Search results for: multi-agent learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6801

Search results for: multi-agent learning

6801 Decoding the Structure of Multi-Agent System Communication: A Comparative Analysis of Protocols and Paradigms

Authors: Gulshad Azatova, Aleksandr Kapitonov, Natig Aminov

Abstract:

Multiagent systems have gained significant attention in various fields, such as robotics, autonomous vehicles, and distributed computing, where multiple agents cooperate and communicate to achieve complex tasks. Efficient communication among agents is a crucial aspect of these systems, as it directly impacts their overall performance and scalability. This scholarly work provides an exploration of essential communication elements and conducts a comparative assessment of diverse protocols utilized in multiagent systems. The emphasis lies in scrutinizing the strengths, weaknesses, and applicability of these protocols across various scenarios. The research also sheds light on emerging trends within communication protocols for multiagent systems, including the incorporation of machine learning methods and the adoption of blockchain-based solutions to ensure secure communication. These trends provide valuable insights into the evolving landscape of multiagent systems and their communication protocols.

Keywords: communication, multi-agent systems, protocols, consensus

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6800 Predicting Shot Making in Basketball Learnt Fromadversarial Multiagent Trajectories

Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

Abstract:

In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. Previous approaches to similar problems center on hand-crafting features to capture domain-specific knowledge. Although intuitive, recent work in deep learning has shown, this approach is prone to missing important predictive features. To circumvent this issue, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories, we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

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6799 Targeted Photoactivatable Multiagent Nanoconjugates for Imaging and Photodynamic Therapy

Authors: Shazia Bano

Abstract:

Nanoconjugates that integrate photo-based therapeutics and diagnostics within a single platform promise great advances in revolutionizing cancer treatments. However, to achieve high therapeutic efficacy, designing functionally efficacious nanocarriers to tightly retain the drug, promoting selective drug localization and release, and the validation of the efficacy of these nanoconjugates is a great challenge. Here we have designed smart multiagent, liposome based targeted photoactivatable multiagent nanoconjugates, doped with a photoactivatable chromophore benzoporphyrin derivative (BPD) labelled with an active targeting ligand cetuximab to target the EGFR receptor (over expressed in various cancer cells) to deliver a combination of therapeutic agents. This study establishes a tunable nanoplatform for the delivery of the photoactivatable multiagent nanoconjugates for tumor-specific accumulation and targeted destruction of cancer cells in complex cancer model to enhance the therapeutic index of the administrated drugs.

Keywords: targeting, photodynamic therapy, photoactivatable, nanoconjugates

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6798 Sampling Effects on Secondary Voltage Control of Microgrids Based on Network of Multiagent

Authors: M. J. Park, S. H. Lee, C. H. Lee, O. M. Kwon

Abstract:

This paper studies a secondary voltage control framework of the microgrids based on the consensus for a communication network of multiagent. The proposed control is designed by the communication network with one-way links. The communication network is modeled by a directed graph. At this time, the concept of sampling is considered as the communication constraint among each distributed generator in the microgrids. To analyze the sampling effects on the secondary voltage control of the microgrids, by using Lyapunov theory and some mathematical techniques, the sufficient condition for such problem will be established regarding linear matrix inequality (LMI). Finally, some simulation results are given to illustrate the necessity of the consideration of the sampling effects on the secondary voltage control of the microgrids.

Keywords: microgrids, secondary control, multiagent, sampling, LMI

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6797 Extending BDI Multiagent Systems with Agent Norms

Authors: Francisco José Plácido da Cunha, Tassio Ferenzini Martins Sirqueira, Marx Leles Viana, Carlos José Pereira de Lucena

Abstract:

Open Multiagent Systems (MASs) are societies in which heterogeneous and independently designed entities (agents) work towards similar, or different ends. Software agents are autonomous and the diversity of interests among different members living in the same society is a fact. In order to deal with this autonomy, these open systems use mechanisms of social control (norms) to ensure a desirable social order. This paper considers the following types of norms: (i) obligation — agents must accomplish a specific outcome; (ii) permission — agents may act in a particular way, and (iii) prohibition — agents must not act in a specific way. All of these characteristics mean to encourage the fulfillment of norms through rewards and to discourage norm violation by pointing out the punishments. Once the software agent decides that its priority is the satisfaction of its own desires and goals, each agent must evaluate the effects associated to the fulfillment of one or more norms before choosing which one should be fulfilled. The same applies when agents decide to violate a norm. This paper also introduces a framework for the development of MASs that provide support mechanisms to the agent’s decision-making, using norm-based reasoning. The applicability and validation of this approach is demonstrated applying a traffic intersection scenario.

Keywords: BDI agent, BDI4JADE framework, multiagent systems, normative agents

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6796 Deep Reinforcement Learning Model for Autonomous Driving

Authors: Boumaraf Malak

Abstract:

The development of intelligent transportation systems (ITS) and artificial intelligence (AI) are spurring us to pave the way for the widespread adoption of autonomous vehicles (AVs). This is open again opportunities for smart roads, smart traffic safety, and mobility comfort. A highly intelligent decision-making system is essential for autonomous driving around dense, dynamic objects. It must be able to handle complex road geometry and topology, as well as complex multiagent interactions, and closely follow higher-level commands such as routing information. Autonomous vehicles have become a very hot research topic in recent years due to their significant ability to reduce traffic accidents and personal injuries. Using new artificial intelligence-based technologies handles important functions in scene understanding, motion planning, decision making, vehicle control, social behavior, and communication for AV. This paper focuses only on deep reinforcement learning-based methods; it does not include traditional (flat) planar techniques, which have been the subject of extensive research in the past because reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional environments. The DRL algorithm used so far found solutions to the four main problems of autonomous driving; in our paper, we highlight the challenges and point to possible future research directions.

Keywords: deep reinforcement learning, autonomous driving, deep deterministic policy gradient, deep Q-learning

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6795 Developing a Multiagent-Based Decision Support System for Realtime Multi-Risk Disaster Management

Authors: D. Moser, D. Pinto, A. Cipriano

Abstract:

A Disaster Management System (DMS) for countries with different disasters is very important. In the world different disasters like earthquakes, tsunamis, volcanic eruption, fire or other natural or man-made disasters occurs and have an effect on the population. It is also possible that two or more disasters arisen at the same time, this means to handle multi-risk situations. To handle such a situation a Decision Support System (DSS) based on multiagents is a suitable architecture. The most known DMSs deal with one (in the case of an earthquake-tsunami combination with two) disaster and often with one particular disaster. Nevertheless, a DSS helps for a better realtime response. Analyze the existing systems in the literature and expand them for multi-risk disasters to construct a well-organized system is the proposal of our work. The here shown work is an approach of a multi-risk system, which needs an architecture, and well-defined aims. In this moment our study is a kind of case study to analyze the way we have to follow to create our proposed system in the future.

Keywords: decision support system, disaster management system, multi-risk, multiagent system

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6794 A Review of Machine Learning for Big Data

Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

Abstract:

Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

Procedia PDF Downloads 399
6793 Leveraging Learning Analytics to Inform Learning Design in Higher Education

Authors: Mingming Jiang

Abstract:

This literature review aims to offer an overview of existing research on learning analytics and learning design, the alignment between the two, and how learning analytics has been leveraged to inform learning design in higher education. Current research suggests a need to create more alignment and integration between learning analytics and learning design in order to not only ground learning analytics on learning sciences but also enable data-driven decisions in learning design to improve learning outcomes. In addition, multiple conceptual frameworks have been proposed to enhance the synergy and alignment between learning analytics and learning design. Future research should explore this synergy further in the unique context of higher education, identifying learning analytics metrics in higher education that can offer insight into learning processes, evaluating the effect of learning analytics outcomes on learning design decision-making in higher education, and designing learning environments in higher education that make the capturing and deployment of learning analytics outcomes more efficient.

Keywords: learning analytics, learning design, big data in higher education, online learning environments

Procedia PDF Downloads 117
6792 OSEME: A Smart Learning Environment for Music Education

Authors: Konstantinos Sofianos, Michael Stefanidakis

Abstract:

Nowadays, advances in information and communication technologies offer a range of opportunities for new approaches, methods, and tools in the field of education and training. Teacher-centered learning has changed to student-centered learning. E-learning has now matured and enables the design and construction of intelligent learning systems. A smart learning system fully adapts to a student's needs and provides them with an education based on their preferences, learning styles, and learning backgrounds. It is a wise friend and available at any time, in any place, and with any digital device. In this paper, we propose an intelligent learning system, which includes an ontology with all elements of the learning process (learning objects, learning activities) and a massive open online course (MOOC) system. This intelligent learning system can be used in music education.

Keywords: intelligent learning systems, e-learning, music education, ontology, semantic web

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6791 How to Guide Students from Surface to Deep Learning: Applied Philosophy in Management Education

Authors: Lihong Wu, Raymond Young

Abstract:

The ability to learn is one of the most critical skills in the information age. However, many students do not have a clear understanding of what learning is, what they are learning, and why they are learning. Many students study simply to pass rather than to learn something useful for their career and their life. They have a misconception about learning and a wrong attitude towards learning. This research explores student attitudes to study in management education and explores how to intercede to lead students from shallow to deeper modes of learning.

Keywords: knowledge, surface learning, deep learning, education

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6790 Blended Learning through Google Classroom

Authors: Lee Bih Ni

Abstract:

This paper discusses that good learning involves all academic groups in the school. Blended learning is learning outside the classroom. Google Classroom is a free service learning app for schools, non-profit organizations and anyone with a personal Google account. Facilities accessed through computers and mobile phones are very useful for school teachers and students. Blended learning classrooms using both traditional and technology-based methods for teaching have become the norm for many educators. Using Google Classroom gives students access to online learning. Even if the teacher is not in the classroom, the teacher can provide learning. This is the supervision of the form of the teacher when the student is outside the school.

Keywords: blended learning, learning app, google classroom, schools

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6789 The Design of the Blended Learning System via E-Media and Online Learning for the Asynchronous Learning: Case Study of Process Management Subject

Authors: Pimploi Tirastittam, Suppara Charoenpoom

Abstract:

Nowadays the asynchronous learning has granted the permission to the anywhere and anything learning via the technology and E-media which give the learner more convenient. This research is about the design of the blended and online learning for the asynchronous learning of the process management subject in order to create the prototype of this subject asynchronous learning which will create the easiness and increase capability in the learning. The pattern of learning is the integration between the in-class learning and online learning via the internet. This research is mainly focused on the online learning and the online learning can be divided into 5 parts which are virtual classroom, online content, collaboration, assessment and reference material. After the system design was finished, it was evaluated and tested by 5 experts in blended learning design and 10 students which the user’s satisfaction level is good. The result is as good as the assumption so the system can be used in the process management subject for a real usage.

Keywords: blended learning, asynchronous learning, design, process management

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6788 A Study on the HTML5 Based Multi Media Contents Authority Tool

Authors: Heesuk Seo, Yongtae Kim

Abstract:

Online learning started in the 1990s, the spread of the Internet has been through the era of e-learning paradigm of online education in the era of smart learning change. Reflecting the different nature of the mobile to anywhere anytime, anywhere was also allows the form of learning, it was also available through the learning content and interaction. We are developing a cloud system, 'TLINKS CLOUD' that allows you to configure the environment of the smart learning without the need for additional infrastructure. Using the big-data analysis for e-learning contents, we provide an integrated solution for e-learning tailored to individual study.

Keywords: authority tool, big data analysis, e-learning, HTML5

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6787 The Different Learning Path Analysis of Students with Different Learning Attitudes and Styles in Arts Creation

Authors: Tracy Ho, Huann-Shyang Lin, Mina Lin

Abstract:

This study investigated the different learning path of students with different learning attitude and learning styles in Arts Creation. Based on direct instruction, guided-discovery learning, and discovery learning theories, a tablet app including the following three learning areas were developed for students: (1) replication and remix practice area, (2) guided creation area, and (3) free creation area. Thirty. students with different learning attitude and learning styles were invited to use this app. Students’ learning behaviors were categorized and defined. The results will provide both educators and researchers with insights that can form a useful foundation for designing different content and strategy with the application of new technologies in school teaching. It also sheds light on how an educational App can be designed to enhance Arts Creation.

Keywords: App, arts creation, learning attitude, learning style, tablet

Procedia PDF Downloads 241
6786 Modern Machine Learning Conniptions for Automatic Speech Recognition

Authors: S. Jagadeesh Kumar

Abstract:

This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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6785 The Effect of Online Learning During the COVID-19 Pandemic on Student Mental

Authors: Adelia Desi Agnesita

Abstract:

The advent of a new disease called covid-19 made many major changes in the world, one of which is the process of learning and teaching. Learning formerly offline but now is done online, which makes students need adaptation to the learning process. The covid-19 pandemic that occurs almost worldwide causes activities that involve many people to be avoided, one of which is learning to teach. In Indonesia, since March 2020, the process of college learning is turning into online/ long-distance learning. It's to prevent the spread of the covid-19. Student online learning presents some of the obstacles to poor signals, many of the tasks, lack of focus, difficulty sleeping, and resulting stress.

Keywords: learning, online, covid-19, pandemic

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6784 Development of Multimedia Learning Application for Mastery Learning Style: A Graduated Difficulty Strategy

Authors: Nur Azlina Mohamed Mokmin, Mona Masood

Abstract:

Guided by the theory of learning style, this study is based on the development of a multimedia learning application for students with mastery learning style. The learning material was developed by applying a graduated difficulty learning strategy. Algebraic fraction was chosen as the learning topic for this application. The effectiveness of this application in helping students learn is measured by giving a pre- and post-test. The result shows that students who learn using the learning material that matches their preferred learning style performs better than the students with a non-personalized learning material.

Keywords: algebraic fractions, graduated difficulty, mastery learning style, multimedia

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6783 Implementation of the Collaborative Learning Approach in Learning of Second Language English

Authors: Ashwini Mahesh Jagatap

Abstract:

This paper presents the language learning strategy with respect to speaking skill with collaborative learning approach. Collaborative learning has been proven to be efficient learning methodology for all kinds of students. Students are working in groups of two or more, reciprocally searching for understanding, Solutions, or meanings, or creating a product. The presentation highlights the different stages which can be implemented during actual implementation of the methodology in the class room teaching learning process.

Keywords: collaborative classroom, collaborative learning approach, language skills, traditional teaching

Procedia PDF Downloads 536
6782 Implications of Learning Resource Centre in a Web Environment

Authors: Darshana Lal, Sonu Rana

Abstract:

Learning Resource Centers (LRC) are acquiring different kinds of documents like books, journals, thesis, dissertations, standard, databases etc. in print and e-form. This article deals with the different types of sources available in LRC. It also discusses the concept of the web, as a tool, as a multimedia system and the different interfaces available on the web. The reasons for establishing LRC are highlighted along with the assignments of LRC. Different features of LRC‘S like self-learning and group learning are described. It also implements a group of activities like reading, learning, educational etc. The use of LRC by students and faculties are given and concluded with the benefits.

Keywords: internet, search engine, resource centre, opac, self-learning, group learning

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6781 Active Learning: Increase Learning through Engagement

Authors: Jihan Albayati, Kim Abdullah

Abstract:

This poster focuses on the significance of active learning strategies and their usage in the ESL classroom. Active learning is a big shift from traditional lecturing to active student engagement which can enhance and enrich student learning; therefore, engaging students is the core of this approach. Students learn more when they participate in the process of learning such as discussions, debates, analysis, synthesis, or any form of activity that requires student involvement. In order to achieve active learning, teachers can use different instructional strategies that are conducive to learning and the selection of these strategies depends on student learning outcomes. Active learning techniques must be carefully designed and integrated into the classroom to increase critical thinking and student participation. This poster provides a concise definition of active learning and its importance, instructional strategies, active learning techniques and their impact on student engagement. Also, it demonstrates the differences between passive and active learners.

Keywords: active learning, learner engagement, student-centered, teaching strategies

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6780 An Ontology for Smart Learning Environments in Music Education

Authors: Konstantinos Sofianos, Michail Stefanidakis

Abstract:

Nowadays, despite the great advances in technology, most educational frameworks lack a strong educational design basis. E-learning has become prevalent, but it faces various challenges such as student isolation and lack of quality in the learning process. An intelligent learning system provides a student with educational material according to their learning background and learning preferences. It records full information about the student, such as demographic information, learning styles, and academic performance. This information allows the system to be fully adapted to the student’s needs. In this paper, we propose a framework and an ontology for music education, consisting of the learner model and all elements of the learning process (learning objects, teaching methods, learning activities, assessment). This framework can be integrated into an intelligent learning system and used for music education in schools for the development of professional skills and beyond.

Keywords: intelligent learning systems, e-learning, music education, ontology, semantic web

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6779 The Influence of Learning Styles on Learners Grade Achievement in E-Learning Environments: An Empirical Study

Authors: Thomas Yeboah, Gifty Akouko Sarpong

Abstract:

Every learner has a specific learning style that helps him/her to study best. This means that any learning method (e-learning method or traditional face-to-face method) a learner chooses should address the learning style of the learner. Therefore, the main purpose of this research is to investigate whether learners’ grade achievement in e-learning environment is improved for learners with a particular learning style. In this research, purposive sampling technique was employed for selecting the sample size of three hundred and twenty (320) students studying a course UGRC 140 Science and Technology in our Lives at Christian Service University College. Data were analyzed by using, percentages, T -test, and one-way ANOVA. A thorough analysis was done on the data collected and the results revealed that learners with the Assimilator learning style and the converger learning style obtained higher grade achievement than both diverger learning style and accommodative learning style. Again, the results also revealed that accommodative learning style was not good enough for e-learning method.

Keywords: e-learning, learning style, grade achievement, accomodative, divergent, convergent, assimilative

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6778 Q-Learning of Bee-Like Robots Through Obstacle Avoidance

Authors: Jawairia Rasheed

Abstract:

Modern robots are often used for search and rescue purpose. One of the key areas of interest in such cases is learning complex environments. One of the key methodologies for robots in such cases is reinforcement learning. In reinforcement learning robots learn to move the path to reach the goal while avoiding obstacles. Q-learning, one of the most advancement of reinforcement learning is used for making the robots to learn the path. Robots learn by interacting with the environment to reach the goal. In this paper simulation model of bee-like robots is implemented in NETLOGO. In the start the learning rate was less and it increased with the passage of time. The bees successfully learned to reach the goal while avoiding obstacles through Q-learning technique.

Keywords: reinforlearning of bee like robots for reaching the goalcement learning for randomly placed obstacles, obstacle avoidance through q-learning, q-learning for obstacle avoidance,

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6777 Intentional Learning vs Incidental Learning

Authors: Shahbaz Ahmed

Abstract:

This study is conducted to demonstrate the knowledge of intentional learning and incidental learning. Hypothesis of this experiment is intentional learning is better than incidental learning, participants were demonstrated and were asked to learn the 10 nonsense syllables in a specific sequence from the colored cards in the end they were asked to recall the background color of each card instead of nonsense syllables. Independent variables of the experiment are the colored cards containing nonsense syllables which are to be memorized by the participants, dependent variables are the number of correct responses made by the participant. The findings of the experiment concluded that intentional learning is better than incidental learning, hence hypothesis is proved.

Keywords: intentional learning, incidental learning, non-sense syllable cards, score sheets

Procedia PDF Downloads 478
6776 The Relevance of Smart Technologies in Learning

Authors: Rachael Olubukola Afolabi

Abstract:

Immersive technologies known as X Reality or Cross Reality that include virtual reality augmented reality, and mixed reality have pervaded into the education system at different levels from elementary school to adult learning. Instructors, instructional designers, and learning experience specialists continue to find new ways to engage students in the learning process using technology. While the progression of web technologies has enhanced digital learning experiences, analytics on learning outcomes continue to be explored to determine the relevance of these technologies in learning. Digital learning has evolved from web 1.0 (static) to 4.0 (dynamic and interactive), and this evolution of technologies has also advanced teaching methods and approaches. This paper explores how these technologies are being utilized in learning and the results that educators and learners have identified as effective learning opportunities and approaches.

Keywords: immersive technologoes, virtual reality, augmented reality, technology in learning

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6775 How to Use E-Learning to Increase Job Satisfaction in Large Commercial Bank in Bangkok

Authors: Teerada Apibunyopas, Nithinant Thammakoranonta

Abstract:

Many organizations bring e-Learning to use as a tool in their training and human development department. It is getting more popular because it is easy to access to get knowledge all the time and also it provides a rich content, which can develop the employees skill efficiently. This study focused on the factors that affect using e-Learning efficiently, so it will make job satisfaction increased. The questionnaires were sent to employees in large commercial banks, which use e-Learning located in Bangkok, the results from multiple linear regression analysis showed that employee’s characteristics, characteristics of e-Learning, learning and growth have influence on job satisfaction.

Keywords: e-Learning, job satisfaction, learning and growth, Bangkok

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6774 Learning Compression Techniques on Smart Phone

Authors: Farouk Lawan Gambo, Hamada Mohammad

Abstract:

Data compression shrinks files into fewer bits than their original presentation. It has more advantage on the internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature, therefore, making them difficult to digest by some students (engineers in particular). This paper studies the learning preference of engineering students who tend to have strong, active, sensing, visual and sequential learning preferences, the paper also studies the three shift of technology-aided that learning has experienced, which mobile learning has been considered to be the feature of learning that will integrate other form of the education process. Lastly, we propose a design and implementation of mobile learning application using software engineering methodology that will enhance the traditional teaching and learning of data compression techniques.

Keywords: data compression, learning preference, mobile learning, multimedia

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6773 An Online Mastery Learning Method Based on a Dynamic Formative Evaluation

Authors: Jeongim Kang, Moon Hee Kim, Seong Baeg Kim

Abstract:

This paper proposes a novel e-learning model that is based on a dynamic formative evaluation. On evaluating the existing format of e-learning, conditions regarding repetitive learning to achieve mastery, causes issues for learners to lose tension and become neglectful of learning. The dynamic formative evaluation proposed is able to supplement limitation of the existing approaches. Since a repetitive learning method does not provide a perfect feedback, this paper puts an emphasis on the dynamic formative evaluation that is able to maximize learning achievement. Through the dynamic formative evaluation, the instructor is able to refer to the evaluation result when making estimation about the learner. To show the flow chart of learning, based on the dynamic formative evaluation, the model proves its effectiveness and validity.

Keywords: online learning, dynamic formative evaluation, mastery learning, repetitive learning method, learning achievement

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6772 Using Learning Apps in the Classroom

Authors: Janet C. Read

Abstract:

UClan set collaboration with Lingokids to assess the Lingokids learning app's impact on learning outcomes in classrooms in the UK for children with ages ranging from 3 to 5 years. Data gathered during the controlled study with 69 children includes attitudinal data, engagement, and learning scores. Data shows that children enjoyment while learning was higher among those children using the game-based app compared to those children using other traditional methods. It’s worth pointing out that engagement when using the learning app was significantly higher than other traditional methods among older children. According to existing literature, there is a direct correlation between engagement, motivation, and learning. Therefore, this study provides relevant data points to conclude that Lingokids learning app serves its purpose of encouraging learning through playful and interactive content. That being said, we believe that learning outcomes should be assessed with a wider range of methods in further studies. Likewise, it would be beneficial to assess the level of usability and playability of the app in order to evaluate the learning app from other angles.

Keywords: learning app, learning outcomes, rapid test activity, Smileyometer, early childhood education, innovative pedagogy

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