Search results for: repetitive learning method
22739 The Training Demands of Nursing Assistants on Urinary Incontinence in Nursing Homes: A Mixed Methods Study
Authors: Lulu Liao, Huijing Chen, Yinan Zhao, Hongting Ning, Hui Feng
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Urinary tract infection rate is an important index of care quality in nursing homes. The aim of the study is to understand the nursing assistant's current knowledge and attitudes of urinary incontinence and to explore related stakeholders' viewpoint about urinary incontinence training. This explanatory sequential study used Knowledge, Practice, and Attitude Model (KAP) and Adult Learning Theories, as the conceptual framework. The researchers collected data from 509 nursing assistants in sixteen nursing homes in Hunan province in China. The questionnaire survey was to assess the knowledge and attitude of urinary incontinence of nursing assistants. On the basis of quantitative research and combined with focus group, training demands were identified, which nurse managers should adopt to improve nursing assistants’ professional practice ability in urinary incontinence. Most nursing assistants held the poor knowledge (14.0 ± 4.18) but had positive attitudes (35.5 ± 3.19) toward urinary incontinence. There was a significant positive correlation between urinary incontinence knowledge and nursing assistants' year of work and educational level, urinary incontinence attitude, and education level (p < 0.001). Despite a general awareness of the importance of prevention of urinary tract infections, not all nurse managers fully valued the training in urinary incontinence compared with daily care training. And the nursing assistants required simple education resources to equip them with skills to address problem about urinary incontinence. The variety of learning methods also highlighted the need for educational materials, and nursing assistants had shown a strong interest in online learning. Related education material should be developed to meet the learning need of nurse assistants and provide suitable training method for planned quality improvement in urinary incontinence.Keywords: mixed methods, nursing assistants, nursing homes, urinary incontinence
Procedia PDF Downloads 13322738 Evaluation of the Efficiency of French Language Educational Software for Learners in Semnan Province, Iran
Authors: Alireza Hashemi
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In recent decades, language teaching methodology has undergone significant changes due to the advent of computers and the growth of educational software. French language education has also benefited from these developments, and various software has been produced to facilitate the learning of this language. However, the question arises whether these software programs meet the educational needs of Iranian learners, particularly in Semnan Province. The aim of this study is to evaluate the efficiency and effectiveness of French language educational software for learners in Semnan Province, considering educational, cultural, and technical criteria. In this study, content analysis and performance evaluation methods were used to examine the educational software ‘Français Facile’. This software was evaluated based on criteria such as teaching methods, cultural compatibility, and technical features. To collect data, standardized questionnaires and semi-structured interviews with learners in Semnan Province were used. Additionally, the SPSS statistical software was employed for quantitative data analysis, and the thematic analysis method was used for qualitative data. The results indicated that the ‘Français Facile’ software has strengths such as providing diverse educational content and an interactive learning environment. However, some weaknesses include the lack of alignment of educational content with the learning culture of learners in Semnan Province and technical issues in software execution. Statistical data showed that 65% of learners were satisfied with the educational content, but 55% reported issues related to cultural alignment with their needs. This study indicates that to enhance the efficiency of French language educational software, there is a need to localize educational content and improve technical infrastructure. Producing locally adapted educational software can improve the quality of language learning and increase the motivation of learners in Semnan Province. This research emphasizes the importance of understanding the cultural and educational needs of learners in the development of educational software and recommends that developers of educational software pay special attention to these aspects.Keywords: educational software, French language, Iran, learners in Semnan province
Procedia PDF Downloads 3022737 Content-Aware Image Augmentation for Medical Imaging Applications
Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang
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Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving
Procedia PDF Downloads 21122736 Common Sports Medicine Injuries in Primary Health Care
Authors: Thuraya Ahmed Hamood Al Shidhani
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Sports Medicine injuries are very common in primary health care. It is not necessary related to direct trauma, but it could be because of repetitive stress and overuse injuries. Knowledge of Primary Health care providers about the common sports medicine injuries and when to refer to a specialist is essential. Common sports injuries are muscle strain, joint sprain, bone bruise, Patellofemoral pain syndrome, Anterior cruciate ligament injuries, meniscal injuries, ankle ligaments injuries, concussion, Rotator cuff tendinosis/impingement syndrome, lateral and medial epicondylitis and fractures. Systematic approach is very useful in evaluation of sports injuries. RICE is important in initial management. Physiotherapy is essential for rehabilitation. Definitive Management is dependent on patient’s condition and function.Keywords: common, sports medicine injuries, primary health care, injuries
Procedia PDF Downloads 7622735 An Assessment of Digital Platforms, Student Online Learning, Teaching Pedagogies, Research and Training at Kenya College of Accounting University
Authors: Jasmine Renner, Alice Njuguna
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The booming technological revolution is driving a change in the mode of delivery systems especially for e-learning and distance learning in higher education. The report and findings of the study; an assessment of digital platforms, student online learning, teaching pedagogies, research and training at Kenya College of Accounting University (hereinafter 'KCA') was undertaken as a joint collaboration project between the Carnegie African Diaspora Fellowship and input from the staff, students and faculty at KCA University. The participants in this assessment/research met for selected days during a six-week period during which, one-one consultations, surveys, questionnaires, foci groups, training, and seminars were conducted to ascertain 'online learning and teaching, curriculum development, research and training at KCA.' The project was organized into an eight-week project workflow with each week culminating in project activities designed to assess digital online teaching and learning at KCA. The project also included the training of distance learning instructors at KCA and the evaluation of KCA’s distance platforms and programs. Additionally, through a curriculum audit and redesign, the project sought to enhance the curriculum development activities related to of distance learning at KCA. The findings of this assessment/research represent the systematic deliberate process of gathering, analyzing and using data collected from DL students, DL staff and lecturers and a librarian personnel in charge of online learning resources and access at KCA. We engaged in one-on-one interviews and discussions with staff, students, and faculty and collated the findings to inform practices that are effective in the ongoing design and development of eLearning earning at KCA University. Overall findings of the project led to the following recommendations. First, there is a need to address infrastructural challenges that led to poor internet connectivity for online learning, training needs and content development for faculty and staff. Second, there is a need to manage cultural impediments within KCA; for example fears of vital change from one platform to another for effectiveness and Institutional goodwill as a vital promise of effective online learning. Third, at a practical and short-term level, the following recommendations based on systematic findings of the research conducted were as follows: there is a need for the following to be adopted at KCA University to promote the effective adoption of online learning: a) an eLearning compatible faculty lab, b) revision of policy to include an eLearn strategy or strategic management, c) faculty and staff recognitions engaged in the process of training for the adoption and implementation of eLearning and d) adequate website resources on eLearning. The report and findings represent a comprehensive approach to a systematic assessment of online teaching and learning, research and training at KCA.Keywords: e-learning, digital platforms, student online learning, online teaching pedagogies
Procedia PDF Downloads 18222734 Evaluating and Supporting Student Engagement in Online Learning
Authors: Maria Hopkins
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Research on student engagement is founded on a desire to improve the quality of online instruction in both course design and delivery. A high level of student engagement is associated with a wide range of educational practices including purposeful student-faculty contact, peer to peer contact, active and collaborative learning, and positive factors such as student satisfaction, persistence, achievement, and learning. By encouraging student engagement, institutions of higher education can have a positive impact on student success that leads to retention and degree completion. The current research presents the results of an online student engagement survey which support faculty teaching practices to maximize the learning experience for online students. The ‘Indicators of Engaged Learning Online’ provide a framework that measures level of student engagement. Social constructivism and collaborative learning form the theoretical basis of the framework. Social constructivist pedagogy acknowledges the social nature of knowledge and its creation in the minds of individual learners. Some important themes that flow from social constructivism involve the importance of collaboration among instructors and students, active learning vs passive consumption of information, a learning environment that is learner and learning centered, which promotes multiple perspectives, and the use of social tools in the online environment to construct knowledge. The results of the survey indicated themes that emphasized the importance of: Interaction among peers and faculty (collaboration); Timely feedback on assignment/assessments; Faculty participation and visibility; Relevance and real-world application (in terms of assignments, activities, and assessments); and Motivation/interest (the need for faculty to motivate students especially those that may not have an interest in the coursework per se). The qualitative aspect of this student engagement study revealed what instructors did well that made students feel engaged in the course, but also what instructors did not do well, which could inform recommendations to faculty when expectations for teaching a course are reviewed. Furthermore, this research provides evidence for the connection between higher student engagement and persistence and retention in online programs, which supports our rationale for encouraging student engagement, especially in the online environment because attrition rates are higher than in the face-to-face environment.Keywords: instructional design, learning effectiveness, online learning, student engagement
Procedia PDF Downloads 28622733 The Use of Self-Determination Theory to Assess the Opportunities and Challenges for Blended E-Learning in Egypt: An Analysis of the Motivations of Logistics Lecturers
Authors: Aisha Tarek Noour, Nick Hubbard
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Blended e-Learning (BL) is proving to be an effective pedagogical tool in many areas of business and management education, but there remains a number of barriers to overcome before its implementation. This paper seeks to analyse the views of lecturers towards BL according to Self-Determination Theory (SDT), and identifies the opportunities and challenges for using BL in Logistics Education in an Egyptian higher education establishment. SDT is approached from a different perspective and the relationship between intrinsic motivation (IM), extrinsic motivation (EM), and amotivation (AM) is analysed and related to the opportunities and challenges of the BL method. The case study methodology comprises of a series of interviews with lecturers employed at three Colleges of International Transport and Logistics (CITLs) at the Arab Academy for Science, Technology, Maritime and Transport (AAST&MT) in Egypt. A structured face-to-face interview was undertaken with 61 interviewees across all faculty positions: Deans, Associate Professors, Assistant Professor, Department Heads, Part-time instructors, Teaching Assistants, and Graduate Teaching Assistants. The findings were based on "content analysis" of the interview transcripts and use of the NVivo10 software program. The research contributes to the application of SDT within the field of BL through an analysis of the views of lecturers towards the opportunities and challenges that BL offers to logistics educators in Egypt.Keywords: intrinsic motivation, extrinsic motivation, amotivation, autonomy, competence, relatedness, self-determination theory and blended e-learning
Procedia PDF Downloads 43522732 A Learning Effects Research Applied a Mobile Guide System with Augmented Reality for Education Center
Authors: Y. L. Chang, Y. H. Huang
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This study designed a mobile guide system that integrates the design principles of guidance and interpretation with augmented reality (AR) as an auxiliary tool for National Taiwan Science Education Center guidance and explored the learning performance of participants who were divided into two visiting groups: AR-guided mode and non-guided mode (without carrying any auxiliary devices). The study included 96 college students as participants and employed a quasi-experimental research design. This study evaluated the learning performance of education center students aided with different guided modes, including their flow experience, activity involvement, learning effects, as well as their attitude and acceptance of using the guide systems. The results showed that (a) the AR guide promoted visitors’ flow experience; (b) the AR-guidance activity involvement and flow experience having a significant positive effect; (c) most of the visitors of mobile guide system with AR elicited a positive response and acceptance attitude. These results confirm the necessity of human–computer–context interaction. Future research can continue exploring the advantages of enhanced learning effectiveness, activity involvement, and flow experience through application of the results of this study.Keywords: augmented reality, mobile guide system, informal learning, flow experience, activity involvement
Procedia PDF Downloads 22522731 Unsupervised Echocardiogram View Detection via Autoencoder-Based Representation Learning
Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah
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Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning
Procedia PDF Downloads 2122730 Noise Reduction in Web Data: A Learning Approach Based on Dynamic User Interests
Authors: Julius Onyancha, Valentina Plekhanova
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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.Keywords: web log data, web user profile, user interest, noise web data learning, machine learning
Procedia PDF Downloads 26022729 Real-Time Classification of Marbles with Decision-Tree Method
Authors: K. S. Parlak, E. Turan
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The separation of marbles according to the pattern quality is a process made according to expert decision. The classification phase is the most critical part in terms of economic value. In this study, a self-learning system is proposed which performs the classification of marbles quickly and with high success. This system performs ten feature extraction by taking ten marble images from the camera. The marbles are classified by decision tree method using the obtained properties. The user forms the training set by training the system at the marble classification stage. The system evolves itself in every marble image that is classified. The aim of the proposed system is to minimize the error caused by the person performing the classification and achieve it quickly.Keywords: decision tree, feature extraction, k-means clustering, marble classification
Procedia PDF Downloads 37822728 Melanoma and Non-Melanoma, Skin Lesion Classification, Using a Deep Learning Model
Authors: Shaira L. Kee, Michael Aaron G. Sy, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar AlDahoul
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Skin diseases are considered the fourth most common disease, with melanoma and non-melanoma skin cancer as the most common type of cancer in Caucasians. The alarming increase in Skin Cancer cases shows an urgent need for further research to improve diagnostic methods, as early diagnosis can significantly improve the 5-year survival rate. Machine Learning algorithms for image pattern analysis in diagnosing skin lesions can dramatically increase the accuracy rate of detection and decrease possible human errors. Several studies have shown the diagnostic performance of computer algorithms outperformed dermatologists. However, existing methods still need improvements to reduce diagnostic errors and generate efficient and accurate results. Our paper proposes an ensemble method to classify dermoscopic images into benign and malignant skin lesions. The experiments were conducted using the International Skin Imaging Collaboration (ISIC) image samples. The dataset contains 3,297 dermoscopic images with benign and malignant categories. The results show improvement in performance with an accuracy of 88% and an F1 score of 87%, outperforming other existing models such as support vector machine (SVM), Residual network (ResNet50), EfficientNetB0, EfficientNetB4, and VGG16.Keywords: deep learning - VGG16 - efficientNet - CNN – ensemble – dermoscopic images - melanoma
Procedia PDF Downloads 7622727 Deep Learning Based, End-to-End Metaphor Detection in Greek with Recurrent and Convolutional Neural Networks
Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos
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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.Keywords: metaphor detection, deep learning, representation learning, embeddings
Procedia PDF Downloads 14622726 Design and Implementation a Platform for Adaptive Online Learning Based on Fuzzy Logic
Authors: Budoor Al Abid
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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.Keywords: machine learning, adaptive, fuzzy logic, data mining
Procedia PDF Downloads 18922725 An Approach for Reliably Transforming Habits Towards Environmental Sustainability Behaviors Among Young Adults
Authors: Dike Felix Okechukwu
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Studies and reports from authoritative sources such as the Intergovernmental Panel on Climate Change (IPCC) have stated that to effectively solve environmental sustainability challenges such as pollution, inappropriate waste disposal, and unsustainable consumption, there is a need for more research to seek solutions towards environmentally sustainable behavior. However, literature thus far reports only sporadic developments of TL in Environmental Sustainability because there are scarce reports showing the reliable process(es) to produce TL - for sustainability projects or otherwise. Nonetheless, a recently published article demonstrates how TL can be used to help young adults gain transformed mindsets and habits toward environmental sustainability behaviors and practices. This study, however, does not demonstrate, on a repeated basis, the dependability of the method or reliability of the procedures in using its proposed methodology to help young adults achieve transformed habits towards environmental sustainability behaviors, especially in diverse contexts. In this study, it is demonstrated, through repeated measures, a reliable process that can be used to achieve transformations in habits and mindsets toward environmental sustainability behaviors. To achieve this, the design adopted is multiple case studies and a thematic analysis techniques. Five cases in diverse contexts were used to analyze pieces of evidence of Transformative Learning Outcomes toward environmentally sustainable behaviors. Results from the study offer fresh perspectives on a reliable methodology that can be adopted to achieve Transformations in Habits and mindsets toward environmental sustainability behaviors.Keywords: environmental sustainability, transformative learning, behaviour, learning, education
Procedia PDF Downloads 8922724 Project Management at University: Towards an Evaluation Process around Cooperative Learning
Authors: J. L. Andrade-Pineda, J.M. León-Blanco, M. Calle, P. L. González-R
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The enrollment in current Master's degree programs usually pursues gaining the expertise required in real-life workplaces. The experience we present here concerns the learning process of "Project Management Methodology (PMM)", around a cooperative/collaborative mechanism aimed at affording students measurable learning goals and providing the teacher with the ability of focusing on the weaknesses detected. We have designed a mixed summative/formative evaluation, which assures curriculum engage while enriches the comprehension of PMM key concepts. In this experience we converted the students into active actors in the evaluation process itself and we endowed ourselves as teachers with a flexible process in which along with qualifications (score), other attitudinal feedback arises. Despite the high level of self-affirmation on their discussion within the interactive assessment sessions, they ultimately have exhibited a great ability to review and correct the wrong reasoning when that was the case.Keywords: cooperative-collaborative learning, educational management, formative-summative assessment, leadership training
Procedia PDF Downloads 16622723 Addressing the Exorbitant Cost of Labeling Medical Images with Active Learning
Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj
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Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net
Procedia PDF Downloads 14722722 Living or Surviving in an Intercultural Context: A Study on Transformative Learning of UK Students in China and Chinese Students in the UK
Authors: Yiran Wang
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As international education continues to expand countries providing such opportunities not only benefit but also face challenges. For traditional destinations, including the United States and the United Kingdom, the number of international students has been falling. At the same time emerging economies, such as China, are witnessing a rapid increase in the number of international students enrolled in their universities. China is, therefore, beginning to play an important role in the competitive global market for higher education. This study analyses and compares the experiences of international students in the UK and China using Transformative Learning theory. While there is an extensive literature on both international higher education and also Transformative Learning theory there are currently three contributions this study makes. First, this research applies the theory to two international student groups: UK students in Chinese universities and Chinese students in UK universities.Second, this study includes a focus on the intercultural learning of Chinese doctoral students in the UK filling a gap in current research. Finally, this investigation has extended the very limited number of current research projects on UK students in China. It is generally acknowledged that international students will experience various challenges when they are in a culturally different context. Little research has focused on how, why, and why not learners are transformed through exposure to their new environment. This study applies Transformative Learning theory to address two research questions: first, do UK international students in Chinese universities and Chinese international students in UK universities experience transformational learning in/during their overseas studies? Second, what factors foster or impede international students’ experience of transformative learning? To answer the above questions, semi-structured interviews were used to investigate international students’ academic and social experiences. Based on the insights provided by Mezirow,Taylor,and previous studies on international students, this study argues that international students’ intercultural experience is a complex process.Transformation can occur in various ways and social and personal perspectives underpin the transformative learning of the students studied. Contributing factors include culture shock, educational conventions,the student’s motivation, expectations, personality, gender and previous work experience.The results reflect the significance of differences in teaching styles in the UK and China and the impact this can have on the student teaching and learning process when they move to a new university.Keywords: intercultural learning, international higher education, transformative learning, UK and Chinese international students
Procedia PDF Downloads 40822721 Assisting Dating of Greek Papyri Images with Deep Learning
Authors: Asimina Paparrigopoulou, John Pavlopoulos, Maria Konstantinidou
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Dating papyri accurately is crucial not only to editing their texts but also for our understanding of palaeography and the history of writing, ancient scholarship, material culture, networks in antiquity, etc. Most ancient manuscripts offer little evidence regarding the time of their production, forcing papyrologists to date them on palaeographical grounds, a method often criticized for its subjectivity. By experimenting with data obtained from the Collaborative Database of Dateable Greek Bookhands and the PapPal online collections of objectively dated Greek papyri, this study shows that deep learning dating models, pre-trained on generic images, can achieve accurate chronological estimates for a test subset (67,97% accuracy for book hands and 55,25% for documents). To compare the estimates of these models with those of humans, experts were asked to complete a questionnaire with samples of literary and documentary hands that had to be sorted chronologically by century. The same samples were dated by the models in question. The results are presented and analysed.Keywords: image classification, papyri images, dating
Procedia PDF Downloads 7422720 A Comprehensive Survey on Machine Learning Techniques and User Authentication Approaches for Credit Card Fraud Detection
Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay
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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey
Procedia PDF Downloads 11022719 Engaging Girls in 'Learn Science by Doing' as Strategy for Enhanced Learning Outcome at the Junior High School Level in Nigeria
Authors: Stella Y. Erinosho
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In an attempt to impact on girls’ interest in science, an instructional package on ‘Learn Science by Doing (LSD)’ was developed to support science teachers in teaching integrated science at the junior secondary level in Nigeria. LSD provides an instructional framework aimed at actively engaging girls in beginners’ science through activities that are discovery-oriented and allow for experiential learning. The goal of this study was to show the impact of application of LSD on girls’ performance and interest in science. The major hypothesis that was tested in the study was that students would exhibit higher learning outcomes (achievement and attitude) in science as effect of exposure to LSD instructional package. A quasi-experimental design was adopted, incorporating four all-girls schools. Three of the schools (comprising six classes) were randomly designated as experimental and one as the control. The sample comprised 357 girls (275 experimental and 82 control) and nine science teachers drawn from the experimental schools. The questionnaire was designed to gather data on students’ background characteristics and their attitude toward science while the cognitive outcomes were measured using tests, both within a group and between groups, the girls who had exposure to LSD exhibited improved cognitive outcomes and more positive attitude towards science compared with those who had conventional teaching. The data are consistent with previous studies indicating that interactive learning activities increase student performance and interest.Keywords: active learning, school science, teaching and learning, Nigeria
Procedia PDF Downloads 38022718 Teaching, Learning and Evaluation Enhancement of Information Communication Technology Education in Schools through Pedagogical and E-Learning Techniques in the Sri Lankan Context
Authors: M. G. N. A. S. Fernando
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This study uses a researchable framework to improve the quality of ICT education and the Teaching Learning Assessment/ Evaluation (TLA/TLE) process. It utilizes existing resources while improving the methodologies along with pedagogical techniques and e-Learning approaches used in the secondary schools of Sri Lanka. The study was carried out in two phases. Phase I focused on investigating the factors which affect the quality of ICT education. Based on the key factors of phase I, the Phase II focused on the design of an Experimental Application Model with 6 activity levels. Each Level in the Activity Model covers one or more levels in the Revised Bloom’s Taxonomy. Towards further enhancement of activity levels, other pedagogical techniques (activity based learning, e-learning techniques, problem solving activities and peer discussions etc.) were incorporated to each level in the activity model as appropriate. The application model was validated by a panel of teachers including a domain expert and was tested in the school environment too. The validity of performance was proved using 6 hypotheses testing and other methodologies. The analysis shows that student performance with problem solving activities increased by 19.5% due to the different treatment levels used. Compared to existing process it was also proved that the embedded techniques (mixture of traditional and modern pedagogical methods and their applications) are more effective with skills development of teachers and students.Keywords: activity models, Bloom’s taxonomy, ICT education, pedagogies
Procedia PDF Downloads 15822717 Measuring Student Teachers' Attitude and Intention toward Cell-Phone Use for Learning in Nigeria
Authors: Shittu Ahmed Tajudeen
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This study examines student-teachers’ attitude and intention towards cell-phone use for learning. The study involves one hundred and ninety (190) trainee teachers in one of the Institutes of Education in Nigeria. The data of the study was collected through a questionnaire on a rating of seven point likert-type Scale. The data collected was used to test the hypothesized model of the study using Structural Equation Modeling approach. The finding of the study revealed that Perceived Usefulness (PU), Perceived Ease of Use (PEU), Subjective Norm (SN) and Attitude significantly influence students’ intention towards adoption of cell-phone for learning. The study showed that perceived ease of use stands to be the strongest predictor of cell-phone use. The model of the study exhibits a good-fit with the data and provides an explanation on student- teachers’ attitude and intention towards cell-phone for learning.Keywords: cell-phone, adoption, structural equation modeling, technology acceptance model
Procedia PDF Downloads 44622716 Design of a Professional Development Framework in Teaching and Learning for Engineering Educators
Authors: Orla McConnell, Cormac MacMahon, Jen Harvey
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Ireland’s national professional development framework for those who teach in higher education, aims to provide guidance and leadership in the planning, developing and engaging in professional development practices. A series of pilot projects have been initiated to help explore the framework’s likely utility and acceptance by educators and their institutions. These projects require engagement with staff in the interpretation and adaption of the framework within their working contexts. The purpose of this paper is to outline the development of one such project with engineering educators at three Institutes of Technology seeking designation as a technological university. The initiative aims to gain traction in the acceptance of the framework with the engineering education community by linking core and discipline-specific teaching and learning competencies with professional development activities most valued by engineering educators. Informed by three strands of literature: professional development in higher education; engineering education; and teaching and learning training provisions, the project begins with a survey of all those involved in teaching and learning in engineering across the three institutes. Based on engagement with key stakeholders, subsequent qualitative research informs the contextualization of the national framework for discipline-specific and institutional piloting. The paper concludes by exploring engineering educator perceptions of the national framework’s utility based on their engagement with the pilot process. Feedback from the pilot indicates that there is a significant gap between the professional development needs of engineering educators and the current professional development provision in teaching and learning.Keywords: engineering education, pilot, professional development, teaching and learning
Procedia PDF Downloads 32222715 Timbuktu Pattern of Islamic Education: A Role Model for the Establishment of Islamic Educational System in Sokoto Caliphate
Authors: A. M. Gada, H. U. Malami
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Timbuktu is one of the eight regions in the present day the Republic of Mali. It flourished as one of the earliest centres of Islamic learning in West Africa in the eleventh century CE. The famous Islamic centre in Timbuktu is situated in the Sankore mosque, which is known to be one of the earliest established Islamic University. This centre produced scholars who were zealous in disseminating Islamic education to different parts of West Africa and beyond. As a result, most of these centres adopted the Timbuktu pattern of learning. Some of the beneficiaries of this noble activity are Muslim scholars which are responsible for the establishment of the Sokoto Caliphate in the early nineteenth century. This paper intends to reflect on the pattern of Islamic education of the Timbuktu scholars and see how it impacted on the Islamic centres of learning established by these Jihad-scholars who were successful in the establishment of an Islamic state known as the Sokoto Caliphate.Keywords: Timbuktu, Sankore, Islamic educational system, Sokoto Caliphate, centres of Islamic learning
Procedia PDF Downloads 40622714 Deep Reinforcement Learning for Advanced Pressure Management in Water Distribution Networks
Authors: Ahmed Negm, George Aggidis, Xiandong Ma
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With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management
Procedia PDF Downloads 7922713 Active Learning in Computer Exercises on Electronics
Authors: Zoja Raud, Valery Vodovozov
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Modelling and simulation provide effective way to acquire engineering experience. An active approach to modelling and simulation proposed in the paper involves, beside the compulsory part directed by the traditional step-by-step instructions, the new optional part basing on the human’s habits to design thus stimulating the efforts towards success in active learning. Computer exercises as a part of engineering curriculum incorporate a set of effective activities. In addition to the knowledge acquired in theoretical training, the described educational arrangement helps to develop problem solutions, computation skills, and experimentation performance along with enhancement of practical experience and qualification.Keywords: modelling, simulation, engineering education, electronics, active learning
Procedia PDF Downloads 38922712 Grounding Chinese Language Vocabulary Teaching and Assessment in the Working Memory Research
Authors: Chan Kwong Tung
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Since Baddeley and Hitch’s seminal research in 1974 on working memory (WM), this topic has been of great interest to language educators. Although there are some variations in the definitions of WM, recent findings in WM have contributed vastly to our understanding of language learning, especially its effects on second language acquisition (SLA). For example, the phonological component of WM (PWM) and the executive component of WM (EWM) have been found to be positively correlated with language learning. This paper discusses two general, yet highly relevant WM findings that could directly affect the effectiveness of Chinese Language (CL) vocabulary teaching and learning, as well as the quality of its assessment. First, PWM is found to be critical for the long-term learning of phonological forms of new words. Second, EWM is heavily involved in interpreting the semantic characteristics of new words, which consequently affects the quality of learners’ reading comprehension. These two ideas are hardly discussed in the Chinese literature, both conceptual and empirical. While past vocabulary acquisition studies have mainly focused on the cognitive-processing approach, active processing, ‘elaborate processing’ (or lexical elaboration) and other effective learning tasks and strategies, it is high time to balance the spotlight to the WM (particularly PWM and EWM) to ensure an optimum control on the teaching and learning effectiveness of such approaches, as well as the validity of this language assessment. Given the unique phonological, orthographical and morphological properties of the CL, this discussion will shed some light on the vocabulary acquisition of this Sino-Tibetan language family member. Together, these two WM concepts could have crucial implications for the design, development, and planning of vocabularies and ultimately reading comprehension teaching and assessment in language education. Hopefully, this will raise an awareness and trigger a dialogue about the meaning of these findings for future language teaching, learning, and assessment.Keywords: Chinese Language, working memory, vocabulary assessment, vocabulary teaching
Procedia PDF Downloads 33522711 Mathematical Reconstruction of an Object Image Using X-Ray Interferometric Fourier Holography Method
Authors: M. K. Balyan
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The main principles of X-ray Fourier interferometric holography method are discussed. The object image is reconstructed by the mathematical method of Fourier transformation. The three methods are presented – method of approximation, iteration method and step by step method. As an example the complex amplitude transmission coefficient reconstruction of a beryllium wire is considered. The results reconstructed by three presented methods are compared. The best results are obtained by means of step by step method.Keywords: dynamical diffraction, hologram, object image, X-ray holography
Procedia PDF Downloads 39022710 International Counseling Learning: The Need for Suitable Training within Counselor Education and Counseling Students
Authors: Paula Lazarim
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As global mobility thrives, researchers emphasize the urgency of global literacy through training qualified counselors to serve internationally in a culturally competent manner. However, the focus thus far has been on how counselors’ preparation to approach international populations fuses with study abroad experiential learning short-term immersions. Looking for better solutions for cultural competency and skills learning related to international counseling, the author of this manuscript examines international counseling's current status, learning scope and goals, and educational opportunities. A guiding framework grounded on relational pedagogy (Reeves & Le Mare, 2017), relational cultural theory (Jordan, 2017), and intercultural education (Nastasi et al., 2020) is applied with four long-term educational modality projects designed to benefit cultural competence, attitude, relational skills development, and learning an intercultural counseling approach. Suggestions that encourage innovative instruction in counselor education and counseling programs at master and doctoral levels, stimulate self-learning, and educate in intercultural relational competence are linked to strategies for engaging in international counseling based on findings of a literature review and training-projects implementation. Ultimately, the author highlights theoretical and practical implications of suitable training to improve counselors' performance and discusses long-term teaching-learning opportunities that positively impact the international counseling community by sending out internationally culturally competent counselors.Keywords: international counseling, counselor education, counseling, relational pedagogy, intercultural education, counselors’ training
Procedia PDF Downloads 197