, Wasawat Nakkiew

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This research aims to study the factors that affect the performance of green supply chain management in the Lampang ceramics industry. The data investigation of this research was questionnaires which were gathered from 20 factories in the Lampang ceramics industry. The research factors are divided into five major groups which are green design, green purchasing, green manufacturing, green logistics and reverse logistics. The questionnaire has consisted of four parts that related to factors green supply chain management and general information of the Lampang ceramics industry. Then, the data were analyzed using descriptive statistic and priority of each factor by using the analytic hierarchy process (AHP). The understanding of factors affecting the green supply chain management of Lampang ceramics industry was indicated in the summary result along with each factor weight. The result of this research could be contributed to the development of indicators or performance evaluation in the future.

Keywords: Lampang ceramics industry, green supply chain management, analysis hierarchy process (AHP), factors affecting

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Authors: Ahmad Tijani Surajudeen, Muhammad Zahiri Awang Mat, Aliy Abdulwahid Adebisi

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With arrival of Islam in the South-Western Nigeria in the late fifteenth and early sixteenth centuries, various masājid established in different parts of the area played vital roles towards the betterment and unity of the Muslims. However, despite the fact that the masājid in the South-Western part of Nigeria contributed immensely to the spiritual and educational enhancement of the Muslims, it has not fully captured the holistic educational roles as a unique model used by the Prophet (S.A.W). Therefore, the primary objective of this paper is to investigate and broaden the roles of masjid towards its compartmentalized and holistic contributions among the Muslims in the south-western Nigeria. The findings from the paper have identified five holistic roles of masjid, namely, spiritual, intellectual, physical, social and emotional contributions which have been exemplified in the prophetic model of masjid. The paper has argued that the five factors must be unreservedly unified towards the betterment of the Muslims and enhancement of Islamic education and Arabic Language in the South-Western Nigeria. However, the challenges of masjid management in the South-Western Nigeria are the main hindrance in achieving the holistic roles of masjid. It is thereby suggested that, the management of masjid should take the identified prophetic model of masjid into account in order to positively improve the affairs of Muslims as well as promoting the teaching and learning of Islamic education and Arabic language among the Muslims in the South-Western Nigeria.

Keywords: worship, Islamic education, Arabic language, prophetic holistic model

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Authors: Fatemeh Torabi, Jamal El-Den, Narumon Sriratanviriyakul

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Perpetual changes in the workplace and daily business activities bring a need for imbedding organizational knowledge sharing within the organizations’ culture, routines and processes. Organizations should adapt to the changing in the environment in order to survive. Accordingly, the management should promote a knowledge sharing culture which might result in knowledge accumulation, hence better response to these changing environmental conditions. Researchers in the field of strategy and marketing stressed that employees’, as well as the overall performance of the organization, would improve as a result of implementing a knowledge-oriented culture. The research investigated the significant impact of knowledge sharing on market response and the competitiveness of organizations. A knowledge sharing framework was developed based on current literary frameworks with additional constructs such as employees’ learning commitments, experiences and prior knowledge. Linear regression was used to analyze the relationships among dependent and independent variables. The research’s results indicated strong positive correlation between the dependent and independent variables, especially in organizational market sharing. We anticipate that this correlation would improve organizational knowledge sharing related practices and the associated knowledge entities. The research posits the introduced framework could be a solid ground for further investigations on how some organizational factors would influence the organization’s response to the market as well as on competitiveness. Final results support all hypotheses. Finding of this research show that knowledge sharing intention had the significant and positive effect on market response and competitiveness of organizations.

Keywords: knowledge management, knowledge sharing, market response, organizational competitiveness

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Authors: Suleman Bawa, Ayiku Emmanuel Lartey

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Purpose - This paper aims to examine the association between knowledge capital and multinational firms’ innovation management. We again explored the impact of transboundary investment and assimilative capacity between knowledge capital and multinational firms’ innovation management. The vital position of knowledge capital and multinational firms’ innovation management in today’s increasingly volatile environment coupled with fierce competition has been extensively acknowledged by academics and industry investment capitals. Design/methodology/approach - The theoretical association model and an empirical correlation analysis were constructed based on relevant research using data collected from 19 multinational firms in Ghana as the subject, and path analysis was constructed using SPSS 22.0 and AMOS 24.0 to test the formulated hypotheses. Findings - Varied conclusions are drawn consequential from theoretical inferences and empirical tests. For multinational firms, knowledge capital relics positively significant to multinational firms’ innovation management. Multinational firms with advanced knowledge capital likely spawn greater corporations’ innovation management. Second, transboundary investment efficiently intermediates the association between knowledge physical capital, knowledge interactive capital, and corporations’ innovation management. At the same time, this impact is insignificant between knowledge of empirical capital and corporations’ innovation management. Lastly, the impact of transboundary investment and assimilative capacity on the association between knowledge capital and corporations’ innovation management is established. We summarized the implications for managers based on our outcomes. Research limitations/implications - Multinational firms must dynamically build knowledge capital to augment corporations’ innovation management. Conversely, knowledge capital motivates multinational firms to implement transboundary investment and cultivate assimilative capacity. Accordingly, multinational firms can efficiently exploit diverse information to augment their corporate innovation management. Practical implications – This paper presents a comprehensive justification of knowledge capital and manufacturing firms’ innovation management by exploring the impact of transboundary investment and assimilative capacity within the manufacturing industry, its sequential progress, and its associated challenges. Originality/value – This paper is amongst the first to find empirical results to back knowledge capital and manufacturing firms’ innovation management by exploring the impact of transboundary investment and assimilative capacity within the manufacturing industry. Additionally, aligning knowledge as a coordinative instrument is a significant input to our discernment in this area.

Keywords: knowledge capital, transboundary investment, innovation management, assimilative capacity

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Authors: Burcu Oralhan, Zeki Oralhan, Nilsun Sariyer, Kumru Uyar

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Data mining has been becoming more and more important and a wide range of applications in recent years. Data mining is the process of find hidden and unknown patterns in big data. One of the applied fields of data mining is Customer Relationship Management. Understanding the relationships between products and customers is crucial for every business. Customer Relationship Management is an approach to focus on customer relationship development, retention and increase on customer satisfaction. In this study, we made an application of a data mining methods in telecommunication customer relationship management side. This study aims to determine the customers profile who likely to leave the system, develop marketing strategies, and customized campaigns for customers. Data are clustered by applying classification techniques for used to determine the churners. As a result of this study, we will obtain knowledge from international telecommunication industry. We will contribute to the understanding and development of this subject in Customer Relationship Management.

Keywords: customer churn analysis, customer relationship management, data mining, telecommunication industry

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Authors: Ebissa Gadissa Kedir

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This paper presents the potential groundwater assessment and sustainable management in the selected study area. It is the most preferred water source in all climatic zones for its convenient availability, drought dependability, excellent quality, and low development cost. The rural areas, which account for more than 85% of the country's population, are encountered a shortage of potable water supply which can be solved by proper groundwater utilization. For the present study area, the groundwater potential is assessed and analysed. Thus, the study area falls in four potential groundwater zones ranging from poor to high. However, the current groundwater management practices in the study area are poor. Despite the pervasive and devastating challenges, immediate and proper responses have not yet been given to the problem. Thus, such frustrating threats and challenges have initiated the researcher to work in the project area.

Keywords: GW potential, GW management, GW sustainability, South gonder, Ethiopia

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Authors: Lizette Grobler

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Although the notion of environmental citizenship has become an established concept linked to scholarship on sustainability internationally, it is not the case in South Africa. This literature review aims to investigate whether the concept is a viable construct in the South African household waste management context. This literature review firstly examines different approaches to environmental citizenship and the normative notions of environmental values, attitudes, and behaviour advocated by proponents of each tradition. Secondly, this paper deals with the application of environmental citizenship as a measure to address household waste. Thirdly, this paper interrogates the utilization of the concept in South African scholarly literature on waste management. The paper argues for the introduction of the concept as a potential approach to behavioural change in the household waste management context.

Keywords: environmental citizenship, environmental responsibility, household waste, ownership of waste

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Authors: Kritchakhris Na-Wattanaprasert

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The objective of this research is to design and develop a prototype of a key performance indicator system this is suitable for warehouse management in a case study and use requirement. In this study, we design a prototype of key performance indicator system (KPI) for warehouse case study of furniture business by methodology in step of identify scope of the research and study related papers, gather necessary data and users requirement, develop key performance indicator base on balance scorecard, design pro and database for key performance indicator, coding the program and set relationship of database and finally testing and debugging each module. This study use Balance Scorecard (BSC) for selecting and grouping key performance indicator. The system developed by using Microsoft SQL Server 2010 is used to create the system database. In regard to visual-programming language, Microsoft Visual C# 2010 is chosen as the graphic user interface development tool. This system consists of six main menus: menu login, menu main data, menu financial perspective, menu customer perspective, menu internal, and menu learning and growth perspective. Each menu consists of key performance indicator form. Each form contains a data import section, a data input section, a data searches – edit section, and a report section. The system generates outputs in 5 main reports, the KPI detail reports, KPI summary report, KPI graph report, benchmarking summary report and benchmarking graph report. The user will select the condition of the report and period time. As the system has been developed and tested, discovers that it is one of the ways to judging the extent to warehouse objectives had been achieved. Moreover, it encourages the warehouse functional proceed with more efficiency. In order to be useful propose for other industries, can adjust this system appropriately. To increase the usefulness of the key performance indicator system, the recommendations for further development are as follows: -The warehouse should review the target value and set the better suitable target periodically under the situation fluctuated in the future. -The warehouse should review the key performance indicators and set the better suitable key performance indicators periodically under the situation fluctuated in the future for increasing competitiveness and take advantage of new opportunities.

Keywords: key performance indicator, warehouse management, warehouse operation, logistics management

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Authors: Ting Gao, Mingyue He

Abstract:

Reconfigurable intelligent surfaces (RISs) are expected to be an important part of next-generation wireless communication networks due to their potential to reduce the hardware cost and energy consumption of millimeter Wave (mmWave) massive multiple-input multiple-output (MIMO) technology. However, owing to the lack of signal processing abilities of the RIS, the perfect channel state information (CSI) in RIS-assisted communication systems is difficult to acquire. In this paper, the uplink channel estimation for mmWave systems with a hybrid active/passive RIS architecture is studied. Specifically, a deep learning-based estimation scheme is proposed to estimate the channel between the RIS and the user. In particular, the sparse structure of the mmWave channel is exploited to formulate the channel estimation as a sparse reconstruction problem. To this end, the proposed approach is derived to obtain the distribution of non-zero entries in a sparse channel. After that, the channel is reconstructed by utilizing the least-squares (LS) algorithm and compressed sensing (CS) theory. The simulation results demonstrate that the proposed channel estimation scheme is superior to existing solutions even in low signal-to-noise ratio (SNR) environments.

Keywords: channel estimation, reconfigurable intelligent surface, wireless communication, deep learning

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