• Journal of Digital Convergence
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• v.15 no.5
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• pp.37-48
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• 2017

Recently, the importance of software education is growing because computational thinking of software education is recognized as a key means of future economic development. Also human resources who will lead the 4th industrial revolution need convergence and creativity, computational thinking based on critical thinking, communication, and collaborative learning is known to be effective in creativity education. Software education is also a time needed to reflect social issues such as collaboration with developers sharing interests and open source development methods. Github is a leading social coding site that facilitates collaborative work among developers and supports community activities in open software development. In this study, we apply operational cases of basic learning of social coding sites, learning for storage server with sources and outputs of lectures, and open collaborative learning by using Github. And we propose educational model consisted of four stages: Introduction to Github, Using Repository, Applying Social Coding, Making personal portfolio and Assessment. The proposal of this paper is very effective for software education by attracting interest and leading to pride in the student.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.177-189
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• 2013

In Smart Education, the roles of digital textbook is very important as face-to-face media to learners. The standardization of digital textbook will promote the industrialization of digital textbook for contents providers and distributers as well as learner and instructors. In this study, the following three objectives-oriented digital textbooks are looking for ways to standardize. (1) digital textbooks should undertake the role of the media for blended learning which supports on-off classes, should be operating on common EPUB viewer without special dedicated viewer, should utilize the existing framework of the e-learning learning contents and learning management. The reason to consider the EPUB as the standard for digital textbooks is that digital textbooks don't need to specify antoher standard for the form of books, and can take advantage od industrial base with EPUB standards-rich content and distribution structure (2) digital textbooks should provide a low-cost open market service that are currently available as the standard open software (3) To provide appropriate learning feedback information to students, digital textbooks should provide a foundation which accumulates and manages all the learning activity information according to standard infrastructure for educational Big Data processing. In this study, the digital textbook in a smart education environment was referred to open digital textbook. The components of open digital textbooks service framework are (1) digital textbook terminals such as smart pad, smart TVs, smart phones, PC, etc., (2) digital textbooks platform to show and perform digital contents on digital textbook terminals, (3) learning contents repository, which exist on the cloud, maintains accredited learning, (4) App Store providing and distributing secondary learning contents and learning tools by learning contents developing companies, and (5) LMS as a learning support/management tool which on-site class teacher use for creating classroom instruction materials. In addition, locating all of the hardware and software implement a smart education service within the cloud must have take advantage of the cloud computing for efficient management and reducing expense. The open digital textbooks of smart education is consdered as providing e-book style interface of LMS to learners. In open digital textbooks, the representation of text, image, audio, video, equations, etc. is basic function. But painting, writing, problem solving, etc are beyond the capabilities of a simple e-book. The Communication of teacher-to-student, learner-to-learnert, tems-to-team is required by using the open digital textbook. To represent student demographics, portfolio information, and class information, the standard used in e-learning is desirable. To process learner tracking information about the activities of the learner for LMS(Learning Management System), open digital textbook must have the recording function and the commnincating function with LMS. DRM is a function for protecting various copyright. Currently DRMs of e-boook are controlled by the corresponding book viewer. If open digital textbook admitt DRM that is used in a variety of different DRM standards of various e-book viewer, the implementation of redundant features can be avoided. Security/privacy functions are required to protect information about the study or instruction from a third party UDL (Universal Design for Learning) is learning support function for those with disabilities have difficulty in learning courses. The open digital textbook, which is based on E-book standard EPUB 3.0, must (1) record the learning activity log information, and (2) communicate with the server to support the learning activity. While the recording function and the communication function, which is not determined on current standards, is implemented as a JavaScript and is utilized in the current EPUB 3.0 viewer, ths strategy of proposing such recording and communication functions as the next generation of e-book standard, or special standard (EPUB 3.0 for education) is needed. Future research in this study will implement open source program with the proposed open digital textbook standard and present a new educational services including Big Data analysis.

• 대한공업교육학회지
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• v.34 no.2
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• pp.103-127
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• 2009

The purpose of this study is to offer the basic data regarding the problems of the employment training activities and their solutions by way of the research and analysis of the awareness of career development of university students and their preparation for employment opportunities. The results of the study are as follows. First, it is necessary that the students themselves make plans for future jobs and their preparation for them, from the start of their university work. This includes taking employment preparation courses as liberal arts requirements. It also needs to have a systematic association with some organizations such as employment preparation centers. Second, it is necessary that the career portfolios of university students be accepted as materials for objective evaluation so that the companies use them at the time of hiring new employees. If those materials are stored and managed in a database even after their graduation, they will be the strong foundation for the competitive power of the university.Third, it is necessary that university students establish the orientation of employment training in advance, according to their personal and disciplinary possibilities by diagnosing the level of basic employment ability they possess and that they find out the appropriate programs, both personal and disciplinary, to enforce the abilities they need to develop further. Accordingly, it is necessary to have an evaluation system in order to assess student's basic employment abilities, so as to increase the degree of their employment preparation and its support strategy based on the evaluation. Fourth, in the higher education level, university students' lower awareness (M=2.86) of their discipline satisfaction, their major selection, and the university's employment opportunity service shows that it is necessary that there be close connection between learning and work. For short-term purpose, the quantitative and qualitative evaluation must be preceded about the various employment training programs and self-development programs offered by the university. From the long-term perspective, it is urgently necessary that the university ensure the human resources development experts for the purpose of diagnosing employment services within the university.

• Journal of Korean Home Economics Education Association
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• v.33 no.1
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• pp.101-127
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• 2021

The purpose of this study is to design and develop a teaching-learning process plan for process-based assessment, focusing on the unit related to life design in middle school home economics(HE: Home Economics part of 「Technology and Home Economics」), to propose a feedback plan after implementing it, and to evaluate the plan through participatory observation and interviews. The student reflection journals, teacher's class journals, participatory observation journals, interviews, and performance tasks, were collected and analyzed to provide foundational date to be utilized for feedback to students, and class improvement. The research results are as follows: First, the developed teaching-learning process plan consists of a total of 8 sessions, i.e. 2 sessions for each of the four learning themes, under the practical question of "What should I do to live the life I want?" The portfolio was composed of five evaluation topics and for evaluation, oral presentation, observational evaluation, self-assessment, and peer evaluation were considered. Second, during the class, feedback from teachers, feedback from fellow students, feedback through results, and a plan to record them were provided. Third, from the analysis of collected data including observation journals and interviews, it was apparent that the students recognized the necessity of process-based assessment after the class, and students acknowledged that through the process-based evaluation in which they are evaluated on the efforts they made and provided with feedbacks, they participated more in class, and it lead them to experience a sense of growth and a feeling that they took a step forward into their future. Teachers suggested that the class through feedback was suitable for the unit and the capacity of the class, but the difficulty they experienced in giving feedback was presented as a disadvantage. For the process-based assessment, follow-up research is needed on various ways to provide feedback on-line and off-line through changes in the perception of assessment.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.