Search results for: learning benefits

Authors: Paulomi (Polly) Burey, Zoe Lynch

Abstract:

In STEM education, students often have difficulty linking static images and words from textbooks or online resources, to the underlying mechanisms of the topic of study. This can often dissuade some students from pursuing study in the physical and chemical sciences. A growing movement in current day students demonstrates that the YouTube generation feel they learn best from video or dynamic, interactive learning tools, and will seek these out as alternatives to their textbooks and the classroom learning environment. Chemistry, and in particular visualization of molecular structures in everyday materials, can prove difficult to comprehend without significant interaction with the teacher of the content and concepts, beyond the timeframe of a typical class. This can cause a learning hurdle for distance education students, and so it is necessary to provide strong electronic tools and resources to aid their learning. As one of the electronic resources, an animation design approach to link everyday materials to their underlying chemistry would be beneficial for student learning, with the focus here being on food. These animations were designed and storyboarded with a scaling approach and commence with a focus on the food material itself and its component parts. This is followed by animated transitions to its underlying microstructure and identifying features, and finally showing the molecules responsible for these microstructural features. The animation ends with a reverse transition back through the molecular structure, microstructure, all the way back to the original food material, and also animates some reactions that may occur during food processing to demonstrate the purpose of the underlying chemistry and how it affects the food we eat. Using this cyclical approach of linking students’ existing knowledge of food to help guide them to understanding more complex knowledge, and then reinforcing their learning by linking back to their prior knowledge again, enhances student understanding. Food is also an ideal material system for students to interact with, in a hands-on manner to further reinforce their learning. These animations were launched this year in a 2nd year University Food Chemistry course with improved learning outcomes for the cohort.

Keywords: chemistry, food science, future pedagogy, STEM Education

Procedia PDF Downloads 159

Authors: Avi Shrivastava

Abstract:

Our world continues to grapple with a lot of social issues. Economic growth and scientific advancements have not completely eradicated poverty, homelessness, discrimination and bias, gender inequality, health issues, mental illness, addiction, and other social issues. So, how do we improve the human condition in a world driven by advanced technology? The answer is simple: we will have to leverage technology to address some of the most important social challenges of the day. AI, or artificial intelligence, has emerged as a critical tool in the battle against issues that deprive marginalized and disadvantaged groups of the right to enjoy benefits that a society offers. Social work professionals can transform their lives by harnessing it. The lack of reliable data is one of the reasons why a lot of social work projects fail. Social work professionals continue to rely on expensive and time-consuming primary data collection methods, such as observation, surveys, questionnaires, and interviews, instead of tapping into AI-based technology to generate useful, real-time data and necessary insights. By leveraging AI’s data-mining ability, we can gain a deeper understanding of how to solve complex social problems and change lives of people. We can do the right work for the right people and at the right time. For example, AI can enable social work professionals to focus their humanitarian efforts on some of the world’s poorest regions, where there is extreme poverty. An interdisciplinary team of Stanford scientists, Marshall Burke, Stefano Ermon, David Lobell, Michael Xie, and Neal Jean, used AI to spot global poverty zones – identifying such zones is a key step in the fight against poverty. The scientists combined daytime and nighttime satellite imagery with machine learning algorithms to predict poverty in Nigeria, Uganda, Tanzania, Rwanda, and Malawi. In an article published by Stanford News, Stanford researchers use dark of night and machine learning, Ermon explained that they provided the machine-learning system, an application of AI, with the high-resolution satellite images and asked it to predict poverty in the African region. “The system essentially learned how to solve the problem by comparing those two sets of images [daytime and nighttime].” This is one example of how AI can be used by social work professionals to reach regions that need their aid the most. It can also help identify sources of inequality and conflict, which could reduce inequalities, according to Nature’s study, titled The role of artificial intelligence in achieving the Sustainable Development Goals, published in 2020. The report also notes that AI can help achieve 79 percent of the United Nation’s (UN) Sustainable Development Goals (SDG). AI is impacting our everyday lives in multiple amazing ways, yet some people do not know much about it. If someone is not familiar with this technology, they may be reluctant to use it to solve social issues. So, before we talk more about the use of AI to accomplish social work objectives, let’s put the spotlight on how AI and social work can complement each other.

Keywords: social work, artificial intelligence, AI based social work, machine learning, technology

Procedia PDF Downloads 101

Authors: Avinash Kharel

Abstract:

Recreational soccer (RS) as a medium of small-sided soccer game (SSG) has an immense positive effect on physical health, mental health and wellbeing. The RS has reflected both acute responses and long-term effects of training on sedentary, trained and clinical population on any age, gender or health status. The enjoyable mode of training elicits greater adherence by optimising intrinsic motivation while offering health benefits that match those achieved by treadmill and cycle ergometer programmes both as continuous and interval forms of training. Additionally, recreational soccer is effective and efficient regimens with highlighted social, motivational and competitive components overcoming the barriers such as cost-efficiency, time-efficiency, assess to facilities and intrinsic motivation. Further, it can be applied as an effective broad-spectrum non-pharmacological treatment of lifestyle diseases producing a positive physiological response in healthy subjects, patients and elderly people regardless of age, gender or training experience.

Keywords: recreational soccer, health benefits, diseases prevention, physiology

Procedia PDF Downloads 87

Authors: Zeeshan Hamid, Asher Ramish

Abstract:

The purpose of this paper is to focus on security and safety issues facing by pharmaceutical industry globally when counterfeit drugs are in question. Hence, there is an intense need to secure and authenticate pharmaceutical products in the emerging counterfeit product market. This paper will elaborate the application of radio frequency identification (RFID) in pharmaceutical industry and to identify its key benefits for patient’s care. The benefits are: help to co-ordinate the stream of supplies, accuracy in chains of supplies, maintaining trustworthy information, to manage the operations in appropriate and timely manners and finally deliver the genuine drug to patient. It is discussed that how RFID supported supply chain information sharing (SCIS) helps to combat against counterfeit drugs. And a solution how to tag pharmaceutical products; since, some products prevent RFID implementation in this industry. In this paper, a proposed model for pharma industry distribution suggested to combat against the counterfeit drugs when they are in supply chain.

Keywords: supply chain, RFID, pharmaceutical industry, counterfeit drugs, patients care

Procedia PDF Downloads 311

Authors: W. S. Barber, S. L. King

Abstract:

This paper is a qualitative case study analysis of the development of a fully online learning community of graduate students through arts-based community building activities. With increasing numbers and types of online learning spaces, it is incumbent upon educators to continue to push the edge of what best practices look like in digital learning environments. In digital learning spaces, instructors can no longer be seen as purveyors of content knowledge to be examined at the end of a set course by a final test or exam. The rapid and fluid dissemination of information via Web 3.0 demands that we reshape our approach to teaching and learning, from one that is content-focused to one that is process-driven. Rather than having instructors as formal leaders, today’s digital learning environments require us to share expertise, as it is the collective experiences and knowledge of all students together with the instructors that help to create a very different kind of learning community. This paper focuses on innovations pursued in a 36 hour 12 week graduate course in higher education entitled “Critical and Reflective Practice”. The authors chronicle their journey to developing a fully online learning community (FOLC) by emphasizing the elements of social, cognitive, emotional and digital spaces that form a moving interplay through the community. In this way, students embrace anywhere anytime learning and often take the learning, as well as the relationships they build and skills they acquire, beyond the digital class into real world situations. We argue that in order to increase student online engagement, pedagogical approaches need to stem from two primary elements, both creativity and critical reflection, that are essential pillars upon which instructors can co-design learning environments with students. The theoretical framework for the paper is based on the interaction and interdependence of Creativity, Intuition, Critical Reflection, Social Constructivism and FOLCs. By leveraging students’ embedded familiarity with a wide variety of technologies, this case study of a graduate level course on critical reflection in education, examines how relationships, quality of work produced, and student engagement can improve by using creative and imaginative pedagogical strategies. The authors examine their professional pedagogical strategies through the lens that the teacher acts as facilitator, guide and co-designer. In a world where students can easily search for and organize information as self-directed processes, creativity and connection can at times be lost in the digitized course environment. The paper concludes by posing further questions as to how institutions of higher education may be challenged to restructure their credit granting courses into more flexible modules, and how students need to be considered an important part of assessment and evaluation strategies. By introducing creativity and critical reflection as central features of the digital learning spaces, notions of best practices in digital teaching and learning emerge.

Keywords: online, pedagogy, learning, communities

Procedia PDF Downloads 403

Authors: Bulatbayeva A. A., Maxutova I. O., Ergalieva A. N.

Abstract:

This article presents a study of the practice of self-assessment of the quality of training cadets in a military higher specialized educational institution. The research was carried out by means of a questionnaire survey aimed at identifying the degree of satisfaction of cadets with the organization of the educational process, quality of teaching, the quality of the organization of independent work, and the system of their assessment. In general, the results of the study are of an intermediate nature. Proven tools will be incorporated into the planning and effective management of the learning process. The results of the study can be useful for the administrators and managers of the military education system for teachers of military higher educational institutions for adjusting the content and technologies of training future specialists. The publication was prepared as part of applied grant research for 2020-2022 by order of the Ministry of Education and Science of the Republic of Kazakhstan on the topic "Development of a comprehensive methodology for assessing the quality of education of graduates of military special educational institutions."

Keywords: teaching quality, quality satisfaction, learning management, quality management, process approach, classroom learning, interactive technologies, teaching quality

Procedia PDF Downloads 126

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 212

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 75

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 158

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 41

Authors: John Acire, Wilfred Lajul, Ogwang Tom

Abstract:

Using a qualitative research technique, this study investigates the influence of Early Childhood Education (ECE) on learning outcomes in lower primary schools in Gulu City, Uganda. The study, which is based on Vygotsky's sociocultural theory of human learning, fills gaps in the current literature on the influence of ECE on learning outcomes. The aims of the study include analyzing the state of learning outcomes, investigating ECE practices, and determining the influence of these practices on learning outcomes in lower primary schools. The findings highlight the critical significance of ECE in promoting children's overall development. Nursery education helps children improve their handwriting, reading abilities, and general cognitive development. Children who have received nursery education have improved their abilities to handle pencils, form letters, and engage in social interactions, highlighting the significance of fine motor skills and socializing. Despite the good elements, difficulties in implementing ECE practices were found, such as differences in teaching styles, financial limits, and potential weariness due to prolonged school hours. The study suggests focused interventions to improve the effectiveness of ECE practices, ensure their connection with educational goals and maximize their influence on children's development. The study's findings show that respondents agree on the importance of nursery education in supporting holistic development, socialization, language competency, and conceptual comprehension. Challenges in nursery education, such as differences in teaching techniques and insufficient resources, highlight the need for comprehensive measures to address these challenges. Furthermore, parental engagement in home learning activities was revealed as an important factor affecting early education outcomes. Children who were engaged at home performed better in lower primary, emphasizing the value of a supportive family environment. Finally, the report suggests measures to enhance parental participation, changes in teaching methods through retraining, and age-appropriate enrolment. Future studies might concentrate on the involvement of parents, ECE policy practice, and the influence of ECE teachers on lower primary school learning results. These ideas are intended to help create a more favorable learning environment by encouraging holistic development and preparing children for success in succeeding academic levels.

Keywords: early childhood education, learning outcomes in lower primary schools, early childhood education practices, how ECE practices influence learning outcomes in lower primary schools

Procedia PDF Downloads 40

Authors: Halima Musa Kamilu

Abstract:

This paper discusses the effective strategies for teaching English language to learners in primary schools in Nigeria. English language development is the systematic use of instructional strategies designed to promote the acquisition of English by pupils in primary schools whose primary language is not English. Learning a second language is through total immersion. These strategies support this learning method, allowing pupils to have the knowledge of English language in a pattern similar to the way they learned their native language through regular interaction with others who already know the language. The focus is on fluency and learning to speak English in a social context with native speakers. The strategies allow for effective acquisition. The paper also looked into the following areas: visuals that reinforce spoken or written words, employ gestures for added emphasis, adjusting of speech, stressing of high-frequency vocabulary words, use of fewer idioms and clarifying the meaning of words or phrases in context, stressing of participatory learning and maintaining a low anxiety level and boosting of enthusiasm. It recommended that the teacher include vocabulary words that will make the content more comprehensible to the learner.

Keywords: effective, strategies, teaching, beginners and primary schools

Procedia PDF Downloads 492

Authors: Majid Alsubaie, Hamed Sarbazhosseini

Abstract:

Many working environments have experienced increased uncertainty due to the fast-moving and unpredictable world. IT systems development projects, in particular, face several challenges because of their rapidly changing environments and emerging technologies. Information technology organizations within these contexts adapt systems development methodology and new software approaches to address this issue. One of these methodologies is the Agile method, which has gained huge attention in recent years. However, due to failure rates in IT projects, there is an increasing demand for the use of hybrid Agile methods among organizations. The scarce research in the area means that organizations do not have solid evidence-based knowledge for the use of hybrid Agile. This research was designed to provide further insights into the development of hybrid Agile methods within systems development projects, including how frameworks and processes are used and what benefits and challenges are gained and faced as a result of hybrid Agile methods. This paper presents how three organizations (two government and one private) use hybrid Agile methods in their Agile environments. The data was collected through interviews and a review of relevant documents. The results indicate that these organizations do not predominantly use pure Agile. Instead, they are waterfall organizations by virtue of systems nature and complexity, and Agile is used underneath as the delivery model. Prince2 Agile framework, SAFe, Scrum, and Kanban were the identified models and frameworks followed. This study also found that customer satisfaction and the ability to build quickly are the most frequently perceived benefits of using hybrid Agile methods. In addition, team resistance and scope changes are the common challenges identified by research participants in their working environments. The findings can help to understand Agile environmental conditions and projects that can help get better success rates and customer satisfaction.

Keywords: agile, hybrid, IT systems, management, success rate, technology

Procedia PDF Downloads 107

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 143

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 230

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 80

Authors: Manana Lobzhanidze

Abstract:

The COVID-19 pandemic has made significant changes in migration processes, notably changes in the study migration process. The constraints caused by the COVID-19 pandemic led to changes in the studying process, which negatively affected its efficiency. The educational process has partially or completely shifted to distance learning; Both labor and study migration have increased significantly in the world. The employment and education market has become global and consequently, a number of challenges have arisen for employers, researchers, and businesses. The role of preparing qualified personnel in achieving high productivity is justified, the benefits for employers and employees are assessed on the one hand, and the role of study migration for the country’s development is examined on the other hand. Research methods. The research is based on methods of analysis and synthesis, quantitative and qualitative, groupings, relative and mean quantities, graphical representation, comparison, analysis and etc. In-depth interviews were conducted with experts to determine quantitative and qualitative indicators. Research findings. Factors affecting study migration are analysed in the paper and the environment that stimulates migration is explored. One of the driving forces of migration is considered to be the desire for receiving higher pay. Levels and indicators of study migration are studied by country. Comparative analysis has found that study migration rates are high in countries where the price of skilled labor is high. The productivity of individuals with low skills is low, which negatively affects the economic development of countries. It has been revealed that students leave the country to improve their skills during study migration. The process mentioned in the article is evaluated as a positive event for a developing country, as individuals are given the opportunity to share the technology of developed countries, gain knowledge, and then introduce it in their own country. The downside of study migration is the return of a small proportion of graduates from developed economies to their home countries. The article concludes that countries with emerging economies devote less resources to research and development, while this is a priority in developed countries, allowing highly skilled individuals to use their skills efficiently. The paper studies the national education system examines the level of competition in the education market and the indicators of educational migration. The level of competition in the education market and the indicators of educational migration are studied. The role of qualified personnel in achieving high productivity is substantiated, the benefits of employers and employees are assessed on the one hand, and the role of study migration in the development of the country is revealed on the other hand. The paper also analyzes the level of competition in the education and labor markets and identifies indicators of study migration. During the pandemic period, there was a great demand for the digital technologies. Open access to a variety of comprehensive platforms will significantly reduce study migration to other countries. As a forecast, it can be said that the intensity of the use of e-learning platforms will be increased significantly in the post-pandemic period. The paper analyzes the positive and negative effects of study migration on economic development, examines the challenges of study migration in light of the COVID-19 pandemic, suggests ways to avoid negative consequences, and develops recommendations for improving the study migration process in the post-pandemic period.

Keywords: study migration, COVID-19 pandemic, factors affecting migration, economic development, post-pandemic migration

Procedia PDF Downloads 125

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 312

Authors: Muhalim Muhalim

Abstract:

Drawing on Lakoff’s theory of metaphor conceptualization, this article explores the conceptualization of language two writing (L2W) of ten students-teachers in Indonesia via metaphors. The ten postgraduate English language teaching students and at the same time (former) English teachers received seven days of intervention in teaching and learning L2. Using introspective log and focus group discussion, the results illuminate us that all participants are unanimous on perceiving L2W as process-oriented rather than product-oriented activity. Specifically, the metaphor conceptualizations exhibit three categories of process-oriented L2W: deliberate process, learning process, and problem-solving process. However, it has to be clarified from the outset that this categorization is not rigid because some of the properties of metaphors might belong to other categories. Results of the study and implications for English language teaching will be further discussed.

Keywords: metaphor conceptualisation, second language, learning writing, teaching writing

Procedia PDF Downloads 411

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

Procedia PDF Downloads 193

Authors: Ailene B. Anonuevo

Abstract:

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

Procedia PDF Downloads 223

Authors: Prajwal Prakash Vasisht, Sharath Rajamurthy, Nishanth Dara

Abstract:

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

Procedia PDF Downloads 46

Authors: Cindy Davis

Abstract:

Higher education is changing globally and there is increasing pressure from professional social work accreditation bodies for academic programs to demonstrate how students have successfully met mandatory graduate competencies. As professional accreditation organizations increase their demand for evidence of graduate competencies, strategies to document and recording learning outcomes becomes increasingly challenging for academics and students. Studies in higher education have found support for the pedagogical value of ePortfolios, a flexible personal learning space that is owned by the student and include opportunity for assessment, feedback and reflection as well as a virtual space to store evidence of demonstration of professional competencies and graduate attributes. Examples of institutional uses of ePortfolios include e-administration of a diverse student population, assessment of student learning, and the demonstration of graduate attributes attained and future student career preparation. The current paper presents a case study on the introduction of ePortfolios for social work graduates in Australia as part of an institutional approach to technology-enhanced learning and e-learning. Social work graduates were required to submit an ePortfolio hosted on PebblePad. The PebblePad platform was selected because it places the student at the center of their learning whilst providing powerful tools for staff to structure, guide and assess that learning. The ePortofolio included documentation and evidence of how the student met each graduate competency as set out by the social work accreditation body in Australia (AASW). This digital resource played a key role in the process of external professional accreditation by clearly documenting and evidencing how students met required graduate competencies. In addition, student feedback revealed a positive outcome on how this resource provided them with a consolidation of their learning experiences and assisted them in obtaining employment post-graduation. There were also significant institutional factors that were key to successful implementation such as investment in the digital technology, capacity building amongst academics, and technical support for staff and students.

Keywords: accreditation, social work, teaching, technology

Procedia PDF Downloads 138

Authors: Theodorou Kyriaki, Ypsilantis George

Abstract:

Vocabulary learning has attracted a lot of attention in recent years, contrary to the neglected part of the past. Along with the interest in finding successful vocabulary teaching strategies, many scholars focused on locating learning strategies used by language learners. As a result, more and more studies in the area of language pedagogy have been investigating the use of strategies in vocabulary learning by different types of learners. A common instrument in this field is the questionnaire, a tool of work that was enriched by questions involving current technology, and it was further implemented to a sample of 300 Greek students whose age varied from 9 and 17 years. Strategies located were grouped into the three categories of memory, cognitive, and compensatory type and associations between these dependent variables were investigated. In addition, relations between dependent and independent variables (such as age, sex, type of school, cultural background, and grade in English) were pursued to investigate the impact on strategy selection. Finally, results were compared to findings of other studies in the same field to contribute to a hypothesis of ethnic differences in strategy selection. Results initially discuss preferred strategies of all participants and further indicate that: a) technology affects strategy selection while b) differences between ethnic groups are not statistically significant. A number of successful strategies are presented, resulting from correlations of strategy selection and final school grade in English.

Keywords: acquisition of English, internet technology, research among Greek students, vocabulary learning strategies

Procedia PDF Downloads 508

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

Procedia PDF Downloads 92

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

Procedia PDF Downloads 492

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 104

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 390

Authors: Jennifer Nutton, Gayle Ployer, Ky Scott, Jenny Morgan

Abstract:

Working in a circle within higher education creates a decolonial space of mutual respect, responsibility, and reciprocity that facilitates collaborative learning and deep connections among learners and instructors. This approach is beyond simply facilitating a group in a circle but opens the door to creating a sacred space connecting each member to the land, to the Indigenous peoples who have taken care of the lands since time immemorial, to one another, and to one’s own positionality. These deep connections not only center human knowledges and relationships but also acknowledges responsibilities to land. Working in a circle as a relational pedagogical praxis also disrupts institutional power dynamics by creating a space of collaborative learning and deep connections in the classroom. Inherent within circle work is to facilitate connections not just academically but emotionally, physically, culturally, and spiritually. Recent literature supports the use of online talking circles, finding that it can offer a more relational and experiential learning environment, which is often absent in the virtual world and has been made more evident and necessary since the pandemic. These deeper experiences of learning and connection, rooted in both knowledge and the land, can then be shared with openness and vulnerability with one another, facilitating growth and change. This process of beginning with the land is critical to ensure we have the grounding to obstruct the ongoing realities of colonialism. The authors, who identify as both Indigenous and non-Indigenous, as both educators and learners, reflect on their teaching and learning experiences in circle. They share a relational pedagogical praxis framework that has been successful in educating future social workers, environmental activists, and leaders in social and human services, health, legal and political fields.

Keywords: circle work, relational pedagogies, decolonization, distance education

Procedia PDF Downloads 75

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

Procedia PDF Downloads 64