• Journal of The Korean Association For Science Education
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• v.24 no.5
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• pp.851-868
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• 2004

The main purposes of this study is to develop a web-based STS biology instruction program (WB-STS) for the scientifically gifted students. The specific main research questions were as follows; 1. How can the WB-STS for biology education be developed and what are the primary components involved in it? 2. Is there any proper validity for developed the WB-STS in biology education? To solve the above mentioned problems, several procedures were applied. First, in order to develop WB-STS for the scientifically gifted students, NCISE, Renzulli' s Enrichment Triad Model and the Iowa Chautauqua program's main characteristics were analyzed systematically and the principles and general process for constructing WB-STS were examined. Additionally, the needs of students and the goals of Biology education were identified thoroughly. And then all these ideas were embodied in an agenda for constructing WB-STS. Second, to analyse the validity and utility of developing WB-STS, a questionnaire was developed and submitted to seven specialists and a group of twenty students who would participate in the experiment later. The main results of study are summarized below: First, WB-STS appeared to be successfully constructed based on Renzulli' s Enrichment Triad Model and the Iowa Chautauqua program. Its main features are that it was made emphasizing a learner-centered approach and constructive learning. It is composed of five steps: Scientific theme selection -${\rightarrow}$Exploration ${\rightarrow}$ Concept & Principle Check ${\rightarrow}$ Finding Solution ${\rightarrow}$ Action. Second, seven specialists and a group of students assessed the developed WB-STS's validity and utility with a questionnaire, the results appeared satisfactory. Students showed high interest in WB-STS and gave a positive evaluation of WB-STS.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.412-425
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• 2008

One of the important elements for improving academic achievement of learners in education through e-learning is to support learners to study by finding questions they want with providing various evaluation questions. However, most of question retrieval systems usually depend on keyword search based on only a syntactical analysis and/or a hierarchical browsing system classified by the topics of subjects. In such a system it is not easy to find integrative questions associated with each other. In order to improve this problem, in this paper we proposed a question management and retrieval system which allows users to easily manage questions and also to effectively find questions for study on the Web. Then, we implemented a system that gives to access questions for the domain of C language programming. The system makes it possible to easily search questions related to not only a single theme but also questions integrated by interrelationship between topics and questions. This is done by supporting to be able to retrieve questions according to conceptual interrelationships between questions from user query. Consequently, it is expected that the proposed system will provide learners to understand the basic theories and the concepts of the subjects as well as to improve the ability of comprehensive knowledge utilization and problem-solving.

• Archives of design research
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• v.19 no.2 s.64
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• pp.163-172
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• 2006

Sign is one of the important factors in city and national image formation, thus requires high level of quality. However, domestic sign emphasize only the sense of attention that leads to big sized signs, thus often results in a poor coordination with the surrounding space. This situation requires employees in sign business want to learn specialized knowledge about design field. Based on these circumstances, we propose sign design software to employees in sign business field as an aid tool that can help to develop good signs in terms of functionality as well as harmony of design. Thus, in this investigation, sign simulation software application case that can design sign and apply this sign to the actual application site is presented. In order to develop this software, literature survey and preliminary studies were performed to analyze the preparation process and environment, and designed sign design element and software elements, user interrace, and finally Java software were utilized. This developed software can be used as a textbook in sign design related departments in schools, and hopefully to enhance the social recognition of sign as well as academic interest.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.