• Title/Summary/Keyword: Learning process

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On the Clustering Networks using the Kohonen's Elf-Organization Architecture (코호넨의 자기조직화 구조를 이용한 클러스터링 망에 관한 연구)

  • Lee, Ji-Young
    • The Journal of Information Technology
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    • v.8 no.1
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    • pp.119-124
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    • 2005
  • Learning procedure in the neural network is updating of weights between neurons. Unadequate initial learning coefficient causes excessive iterations of learning process or incorrect learning results and degrades learning efficiency. In this paper, adaptive learning algorithm is proposed to increase the efficient in the learning algorithms of Kohonens Self-Organization Neural networks. The algorithm updates the weights adaptively when learning procedure runs. To prove the efficiency the algorithm is experimented to clustering of the random weight. The result shows improved learning rate about 42~55% ; less iteration counts with correct answer.

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Learning Time Prediction Model for Web-based Instruction (웹 기반 학습을 위한 학습 시간 예측 모델)

  • 김창화;장기영
    • Journal of KIISE:Software and Applications
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    • v.30 no.10
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    • pp.983-991
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    • 2003
  • The Web-based instruction on the internet provides lots of learners with the related information and knowledge beyond time and space. But in the Web-based instruction, there is a problem that the teaming process statuses for learners can be known only through an exam. This paper introduces a web monitoring method to check whether the learner has some problems in learning process and to be able to find out the students with the problems. In the method this paper proposes a learning time prediction model for predicting the proper next study time intervals based on the learner`s learning times and grades on Previous learning units. This method provides the educator with the learning Process statuses for learners. The Loaming prediction model for web-based monitoring can be used to stimulate learners to take the good teaming processes by sending automatically alerting messages if their real teaming times exceeds on his predicted learning time interval. The results of the estimation through case study on the web-based monitoring to use the teaming time prediction model show that most of on-line learners with Poor teaming process statuses get poor grades. In addition, the results show that learner`s poor habits keep going on without change.

An Empirical Investigation of the Impact of Customer Learning on Customer Experience in the Context of Knowledge Product Use

  • KIM, Yong Jin;YIM, Myung-Seong
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.12
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    • pp.969-976
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    • 2020
  • The role of customers has changed from that of passive users to value co-creators. Therefore, it is important to understand how customer learning takes place and how it affects customer experiences with services and products. However, while past studies insist on the importance of the issues in designing customer experiences, they do not empirically address these issues. This study investigates the support processes for customer learning, and their impact on customer learning, which in turn influences customer experience. To test the hypotheses, we employed the survey method. Target informants were the actual users of Apple iPods. A total of 200 survey questionnaires were distributed and 146 were collected. Among these, seven erroneous responses were excluded, leaving 139 usable ones. The proposed model was empirically analyzed using the Covariance-based SEM (Structural Equation Modelling) technique. The findings of this study suggest that, among the three support processes in customer learning, learning-by-doing support and learning-by-investment support positively affect customer learning, which influences customer experience. This study contributes to the literature by identifying different types of support for different kinds of customer learning processes and by empirically testing the impact of the support for the process on customer learning, and in turn, its impact on customer experience.

A Design and Implementation of Web-based Learning System with Self-Study Plan (자기 학습 계획을 갖는 웹기반 학습 시스템의 설계 및 구현)

  • Jang, Duk-Sung;Cho, Hyun-Uk
    • The KIPS Transactions:PartA
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    • v.11A no.4
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    • pp.297-302
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    • 2004
  • In the information-oriented society, the paradigm of education has changed from the existing traditional teaching-centered education to the learning-centered education. In the Web-based Learning System which an learning-centered educational environment using the internet, students should have responsibility of their learning as taking more opportunities to participate their learning positively, to control their process of learning and to evaluate their learning by themselves to improve self-directed loaming ability. In this paper, the Web-based Learning System with a Self-Study Plan to lead students to select own purposes and methods of the study and write a self_evaluation is developed. The Self-Study Plan is a guide to lead the process, an order to have an individualized study and a report to evaluate own study. In addition, the suggested System is designed through object-oriented method using the extension mechanism of UML to archive the improvement of reuse and maintenance.

The Effects of Science Teaching and Learning Using Student-led Instructional Strategies on Elementary School Students' Science Core Competencies (학생주도형 수업전략을 활용한 과학 교수 학습이 초등학생의 과학과 핵심역량에 미치는 효과)

  • Kang, Hountae;Noh, Sukgoo
    • Journal of Korean Elementary Science Education
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    • v.39 no.2
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    • pp.228-242
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    • 2020
  • The purpose of this study is to develop a student-led instructional strategy that is central to the teaching-learning process and to investigate its effects. For this study, we analyzed the learner-centered learning types (discovery learning, problem-based learning, inquiry learning) and extracted elements applicable to newly developed teaching-learning. Based on this, a student-led class strategy was established using pre-learning, teacher collaboration, small group composition, and limited open data and product presentation, and then science classes were conducted. As a result of the post-tests of the five science core competencies of the experimental group using the student-led instructional strategy and the comparative group conducting lecture-based classes, the experimental group showed higher scores than the comparative group in the scientific thinking, scientific communication, and scientific attitudes (p<.05). Based on these results, it was confirmed that the student-led class, in which the student self-adjusts the entire process of designing, exploring, and presenting learning, can help the student's scientific ability. In addition, I would like to discuss the implications of teachers' teaching-learning composition.

A Study on Elements and Procedure of Instruction Consulting for Successful Flipped Learning (성공적인 Flipped Learning을 위한 수업컨설팅 요소 및 절차 연구)

  • Choi, Jeong-bin;Kang, Seung-Chan
    • Journal of Engineering Education Research
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    • v.19 no.2
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    • pp.76-82
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    • 2016
  • The purpose of this study is to identify core elements required of instruction consulting and to develop a systematic consulting procedure for successful Flipped Learning. The main contents of this study to achieve its purpose are as follows. First, core elements required of consulting are deduced by analyzing cases of instruction implemented with Flipped Learning. Second, consulting procedure is constructed based on core consulting elements of Flipped Learning. Based on the study results, the 3P process is suggested as the elements and procedure of instruction consulting for Flipped Learning. The 3P process has the following characteristics. The first stage Preparation involves guiding students to have an objective viewpoint about the lesson beginning with building a relationship with the instructor. Also, a lesson plan and source materials for lesson are selected and developed. The second stage Performance involves implementing lesson coaching oriented towards cooperative problem-solving to find better direction. The last stage Post-review involves introspection necessary for continuous quality improvement of lessons. The validity of the instruction consulting elements for Flipped Learning applied to deduce the aforementioned results has been verified after specialist review and field application.

Application of Distance Learning to Practical Cooking Class - With a Focus on Korean Food Cooking Class in Culinary College Students - (조리실기 과목의 원격교육 활용을 위한 실증연구 - 2년제 조리전공 대학생을 대상으로 한 한식교과목을 중심으로 -)

  • Kang, Jae-Hee;Chong, Yu-Kyeong
    • Journal of the Korean Society of Food Culture
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    • v.26 no.3
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    • pp.249-260
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    • 2011
  • The current research aims to verify whether distance learning can be adopted in practical cooking class for Korean foods in a two-year college. The distance learning education can be a supplementary method to the traditional cooking class. The face-to-face teaching method and the distance learning method were compared in order to determine which of the one is more effective teaching method in the practical cooking class. The results of the present experimental study were analyzed based on the participant's learning expectation and satisfaction, the evaluation of the experimental process, and the academic performance. The results of this study showed that the participants in the face-to-face class evaluated their class experience higher than those in the distance learning class with respect to the participant's learning expectation and satisfaction, and the evaluation of the experimental process. On the contrary, regarding the academic performance, the participants in the distance learning class showed higher scores than those in the face-to-face class. The end result supports the claim that the distance learning method is more effective in the participants for gaining cooking knowledge.

Development and Distribution of Deep Fake e-Learning Contents Videos Using Open-Source Tools

  • HO, Won;WOO, Ho-Sung;LEE, Dae-Hyun;KIM, Yong
    • Journal of Distribution Science
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    • v.20 no.11
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    • pp.121-129
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    • 2022
  • Purpose: Artificial intelligence is widely used, particularly in the popular neural network theory called Deep learning. The improvement of computing speed and capability expedited the progress of Deep learning applications. The application of Deep learning in education has various effects and possibilities in creating and managing educational content and services that can replace human cognitive activity. Among Deep learning, Deep fake technology is used to combine and synchronize human faces with voices. This paper will show how to develop e-Learning content videos using those technologies and open-source tools. Research design, data, and methodology: This paper proposes 4 step development process, which is presented step by step on the Google Collab environment with source codes. This technology can produce various video styles. The advantage of this technology is that the characters of the video can be extended to any historical figures, celebrities, or even movie heroes producing immersive videos. Results: Prototypes for each case are also designed, developed, presented, and shared on YouTube for each specific case development. Conclusions: The method and process of creating e-learning video contents from the image, video, and audio files using Deep fake open-source technology was successfully implemented.

The Effect of Learning Strategy, Learning Attitude, Achievement Motivation on Satisfaction of Online Extracurricular Participants (온라인 비교과 프로그램 참여자의 학습전략, 학습태도, 성취동기가 만족도에 미치는 영향)

  • Park Hyejin;Kwon Youngae
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.19 no.1
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    • pp.13-21
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    • 2023
  • This study was conducted with students who participated in an online extracurricular after COVID-19 in order to analyze the effects of college students' learning strategy, learning attitude, and achievement motivation on satisfaction. After participating in the online extracurricular, an online survey was conducted, and responses from 163 students were collected. Based on the collected data, the study results were analyzed. The results of the study are as follows. First, learning strategy was found to have a positive effect on satisfaction. These results can be inferred that positive recognition worked in the process of actually applying the learning strategies acquired through the extracurricular to their own learning. Second, learning attitude had a positive effect on satisfaction. The learner's learning attitude to develop necessary skills through experience and the sense of achievement experienced in the process of participating in the online extracurricular had a positive effect on satisfaction. Third, achievement motivation was found to have a positive effect on satisfaction. It can be inferred that the learner's active behavior by participating in the program acts as a motivation for achievement and affects satisfaction. Finally, through this study, a plan for effectively operating extracurricular in an online environment was presented.

Privacy-Preserving Deep Learning using Collaborative Learning of Neural Network Model

  • Hye-Kyeong Ko
    • International journal of advanced smart convergence
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    • v.12 no.2
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    • pp.56-66
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    • 2023
  • The goal of deep learning is to extract complex features from multidimensional data use the features to create models that connect input and output. Deep learning is a process of learning nonlinear features and functions from complex data, and the user data that is employed to train deep learning models has become the focus of privacy concerns. Companies that collect user's sensitive personal information, such as users' images and voices, own this data for indefinite period of times. Users cannot delete their personal information, and they cannot limit the purposes for which the data is used. The study has designed a deep learning method that employs privacy protection technology that uses distributed collaborative learning so that multiple participants can use neural network models collaboratively without sharing the input datasets. To prevent direct leaks of personal information, participants are not shown the training datasets during the model training process, unlike traditional deep learning so that the personal information in the data can be protected. The study used a method that can selectively share subsets via an optimization algorithm that is based on modified distributed stochastic gradient descent, and the result showed that it was possible to learn with improved learning accuracy while protecting personal information.