Search results for: traditional learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10894

Search results for: traditional learning

10414 Analysis of Cooperative Learning Behavior Based on the Data of Students' Movement

Authors: Wang Lin, Li Zhiqiang

Abstract:

The purpose of this paper is to analyze the cooperative learning behavior pattern based on the data of students' movement. The study firstly reviewed the cooperative learning theory and its research status, and briefly introduced the k-means clustering algorithm. Then, it used clustering algorithm and mathematical statistics theory to analyze the activity rhythm of individual student and groups in different functional areas, according to the movement data provided by 10 first-year graduate students. It also focused on the analysis of students' behavior in the learning area and explored the law of cooperative learning behavior. The research result showed that the cooperative learning behavior analysis method based on movement data proposed in this paper is feasible. From the results of data analysis, the characteristics of behavior of students and their cooperative learning behavior patterns could be found.

Keywords: behavior pattern, cooperative learning, data analyze, k-means clustering algorithm

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10413 AI-Driven Forecasting Models for Anticipating Oil Market Trends and Demand

Authors: Gaurav Kumar Sinha

Abstract:

The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

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10412 A Comparison of Methods for Neural Network Aggregation

Authors: John Pomerat, Aviv Segev

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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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10411 Investigating the Effect of Handicrafts Recreation on the Interior Design of Traditional Arts Gallery

Authors: Amir Masoud Dabagh, Mahsa Khaleghi

Abstract:

The world has entered a new phase of cultural, social, economic, and so on in the last two centuries. Apart from its positive benefits and achievements to the world, it has also incurred many costs, most of which can be mentioned as destroying or at least diminishing the role of the costumes, traditions and authentic culture of the past communities. Understanding what lasts in traditional arts is vital and worthy of study because receiving it and embracing art and forms of art using that last the artistic creation removes the age-old color and smell of its face, making it immortal and persistent in all ages. This paper attempts to present traditional art concepts and solutions for interior design with the approach of handicrafts recreation as a symbol and manifestation of national identity and proof of ancient civilizations, which is at the center of tourists' attention today. The research method is a descriptive-analytical one that first explores the theoretical foundations of research, which are the concepts of recreation and traditional arts, and analyzes the process of recreation that conceals the recollection of past experiences as well as the dynamics and creativity.

Keywords: recreation, handicrafts, interior design, concept, traditional arts

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10410 Virtua-Gifted and Non-Gifted Students’ Motivation toward Virtual Flipped Learning from L2 Motivational Self-System Lense

Authors: Kamal Heidari

Abstract:

Covid-19 has borne drastic effects on different areas of society, including the education area, in that it brought virtual education to the center of attention, as an alternative to in-person education. In virtual education, the importance of flipped learning doubles, as students are supposed to take the main responsibility of teaching/learning process; and teachers play merely a facilitative/monitoring role. Given the students’ responsibility in virtual flipped learning, students’ motivation plays a pivotal role in the effectiveness of this learning method. The L2 Motivational Self-System (L2MSS) model is a currently proposed model elaborating on students’ motivation based on three sub-components: ideal L2 self, ought-to L2 self, and L2 learning experience. Drawing on an exploratory sequential mixed-methods research design, this study probed the effect of virtual flipped learning (via SHAD platform) on 112 gifted and non-gifted students’ motivation based on the L2 MSS. This study uncovered that notwithstanding the point that virtual flipped learning improved both gifted and non-gifted students’ motivation, it differentially affected their motivation. In other words, gifted students mostly referred to ideal L2 self, while non-gifted ones referred to ought-to L2 self and L2 learning experience aspects of motivation.

Keywords: virtual flipped learning, giftedness, motivation, L2MSS

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10409 Models and Metamodels for Computer-Assisted Natural Language Grammar Learning

Authors: Evgeny Pyshkin, Maxim Mozgovoy, Vladislav Volkov

Abstract:

The paper follows a discourse on computer-assisted language learning. We examine problems of foreign language teaching and learning and introduce a metamodel that can be used to define learning models of language grammar structures in order to support teacher/student interaction. Special attention is paid to the concept of a virtual language lab. Our approach to language education assumes to encourage learners to experiment with a language and to learn by discovering patterns of grammatically correct structures created and managed by a language expert.

Keywords: computer-assisted instruction, language learning, natural language grammar models, HCI

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10408 Using Diagnostic Assessment as a Learning and Teaching Approach to Identify Learning Gaps at a Polytechnic

Authors: Vijayan Narayananayar

Abstract:

Identifying learning gaps is crucial in ensuring learners have the necessary knowledge and skills to succeed. The Learning and Teaching (L&T) approach requires tutors to identify gaps in knowledge and improvise learning activities to close them. One approach to identifying learning gaps is through diagnostic assessment, which uses well-structured questions and answer options. The paper focuses on the use of diagnostic assessment as a learning and teaching approach in a foundational module at a polytechnic. The study used diagnostic assessment over two semesters, including the COVID and post-COVID semesters, to identify gaps in learning. The design of the diagnostic activity, pedagogical intervention, and survey responses completed by learners were analyzed. Results showed that diagnostic assessment can be an effective tool for identifying learning gaps and designing interventions to address them. Additionally, the use of diagnostic assessment provides an opportunity for tutors to engage with learners on a one-to-one basis, tailoring teaching to individual needs. The paper also discusses the design of diagnostic questions and answer options, including characteristics that need to be considered in achieving the target of identifying learning gaps. The implications of using diagnostic assessment as a learning and teaching approach include bridging the gap between theory and practice, and ensuring learners are equipped with skills necessary for their future careers. This paper can be useful in helping educators and practitioners to incorporate diagnostic assessment into their L&T approach.

Keywords: assessment, learning & teaching, diagnostic assessment, analytics

Procedia PDF Downloads 85
10407 The Impact of Training Method on Programming Learning Performance

Authors: Chechen Liao, Chin Yi Yang

Abstract:

Although several factors that affect learning to program have been identified over the years, there continues to be no indication of any consensus in understanding why some students learn to program easily and quickly while others have difficulty. Seldom have researchers considered the problem of how to help the students enhance the programming learning outcome. The research had been conducted at a high school in Taiwan. Students participating in the study consist of 330 tenth grade students enrolled in the Basic Computer Concepts course with the same instructor. Two types of training methods-instruction-oriented and exploration-oriented were conducted. The result of this research shows that the instruction-oriented training method has better learning performance than exploration-oriented training method.

Keywords: learning performance, programming learning, TDD, training method

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10406 The Relation between Learning Styles and English Achievement in the Language Training Centre

Authors: Nurul Yusnita

Abstract:

Many studies have been developed to help the students to get good achievement in English learning. They can be from the teaching method or psychological ones. One of the psychological studies in educational research is learning style. In some ways, learning style can affect the achievement of the students. This study aimed to examine 4 (four) learning styles and their relations to English achievement among the students learning English in Language Training Center of Universitas Muhammadiyah Yogyakarta (LTC UMY). The method of this study was descriptive analytical. The sample consisted of 39 Accounting students in LTC UMY. The data was collected through questionnaires with Likert-scale. The achievement was obtained from the grade of the students. To analyze the questionnaires and to see the relation between the learning styles and the student achievement, SPSS statistical software of correlational analysis was used. The result showed that both visual and auditory had the same percentage of 35.9% (14 students). 3 students (7.7%) had kinaesthetic learning style and 8 students (20.5%) had visual and auditory ones. Meanwhile, there were 5 students (12.8%) who had visual learning style could increase their grades. Only 1 student (2.5%) who had visual and auditory could improve his grade. Besides grade increase, there were also grade decrease. Students with visual, auditory, visual and auditory, and kinaesthetic learning styles were 3 students (7.7%), 5 students (12%), 4 students (10.2%) and 1 student (2.5%) respectively. In conclusion, there was no significant relationship between learning style and English achievement. Most of the good achievers were the students with visual and auditory learning styles and most of them preferred visual method. The implication is the teachers and material designers could improve their method through visual things to achieve effective English teaching learning.

Keywords: accounting students, English achievement, language training centre, learning styles

Procedia PDF Downloads 251
10405 Artificial Intelligence in Melanoma Prognosis: A Narrative Review

Authors: Shohreh Ghasemi

Abstract:

Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

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10404 Motivating Factors of Mobile Device Applications toward Learning

Authors: Yen-Mei Lee

Abstract:

Mobile learning (m-learning) has been applied in the education field not only because it is an alternative to web-based learning but also it possesses the ‘anytime, anywhere’ learning features. However, most studies focus on the technology-related issue, such as usability and functionality instead of addressing m-learning from the motivational perspective. Accordingly, the main purpose of the current paper is to integrate critical factors from different motivational theories and related findings to have a better understand the catalysts of an individual’s learning motivation toward m-learning. The main research question for this study is stated as follows: based on different motivational perspectives, what factors of applying mobile devices as medium can facilitate people’s learning motivations? Self-Determination Theory (SDT), Uses and Gratification Theory (UGT), Malone and Lepper’s taxonomy of intrinsic motivation theory, and different types of motivation concepts were discussed in the current paper. In line with the review of relevant studies, three motivating factors with five essential elements are proposed. The first key factor is autonomy. Learning on one’s own path and applying personalized format are two critical elements involved in the factor of autonomy. The second key factor is to apply a build-in instant feedback system during m-learning. The third factor is creating an interaction system, including communication and collaboration spaces. These three factors can enhance people’s learning motivations when applying mobile devices as medium toward learning. To sum up, in the currently proposed paper, with different motivational perspectives to discuss the m-learning is different from previous studies which are simply focused on the technical or functional design. Supported by different motivation theories, researchers can clearly understand how the mobile devices influence people’s leaning motivation. Moreover, instructional designers and educators can base on the proposed factors to build up their unique and efficient m-learning environments.

Keywords: autonomy, learning motivation, mobile learning (m-learning), motivational perspective

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10403 A Study of Learning to Enhance Ability Career Skills Consistent With Disruptive Innovation in Creative Strategies for Advertising Course

Authors: Kornchanok Chidchaisuwan

Abstract:

This project is a study of learning activities through experience to enhance career skills and technical abilities on the creative strategies for advertising course of undergraduate students. This instructional model consisted of study learning approaches: 1) Simulation-based learning: used to create virtual learning activities plans for work like working at advertising companies. 2) Project-based learning: Actual work based on the processed creating and focus on producing creative works to present on new media channels. The results of learning management found that there were effects on the students in various areas, including 1) The learners have experienced in the step by step of advertising work process. 2) The learner has the skills to work from the actual work (Learning by Doing), allowing the ability to create, present, and produce the campaign accomplished achievements and published on online media at a better level.

Keywords: technical, advertising, presentation, career skills, experience, simulation based learning

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10402 Nutrition Strategy Using Traditional Tibetan Medicine in the Preventive Measurement

Authors: Ngawang Tsering

Abstract:

Traditional Tibetan medicine is primarily focused on promoting health and keeping away diseases from its unique in prescribing specific diet and lifestyle. The prevalence of chronic diseases has been rising day by day and kills a number of people due to the lack of proper nutritional design in modern times. According to traditional Tibetan medicine, chronic diseases such as diabetes, cancer, cardiovascular diseases, respiratory diseases, and arthritis are heavily associated with an unwholesome diet and inappropriate lifestyles. Diet and lifestyles are the two main conditions of diseases and healthy life. The prevalence of chronic diseases is one of the challenges, with massive economic impact and expensive health issues. Though chronic diseases are challenges, it has a solution in the preventive measurements by using proper nutrition design based on traditional Tibetan medicine. Until today, it is hard to evaluate whether traditional Tibetan medicine nutrition strategy could play a major role in preventive measurement as of the lack of current research evidence. However, compared with modern nutrition, it has an exclusive valuable concept, such as a holistic way and diet or nutrition recommendation based on different aspects. Traditional Tibetan medicine is one of the oldest ancient existing medical systems known as Sowa Rigpa (Science of Healing) highlights different aspects of dietetics and nutrition, namely geographical, seasonal, age, personality, emotional, food combination, the process of individual metabolism, potency, and amount of food. This article offers a critical perspective on the preventive measurement against chronic diseases through nutrition design using traditional Tibetan medicine and also needs attention for a deeper understanding of traditional Tibetan medicine in the modern world.

Keywords: traditional Tibetan medicine, nutrition, chronic diseases, preventive measurement, holistic approach, integrative

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10401 The Results of Research Based-Learning for Developing the Learning and Innovation Skills of Undergraduate Students

Authors: Jatuphum Ketchatturat

Abstract:

The objective of this research was to study the learning and innovation skills of undergraduate students after Research-Based Learning had been applied. Eighty research participants were selected from undergraduate students enrolled in Educational Research Program using the Purposive Sampling Method. Research Methodology was Descriptive Research, the research took one semester to complete. The research instruments consisted of (1) Research Skill Assessment Form, (2) Research Quality Assessment Form, (3) Scale of learning and innovation skills 25 items. The quantitative data were analysed using descriptive statistics including, frequency, percentage, average and standard deviation. The qualitative data were analyzed using content analysis. The research results were (1) The students were able to conduct research that focused on educational research, which has a fair to the excellent level of standards of a research learning outcome, research skills, and research quality. The student’s learning and innovation skills have relating to research skills and research quality. (2) The findings found that the students have been developed to be learning and innovation skills such as systematic thinking, analytical thinking, critical thinking, creative problem solving, collaborative, research-creation, communication, and knowledge and experience sharing to friends, community and society.

Keywords: learning and innovation skills, research based learning, research skills, undergraduate students

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10400 Reconstruction and Renewal of Traditional Houses and its Impact on Tourism Development in Rasht

Authors: Parvaneh Ziviyar, Simin Armaghan

Abstract:

Traditional house in Rasht contains monuments and heritage of ancestors who once lived in these houses. These houses represent the customs, culture and lifestyle of the people of Rasht and bridge the gap between modern people and their past that is being forgotten. Maintenance of the buildings and architectural heritage together with their unique architecture and climatic related construction has an important role in tourism attraction and sustainable development. The purpose of this study was to develop a new definition of vacation shacks that is different with the definition of Cultural Heritage Organization. The place to stay and visit that is rebuilt or renovated based on traditional architectural style of Rasht and yet provides modern amenities so that it would not undermine indigenous traditional sense of the house. Data collection for this study is based on review of literature and field study. Results and the statistics of this study will prove that the research hypothesis is supported and there is a correlation between traditional houses of Rasht, as tourism–accommodation place and tourist attraction. It also indicates the capability and potential of these ancient monuments in the introduction of the culture of this land, and calling people and many tourists come to visit and stay in such places.

Keywords: architecture, traditional houses, vacation shacks, tourism

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10399 Learning to Translate by Learning to Communicate to an Entailment Classifier

Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

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10398 Yeasts Associated to Spontaneous Date Vinegar Process

Authors: F. Halladj, H. Amellal, S. Benamara

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Current consumer trends go towards natural products defined as the products obtained by a traditional manufacturing method. Vinegar is one of those products marketed; it may be industrially obtained by a submerged (fast) or traditional (slow) processes. The latter exhibited a high quality because of its complex microbiological transformations (or two-stage fermentation) by the native must flora. Moreover, although that Acetic acid bacteria have traditionally been considered to play the leading role in vinegar production, some studies have recently highlighted that also yeasts metabolism can affect traditional vinegar chemical properties in a remarkable way. Thus, the aim of this study was to monitor a traditional slow process of vinegar as applied in the south of Algeria using date with hard texture (Degla-Beida variety) to isolate and identify the involved yeasts in order to select them as starter culture. Phenotypic and molecular analysis show that the non-Saccharomyces were the main yeasts species isolated throughout the alcoholic spontaneous fermentation and they included Hanseniaspora guilliermondii and Torulaspora delbrueckii.

Keywords: date vinegar, traditional production, yeasts, Phenotypic, Algeria

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10397 Autonomous Quantum Competitive Learning

Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

Abstract:

Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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10396 Changing the Traditional Role of CFOs

Authors: Seyedmohammad Mousavian

Abstract:

Technological advancements are becoming unprecedentedly dominant everywhere. This dominance requires drastic chTechnological advancements are becoming unprecedentedly dominant everywhere. This dominance requires drastic changes in traditional thinking, procedures, and responsibilities. Chief Financial Officers (CFOs) have long played a key role in every organization around the globe and must adapt themselves to the disruptive technology which brings positive and negative points. This paper will discuss the shift of the traditional role of CFOs from just reporting toward more innovative roles like “Storytelling”, business partnering, and strategic planning.

Keywords: accounting information system, technology, data, CFO, finance

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10395 Continuity and Changes on Traditional Puppetry in Java: The Existences of Wayang Hip Hop

Authors: Taufik Hidayah

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Wayang is a traditional puppet show originated from Java. This traditional art is characterized by distinctive Hinduism influence. Wayang reflects the social life of the Javanese society. It contains Javanese philosophy, myths, magical stories, and religion, as well as educational media and transmission for noble values of Javanese society conveyed through the story. Nowadays, the performance of wayang has faced a new challenge to maintain its existence in the public life of Javanese society. Modernity has penetrated into every shape of culture. Many people consider traditional culture as old fashioned, particularly the young generation. That is one of the reasons why many people have left traditional culture. For maintaining the existence of wayang, a new art called ‘wayang hip hop’ has arisen. Wayang hip hop seeks to modify wayang show into a more modern form, but without removing any principles and main functions of wayang art. This article will discuss theoretically the changes and traditional continuity in wayang hip hop based on a literature review and qualitative approaches. Wayang hip hop uses hip-hop music as the background music in the show. It will discuss about the impact that comes with the existential strengthening of wayang hip hop especially among the Javanese society and discuss the opportunities that arise regarding the function of wayang hip-hop as a medium of education, social criticism, and cultural revitalization of the Javanese society.

Keywords: cultural revitalization, social criticism, education, continuity and change

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10394 Enhancing Experiential Learning in a Smart Flipped Classroom: A Case Study

Authors: Fahri Benli, Sitalakshmi Venkartraman, Ye Wei, Fiona Wahr

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A flipped classroom which is a form of blended learning shifts the focus from a teacher-centered approach to a learner-centered approach. However, not all learners are ready to take the active role of knowledge and skill acquisition through a flipped classroom and they continue to delve in a passive mode of learning. This challenges educators in designing, scaffolding and facilitating in-class activities for students to have active learning experiences in a flipped classroom environment. Experiential learning theories have been employed by educators in the past in physical classrooms based on the principle that knowledge could be actively developed through direct experience. However, with more of online teaching witnessed recently, there are inherent limitations in designing and simulating an experiential learning activity for an online environment. In this paper, we explore enhancing experiential learning using smart digital tools that could be employed in a flipped classroom within a higher education setting. We present the use of smart collaborative tools online to enhance the experiential learning activity to teach higher-order cognitive concepts of business process modelling as a case study.

Keywords: experiential learning, flipped classroom, smart software tools, online learning higher-order learning attributes

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10393 Developing EFL Research Skills of Pre-Master Students through a Suggested Quest Based Learning Strategy

Authors: Heba Mustafa Abdullah

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The research aimed at examining the effect of a using a quest based learning strategy on developing EFL Pre-Master Students. The study adopted the quasi-experimental design. The sample of the research consists of a group of 30 students enrolled in Pre-Master program, Curriculum and EFL Instruction Department, Faculty of Graduate Studies in Education Tools of the study included a EFL research skills checklist and EFL research skills test. Results revealed that there were statistically significant differences at 0.01 levels with regard to some research skills. Results were discussed in relation to several factors that affected the language learning process. Finally, the research provided beneficial contributions in relation to manipulating e-learning technologies in general and Quest based learning strategy in particular with respect to EFL research skills.

Keywords: English as foreign language, e-Learning, research skills, quest based learning

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10392 Federated Knowledge Distillation with Collaborative Model Compression for Privacy-Preserving Distributed Learning

Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

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10391 Perception Differences in Children Learning to Golf with Traditional versus Modified (Scaled) Equipment

Authors: Lindsey D. Sams, Dean R. Gorman, Cathy D. Lirgg, Steve W. Dittmore, Jack C. Kern

Abstract:

Golf is a lifetime sport that provides numerous physical and psychological benefits. The game has struggled with attrition and retention within minority groups and this has exposed the lack of a modified introduction to the game that is uniformly accessible and developmentally appropriate. Factors that have been related to sport participatory behaviors include perceived competence, enjoyment and intention. The purpose of this study was to examine self-reported perception differences in competence and enjoyment between learners using modified and traditional equipment as well as the potential effects these factors could have on intent for future participation. For this study, SNAG Golf was chosen to serve as the scaled equipment used by the modified equipment group. The participants in this study were 99 children (24 traditional equipment users/ 75 modified equipment users) located across the U.S. with ages ranging from 7 to 12 years (2nd-5th grade). Utilizing a convenience sampling method, data was obtained on a voluntary basis through surveys measuring children’s golf participation and self-perceptions concerning perceived competence, enjoyment and intention to continue participation. The scales used for perceived competence and enjoyment included Susan Harter’s Self-Perception Profile for Children (SPPC) along with the Physical Activity Enjoyment Scale (PACES). Analysis revealed no significant differences for enjoyment, perceived competence or intention between children learning with traditional golf equipment and modified golf equipment. This was true even though traditional equipment users reported significantly higher experience levels than that of modified users. Intention was regressed on the enjoyment and perceived competence variables. Congruent with current literature, enjoyment was a strong predictor of intention to continue participation, for both groups. Modified equipment users demonstrated significantly lower experience levels but reported similar levels of competence, enjoyment and intent to continue participation as reported by the more experienced, and potentially more skilled, traditional users. The ability to immediately generate these positive affects suggests the potential adoption of a more effective way to learn golf and a method that is conducive to participatory behaviors related to attrition and retention. These implications in turn, highlight an equipment candidate ideal for inception into physical education programs where new learners are introduced to various sports in safe and developmentally appropriate environments. A major goal of this study was to provide foundational research that instigates the further examination of golf’s introductory teaching methodologies, as there is a lack of its presence in current literature. Future research recommendations range from improvements in the current research design to expansive approaches related to the topic, such as progressive skill development, knowledge of the game’s tactical and strategic concepts, playing ability and teaching effectiveness when utilizing modified versus traditional equipment.

Keywords: adaptive sports, enjoyment, golf participation, modified equipment, perceived competence, SNAG golf

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10390 Impact of Knowledge Management on Learning Organizations

Authors: Gunmala Suri

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The purpose of this study was to investigate the relationship between various dimensions of Knowledge Management and Learning Organizations. On the basis of the dimensions of Learning Organization, Hypothesis were formulated. Knowledge Management (KM) is taken as the independent variable and Learning Organization (LO) as a dependent variable. KM had 5 dimensions and LO had 7. For this study, a total of 92 participants took part and answered the questionnaire. The respondents were selected using Judgemental and Snowball sampling. The respondents were from SMEs in and around Chandigarh. SPSS was used to for the data analysis purposes. The results showed that the dimensions of KM had a positive influence on the dimensions of LO. The hypothesis were accepted.

Keywords: knowledge management leadership, knowledge management, learning organization, knowledge management culture

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10389 A Study on Pre-Service English Teachers' Language Self Efficacy and Learning Goal Orientation

Authors: Erteki̇n Kotbaş

Abstract:

Teaching English as a Foreign Language (EFL) is on the front burner of many countries in the world, in particular for English language teaching departments that train EFL teachers. Under the head of motivational theories in foreign language education, there are numerous researches in literature. However; researches comprising English language self-efficacy and teachers’ learning goal orientation which has a positive impact on learning teachings skills are scarce. Examination of these English language self-efficacy beliefs and learning goal orientations of pre-service EFL teachers may broaden the horizons, considering the importance of self-efficacy and goal orientation on learning and teaching activities. At this juncture, present study aims to investigate the strong relationship between English language self efficacy and teachers’ learning goal orientation from Turkish context in addition to teacher students’ grade factor.

Keywords: English language, learning goal orientation, self efficacy, pre-service teachers

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10388 A Study and Design Scarf Collection Applied Vietnamese Traditional Patterns by Using Printing Method on Fabric

Authors: Mai Anh Pham Ho

Abstract:

Scarf products today is a symbol of fashion to decorate, to make our life more beautiful and bring new features to our living space. It also shows the cultural identity by using the traditional patterns that make easily to introduce the image of Vietnam to other nations all over the world. Therefore, the purpose of this research is to classify Vietnamese traditional patterns according to the era and dynasties. Vietnamese traditional patterns through the dynasties of Vietnamese history are done and classified by five groups of patterns including the geometric patterns, the natural patterns, the animal patterns, the floral patterns, and the character patterns in the Prehistoric times, the Bronze and Iron age, the Chinese domination, the Ngo-Dinh-TienLe-Ly-Tran-Ho dynasty, and the LeSo-Mac-LeTrinh-TaySon-Nguyen dynasty. Besides, there are some special kinds of Vietnamese traditional patterns like buffalo, lotus, bronze-drum, Phuc Loc Tho character, and so on. Extensive research was conducted for modernizing scarf collection applied Vietnamese traditional patterns which the fashion trend is used on creating works. The concept, target, image map, lifestyle map, motif, colours, arrangement and completion of patterns on scarf were set up. The scarf collection is designed and developed by the Adobe Illustrator program with three colour ways for each scarf. Upon completion of the research, digital printing technology is chosen for using on scarf collection which Vietnamese traditional patterns were researched deeply and widely with the purpose of establishment the basic background for Vietnamese culture in order to identify Vietnamese national personality as well as establish and preserve the cultural heritage.

Keywords: scarf collection, Vietnamese traditional patterns, printing methods, fabric design

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10387 Improving Listening Comprehension for EFL Pre-Intermediate Students through a Blended Learning Strategy

Authors: Heba Mustafa Abdullah

Abstract:

The research aimed at examining the effect of using a suggested blended learning (BL) strategy on developing EFL pre- intermediate students. The study adopted the quasi-experimental design. The sample of the research consisted of a group of 26 EFL pre- intermediate students. Tools of the study included a listening comprehension checklist and a pre-post listening comprehension test. Results were discussed in relation to several factors that affected the language learning process. Finally, the research provided beneficial contributions in relation to manipulating BL strategy with respect to language learning process in general and oral language learning in particular.

Keywords: blended learning, english as a foreign language, listening comprehension, oral language instruction

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10386 Identifying E-Learning Components at North-West University, Mafikeng Campus

Authors: Sylvia Tumelo Nthutang, Nehemiah Mavetera

Abstract:

Educational institutions are under pressure from their competitors. Regulators and community groups need educational institutions to adopt appropriate business and organizational practices. Globally, educational institutions are now using e-learning as the best teaching and learning approach. E-learning is becoming the center of attention to the learning institutions, educational systems and software inventors. North-West University (NWU) is currently using eFundi, a Learning Management System (LMS). LMS are all information systems and procedures that adds value to students learning and support the learning material in text or any multimedia files. With various e-learning tools, students would be able to access all the materials related to the course in electronic copies. The study was tasked with identifying the e-learning components at the NWU, Mafikeng campus. Quantitative research methodology was considered in data collection and descriptive statistics for data analysis. The Activity Theory (AT) was used as a theory to guide the study. AT outlines the limitations amongst e-learning at the macro-organizational level (plan, guiding principle, campus-wide solutions) and micro-organization (daily functioning practice, collaborative transformation, specific adaptation). On a technological environment, AT gives people an opportunity to change from concentrating on computers as an area of concern but also understand that technology is part of human activities. The findings have identified the university’s current IT tools and knowledge on e-learning elements. It was recommended that university should consider buying computer resources that consumes less power and practice e-learning effectively.

Keywords: e-learning, information and communication technology (ICT), teaching, virtual learning environment

Procedia PDF Downloads 261
10385 A Dynamic Ensemble Learning Approach for Online Anomaly Detection in Alibaba Datacenters

Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

Abstract:

Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

Procedia PDF Downloads 179