• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.117-134
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• 2004

This study suggests a data driven optimization approach, which simulates the models of human learning processes from cognitive sciences. It shows how the human learning processes can be simulated and applied to solving combinatorial optimization problems. The main advantage of using this method is in applying it into problems, which are very difficult to simulate. 'Undecidable' problems are considered as best possible application areas for this suggested approach. The concept of an 'undecidable' problem is redefined. The learning models in human learning and decision-making related to combinatorial optimization in cognitive and neural sciences are designed, simulated, and implemented to solve an optimization problem. We call this approach 'SLO : simulated learning for optimization.' Two different versions of SLO have been designed: SLO with position & link matrix, and SLO with decomposition algorithm. The methods are tested for traveling salespersons problems to show how these approaches derive new solution empirically. The tests show that simulated learning for optimization produces new solutions with better performance empirically. Its performance, compared to other hill-climbing type methods, is relatively good.

• International Journal of Contents
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• v.6 no.1
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• pp.12-19
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• 2010

In this paper, attendance in distance learning courses of a cyber university has been surveyed in an effort to verify the effectiveness of distance learning. Based on survey data from 4,749 distance learning participants, major attending place, major reasons for attending online class, fidelity to online classes, attending time per week, perceived educational effectiveness, perceived and relative seriousness of problems, and other variables have been evaluated. The results indicate that perceptional seriousness of the investigated problems is not statistically important. The findings indicate that, among operational problems, self willingness and cheating are the most remarkable. In contrast, the relative seriousness of traditionally recognized problems such as H/W availability and network speed among environmental problems is least remarkable. An analysis of demographic differences such as sex, employment, and school year in terms of seriousness of problems is also performed. The results reveal the existence of statistically significant differences according to sex, employment, and school year with regard to almost all elements of environment, actual current conditions, and seriousness of problems, with the exception of some elements such as attending place and perceived fidelity.

• Journal of the Korean School Mathematics Society
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• v.2 no.1
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• pp.167-179
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• 1999

The aim of this study is to improve the basic learning ability of those who make poor progress in mathematics and to keep positive and active learning attitudes in class afterward by using problems whith both make them advance their basic learning ability and supplement lack of previous learning in class or after school. supplementary problems were developed by focusing the ability of basic calculation, the comprehension of concepts, principles, and rules by analyzing necessary contents precisely each domain after itemizing learning contents each unit. the results of the study are this: 1) The students who solved the problems, that were developed to improve the basic learning ability and to supplement the earlier learning during their classes or giving homework, made significant progress in their scholastic achievement; more than those who were not involved. 2) Meaningful changes were demonstrated in the motivation for achievement among the domains of learning attitudes before and after the experiment but, not in their interest, the consciousness of purpose, attention, voluntary and efficient learning as shown in their learning habits. In this study, therefore, the problems which were developed to improve the basic learning ability and to supplement the earlier learning by focusing on the competence for basic calculation, and the comprehension of concepts, principles and rules were effective positively only in the area of motivation for achievement. there were no meaningful differences in the other domains.

• School Mathematics
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• v.2 no.2
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• pp.333-355
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• 2000

In this paper, possibility of practical use of cryptarithmetic problems in teaching and learning of mathematics is discussed. There might be seven cases to use them practically like followings: (1) Cryptarithmetic problems might be used for deepening the mathematical knowledges. (2) Cryptarithmetic problems might be used for fostering mathematical thinking abilities. (3) Cryptarithmetic problems might be used for fostering problem solving abilities. (4) Cryptarithmetic problems might be used as open ended problems. (5) Cryptarithmetic problems might be used as materials for personalized learning. (6) Cryptarithmetic problems might be used as materials for cooperative learning. (7) Cryptarithmetic problems might be used as materials for problems posing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.683-688
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• 2018

In the 21stcentury, teachers must welcome new technology to ensure the best learning in virtual classrooms, aside from the physical classroom. Google Classroom provides a vital chance to promote blended learning and professional development. The purpose of this study is to specify the procedures in problem design when employing blended problem-based learning (BPBL) and to design problems for learning the contents of the subject. The design of problems is crucial for effective BPBL. The underlying theory of BPBL is that learning is most effectively initiated and facilitated by posing and solving real-life problems that interest the learner, because working on such problems makes learning meaningful and motivates students. Ineffective problem-based learning (PBL) could affect students when acquiring sufficient domain knowledge, activating appropriate prior knowledge, and properly directing their own learning. The procedures for designing good problems are composed of the selection of educational content, figuring out the learner's characteristics, finding problems, setting up roles and situations, and writing down problems. Using these procedures, we designed five integration problems covering the contents of management subjects. Planned management subjects based on BPBL in a Mongolian university focuses on the process of designing problems.

• The Journal of the Korea Contents Association
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• v.6 no.3
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• pp.102-107
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• 2006

While Internet-based distance learning has proliferated, its educational effectiveness remains controversial. As such, investigation into the problems of Internet-based distance learning is important and fundamental for an assessment of its educational effectiveness. In this study, problems of Internet-based distance learning are grouped into four categories, environmental problems, student problems, course design problems and operational problems. Based on survey data from 606 distance learning participants, perceptional and relative seriousness of problems are analysed. The results indicate that perceptional seriousness of all the problems is not statistically important. However, the findings indicate that the relative seriousness of self willingness among student problems and cheating within operational problems is most remarkable. In contrast, the relative seriousness of traditionally recognized problems such as H/W availability and network speed among environmental problems is least remarkable. An analysis of demographic differences such as sex, employment and age in terms of seriousness of problem is also performed. The results reveal the existence of statistically significant differences according to sex, employment, and age difference with regard to seriousness of problems.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.222-228
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• 2019

In recent years, in order to enhance the problem-solving skills required by the industrial field, universities have introduced the Problem-Based Learning(PBL) method to solve the problems caused by the lack of creativity, problem solving ability and self-directed learning. This study applied PBL class methods such as 'learning based on individual specific problems', 'self-directed learning', and 'small-group learning of small members' to practical design of fashion design. To do this, I conducted a questionnaire after conducting research based on the PBL module for one semester in a practical class of fashion design major at P University. As a result of the survey, the satisfaction and achievement of the class conducted by PBL learning method was improved than the existing teaching method. As such, if PBL class is used as a way of solving problems through close communication between professors and learners, it is expected to be established as a learner-centered education method that can improve creativity and professionalism.

• School Mathematics
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• v.11 no.1
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• pp.165-186
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• 2009

Problem-Based Learning has many implications on teaching and learning. Through the problem-Based Learning, students device their plans to solve the given problems and discuss with workers to find and share some ideas or mathematical contents needed to solve those problems. In this paper we studied characteristics of Problem-Based Learning problem and tried o find out the standard criterion of problem analysis that were appropriate to Problem-Based Learning. We applied them to analyze problems in textbooks and problems that were developed for Problem-Based Learning. Using he result, the further research questions and implications were suggested.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.281-285
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• 2005

Learning and evolving are two basics for data mining. As compared with classical learning theory based on objective function with minimizing training errors, the recently evolutionary computing has had an efficient approach for constructing optimal model without the minimizing training errors. The global search of evolutionary computing in solution space can settle the local optima problems of learning models. In this research, combining co-evolving algorithm into statistical learning theory, we propose an co-evolutionary computing for statistical learning theory for overcoming local optima problems of statistical learning theory. We apply proposed model to classification and prediction problems of the learning. In the experimental results, we verify the improved performance of our model using the data sets from UCI machine learning repository and KDD Cup 2000.

• The Journal of Bigdata
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• v.5 no.1
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• pp.89-96
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• 2020

Deep learning using an artificial neural network has been recently researched and developed in various fields such as image recognition, big data and data analysis. However, federated learning has emerged to solve issues of data privacy invasion and problems that increase the cost and time required to learn. Federated learning presented learning techniques that would bring the benefits of distributed processing system while solving the problems of existing deep learning, but there were still problems with server-client system and motivations for providing learning data. So, we replaced the role of the server with a blockchain system in federated learning, and conducted research to solve the privacy and security problems that are associated with federated learning. In addition, we have implemented a blockchain-based system that motivates users by paying compensation for data provided by users, and requires less maintenance costs while maintaining the same accuracy as existing learning. In this paper, we present the experimental results to show the validity of the blockchain-based system, and compare the results of the existing federated learning with the blockchain-based federated learning. In addition, as a future study, we ended the thesis by presenting solutions to security problems and applicable business fields.