• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.1
• /
• pp.7-18
• /
• 2013

These days, the teaching and learning system has been increasing for the rapid advancement of the information technologies. We can access education systems of good quality anytime, anywhere and we can use the individually personalized teaching and learning system depending on developing the wireless communication technology and the multimedia processing technology. The more the various systems develop, the more software security systems become important. There are a lot kind of fault analysis methods to evaluate software security systems. However, the only assessment method to evaluate software security system is not enough to analysis properly on account of the various types and characteristic of software systems by progressing information technology. Therefore, this paper proposes an integrative method of Fault Tree Analysis (FTA) and Fault Modes and Effect Analysis(FMEA) to evaluate the security of e-teaching and learning system as an illustration.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.4
• /
• pp.1-10
• /
• 2019

This study investigates maker pedagogy as learning method with graduate students. The exemplary maker pedagogy instructional model in this study is intended to enhance student's research competence. This study examines how the teacher designs and implements maker pedagogy instructional model, and what students have experienced in conduction research project. students provide evidence that they have improved their competence to raise research questions, to make use of research methodology. Their learning experience depends on whether they are heterogeneously grouped or homogeneously grouped in terms of intellectual ability, research experience, etc. Additionally, students suggest that the teacher needs to administrate the learning process regularly, to build up an interdisciplinary network to provide students knowledge and methodologies needed for conducting research, and to create learning environment where each student is possibly enriched with individual accountability and responsibility on each own learning process. In conclusion, this study provides several suggestions for more valuable maker pedagogy instructional models in graduate class.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.12
• /
• pp.3798-3814
• /
• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.

• Geophysics and Geophysical Exploration
• /
• v.25 no.2
• /
• pp.71-84
• /
• 2022

When acquiring seismic data, various types of simultaneously recorded seismic noise hinder accurate interpretation. Therefore, it is essential to attenuate this noise during the processing of seismic data and research on seismic noise attenuation. For this purpose, machine learning is extensively used. This study attempts to attenuate noise in prestack seismic data using unsupervised machine learning. Three unsupervised machine learning models, N2NUNET, PATCHUNET, and DDUL, are trained and applied to synthetic and field prestack seismic data to attenuate the noise and leave clean seismic data. The results are qualitatively and quantitatively analyzed and demonstrated that all three unsupervised learning models succeeded in removing seismic noise from both synthetic and field data. Of the three, the N2NUNET model performed the worst, and the PATCHUNET and DDUL models produced almost identical results, although the DDUL model performed slightly better.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.355-360
• /
• 2021

COVID-19 has brought major changes to school education. Although it was attempted to guarantee students' right to learn through romote learning, the limitations of remote learning compared to face-to-face classes were clear. Nevertheless, the method of remote learning is undoubtedly a learning method that needs to be continuously developed in terms of being able to consider separated time and space and enabling learners to learn individually and autonomously. Therefore, in this study, real-time romote learning cases were analyzed at the elementary school stage, and problems in real-time remote classes were discovered and improved through teacher interviews. The problems with real-time remote classes in elementary school unit classes examined through examples are: First, that the proportion of teacher activity is high due to the anxiety of the unfamiliar environment of remote classes, and second, even though it is a real-time interactive class, it It was impossible to provide feedback. As a solution to this, it is necessary to consider the basic class steps (introduction-deployment-organization) and the use of class tools to provide appropriate communication and feedback was suggested.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.121-127
• /
• 2023

The purpose of this pilot study is to examine the responses of middle school students to English learning after conducting English writing activities using DALL-E2, an image-generating artificial intelligence tool. To this end, an experimental class was conducted for 3 weeks for 15 middle school English learners, and the results are summarized as follows. First, as a result of a survey on English writing activities using DALL-E2, it was found that confidence, interest, and awareness of writing using artificial intelligence-based tools changed positively. In addition, it was confirmed that there was a statistically significant difference, which meant that learning using artificial intelligence had a positive effect on English writing and overall English learning. Second, as a result of analyzing the English writing activities using DALL-E2, core themes could be extracted into three (cognitive, affective, and psychodynamic characteristics), and the use and implementation of artificial intelligence-based DALL-E2 in English learning showed potential to increase learning interest, challenge, will, and desire in learning and ultimately contribute to enhancing productive skill.

• Journal of Korean Academy of Nursing
• /
• v.26 no.2
• /
• pp.281-289
• /
• 1996

Neural networks have recently attracted considerable attention in the field of classification and other areas. The purpose of this study was to demonstrate an experiment using back-propagation neural network model applied to nursing diagnosis. The network's structure has three layers ; one input layer for representing signs and symptoms and one output layer for nursing diagnosis as well as one hidden layer. The first prototype of a nursing diagnosis system for patients with stomach cancer was developed with 254 nodes for the input layer and 20 nodes for the output layer of 20 nursing diagnoses, by utilizing learning data set collected from 118 patients with stomach cancer. It showed a hitting ratio of .93 when the model was developed with 20,000 times of learning, 6 nodes of hidden layer, 0.5 of momentum and 0.5 of learning coefficient. The system was primarily designed to be an aid in the clinical reasoning process. It was intended to simplify the use of nursing diagnoses for clinical practitioners. In order to validate the developed model, a set of test data from 20 patients with stomach cancer was applied to the diagnosis system. The data for 17 patients were concurrent with the result produced from the nursing diagnosis system which shows the hitting ratio of 85％. Future research is needed to develop a system with more nursing diagnoses and an evaluation process, and to expand the system to be applicable to other groups of patients.

• The Mathematical Education
• /
• v.56 no.2
• /
• pp.213-234
• /
• 2017

The purpose of this study is to examine the perceptions and needs of the 2015 revised curriculum for elementary school teachers and to draw implications for the application of the 2015 revised mathematics curriculum. For this, the major changes in the 2015 revised mathematics curriculum were examined. Major changes in the 2015 revised mathematics curriculum are as follows: 1) Introduce and emphasize mathematical competencies, 2) Restructure the content system, 3) Reduce mathematics contents to teach, 4) Emphasize the learner's affective domain, 5) Emphasize the use of technology, 6) Improve teaching and learning methods and evaluation methods. Also, a survey was conducted for elementary school teachers to analyze the perceptions and demands of the 2015 Revised Mathematics Curriculum. The contents of the survey are consisted of contents of the teachers' awareness of the main changes of the 2015 Revised Curriculum and their demands to implement the 2015 Revised Curriculum in schools. Finally, conclusions and suggestions were drawn based on the survey results. The conclusions and suggestions are as follows: 1) there is a lack of teachers' awareness of the 2015 Revised Curriculum, 2) Support for mathematics curriculum competencies is needed, 3) A variety of teaching and learning materials are needed for emphasizing the learner's affective domain, using the technology, and improving teaching and learning methods and evaluation methods.

• The Journal of Korean Academic Society of Nursing Education
• /
• v.24 no.4
• /
• pp.376-390
• /
• 2018

Purpose: The purpose of this study was to (a) synthesize nursing education literature using a smartphone for Korean nursing college students based on Whittemore and Knafl's integrative five-step review method and to (b) evaluate the quality appraisal of each article using Gough's weight of evidence. Methods: Articles published in Korea were identified through electronic search engines and scholarly websites using a combination of three search terms, including nursing student, smartphone, and education. Scientific, peer-reviewed articles in nursing education for Korean college nursing students, written in Korean or in English, and published between January 2000 and May 2018 were included in this review. Thirteen papers met the inclusion criteria and had above average ratings in quality appraisals. Results: Three characteristics related to nursing education using a smartphone were derived: (a) as a familiar media, motivating learning and enabling self-directed learning, (b) for the purpose of education or evaluation utilizing the educational movie of application, and (c) the iterative exercise of smartphone usage reinforces student learning. Conclusion: Smartphone use is an effective tool for improving nursing knowledge and skills for nursing college students in nursing education. Future research is needed to standardize smartphone applications across schools for nursing education.

• Journal of Korean language education
• /
• v.29 no.3
• /
• pp.117-144
• /
• 2018

The purpose of this study is to explore the linguistic elements that can promote academic literacy in terms of content-based instructions for KSL learners. In order to study the characteristics of learning languages for subjects, focus was given to the framework of systematic functional linguistics that has been extensively used in ELL teaching and learning research in the United States and Australia. History, which is taught in all classes and classified as a required course, was the subject of analysis. From the history curriculum, the elementary school level texts "Social Studies 5-2" and "Social Studies 6-1" were chosen for the analysis. Based on the results, we can come to the following conclusions. First, history textbooks are divided into narrative and analytical explanatory sub-genres based on their content, and there are differences in the factors that need to be focused on to find the main information. Second, the vocabulary of history textbooks should focus on the use of verbs which comprehend material processes. Particularly, learners should pay attention to the differences in meaning between low-frequency expressions. We hope that the results of this study will have a positive effect on history subject learning for learners in the "Adaptive Korean Course" and will help establish direction in terms of building curriculum contents for KSL learners.