Search results for: online teaching and learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10050

Search results for: online teaching and learning

6390 Learning Aid for Kids in India

Authors: Prabir Mukhopadhyay, Atul Kohale

Abstract:

Going to school for Indian kids is a panic situation. Many of them are unable to adjust themselves to the confinement of the school building and this problem is compounded by other factors like unknown people in the vicinity, absence of either parents etc. This project aims at addressing these issues by exposing the kids at home to the learning environment. The purpose is to design a physical model with interfaces at each surface. The model would be like a cube with interactive surfaces where the child would be able to draw, paint, complete a picture and do such fun activities.

Keywords: interface, kids, play, computer systems engineering

Procedia PDF Downloads 207
6389 Prediction of Remaining Life of Industrial Cutting Tools with Deep Learning-Assisted Image Processing Techniques

Authors: Gizem Eser Erdek

Abstract:

This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

Procedia PDF Downloads 69
6388 MULTI-FLGANs: Multi-Distributed Adversarial Networks for Non-Independent and Identically Distributed Distribution

Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

Abstract:

Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

Procedia PDF Downloads 151
6387 Lung Disease Detection from the Chest X Ray Images Using Various Transfer Learning

Authors: Aicha Akrout, Amira Echtioui, Mohamed Ghorbel

Abstract:

Pneumonia remains a significant global health concern, posing a substantial threat to human lives due to its contagious nature and potentially fatal respiratory complications caused by bacteria, fungi, or viruses. The reliance on chest X-rays for diagnosis, although common, often necessitates expert interpretation, leading to delays and potential inaccuracies in treatment. This study addresses these challenges by employing transfer learning techniques to automate the detection of lung diseases, with a focus on pneumonia. Leveraging three pre-trained models, VGG-16, ResNet50V2, and MobileNetV2, we conducted comprehensive experiments to evaluate their performance. Our findings reveal that the proposed model based on VGG-16 demonstrates superior accuracy, precision, recall, and F1 score, achieving impressive results with an accuracy of 93.75%, precision of 94.50%, recall of 94.00%, and an F1 score of 93.50%. This research underscores the potential of transfer learning in enhancing pneumonia diagnosis and treatment outcomes, offering a promising avenue for improving healthcare delivery and reducing mortality rates associated with this debilitating respiratory condition.

Keywords: chest x-ray, lung diseases, transfer learning, pneumonia detection

Procedia PDF Downloads 34
6386 Practice Based Approach to the Development of Family Medicine Residents’ Educational Environment

Authors: Lazzat M. Zhamaliyeva, Nurgul A. Abenova, Gauhar S. Dilmagambetova, Ziyash Zh. Tanbetova, Moldir B. Ahmetzhanova, Tatyana P. Ostretcova, Aliya A. Yegemberdiyeva

Abstract:

Introduction: There are many reasons for the weak training of family doctors in Kazakhstan: the unified national educational program is not focused on competencies, the role of a general practitioner (GP) is not clear, poor funding for the health care and education system, outdated teaching and assessment methods, inefficient management. We highlight two issues in particular. Firstly, academic teachers of family medicine (FM) in Kazakhstan do not practice as family doctors; most of them are narrow specialists (pediatricians, therapists, surgeons, etc.); they usually hold one-time consultations; clinical mentors from practical healthcare (non-academic teachers) do not have the teaching competences, and the vast majority of them are also narrow specialists. Secondly, clinical sites (polyclinics) are unprepared for general practice and do not follow the principles of family medicine; residents do not like to be in primary health care (PHC) settings due to the chaos that is happening there, as well as due to the lack of the necessary equipment for mastering and consolidating practical skills. Aim: We present the concept of the family physicians’ training office (FPTO), which is being created as a friendly learning environment for young general practitioners and for the involvement of academic teachers of family medicine in the practical work and innovative development of PHC. Methodology: In developing the conceptual framework and identifying practical activities, we drew on literature and expert input, and interviews. Results: The goal of the FPTO is to create a favorable educational and clinical environment for the development of the FM residents’ competencies, in which the residents with academic teachers and clinical mentors could understand and accept the principles of family medicine, improve clinical knowledge and skills, and gain experience in improving the quality of their practice in scientific basis. Three main areas of office activity are providing primary care to the patients, improving educational services for FM residents and other medical workers, and promoting research in PHC and innovations. The office arranges for residents to see outpatients at least 50% of the time, and teachers of FM departments at least 1/4 of their working time conduct general medical appointments next to residents. Taking into account the educational and scientific workload, the number of attached population for one GP does not exceed 500 persons. The equipment of the office allows FPTO workers to perform invasive and other manipulations without being sent to other clinics. In the office, training for residents is focused on their needs and aimed at achieving the required level of competence. International methodologies and assessment tools are adapted to local conditions and evaluated for their effectiveness and acceptability. Residents and their faculty actively conduct research in the field of family medicine. Conclusions: We propose to change the learning environment in order to create teams of like-minded people, to unite residents and teachers even more for the development of family medicine. The offices will also invest resources in developing and maintaining young doctors' interest in family medicine.

Keywords: educational environment, family medicine residents, family physicians’ training office, primary care research

Procedia PDF Downloads 132
6385 Proposal for a Framework for Teaching Entrepreneurship and Innovation Using the Methods and Current Methodologies

Authors: Marcelo T. Okano, Jaqueline C. Bueno, Oduvaldo Vendrametto, Osmildo S. Santos, Marcelo E. Fernandes, Heide Landi

Abstract:

Developing countries are increasingly finding that entrepreneurship and innovation are the ways to speed up their developments and initiate or encourage technological development. The educational institutions such as universities, colleges and colleges of technology, has two main roles in this process, to guide and train entrepreneurs and provide technological knowledge and encourage innovation. Thus there was completing the triple helix model of innovation with universities, government and industry. But the teaching of entrepreneurship and innovation can not be only the traditional model, with blackboard, chalk and classroom. The new methods and methodologies such as Canvas, elevator pitching, design thinking, etc. require students to get involved and to experience the simulations of business, expressing their ideas and discussing them. The objective of this research project is to identify the main methods and methodologies used for the teaching of entrepreneurship and innovation, to propose a framework, test it and make a case study. To achieve the objective of this research, firstly was a survey of the literature on the entrepreneurship and innovation, business modeling, business planning, Canvas business model, design thinking and other subjects about the themes. Secondly, we developed the framework for teaching entrepreneurship and innovation based on bibliographic research. Thirdly, we tested the framework in a higher education class IT management for a semester. Finally, we detail the results in the case study in a course of IT management. As important results we improve the level of understanding and business administration students, allowing them to manage own affairs. Methods such as canvas and business plan helped students to plan and shape the ideas and business. Pitching for entrepreneurs and investors in the market brought a reality for students. The prototype allowed the company groups develop their projects. The proposed framework allows entrepreneurship education and innovation can leave the classroom, bring the reality of business roundtables to university relying on investors and real entrepreneurs.

Keywords: entrepreneurship, innovation, Canvas, traditional model

Procedia PDF Downloads 572
6384 Improving Graduate Student Writing Skills: Best Practices and Outcomes

Authors: Jamie Sundvall, Lisa Jennings

Abstract:

A decline in writing skills and abilities of students entering graduate school has become a focus for university systems within the United States. This decline has become a national trend that requires reflection on the intervention strategies used to address the deficit and unintended consequences as outcomes in the profession. Social work faculty is challenged to increase written scholarship within the academic setting. However, when a large number of students in each course have writing deficits, there is a shift from focus on content, ability to demonstrate competency, and application of core social work concepts. This qualitative study focuses on the experiences of online faculty who support increasing scholarship through writing and are following best practices preparing students academically to see improvements in written presentation in classroom work. This study outlines best practices to improve written academic presentation, especially in an online setting. The research also highlights how a student’s ability to show competency and application of concepts may be overlooked in the online setting. This can lead to new social workers who are prepared academically, but may unable to effectively advocate and document thought presentation in their writing. The intended progression of writing across all levels of higher education moves from summary, to application, and into abstract problem solving. Initial findings indicate that it is important to reflect on practices used to address writing deficits in terms of academic writing, competency, and application. It is equally important to reflect on how these methods of intervention impact a student post-graduation. Specifically, for faculty, it is valuable to assess a social worker’s ability to engage in continuity of documentation and advocacy at micro, mezzo, macro, and international levels of practice.

Keywords: intervention, professional impact, scholarship, writing

Procedia PDF Downloads 136
6383 Policy and Practice of Later-Life Learning in China: A Critical Document Discourse Analysis

Authors: Xue Wu

Abstract:

Since the 1980s, a series of policies and practices have been implemented in China in response to the unprecedented rate of ageing population. The paper provides a detailed narrative of what later-life learning policy discourses have been advocated and gives a description on relevant practical issues during the past three decades. The research process based on the discourse approach with a systematic review of the government-issued documents. It finds that the main practices taken by central government at various levels were making University of the Aged (UA) available in all urban and rural regions to consolidate the newly student enrollments; focusing social-recreational, leisure and cultural activities on 55-75 age group; and utilizing various methods including voluntary works and tourism to improve older adults’ physical and mental wellness. Although there were greater achievements with 30 years of development, many problems still exist. Finding reveals that the curriculum should be modified to meet the needs of the local development, to promote older adults’ contact and contribution to the community, and to enhance technical competences of those in rural areas involving in agricultural production. Central government should also integrate resources from all sectors of the society for further developing later-life learning in China. The result of this paper highlights the value to promote community-based later-life learning for building a society for active ageing and ageing in place.

Keywords: ageing population, China, later-life learning, policy, University of the Aged

Procedia PDF Downloads 142
6382 Forecasting the Future Implications of ChatGPT Usage in Education Based on AI Algorithms

Authors: Yakubu Bala Mohammed, Nadire Chavus, Mohammed Bulama

Abstract:

Generative Pre-trained Transformer (ChatGPT) represents an artificial intelligence (AI) tool capable of swiftly generating comprehensive responses to prompts and follow-up inquiries. This emerging AI tool was introduced in November 2022 by OpenAI firm, an American AI research laboratory, utilizing substantial language models. This present study aims to delve into the potential future consequences of ChatGPT usage in education using AI-based algorithms. The paper will bring forth the likely potential risks of ChatGBT utilization, such as academic integrity concerns, unfair learning assessments, excessive reliance on AI, and dissemination of inaccurate information using four machine learning algorithms: eXtreme-Gradient Boosting (XGBoost), Support vector machine (SVM), Emotional artificial neural network (EANN), and Random forest (RF) would be used to analyze the study collected data due to their robustness. Finally, the findings of the study will assist education stakeholders in understanding the future implications of ChatGPT usage in education and propose solutions and directions for upcoming studies.

Keywords: machine learning, ChatGPT, education, learning, implications

Procedia PDF Downloads 225
6381 Knowledge and Attitude: Challenges for Continuing Education in Health

Authors: André M. Senna, Mary L. G. S. Senna, Rosa M. Machado-de-Sena

Abstract:

One of the great challenges presented in educational practice is how to ensure the students not only acquire knowledge of training courses throughout their academic life, but also how to apply it in their current professional activities. Consequently, aiming to incite changes in the education system of healthcare professionals noticed the inadequacy of the training providers to solve the social problems related to health, the education related to these procedures should initiate in the earliest years of process. Following that idea, there is another question that needs an answer: If the change in the education should start sooner, in the period of basic training of healthcare professionals, what guidelines should a permanent education program incorporate to promote changes in an already established system? For this reason, the objective of this paper is to present different views of the teaching-learning process, with the purpose of better understanding the behavior adopted by healthcare professionals, through bibliographic study. The conclusion was that more than imparting knowledge to the individual, a larger approach is necessary on permanent education programs concerning the performance of professional health services in order to foment significant changes in education.

Keywords: Health Education, continuing education, training, behavior

Procedia PDF Downloads 259
6380 The Appropriate Number of Test Items That a Classroom-Based Reading Assessment Should Include: A Generalizability Analysis

Authors: Jui-Teng Liao

Abstract:

The selected-response (SR) format has been commonly adopted to assess academic reading in both formal and informal testing (i.e., standardized assessment and classroom assessment) because of its strengths in content validity, construct validity, as well as scoring objectivity and efficiency. When developing a second language (L2) reading test, researchers indicate that the longer the test (e.g., more test items) is, the higher reliability and validity the test is likely to produce. However, previous studies have not provided specific guidelines regarding the optimal length of a test or the most suitable number of test items or reading passages. Additionally, reading tests often include different question types (e.g., factual, vocabulary, inferential) that require varying degrees of reading comprehension and cognitive processes. Therefore, it is important to investigate the impact of question types on the number of items in relation to the score reliability of L2 reading tests. Given the popularity of the SR question format and its impact on assessment results on teaching and learning, it is necessary to investigate the degree to which such a question format can reliably measure learners’ L2 reading comprehension. The present study, therefore, adopted the generalizability (G) theory to investigate the score reliability of the SR format in L2 reading tests focusing on how many test items a reading test should include. Specifically, this study aimed to investigate the interaction between question types and the number of items, providing insights into the appropriate item count for different types of questions. G theory is a comprehensive statistical framework used for estimating the score reliability of tests and validating their results. Data were collected from 108 English as a second language student who completed an English reading test comprising factual, vocabulary, and inferential questions in the SR format. The computer program mGENOVA was utilized to analyze the data using multivariate designs (i.e., scenarios). Based on the results of G theory analyses, the findings indicated that the number of test items had a critical impact on the score reliability of an L2 reading test. Furthermore, the findings revealed that different types of reading questions required varying numbers of test items for reliable assessment of learners’ L2 reading proficiency. Further implications for teaching practice and classroom-based assessments are discussed.

Keywords: second language reading assessment, validity and reliability, Generalizability theory, Academic reading, Question format

Procedia PDF Downloads 80
6379 Current Methods for Drug Property Prediction in the Real World

Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

Abstract:

Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

Procedia PDF Downloads 76
6378 Technology and the Need for Integration in Public Education

Authors: Eric Morettin

Abstract:

Cybersecurity and digital literacy are pressing issues among Canadian citizens, yet formal education does not provide today’s students with the necessary knowledge and skills needed to adapt to these challenging issues within the physical and digital labor-market. Canada’s current education systems do not highlight the importance of these respective fields, aside from using technology for learning management systems and alternative methods of assignment completion. Educators are not properly trained to integrate technology into the compulsory courses within public education, to better prepare their learners in these topics and Canada’s digital economy. ICTC addresses these gaps in education and training through cross-Canadian educational programming in digital literacy and competency, cybersecurity and coding which is bridged with Canada’s provincially regulated K-12 curriculum guidelines. After analyzing Canada’s provincial education, it is apparent that there are gaps in learning related to technology, as well as inconsistent educational outcomes that do not adequately represent the current Canadian and global economies. Presently only New Brunswick, Nova Scotia, Ontario, and British Columbia offer curriculum guidelines for cybersecurity, computer programming, and digital literacy. The remaining provinces do not address these skills in their curriculum guidelines. Moreover, certain courses across some provinces not being updated since the 1990’s. The three territories respectfully take curriculum strands from other provinces and use them as their foundation in education. Yukon uses all British Columbia curriculum. Northwest Territories and Nunavut respectfully use a hybrid of Alberta and Saskatchewan curriculum as their foundation of learning. Education that is provincially regulated does not allow for consistency across the country’s educational outcomes and what Canada’s students will achieve – especially when curriculum outcomes have not been updated to reflect present day society. Through this, ICTC has aligned Canada’s provincially regulated curriculum and created opportunities for focused education in the realm of technology to better serve Canada’s present learners and teachers; while addressing inequalities and applicability within curriculum strands and outcomes across the country. As a result, lessons, units, and formal assessment strategies, have been created to benefit students and teachers in this interdisciplinary, cross-curricular, practice - as well as meeting their compulsory education requirements and developing skills and literacy in cyber education. Teachers can access these lessons and units through ICTC’s website, as well as receive professional development regarding the assessment and implementation of these offerings from ICTC’s education coordinators, whose combines experience exceeds 50 years of teaching in public, private, international, and Indigenous schools. We encourage you to take this opportunity that will benefit students and educators, and will bridge the learning and curriculum gaps in Canadian education to better reflect the ever-changing public, social, and career landscape that all citizens are a part of. Students are the future, and we at ICTC strive to ensure their futures are bright and prosperous.

Keywords: cybersecurity, education, curriculum, teachers

Procedia PDF Downloads 78
6377 Application of Fourier Series Based Learning Control on Mechatronic Systems

Authors: Sandra Baßler, Peter Dünow, Mathias Marquardt

Abstract:

A Fourier series based learning control (FSBLC) algorithm for tracking trajectories of mechanical systems with unknown nonlinearities is presented. Two processes are introduced to which the FSBLC with PD controller is applied. One is a simplified service robot capable of climbing stairs due to special wheels and the other is a propeller driven pendulum with nearly the same requirements on control. Additionally to the investigation of learning the feed forward for the desired trajectories some considerations on the implementation of such an algorithm on low cost microcontroller hardware are made. Simulations of the service robot as well as practical experiments on the pendulum show the capability of the used FSBLC algorithm to perform the task of improving control behavior for repetitive task of such mechanical systems.

Keywords: climbing stairs, FSBLC, ILC, service robot

Procedia PDF Downloads 308
6376 Functional English: Enhancing Competencies at the Undergraduate Level in Nagaland, India

Authors: Arenkala Kichu

Abstract:

This paper consolidates and tries to bring out the findings that investigated in Kohima and Mokokchung districts in Nagaland, which is in the northeastern part of India. The aim of this paper is to test the speaking and writing skills of the undergraduate learners who opt functional English as one of their papers. functional English is taught in just two colleges; Fazl Ali College and Kohima Colleges, out of 15 government and 36 private colleges in the state. This research (based on several observations made by Naga researchers) hypothesizes that functional English enhances competencies at the undergraduate level, which would open doors to work, learn more and better prospects. It is expected that learners in Functional English class, which follows the communicative language teaching method, might be the answers to those problems, as to why proficiency level still leaves much to be desired, in spite of the advent of the education over a hundred years ago. This type of teaching follows only in functional English class in these two colleges.

Keywords: enhancing competencies, speaking skills, undergraduate level, writing skills

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6375 Pupils' and Teachers' Perceptions and Experiences of Welsh Language Instruction

Authors: Mirain Rhys, Kevin Smith

Abstract:

In 2017, the Welsh Government introduced an ambitious, new strategy to increase the number of Welsh speakers in Wales to 1 million by 2050. The Welsh education system is a vitally important feature of this strategy. All children attending state schools in Wales learn Welsh as a second language until the age of 16 and are assessed at General Certificate of Secondary Education (GCSE) level. In 2013, a review of Welsh second language instruction in Key Stages 3 and 4 was completed. The report identified considerable gaps in teachers’ preparation and training for teaching Welsh; poor Welsh language ethos at many schools; and a general lack of resources to support the instruction of Welsh. Recommendations were made across a number of dimensions including curriculum content, pedagogical practice, and teacher assessment, training, and resources. With a new national curriculum currently in development, this study builds on this review and provides unprecedented detail into pupils’ and teachers’ perceptions of Welsh language instruction. The current research built on data taken from an existing capacity building research project on Welsh education, the Wales multi-cohort study (WMS). Quantitative data taken from WMS surveys with over 1200 pupils in schools in Wales indicated that Welsh language lessons were the least enjoyable subject among pupils. The current research aimed to unpick pupil experiences in order to add to the policy development context. To achieve this, forty-four pupils and four teachers in three schools from the larger WMS sample participated in focus groups. Participants from years 9, 11 and 13 who had indicated positive, negative and neutral attitudes towards the Welsh language in a previous WMS survey were selected. Questions were based on previous research exploring issues including, but not limited to pedagogy, policy, assessment, engagement and (teacher) training. A thematic analysis of the focus group recordings revealed that the majority of participants held positive views around keeping the language alive but did not want to take on responsibility for its maintenance. These views were almost entirely based on their experiences of learning Welsh at school, especially in relation to their perceived lack of choice and opinions around particular lesson strategies and assessment. Analysis of teacher interviews highlighted a distinct lack of resources (materials and staff alike) compared to modern foreign languages, which had a negative impact on student motivation and attitudes. Both staff and students indicated a need for more practical, oral language instruction which could lead to Welsh being used outside the classroom. The data corroborate many of the review’s previous findings, but what makes this research distinctive is the way in which pupils poignantly address generally misguided aims for Welsh language instruction, poor pedagogical practice and a general disconnect between Welsh instruction and its daily use in their lives. These findings emphasize the complexity of incorporating the educational sector in strategies for Welsh language maintenance and the complications arising from pedagogical training, support, and resources, as well as teacher and pupil perceptions of, and attitudes towards, teaching and learning Welsh.

Keywords: bilingual education, language maintenance, language revitalisation, minority languages, Wales

Procedia PDF Downloads 107
6374 A Machine Learning Based Method to Detect System Failure in Resource Constrained Environment

Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

Abstract:

Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

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6373 The Unspoken Learning Landscape of Indigenous Peoples (IP) Learners: A Process Documentation and Analysis

Authors: Ailene B. Anonuevo

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The aim of the study was to evaluate the quality of life presently available for the IP students in selected schools in the Division of Panabo City. This further explores their future dreams and current status in classes and examines some implications relative to their studies. The study adopted the mixed methodology and used a survey research design as the operational framework for data gathering. Data were collected by self-administered questionnaires and interviews with sixty students from three schools in Panabo City. In addition, this study describes the learners’ background and school climate as variables that might influence their performance in school. The study revealed that an IP student needs extra attention due to their unfavorable learning environment. The study also found out that like any other students, IP learners yearns for a brighter future with the support of our government.

Keywords: IP learners, learning landscape, school climate, quality of life

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6372 Adapted Intersection over Union: A Generalized Metric for Evaluating Unsupervised Classification Models

Authors: Prajwal Prakash Vasisht, Sharath Rajamurthy, Nishanth Dara

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In a supervised machine learning approach, metrics such as precision, accuracy, and coverage can be calculated using ground truth labels to help in model tuning, evaluation, and selection. In an unsupervised setting, however, where the data has no ground truth, there are few interpretable metrics that can guide us to do the same. Our approach creates a framework to adapt the Intersection over Union metric, referred to as Adapted IoU, usually used to evaluate supervised learning models, into the unsupervised domain, which solves the problem by factoring in subject matter expertise and intuition about the ideal output from the model. This metric essentially provides a scale that allows us to compare the performance across numerous unsupervised models or tune hyper-parameters and compare different versions of the same model.

Keywords: general metric, unsupervised learning, classification, intersection over union

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6371 A Review of Deep Learning Methods in Computer-Aided Detection and Diagnosis Systems based on Whole Mammogram and Ultrasound Scan Classification

Authors: Ian Omung'a

Abstract:

Breast cancer remains to be one of the deadliest cancers for women worldwide, with the risk of developing tumors being as high as 50 percent in Sub-Saharan African countries like Kenya. With as many as 42 percent of these cases set to be diagnosed late when cancer has metastasized and or the prognosis has become terminal, Full Field Digital [FFD] Mammography remains an effective screening technique that leads to early detection where in most cases, successful interventions can be made to control or eliminate the tumors altogether. FFD Mammograms have been proven to multiply more effective when used together with Computer-Aided Detection and Diagnosis [CADe] systems, relying on algorithmic implementations of Deep Learning techniques in Computer Vision to carry out deep pattern recognition that is comparable to the level of a human radiologist and decipher whether specific areas of interest in the mammogram scan image portray abnormalities if any and whether these abnormalities are indicative of a benign or malignant tumor. Within this paper, we review emergent Deep Learning techniques that will prove relevant to the development of State-of-The-Art FFD Mammogram CADe systems. These techniques will span self-supervised learning for context-encoded occlusion, self-supervised learning for pre-processing and labeling automation, as well as the creation of a standardized large-scale mammography dataset as a benchmark for CADe systems' evaluation. Finally, comparisons are drawn between existing practices that pre-date these techniques and how the development of CADe systems that incorporate them will be different.

Keywords: breast cancer diagnosis, computer aided detection and diagnosis, deep learning, whole mammogram classfication, ultrasound classification, computer vision

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6370 The School Based Support Program: An Evaluation of a Comprehensive School Reform Initiative in the State of Qatar

Authors: Abdullah Abu-Tineh, Youmen Chaaban

Abstract:

This study examines the development of a professional development (PD) model for teacher growth and learning that is embedded into the school context. The School based Support Program (SBSP), designed for the Qatari context, targets the practices, knowledge and skills of both school leadership and teachers in an attempt to improve student learning outcomes. Key aspects of the model include the development of learning communities among teachers, strong leadership that supports school improvement activities, and the use of research-based PD to improve teacher practices and student achievement. This paper further presents findings from an evaluation of this PD program. Based on an adaptation of Guskey’s evaluation of PD models, 100 teachers at the participating schools were selected for classroom observations and 40 took part in in-depth interviews to examine changed classroom practices. The impact of the PD program on student learning was also examined. Teachers’ practices and their students’ achievement in English, Arabic, mathematics and science were measured at the beginning and at the end of the intervention.

Keywords: initiative, professional development, school based support Program (SBSP), school reform

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6369 Non-Cognitive Skills Associated with Learning in a Serious Gaming Environment: A Pretest-Posttest Experimental Design

Authors: Tanja Kreitenweis

Abstract:

Lifelong learning is increasingly seen as essential for coping with the rapidly changing work environment. To this end, serious games can provide convenient and straightforward access to complex knowledge for all age groups. However, learning achievements depend largely on a learner’s non-cognitive skill disposition (e.g., motivation, self-belief, playfulness, and openness). With the aim of combining the fields of serious games and non-cognitive skills, this research focuses in particular on the use of a business simulation, which conveys change management insights. Business simulations are a subset of serious games and are perceived as a non-traditional learning method. The presented objectives of this work are versatile: (1) developing a scale, which measures learners’ knowledge and skills level before and after a business simulation was played, (2) investigating the influence of non-cognitive skills on learning in this business simulation environment and (3) exploring the moderating role of team preference in this type of learning setting. First, expert interviews have been conducted to develop an appropriate measure for learners’ skills and knowledge assessment. A pretest-posttest experimental design with German management students was implemented to approach the remaining objectives. By using the newly developed, reliable measure, it was found that students’ skills and knowledge state were higher after the simulation had been played, compared to before. A hierarchical regression analysis revealed two positive predictors for this outcome: motivation and self-esteem. Unexpectedly, playfulness had a negative impact. Team preference strengthened the link between grit and playfulness, respectively, and learners’ skills and knowledge state after completing the business simulation. Overall, the data underlined the potential of business simulations to improve learners’ skills and knowledge state. In addition, motivational factors were found as predictors for benefitting most from the applied business simulation. Recommendations are provided for how pedagogues can use these findings.

Keywords: business simulations, change management, (experiential) learning, non-cognitive skills, serious games

Procedia PDF Downloads 103
6368 Satisfaction of the Training at ASEAN Camp: E-Learning Knowledge and Application at Chantanaburi Province, Thailand

Authors: Sinchai Poolklai

Abstract:

The purpose of this research paper was aimed to examine the level of satisfaction of the faculty members who participated in the ASEAN camp, Chantaburi, Thailand. The population of this study included all the faculty members of Suan Sunandha Rajabhat University who participated in the training and activities of the ASEAN camp during March, 2014. Among a total of 200 faculty members who answered the questionnaire, the data was complied by using SPSS program. Percentage, mean and standard deviation were utilized in analyzing the data. The findings revealed that the average mean of satisfaction was 4.37, and standard deviation was 0.7810. Moreover, the mean average can be used to rank the level of satisfaction from each of the following factors: lower cost, less time consuming, faster delivery, more effective learning, and lower environment impact.

Keywords: ASEAN camp, e-learning, satisfaction, application

Procedia PDF Downloads 386
6367 Enhancing Student Learning Outcomes Using Engineering Design Process: Case Study in Physics Course

Authors: Thien Van Ngo

Abstract:

The engineering design process is a systematic approach to solving problems. It involves identifying a problem, brainstorming solutions, prototyping and testing solutions, and evaluating the results. The engineering design process can be used to teach students how to solve problems in a creative and innovative way. The research aim of this study was to investigate the effectiveness of using the engineering design process to enhance student learning outcomes in a physics course. A mixed research method was used in this study. The quantitative data were collected using a pretest-posttest control group design. The qualitative data were collected using semi-structured interviews. The sample was 150 first-year students in the Department of Mechanical Engineering Technology at Cao Thang Technical College in Vietnam in the 2022-2023 school year. The quantitative data were collected using a pretest-posttest control group design. The pretest was administered to both groups at the beginning of the study. The posttest was administered to both groups at the end of the study. The qualitative data were collected using semi-structured interviews with a sample of eight students in the experimental group. The interviews were conducted after the posttest. The quantitative data were analyzed using independent sample T-tests. The qualitative data were analyzed using thematic analysis. The quantitative data showed that students in the experimental group, who were taught using the engineering design process, had significantly higher post-test scores on physics problem-solving than students in the control group, who were taught using the conventional method. The qualitative data showed that students in the experimental group were more motivated and engaged in the learning process than students in the control group. Students in the experimental group also reported that they found the engineering design process to be a more effective way of learning physics. The findings of this study suggest that the engineering design process can be an effective way of enhancing student learning outcomes in physics courses. The engineering design process engages students in the learning process and helps them to develop problem-solving skills.

Keywords: engineering design process, problem-solving, learning outcome of physics, students’ physics competencies, deep learning

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6366 Reinforcement Learning for Quality-Oriented Production Process Parameter Optimization Based on Predictive Models

Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Producing faulty products can be costly for manufacturing companies and wastes resources. To reduce scrap rates in manufacturing, process parameters can be optimized using machine learning. Thus far, research mainly focused on optimizing specific processes using traditional algorithms. To develop a framework that enables real-time optimization based on a predictive model for an arbitrary production process, this study explores the application of reinforcement learning (RL) in this field. Based on a thorough review of literature about RL and process parameter optimization, a model based on maximum a posteriori policy optimization that can handle both numerical and categorical parameters is proposed. A case study compares the model to state–of–the–art traditional algorithms and shows that RL can find optima of similar quality while requiring significantly less time. These results are confirmed in a large-scale validation study on data sets from both production and other fields. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, production process optimization, evolutionary algorithms, policy optimization, actor critic approach

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6365 Glucose Monitoring System Using Machine Learning Algorithms

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

Abstract:

The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

Procedia PDF Downloads 196
6364 Enhancing French Vocabulary Acquisition: The Impact of Explicit Instruction on Productive Non-Cognate Suffixes for Beginner Learners

Authors: Deborah Idowu

Abstract:

This research delves into the effectiveness of explicitly teaching productive non-cognate French suffixes to English beginner learners of the French language. It is widely accepted that cognates, especially orthographic ones, can be inferred by learners from their first language (in this case, English). The same is the case for derived French words with cognate suffixes, provided the learner is familiar with the lemma, which can either be cognate or non-cognate. However, the same cannot be said for derived French words with non-cognate suffixes. These suffixes often pose challenges to learners, even when the base word is familiar to them. The primary goal of this research is to enhance the vocabulary comprehension and expansion of English-speaking beginners in French by focusing on the recognition of derived French words that may not align with their L1 knowledge. The methodology employed in this study of derivational morphology involves an experimental group receiving explicit instruction on productive non-cognate suffixes, while a control group does not. By utilizing confidence ratings and other analytical tools, the analysis aims to measure the impact of this targeted instruction on the learners' ability to understand and incorporate non-cognate suffixes into their French vocabulary. Through this experimental approach, the research seeks to provide valuable insights into how explicit instruction on non-cognate suffixes can benefit beginner French learners, ultimately aiding them in navigating the intricacies of French derivational morphology. The objectives of this research are as follows: i. to investigate the impact of explicitly teaching productive non-cognate suffixes on the vocabulary comprehension and expansion of beginner learners of the French language; ii. to assess the effectiveness of targeted instruction on non-cognate suffixes in aiding English-speaking learners in recognizing and understanding derived French words that may not align with their native language knowledge, iii. to compare the vocabulary acquisition and retention of beginner French learners who receive explicit instruction on non-cognate suffixes with those who do not to determine the effectiveness of this instructional approach, iv. to analyze the confidence ratings and other analytical methods to gauge the learners' ability to integrate non-cognate suffixes into their French vocabulary and comprehend the meaning of derived words more effectively, v. to contribute insights into how explicit instruction on non-cognate suffixes can enhance the overall language learning experience for beginner learners of French, particularly in the area of French derivational morphology.

Keywords: suffixes, derivational morphology, non-cognates, vocabulary acquisition, French language learners

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6363 Integrated Models of Reading Comprehension: Understanding to Impact Teaching—The Teacher’s Central Role

Authors: Sally A. Brown

Abstract:

Over the last 30 years, researchers have developed models or frameworks to provide a more structured understanding of the reading comprehension process. Cognitive information processing models and social cognitive theories both provide frameworks to inform reading comprehension instruction. The purpose of this paper is to (a) provide an overview of the historical development of reading comprehension theory, (b) review the literature framed by cognitive information processing, social cognitive, and integrated reading comprehension theories, and (c) demonstrate how these frameworks inform instruction. As integrated models of reading can guide the interpretation of various factors related to student learning, an integrated framework designed by the researcher will be presented. Results indicated that features of cognitive processing and social cognitivism theory—represented in the integrated framework—highlight the importance of the role of the teacher. This model can aid teachers in not only improving reading comprehension instruction but in identifying areas of challenge for students.

Keywords: explicit instruction, integrated models of reading comprehension, reading comprehension, teacher’s role

Procedia PDF Downloads 93
6362 Students’ Post COVID-19 Experiences with E-Learning Platforms among Undergraduate Students of Public Universities in the Ashanti Region, Ghana

Authors: Michael Oppong, Stephanie Owusu Ansah, Daniel Ofori

Abstract:

The study investigated students’ post-covid-19 experiences with e-learning platforms among undergraduate students of public universities in the Ashanti region of Ghana. The study respectively drew 289 respondents from two public universities, i.e., Kwame Nkrumah University of Science and Technology (KNUST) Business School and the Kumasi Technical University (KsTU) Business School in Ghana. Given that the population from the two public universities was fairly high, sampling had to be done. The overall population of the study was 480 students randomly sampled from the two public universities using the sampling ratio given by Alreck and Settle (2004). The population constituted 360 students from the Kwame Nkrumah University of Science and Technology (KNUST) Business School and 120 from the Kumasi Technical University Business School (KsTU). The study employed questionnaires as a data collection tool. The data gathered were 289 responses out of 480 questionnaires administered, representing 60.2%. The data was analyzed using pie charts, bar charts, percentages, and line graphs. Findings revealed that the e-learning platforms were still useful. However, the students used it on a weekly basis post-COVID-19, unlike in the COVID-19 era, where it was used daily. All other academic activities, with the exception of examinations, are still undertaken on the e-learning platforms; however, it is underutilized in the post-COVID-19 experience. The study recommends that universities should invest in infrastructure development to enable all academic activities, most especially examinations, to be undertaken using the e-learning platforms to curtail future challenges.

Keywords: e-learning platform, undergraduate students, post-COVID-19 experience, public universities

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6361 Role of Special Training Centers (STC) in Right to Education Act Challenges And Remedies

Authors: Anshu Radha Aggarwal

Abstract:

As per the Right to Education Act (RTE), 2009, every child in the age group of 6-14 years shall be admitted in a neighborhood school. All the Out of School Children identified have to be enrolled / mainstreamed in to age appropriate class and there-after be provided special training. This paper addresses issues emerging from provisions in the RTE Act that specifically refer to the enrolment of out-of school children into age appropriate classes and the requirement to provide special trainings that will enable this to take place. In the context of RTE Act, the Out-of-School Children are first enrolled in the formal school and then they are provided with Special Training through NRSTCs (Long Term / Short term basis). These centers are functioning in formal school campus itself. This paper specifies the role of special training centers (STC). It presents a re-envisioning of assessment that recognizes two principal functions of assessment, assessment for learning and assessment of learning, instead of the more familiar categories of formative, diagnostic, summative, and evaluative assessment. The use of these two functions of assessment highlights and emphasizes the role of special training centers (STC) to assess their level for giving them appropriate special training and to evaluate their improvement in learning level. Challenge of problem faced by teachers to do diagnostic assessment, including its place in the sequence of assessment procedures appropriate in identifying and addressing individual children’s learning difficulties are solved by special training centers (STC). It is important that assessment is used to identify children with learning difficulties at the earliest possible stage so that appropriate support and intervention can be put in place. So appropriate challenges with tools are presented here for their assessment at entry level and at completion level of primary children by special training centers (STC).

Keywords: right to education, assessment, challenges, out of school children

Procedia PDF Downloads 457