• Journal of The Korean Association For Science Education
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• v.31 no.5
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• pp.663-679
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• 2011

This case study focused on three science teachers who participated in the Research Experience for Teachers (RET) program conducted by the Center for Bridging Advanced Science and Education (CBASE). The RET program provides opportunities for participants to experience experimentations in a science laboratory for six months, enabling teachers develop teaching materials based on their experience from the RET program. The purpose of this study was to explore how the teachers had developed their professionalism through participation in the program and which factors promoted the professional development of science teachers. In this research, we defined pedagogical content knowledge (PCK) as the required knowledge for teachers to develop for their professional development. As a result of the RET program, all three participants showed integration of PCK elements: orientation to teaching science, knowledge of science, knowledge of students, knowledge of teaching, and knowledge of sources. The PCK elements which had been developed by the RET program were applied in school context and the teachers' belief became clear and strong. The teachers were able to understand the process of authentic science as they learned it from 'legitimate peripheral participation' in the authentic research context. They also showed dynamic integration between newly established elements of PCK by reflecting on the school context while developing the teaching materials. The professional development of each teacher was different depending on the purpose and PCK, which participants had already possess. This study will provide meaningful implication for the development of professional development program for science teachers based on research experience.

• Journal of Korean Home Economics Education Association
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• v.22 no.2
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• pp.133-153
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• 2010

The purpose of this study is to find out the philosophy embedded in the newly revised 2007 Home Economics curriculum. Furthermore, it analyses the current situation and future tasks of textbooks in view of that philosophy. With this analysis it tries to give alternative teaching-learning strategies for making the best use of the existing textbooks. This study deals with the newly revised 2007 Home Economics curriculum. It also analyses the twelve sorts of textbooks for the first grade students in secondary schools, which are supposed to be based on that curriculum. As a research method this study takes a qualitative approach. As follows are the results of this study. First, in the character and objectives of the curriculum is embedded the critical science perspective of Home Economics curriculum. Second, the current situation and future tasks of the textbooks are analysed with the criteria by Yang, mi-kyung about textbook construction. And we have ascertained the following problems. The current textbooks are not well designed so that teachers have the appropriate orientation, encourage students to nurture the critical thinking abilities, and urge students to employ practical reasoning in the context of society, history and culture. Third, this study proposes five alternative teaching-learning strategies for making the best use of the current textbooks in order to tackle the above-mentioned problems.

• Structural Engineering and Mechanics
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• v.63 no.4
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• pp.429-438
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• 2017

Structural design has an imperative role in deciding the failure possibility of a Reinforced Concrete (RC) structure. Recent research works achieved the goal of predicting the structural failure of the RC structure with the assistance of machine learning techniques. Previously, the Artificial Neural Network (ANN) has been trained supported by Particle Swarm Optimization (PSO) to classify RC structures with reasonable accuracy. Though, keeping in mind the sensitivity in predicting the structural failure, more accurate models are still absent in the context of Machine Learning. Since the efficiency of multi-objective optimization over single objective optimization techniques is well established. Thus, the motivation of the current work is to employ a Multi-objective Genetic Algorithm (MOGA) to train the Neural Network (NN) based model. In the present work, the NN has been trained with MOGA to minimize the Root Mean Squared Error (RMSE) and Maximum Error (ME) toward optimizing the weight vector of the NN. The model has been tested by using a dataset consisting of 150 RC structure buildings. The proposed NN-MOGA based model has been compared with Multi-layer perceptron-feed-forward network (MLP-FFN) and NN-PSO based models in terms of several performance metrics. Experimental results suggested that the NN-MOGA has outperformed other existing well known classifiers with a reasonable improvement over them. Meanwhile, the proposed NN-MOGA achieved the superior accuracy of 93.33% and F-measure of 94.44%, which is superior to the other classifiers in the present study.

• Journal of the Korean Institute of Educational Facilities
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• v.25 no.4
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• pp.19-30
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• 2018

The school classroom is a common living place where students spend 7 to 14 hours a day to prepare for their careers. Therefore, if the ventilation of the classroom is not properly performed, it may lead to the deterioration of learning ability due to the unclear air. The concentration of carbon dioxide in the classroom is reported to be high, and the increase in carbon dioxide concentration has a negative effect on the learner's academic performance. In this context, the purpose of this study is to propose a methodology for intelligent and responsive window opening-closing operation process that can reduce the concentration of $CO_2$ in the classroom in order to build a support space that can create an effective teaching-learning environment for adolescents. The specific objectives are as follows. First of all, we define the concept of window opening-closing operation. Secondly, twe develop the operation process of window opening-closing. Thirdly, we develop an algorithm for real-time window opening and closing (process) (Window Opening-Closing Operation Process). Finally, we verify the intelligent responsive window opening-closing operation process through developing examples of window opening-closing operation process using the parametric design program. This study is a preliminary study to develop algorithms necessary for window opening-closing operation. Based on the first-order algorithm, We simulated window opening-closing operations according to a hypothetical scenario. As a result, This study can show that the window is open and close depending on the $CO_2$ concentration, but the $CO_2$ concentration in the room is higher than outdoors. Consequentially, we suggest that it is necessary to develop an algorithm to supplement these results because window is often not working when the temperature difference between indoor and outdoor in winter is large.

• International Journal of Knowledge Content Development & Technology
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• v.10 no.4
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• pp.29-46
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• 2020

The paper describes the quantitative and qualitative dimensions of artificial neural networks (ANN) in India in the global context. The study is based on research publications data (8260) as covered in the Scopus database during 1999-2018. ANN research in India registered 24.52% growth, averaged 11.95 citations per paper, and contributed 9.77% share to the global ANN research. ANN research is skewed as the top 10 countries account for 75.15% of global output. India ranks as the third most productive country in the world. The distribution of research by type of ANN networks reveals that Feed Forward Neural Network type accounted for the highest share (10.18% share), followed by Adaptive Weight Neural Network (5.38% share), Feed Backward Neural Network (2.54% share), etc. ANN research applications across subjects were the largest in medical science and environmental science (11.82% and 10.84% share respectively), followed by materials science, energy, chemical engineering and water resources (from 6.36% to 9.12%), etc. The Indian Institute of Technology, Kharagpur and the Indian Institute of Technology, Roorkee lead the country as the most productive organizations (with 289 and 264 papers). Besides, the Indian Institute of Technology, Kanpur (33.04 and 2.76) and Indian Institute of Technology, Madras (24.26 and 2.03) lead the country as the most impactful organizations in terms of citation per paper and relative citation index. P. Samui and T.N. Singh have been the most productive authors and G.P.S.Raghava (86.21 and 7.21) and K.P. Sudheer (84.88 and 7.1) have been the most impactful authors. Neurocomputing, International Journal of Applied Engineering Research and Applied Soft Computing topped the list of most productive journals.

• 중국학논총
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• no.62
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• pp.85-100
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• 2019

The article purpose is 'Reading Chinese translation text as a Korean integrated education for Chinese students'. Although number of foreign students has increased rapidly to the economic growth of Korea, the influence of Korean Wave, and the popularity of Korean popular culture like K-pop at domestic universities but the problems of their curriculum have been found in many places. Korean literary education through novel text has an important place in Korean studies, but literary education is often excluded in Korean language education as a foreign language education. Chinese students already have background knowledge of Korean translation novels through Chinese novels. They can get the learning effect as the Korean language study. Second, they can compared with Korean national violence and Chinese national violence through 'Red Revolution' and understand about Korean-Chinese understanding of the times, social and cultural phenomena, Third, they are able to study the theory of literature itself. also It was the educational purpose pursued by the humanities. Chinese students develop their Korean language skills by studying the Brothers which are translated into Korean, and we can see the similarities and differences of national violence by comparing Korea's '4.19' with China's 'Cultural Revolution' After comparing people, background, dynamics of the space where they are located, we can raise awareness of the historical and social problems of both countries. It is possible to study subjects' memories of space, change of local meaning, the formation of urban space or individual space in the text in the specific space where national violence occurs. In this way, the method of learning Korean integrated education through Brothers of the Chinese translation novels makes an opportunity to look at national violence in the Korean-Chinese space of the 1960s and 1970s. It has a subjective perspective from subordination to the nationality of the modern nation-state. This is an educational effect that can be obtained through reading a Chinese translation novel as a Korean language integrated education.

• Korean Journal of Clinical Pharmacy
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• v.34 no.2
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• pp.134-139
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• 2024

Background: Increasing numbers of studies and research about artificial intelligence (AI) and machine learning (ML) have led to their application in clinical trials. The purpose of this study is to analyze computer-based new technologies (AI/ML) applied on clinical trials registered on ClinicalTrials.gov to elucidate current usage of these technologies. Methods: As of March 1st, 2023, protocols listed on ClinicalTrials.gov that claimed to use AI/ML and included at least one of the following interventions-Drug, Biological, Dietary Supplement, or Combination Product-were selected. The selected protocols were classified according to their context of use: 1) drug discovery; 2) toxicity prediction; 3) enrichment; 4) risk stratification/management; 5) dose selection/optimization; 6) adherence; 7) synthetic control; 8) endpoint assessment; 9) postmarketing surveillance; and 10) drug selection. Results: The applications of AI/ML were explored in 131 clinical trial protocols. The areas where AI/ML was most frequently utilized in clinical trials included endpoint assessment (n=80), followed by dose selection/optimization (n=15), risk stratification/management (n=13), drug discovery (n=4), adherence (n=4), drug selection (n=1) and enrichment (n=1). Conclusion: The most frequent application of AI/ML in clinical trials is in the fields of endpoint assessment, where the utilization is primarily focuses on the diagnosis of disease by imaging or video analyses. The number of clinical trials using artificial intelligence will increase as the technology continues to develop rapidly, making it necessary for regulatory associates to establish proper regulations for these clinical trials.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.113-122
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• 2018

The purpose of this study is to investigate the effects of the educational context variables on students' science achievement and interest in TIMSS 2015. TIMSS 2015 science data and questionnaire results were used to fit the Hierarchical Linear Model (HLM) in this study. According to the results, books at home, parents' level of education, and students' views on science lessons have significant influence on science achievement of above-high level 4th-grade students, and books at home on below-intermediate level 4th-grade students. Books at home, students' views on science lessons, and school composition by student economic background have significant influence on science achievement of above-high level 8th-grade students, and books at home and students' views on science lessons on science achievement of below-Intermediate level 8th-grade students. In all grade levels, books at home, and students' views on science lessons have significant influence on science achievement and interest. Discussed in the conclusion are ways to improve science teaching and learning including offering systematic reading programs for all students, reinforcement of student-participation in science classes, connecting science hands-on activities with science concepts for below-Intermediate level elementary students, and so on.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.91-104
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• 2021

This study explored users' emotional states identified from the wake-up words -"Hi, KIA!"- using a machine learning algorithm considering the user interface of passenger cars' voice. We targeted four emotional states, namely, excited, angry, desperate, and neutral, and created a total of 12 emotional scenarios in the context of car driving. Nine college students participated and recorded sentences as guided in the visualized scenario. The wake-up words were extracted from whole sentences, resulting in two data sets. We used the soundgen package and svmRadial method of caret package in open source-based R code to collect acoustic features of the recorded voices and performed machine learning-based analysis to determine the predictability of the modeled algorithm. We compared the accuracy of wake-up words (60.19%: 22%~81%) with that of whole sentences (41.51%) for all nine participants in relation to the four emotional categories. Accuracy and sensitivity performance of individual differences were noticeable, while the selected features were relatively constant. This study provides empirical evidence regarding the potential application of the wake-up words in the practice of emotion-driven user experience in communication between users and the artificial intelligence system.

• Journal of The Korean Association of Information Education
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• v.20 no.4
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• pp.357-366
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• 2016

The ability of computational thinking is a key competence that person of talent in the future should keep. Computational thinking is a serial process in which a problem is defined in context of computing, stages of abstraction are processed in order to find the efficient solution, the most appropriate process and resources for a solution are selected and combined through algorithms which use various concepts, principles and methods for automatic implementation of abstract concepts. It needs appropriate learning content in stage of elementary school. This study has verified the effect it made on improvement of learner's creative personality by developing and applying the educational content for software education based on the integrative production. The result of study confirmed that learning through the educational content for software education based on the integrative production affects improvement on learner's creativity positively and suggested a method of applying it to computing education in elementary school.