• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.167-173
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• 2021

The purpose of this study is to discuss the types of algorithms and data categories in AI education for elementary school students. The study surveyed 11 pre-elementary teachers after providing education and practice on various data, artificial intelligence algorithm, and AI education platform for 15 weeks. The categories of data and algorithms considering the elementary school level, and educational tools were presented, and their suitability was analyzed. Through the questionnaire, it was concluded that it is most suitable for the teacher to select and preprocess data in advance according to the purpose of the class, and the classification and prediction algorithms are suitable for elementary AI education. In addition, it was confirmed that Entry is most suitable as an AI educational tool, and materials that explain mathematical knowledge are needed to educate the concept of learning of AI. This study is meaningful in that it specifically presents the categories of algorithms and data with in AI education for elementary school students, and analyzes the need for related mathematics education and appropriate AI educational tools.

• Convergence Security Journal
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• v.24 no.2
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• pp.9-17
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• 2024

This paper examines the security threats to enterprise Generative Artificial Intelligence systems and proposes countermeasures. As AI systems handle vast amounts of data to gain a competitive edge, security threats targeting AI systems are rapidly increasing. Since AI security threats have distinct characteristics compared to traditional human-oriented cybersecurity threats, establishing an AI-specific response system is urgent. This study analyzes the importance of AI system security, identifies key threat factors, and suggests technical and managerial countermeasures. Firstly, it proposes strengthening the security of IT infrastructure where AI systems operate and enhancing AI model robustness by utilizing defensive techniques such as adversarial learning and model quantization. Additionally, it presents an AI security system design that detects anomalies in AI query-response processes to identify insider threats. Furthermore, it emphasizes the establishment of change control and audit frameworks to prevent AI model leakage by adopting the cyber kill chain concept. As AI technology evolves rapidly, by focusing on AI model and data security, insider threat detection, and professional workforce development, companies can improve their digital competitiveness through secure and reliable AI utilization.

• Journal of Science Education
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• v.32 no.1
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• pp.33-46
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• 2008

The purpose of this study was to know whether or not any wrongful description or simple errors were in photosynthesis unit of Biology II textbook under 7th national curriculum and if so, to know whether or not high school teachers recognized and corrected properly the mistakes. The mistakes in photosynthesis unit of text books were determined by the comparison with several reference books and through examination by three plant physiologists in 8 different Biology II textbooks. After the mistakes were analysed, the survey using contents of textbook containing the mistakes was conducted on high school teachers teaching Biology II. As a result, 48 mistakes were determined in 13 subjects. As many as four mistakes were found even in one subject in a certain textbook and a same mistake was found repeatedly in several textbooks. The survey result showed that the teachers who pointed exactly the mistakes out corrected properly, however, the percentage of these ones out of 35 teachers replied to survey was less than 50%. The ratios of correction out of total number of responses were high in question #6 (43%), #4-3 (40%), and #1-2 (32%) which were containing a simple mistake in graph, a wrong word and a wrong picture, respectively. But, no one pointed out and made correction in question #5-1 and #5-2 which were containing Z scheme of light reaction without the legend of vertical axis that should be explained as electron energy or standard reduction potential. The result indicates the possibility that the mistakes in photosynthesis unit of Biology II textbook can be corrected and teached properly by teachers may be low. In order to reduce the possibility that students may have misconceptions about photosynthesis, the list of print's errors should be provided to the teachers and/or the training program and/or workshop for in-service high school biology teachers was recommended.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.105-114
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• 2017

Nowadays, novel and innovative technology including 3D printers, internet of things (IoT), and wearable devices are rapidly emerging. As we must constantly keep up with the most recent trends, words like convergence, multidisciplinarity, and design revolution indeed define society today. Due to the expansion of such diverse technological, industrial, and academic convergence trends, the role of design is becoming evermore essential in development of products as well as creative services. Even the government is pushing towards a 'creative economy' by encouraging ICT convergence to create novel industries as well as advanced jobs. In order to adapt flexibly to such changes in global trends, a solid academic curriculum centered around 'ICT+Design' must be developed. In the current research, we analyzed various literature and benchmarked the major universities both domestic and foreign. Also we utilized a survey-based approach against subjects who are experts or design specialists working in environments related to industry and research. In our proposed integrated ICT+Design educational curriculum, students familiarize themselves with design perspectives and methodology to creatively carry out the course. Moreover, experts from design and ICT came together in an act of 'Radical Collaboration' in which they shared their unique 'Design Thinking' in order to promote understanding and cooperation. Furthermore, industry experts have also taken part as mentors in order to create a workplace-oriented course with various integrated projects. Most importantly, the course was designed so that in addition to research, students can really get hands-on with their ideas in the creativity-integrated workplace.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.595-604
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• 2004

Automatic analysis of concepts or semantic relations from text documents enables not only an efficient acquisition of relevant information, but also a comparison of documents in the concept level. We present a multiple cause model-based approach to text analysis, where latent topics are automatically extracted from document sets and similarity between documents is measured by semantic kernels constructed from the extracted topics. In our approach, a document is assumed to be generated by various combinations of underlying topics. A topic is defined by a set of words that are related to the same topic or cooccur frequently within a document. In a network representing a multiple-cause model, each topic is identified by a group of words having high connection weights from a latent node. In order to facilitate teaming and inferences in multiple-cause models, some approximation methods are required and we utilize an approximation by Helmholtz machines. In an experiment on TDT-2 data set, we extract sets of meaningful words where each set contains some theme-specific terms. Using semantic kernels constructed from latent topics extracted by multiple cause models, we also achieve significant improvements over the basic vector space model in terms of retrieval effectiveness.

• Therapeutic Science for Rehabilitation
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• v.10 no.1
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• pp.53-61
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• 2021

Introduction : OMFT is a therapeutic technique based on sensorimotor, motor control and motor learning, and its major goal is to improve oral motor function. The oral motor conceptual hierarchical development is divided into 5 steps: 1) sensorimotor, 2) movement integration, 3) structural movement, 4) functional oral motor, and 5) comprehensive oral motor. Discussion : The OMFT consists of 3 techniques, 10 categories, and 50 sub-item. 1) Warming up technique: 2 categories, 12 sub-item, warming up by sensory awareness and adaptation, therapy situation adaptation, neck movement; 2) Key point technique: 7 categories, 30 sub-item, oral motor facilitation and increasing chewing skill by direct stroke of oral structures such as the face, lips, cheeks, gum, jaws, and tongue; 3) Application technique: 1 category, 8 sub-item, facilitate food intake and swallowing. Conclusion : The goal of this article is to introduce 3 techniques, 50 sub-item of OMFT, as a comprehensive oral motor therapy method, for application to clients. This article provides information that will help oral motor specialists in treating clients with oral motor problems more effectively and professionally.

• The Mathematical Education
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• v.62 no.2
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• pp.289-302
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• 2023

In today's digital information society, student knowledge and skills to analyze big data and make informed decisions have become an important goal of school mathematics. Integrating big data statistical projects with digital technologies in high school <Artificial Intelligence> mathematics courses has the potential to provide students with a learning experience of high impact that can develop these essential skills. This paper proposes a set of guidelines for designing effective big data statistical project-based tasks and evaluates the tasks in the artificial intelligence mathematics textbook against these criteria. The proposed guidelines recommend that projects should: (1) align knowledge and skills with the national school mathematics curriculum; (2) use preprocessed massive datasets; (3) employ data scientists' problem-solving methods; (4) encourage decision-making; (5) leverage technological tools; and (6) promote collaborative learning. The findings indicate that few textbooks fully align with these guidelines, with most failing to incorporate elements corresponding to Guideline 2 in their project tasks. In addition, most tasks in the textbooks overlook or omit data preprocessing, either by using smaller datasets or by using big data without any form of preprocessing. This can potentially result in misconceptions among students regarding the nature of big data. Furthermore, this paper discusses the relevant mathematical knowledge and skills necessary for artificial intelligence, as well as the potential benefits and pedagogical considerations associated with integrating technology into big data tasks. This research sheds light on teaching mathematical concepts with machine learning algorithms and the effective use of technology tools in big data education.

• Journal of The Korean Association For Science Education
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• v.25 no.7
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• pp.746-753
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• 2005

In order to be efficient teachers should understand the current level of leaners through diagnostic evaluation. However, it is arduous to administer a diagnostic examination in every class because of various limitations. This study examined, the major issues arising from the development of a new science diagnostic evaluation system by incorporating the using knowledge state analysis method. The proposed evaluation system was based on the knowledge state analysis method. Knowledge state analysis is a method where by a distinguished collection of knowledge uses the theory of knowledge space. The theory of knowledge space is very advantageous when analyzing knowledge in strong hierarchies like mathematics and science. It helps teaching plan through methodically analyzing a hierarchy viewpoint for students' knowledge structure. The theory can also enhance objective validity as well as support a considerable amount of data fast by using the computer. In addition, student understanding is improved through individualistic feedback. In this study, an evaluation instrument was developed that measured student learning outcome, which is unattainable from the existing method. The instrument was administered to pre-service physics teachers, and the results of student evaluation was analyzed using the theory of knowledge space. Following this, a revised diagnostic evaluation system for facilitating student individualized learning was constructed.

• Journal of The Korean Association For Science Education
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• v.37 no.3
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• pp.523-537
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• 2017

The purpose of this study is to investigate the features of elementary students' intuitive thinking emerged during problem solving activities as it related to thermal phenomena, focusing on when intuitive thinking appears and how it is related to logical thinking. For this, we presented a problem related to thermal phenomena to nine 5th-grade students, and examined how students' thinking emerged in the activities. We conducted clinical interviews to investigate the thinking process of students. The results of this study are as follows. First, students made their own solutions and justified it later during the emergence process of intuitive thinking. It was also found that students connected concrete materials and abstract concepts intuitively. They solved the problem by making predictions even when information is insufficient. Second, it was shown that intuitive thinking can emerge through the intended strategies such as drawing a mental image, thinking from a different perspective, and integrating methods. These results, which are related to the students' intuitive thinking has received little attention and will be the basis for helping students in the context of discovery of their problem solving activities.

• Journal of Gifted/Talented Education
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• v.15 no.1
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• pp.1-10
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• 2005

Overexcitaility (OE) as a concept that is related to developmental potential, has been shown to differ by intelligence, gender, involvement in school programs and artistic interest in American populations of students. Overexitability, used to describe the five ways that people might experience developmental potential for emotional growth, are emotional, intellectual, imaginational, sensual, and psychomotor. Little is known about the profiles of groups of gifted learners outside of studies conducted in the United States. In order to better understand the emotional needs of Korean students, the purpose of this study was to determine the overexcitability profiles of students enrolled in four high schools, each with a different domain focus: math and sciences, visual and performing arts, and foreign languages. 341 subjects of this study completed the Overexcitability Questionnaire II. Multivariate Analysis of Variance (MANOVA) was conducted to determine statistical differences. The results showed that Mean scores of psychomotor, sensual and imaginational are highest in the Art High School, intellectual is highest in the Science High School and emotional is highest in the Foreign Language High School. There were significant differences among the schools. Each major also showed significant difference. The results showed that mean score of psychomotor is highest in the Dance major, sensual, imaginational and emotional are highest in the Drama majore and intellectual is highest in the Science major. The results showed that the mean scores of psychomotor, imaginational and intellectual are higher in the male students than female students. On the other hand the mean scores of sensual and emotional are higher in the female students than in the male students.