• Journal of Internet Computing and Services
• /
• v.16 no.6
• /
• pp.123-131
• /
• 2015

Recently the development of ICT has a big impact on education field, and diffusion of smart devices has brought new education paradigm. Since people has an opportunity to use various contents anytime and communicate in an interactive way, the method of learning has changing. In 2011, Korean government has established the smart education promotion plan to be a first mover in the paradigm shift from e-learning to smart learning. Especially, government aimed to improve the quality of learning materials and method in public schools, and also to decrease the high expenditure on private education. However, the achievement of smart education policy has not emerged yet, and the refinement of smart learning policy and strategy is essential at this moment. Therefore, the purpose of this study is to propose the successful strategies for smart learning in public education. First, this study explores the status of public education and smart learning environment in Korea. Then, it derives the key success factors through SWOT(Strength, Weakness, Opportunity, Threat) analysis, and suggests strategic priorities through AHP(Analytic Hierarchy Priority) method. The interview and survey were conducted with total 20 teachers, who works in public schools. As a results, focusing on weakness-threat(WT) strategy is the most prior goal for public education, to activate the smart learning. As sub-factors, promoting the education programs for teachers($W_2$), which is still a weakness, appeared as the most important factor to be improved. The second sub-factor with high priority was an efficient optimizing the capability of new learning method($S_4$), which is a strength of systematic public education environment. The third sub-factor with high priority was the extension of limited government support($T_4$), which could be a threat to other public schools with no financial support. In other words, the results implicate that government institution factors should be considered with high priority to make invisible achievement in smart learning. This study is significant as an initial approach with strategic perspective for public education. While the limitation of this study is that survey and interview were conducted with only teachers. Accordingly, the future study needs to be analyzed in effectiveness and feasibility, by considering perspectives from field experts and policy makers.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.34 no.12
• /
• pp.1980-1991
• /
• 2010

This study proposes the O P E N Triad framework as a future set of tools and perspectives for individual members and institutes to further their professional and academic potential as well as prospect and vitalize the future of the Korean Clothing and Textiles discipline through a global perspective. The millennial generation desires On-demand, Personal, Engaging, and Networked (O P E N) experiences effecting cultural change for creative and influential interaction in transactions, communication, and education. O P E N Individuals offers a WebSphere model as a holistic learning system that has a synergizing value of education across academic courses, industries, and cultures. Through a digitalized and virtualized class, it complements relevant technologies already familiar to the student population. By employing environmental scanning approaches, the most influential and viable future global issues related to the clothing and textiles discipline are identified and dialogued within O P E N Institutes. For future clothing and textiles institutes, this scanning allows them to be open to new ideas, to focus on inter-engagements, to collaborate among individuals, to associate as a part of web of people, organizations, and ideas, to personalize an institutes curricula, and to dialogue generative knowledge. O P E N Industries reveals three dominant future issues that cross academia and industry, sustainability, supply chain management, and social networking. In-depth interviews with U.S. industry experts identified interdependent gaps in global consumer experience practices and suggested the following gaps as future research areas: a standardized business model to the entrepreneurial model, strategic management to a sustainable competitive advantage, standardized to differentiated products, services and operations, market segmentation to global consumer clusters, business-driven marketplaces to consumer-engaged marketspaces, and excellent services to optimal experience. This O P E N Triad framework empowers millennial students, universities, and industries to anticipate and prepare for a radically changing world.

• School Mathematics
• /
• v.1 no.1
• /
• pp.123-133
• /
• 1999

For an appropriate assessment in mathematics, students should play an active role in their learning by becoming aware of what they have learned in mathematics and by being able to assess their attainment of mathematical knowledge. The process of actively examining and monitoring students' own progress in learning and understanding of their mathematical knowledge, process, and attitude is called self-assessment, Researchers in mathematics education have found some important facts about the meta-cognitive process which is related to self-assessment : i. e. meta-cognition progress is composed of being aware of ones' own personal thinking of content knowledge and cognitive process(self-awareness) and engagement in self-evaluation. Tipical method for self-assessment in mathematics developed upon above finding about meta-cognitive progress is describing about students' knowledge and their problem solving strategies. In the beginning of the description in mathematics about themselves, students are required to answer which part they know and which part they don't know. Self-assessment of students' attitudes and dispositions can be just as important as assessment of their specific mathematical abilities. To make the self-assessment method a success, teachers should let students' have confidence and earn their cooperation by let them overcoming fear to be known the their ability to other students. In conclusion, self-assessment encourages students to assume an active role in development of mathematical power. For teachers, student self-assessment activities can provide a prism through which the development of students' mathematical power can be viewed.

• Korea Journal of Hospital Management
• /
• v.14 no.2
• /
• pp.75-98
• /
• 2009

As the organizational environments are changing, organizational innovation has become a critical success factor for the healthcare organizations. Although there are lots of successful innovation cases in other industries, healthcare organization's management innovation cases are rare in Korea. This case study is focused on successful change process of a Maeumsarang psychiatric hospital. Main findings are: (a) virtuous cycle of healthcare service innovation and organizational innovation, (b) intensive training and learning, (c) usage of external resources, (d) high commitment HRM system, (e) CEO leadership, and (f) synchronization of planning and execution. Based on these findings, managerial implications are derived and future research directions are proposed.

• KIPS Transactions on Computer and Communication Systems
• /
• v.7 no.5
• /
• pp.127-136
• /
• 2018

In this paper, we propose a PIN entry method that combines with machine learning technique on smartphone. We use not only a PIN but also touch time intervals and locations as factors to identify whether the user is correct or not. In the user registration phase, a remote server was used to train/create a machine learning model using data that collected from end-user device (i.e. smartphone). In the user authentication phase, the pre-trained model and the saved PIN was used to decide the authentication success or failure. We examined that there is no big inconvenience to use this technique (FRR: 0%) and more secure than the previous PIN entry techniques (FAR : 0%), through usability and security experiments, as a result we could confirm that this technique can be used sufficiently. In addition, we examined that a security incident is unlikely to occur (FAR: 5%) even if the PIN is leaked through the shoulder surfing attack experiments.

• Journal of Distribution Science
• /
• v.12 no.11
• /
• pp.45-53
• /
• 2014

Purpose - Goal setting is effective in any domain in which an individual or group has some control over the outcomes. It applies not only to work tasks but also to sports and health, and in various other settings. Its success depends on considering the mediators and moderators determining its efficacy and applicability. This study investigates the individual factors influencing academic goal attainability. Unlike previous studies, we focused on the effect of the relationships between individual traits (passion, tenacity, self-control) and specific motivation (vision, self-efficacy, implementation intentions) with academic goal attainability, rather than the effects of the relationship between commitment and the goal shielding mechanism with goal attainability. Research design, data, and methodology - Data collected through questionnaires were analyzed by the SPSS program. A total of 293 school students, who participated in the TOEIC program, participated in the survey. Slightly more than half were female (male: n=145 vs. female: n=148). We verified nine hypotheses through various statistical methods (reliability analysis, exploratory factor analysis, confirmatory factor analysis, structural equation model for the hypothesis test, bootstrapping test for the mediation test). Results - Data was analyzed in three phases. The first phase involved measurement analysis (i.e., item purification and factor structure confirmation), involving the scales of the three variables of individual traits, three mechanism variables, and goal attainability. The second phase involved estimating the proposed structural relationships among the key constructs (see Figure 1), using the results to test H1 to H9. The final phase involved examining the mediating effects of the three variables (vision, implementation intention, and self-efficacy). The research model shows that the independent variable passion has a significant result with both the mediators-vision and self-efficacy. Further, vision and self-efficacy significantly affect goal attainability. The second variable, self-control, shows a significant effect when mediated by implementation intentions, but the direct relationship between implementation intension and goal attainability shows an insignificant result. However, when further mediated by self-efficacy, it showed a significant effect between self-efficacy and goal attainability. Similarly, the third variable, tenacity, shows an insignificant result when mediated by vision. In contrast, the mediator self-efficacy shows a positive effect between tenacity and goal attainability. Conclusions - This study shows how these individual traits, when mediated with the appropriate motivational factors, resulted significantly in the attainability of academic goals. We may identify several theoretical and practical contributions. Theoretically, we developed a step further in the research into consumer goals and related studies. Future research could examine the effects of different learning goal types and their combinations with performance goals (e.g., learning goals first, then performance goals), different types of goal framing (approach success vs. avoid failure), the relation between goals and cognition (which, by implication, entails all of cognitive psychology), goal hierarchies, and macro goal studies with organizations of different sizes. More studies on the relationship between conscious and subconscious goals would also be valuable.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.3
• /
• pp.133-140
• /
• 2022

We investigate the performance of deep learning-based Korean language models on a task of predicting the score range of Korean essays written by foreign students. We construct a data set containing a total of 304 essays, which include essays discussing the criteria for choosing a job ('job'), conditions of a happy life ('happ'), relationship between money and happiness ('econ'), and definition of success ('succ'). These essays were labeled according to four letter grades (A, B, C, and D), and a total of eleven essay score range prediction experiments were conducted (i.e., five for predicting the score range of 'job' essays, five for predicting the score range of 'happiness' essays, and one for predicting the score range of mixed topic essays). Three deep learning-based Korean language models, KoBERT, KcBERT, and KR-BERT, were fine-tuned using various training data. Moreover, two traditional probabilistic machine learning classifiers, naive Bayes and logistic regression, were also evaluated. Experiment results show that deep learning-based Korean language models performed better than the two traditional classifiers, with KR-BERT performing the best with 55.83% overall average prediction accuracy. A close second was KcBERT (55.77%) followed by KoBERT (54.91%). The performances of naive Bayes and logistic regression classifiers were 52.52% and 50.28% respectively. Due to the scarcity of training data and the imbalance in class distribution, the overall prediction performance was not high for all classifiers. Moreover, the classifiers' vocabulary did not explicitly capture the error features that were helpful in correctly grading the Korean essay. By overcoming these two limitations, we expect the score range prediction performance to improve.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.5
• /
• pp.179-186
• /
• 2021

Manipulation of complex objects with an anthropomorphic robot hand like a human hand is a challenge in the human-centric environment. In order to train the anthropomorphic robot hand which has a high degree of freedom (DoF), human demonstration augmented deep reinforcement learning policy optimization methods have been proposed. In this work, we first demonstrate augmentation of human demonstration in deep reinforcement learning (DRL) is effective for object manipulation by comparing the performance of the augmentation-free Natural Policy Gradient (NPG) and Demonstration Augmented NPG (DA-NPG). Then three DRL policy optimization methods, namely NPG, Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO), have been evaluated with DA (i.e., DA-NPG, DA-TRPO, and DA-PPO) and without DA by manipulating six objects such as apple, banana, bottle, light bulb, camera, and hammer. The results show that DA-NPG achieved the average success rate of 99.33% whereas NPG only achieved 60%. In addition, DA-NPG succeeded grasping all six objects while DA-TRPO and DA-PPO failed to grasp some objects and showed unstable performances.

• The Journal of Society for e-Business Studies
• /
• v.21 no.1
• /
• pp.15-32
• /
• 2016

Online news on the Internet, as published open data, contain facts or opinions about a specific affair and hence influences considerably on the decisions of the general publics who are interested in a particular issue. Therefore, we can predict the people's choices related with the issue by analyzing a large number of related internet news. This study aims to propose a text analysis methodto predict the outcomes of events that take place in a specific place. We used topics of the news articles because the topics contains more essential text than the news articles. Moreover, when it comes to mobile environment, people tend to rely more on the news topics before clicking into the news articles. We collected the titles of news articles and divided them into the learning and evaluation data set. Morphemes are extracted and their polarity values are identified with the learning data. Then we analyzed the sensitivity of the entire articles. As a result, the prediction success rate was 70.6% and it showed a clear difference with other analytical methods to compare. Derived prediction information will be helpful in determining the expected demand of goods when preparing the event.

• Journal of Technology Innovation
• /
• v.13 no.2
• /
• pp.23-43
• /
• 2005

Industrial clusters are geographical concentrations of interconnected companies, specialised suppliers, service providers, firms in related industries, and associated institutions (for example, universities, standard agencies, and trade associations) that combine to create new products and/or services in specific lines of business. At present, the concept of industrial cluster becomes very popular worldwide, policy makers at national, regional and local levels and business people in both forerunner and latecomer countries are keen to implement the cluster concept as an economic development model. Though understanding of clusters and related promoting policies varies from one place to another, the underlying benefits of clusters from collective learning and knowledge spillovers between participating actors strongly attract the attention of these people. In Thailand, a latecomer country in terms of technological catching up, the cluster concept has been used as a means to rectify weakness and fragmentation of its innovation systems. The present Thai government aspires to apply the concept to promote both high-tech manufacturing clusters, services clusters and community-based clusters at the grass-root level. This paper analyses three very different clusters in terms of technological sophistication and business objectives, i.e., hard disk drive, software and chili paste. It portrays their significant actors, the extent of interaction among them and the evolution of the clusters. Though are very dissimilar, common characteristics attributed to qualified success are found. Main driving forces of the three clusters are cluster intermediaries. Forms of these organizations are different from a government research and technology organization (RTO), an industrial association, to a self-organised community-based organization. However, they perform similar functions of stimulating information and knowledge sharing, and building trust among participating firms/individuals in the clusters. Literature in the cluster studies argues that government policies need to be cluster specific. In this case, the best way to design and implement cluster-specific policies is through working closely with intermediaries and strengthening their institutional especially in linking member firms/individuals to other actors in clusters such as universities, government R&D institutes, and financial institutions.