• The Journal of the Korea Contents Association
• /
• v.21 no.4
• /
• pp.26-37
• /
• 2021

This study conducted a big data analysis on news to identify the agenda of media literacy, which has been socially discussed, and on which relevant policy directions will be proposed. To this end 1,336 articles from January 1, 2019 to September 30, 2020 were collected and a topic modeling analysis was conducted according to four periods. Five topics for each period were derived through the analysis, and implications based on the results are as follows. First, the government should implement a nation-level systematic approach to media literacy education according to life cycle stages to generate economic and cultural value. Second, local communities and schools should provide systematic support and education guidance activities to ensure a sustainable ecosystem for media literacy and prevent an educational gap and loss in learning. Third, efforts should be made in various aspects to minimize the side effects resulting from constantly providing media literacy education; furthermore a culture of desirable media application should be established. Finally, a research environment for scientific research on media literacy, active exchange of experience and value obtained in the field, and long-term accumulation of research results should be encouraged to develop a robust knowledge exchange culture.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.514-517
• /
• 2021

The purpose of this study is to discover the occupational identity by examining the narrative of the life of a vocational training teacher with self-esteem in programming fields. The following six types of occupational identity were found: 'a positive image of a vocational training teacher(fits oneself)', 'I feel proud of myself while doing vocational training activities.', 'a teacher who continues to develop him/herself as an expert in the subject class', 'a teacher who immerses him/herself as an expert on student change and growth', 'a teacher engaged in leading activities to create opportunities for vocational training', and 'a teacher of continuous pursuit'. This study has significance in exploring the structure of occupational identity recognition and experience of its formation of a self-esteemed vocational training teacher in programming fields, which have not been studied.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.88-88
• /
• 2021

최근 수자원과 수질관리 분야에 자료기반 머신러닝 모델과 딥러닝 모델의 활용이 급증하고 있다. 그러나 딥러닝 모델은 Blackbox 모델의 특성상 고전적인 질량, 운동량, 에너지 보존법칙을 고려하지 않고, 데이터에 내재된 패턴과 관계를 해석하기 때문에 물리적 법칙을 만족하지 않는 예측결과를 가져올 수 있다. 또한, 딥러닝 모델의 예측 성능은 학습데이터의 양과 변수 선정에 크게 영향을 받는 모델이기 때문에 양질의 데이터가 제공되지 않으면 모델의 bias와 variation이 클 수 있으며 정확도 높은 예측이 어렵다. 최근 이러한 자료기반 모델링 방법의 단점을 보완하기 위해 프로세스 기반 수치모델과 딥러닝 모델을 결합하여 두 모델링 방법의 장점을 활용하는 연구가 활발히 진행되고 있다(Read et al., 2019). Process-Guided Deep Learning (PGDL) 방법은 물리적 법칙을 반영하여 딥러닝 모델을 훈련시킴으로써 순수한 딥러닝 모델의 물리적 법칙 결여성 문제를 해결할 수 있는 대안으로 활용되고 있다. PGDL 모델은 딥러닝 모델에 물리적인 법칙을 해석할 수 있는 추가변수를 도입하며, 딥러닝 모델의 매개변수 최적화 과정에서 Cost 함수에 물리적 법칙을 위반하는 경우 Penalty를 추가하는 알고리즘을 도입하여 물리적 보존법칙을 만족하도록 모델을 훈련시킨다. 본 연구의 목적은 대청호의 수심별 수온을 예측하기 위해 역학적 모델과 딥러닝 모델을 융합한 PGDL 모델을 개발하고 적용성을 평가하는데 있다. 역학적 모델은 2차원 횡방향 평균 수리·수질 모델인 CE-QUAL-W2을 사용하였으며, 대청호를 대상으로 2017년부터 2018년까지 총 2년간 수온과 에너지 수지를 모의하였다. 기상(기온, 이슬점온도, 풍향, 풍속, 운량), 수문(저수위, 유입·유출 유량), 수온자료를 수집하여 CE-QUAL-W2 모델을 구축하고 보정하였으며, 모델은 저수위 변화, 수온의 수심별 시계열 변동 특성을 적절하게 재현하였다. 또한, 동일기간 대청호 수심별 수온 예측을 위한 순환 신경망 모델인 LSTM(Long Short-Term Memory)을 개발하였으며, 종속변수는 수온계 체인을 통해 수집한 수심별 고빈도 수온 자료를 사용하고 독립 변수는 기온, 풍속, 상대습도, 강수량, 단파복사에너지, 장파복사에너지를 사용하였다. LSTM 모델의 매개변수 최적화는 지도학습을 통해 예측값과 실측값의 RMSE가 최소화 되로록 훈련하였다. PGDL 모델은 동일 기간 LSTM 모델과 동일 입력 자료를 사용하여 구축하였으며, 역학적 모델에서 얻은 에너지 수지를 만족하지 않는 경우 Cost Function에 Penalty를 추가하여 물리적 보존법칙을 만족하도록 훈련하고 수심별 수온 예측결과를 비교·분석하였다.

• Phonetics and Speech Sciences
• /
• v.15 no.3
• /
• pp.75-82
• /
• 2023

Automatic speech recognition (ASR) has been revolutionized with deep learning-based approaches, among which self-supervised learning methods have proven to be particularly effective. In this study, we aim to enhance the performance of OpenAI's Whisper model, a multilingual ASR system on the Korean language. Whisper was pretrained on a large corpus (around 680,000 hours) of web speech data and has demonstrated strong recognition performance for major languages. However, it faces challenges in recognizing languages such as Korean, which is not major language while training. We address this issue by fine-tuning the Whisper model with an additional dataset comprising about 1,000 hours of Korean speech. We also compare its performance against a Transformer model that was trained from scratch using the same dataset. Our results indicate that fine-tuning the Whisper model significantly improved its Korean speech recognition capabilities in terms of character error rate (CER). Specifically, the performance improved with increasing model size. However, the Whisper model's performance on English deteriorated post fine-tuning, emphasizing the need for further research to develop robust multilingual models. Our study demonstrates the potential of utilizing a fine-tuned Whisper model for Korean ASR applications. Future work will focus on multilingual recognition and optimization for real-time inference.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_1
• /
• pp.1739-1756
• /
• 2021

Atmospheric nitrogen dioxide (NO₂) is mainly caused by anthropogenic emissions. It contributes to the formation of secondary pollutants and ozone through chemical reactions, and adversely affects human health. Although ground stations to monitor NO₂ concentrations in real time are operated in Korea, they have a limitation that it is difficult to analyze the spatial distribution of NO₂ concentrations, especially over the areas with no stations. Therefore, this study conducted a comparative experiment of spatial interpolation of NO₂ concentrations based on two linear-regression methods(i.e., multi linear regression (MLR), and regression kriging (RK)), and two machine learning approaches (i.e., random forest (RF), and support vector regression (SVR)) for the year of 2020. Four approaches were compared using leave-one-out-cross validation (LOOCV). The daily LOOCV results showed that MLR, RK, and SVR produced the average daily index of agreement (IOA) of 0.57, which was higher than that of RF (0.50). The average daily normalized root mean square error of RK was 0.9483%, which was slightly lower than those of the other models. MLR, RK and SVR showed similar seasonal distribution patterns, and the dynamic range of the resultant NO₂ concentrations from these three models was similar while that from RF was relatively small. The multivariate linear regression approaches are expected to be a promising method for spatial interpolation of ground-level NO₂ concentrations and other parameters in urban areas.

• Journal of Korean Home Economics Education Association
• /
• v.31 no.3
• /
• pp.155-177
• /
• 2019

The study aims to develop a teaching-learning plan that can solve the problem of the clothing and textiles area faced by the teenager as course of critical science perspective improving the empowerment. As a research method, it was conceptualized by applying the Laster(1986)'s curriculum development process. And it was applied to the conceptual framework of practical reasoning presented in: "Family, Food and Society A Teacher's guide" (Staaland & Storm, 1996). The results of this study are summarized as follows. First, based on the results of reviewing literature related to the clothing and textiles area, ongoing concerns related to the clothing and textiles is "Should we do with regard to clothing and textiles for families in the community? The valued ends is defined as a complex position with a high degree of freedom and a high responsibility, and the goal of learning is interdependence, emotional maturity, intellectual development, and communication ability. For the contents of education and activity structure, practical reasoning process was used as conceptual framework of education contents, and included sub-concerns, broad concepts, sub-concepts and intellectual and social skills. Second, based on the practical reasoning, we developed a teaching and learning plan in the clothing and textiles. As a result, a total of 12 plan of 5 modules were developed. And were developed a total of 31 tutorials, reading materials, picture materials, group activities, and video materials. The results of this study can be applied to teachers who want to try out practical inference process in class or teachers who have difficulty in practicing reasoning process in the field.

• Journal of the Korean earth science society
• /
• v.32 no.7
• /
• pp.784-797
• /
• 2011

The purposes of this study are: (1) to develop educational program designed to improve high school students' knowledge integration and their system thinking skills about global warming and (2) to identify the change of students' system thinking level. The developed program was implemented to twenty seven high school students, and six students grouped into three highs and three lows in their performance were selected to analyze their level of system thinking. The word association, casual map and drawing were used to measure and identify any significant change. As a result, the low level system thinking group improved their system thinking skills for global warming and the earth and sub-systems after the intervention. However, participants' misconception remained the same. And the high level systems thinking group showed more organize system thinking skills about a global warming topic. It is suggested that more educational programs be developed on various topics in order for high school students to improve their systems thinking skills as well as knowledge integration of earth systems and earth environment in school curriculum.

• 한국공간정보시스템학회:학술대회논문집
• /
• 2001.11a
• /
• pp.275-286
• /
• 2001

습지 분류의 목표는 '목록작성(inventory)과 평가와 관리를 위해 자연적인 생태계에 범위를 설정하는 것'이다. 또한 등질적인 속성을 갖는 생태단위를 기술하고, 자원관리 의사결정에 도움을 줄 수 있는 체계로 단위를 만들어내고, 목록작성과 지도화에 필요한 단위를 제공하면, 습지에 관한 개념과 용어의 통일성을 제공하는 것 등이다. 해안지형 가운데 해안 습지의 분류에는 우선, 1) 형태, 2) 생성요인, 3) 자갈, 모래, 펄 같은 기질 물질과 4)현재의 환경이라는 요소가 모두 고려되어야만 하는데 아직 국내에는 이에 대한 연구가 절대적으로 부족하여 이에 대한 규정이 부족한 현실이다. 따라서 현 단계에서 ISO/IEC 규정대로 각 코드는 엄밀히 상호배타적인 개념일 것, 정수로 표시할 것과 순차적으로 증가하는 숫자로 표시할 것 등의 전제조건을 만족시키는 전제 하에서 해안습지를 분류하는 것은 매우 힘든 작업이라 생각한다. 하지만 국토공간의 효율적 관리와 보존을 위해서는 위치와 장소에 따라 차이를 보이는 지질, 지형, 토양, 식생, 수리 현상 등 제반 지표 환경요소에 대한 체계화된 정보의 축척이 있어야 가능하다. 우리나라의 경우 지질 정보는 지질자원연구원에서 발행하는 지질도와, 농촌진흥청에서 발행하는 토양도, 임업연구원에서 발행하는 임상도 등의 주제도가 있으나, 지표환경을 나타내주는 지형에 대한 정보체계는 아직 이루러진 바가 없고, 대학의 석사학위논문이나, 실험적인 수준의 연구에 머물고 있는 실정이다. 이번 연구에서는 지형분류도 작성과 관련한 외국의 사례를 집중적으로 분석하고, 지형정보의 체계적 관리를 위해 가장 필요한 해안습지 지형분류도를 작성하기 위해 가장 기초적인 단계인 해안습지 지형분류체계에 대한 국내외의 연구성과를 비교하여 시안을 작성 표준화를 위한 첫 단계 시도를 소개하였다.분석 결과는 문장, 그림 및 도표, 장 끝의 질문, 학생의 학습 활동 수 등이 $0.4{\sim}1.5$ 사이의 값으로 학생 참여를 적절히 유도하는 발견 지향적 인 것으로 조사되었다. 그러나 장의 요약은 본문 내용을 반복하는 내용으로 구성되었다. 이와 같이 공통과학 과목은 새로운 현대 사회에 부응하는 교과 목표와 체계를 지향하고 있지만 아직도 통합과학으로서의 내용과 체계를 완전히 갖추고 있지 못할 뿐만 아니라 현재 사용되고 있는 7종의 교과서가 교육 목표를 충분히 반영하지 못하고 있다. 따라서 교사의 역할이 더욱더 중요하게 되었다.괴리가 작아진다. 이 결과에 따르면 위탁증거금의 징수는 그 제도의 취지에 부합되고 있다. 다만 제도운용상의 이유이거나 혹은 우리나라 주식시장의 투자자들이 비합리적인 투자형태를 보임에 따라 그 정책적 효과는 때로 역기능적인 결과로 초래하였다. 그럼에도 불구하고 이 연구결과를 통하여 최소한 주식시장(株式市場)에서 위탁증거금제도는 그 제도적 의의가 여전히 있다는 사실이 확인되었다. 또한 우리나라 주식시장에서 통상 과열투기 행위가 빈번히 일어나 주식시장을 교란시킴으로써 건전한 투자풍토조성에 저해된다는 저간의 우려가 매우 커왔으나 표본 기간동안에 대하여 실증분석을 한 결과 주식시장 전체적으로 볼 때 주가변동율(株價變動率), 특히 초과주가변동율(超過株價變動率)에 미치는 영향이 그다지 심각한 정도는 아니었으며 오히려 우리나라의 주식시장은 미국시장에 비해 주가가 비교적 안정적인 수준을 유지해 왔다고 볼 수 있다.36.4%)와 외식을 선호(29.1%)${\lrcorner}$ 하기 때문에 패스트푸드를 이용하게 된 것으로 응답 하였으며, 남 여 대학생간에는 유의한 차이(p<0.05)가 인정되었다. 응답자의 체형은 ${\ulcorner}$

• Journal of Science Education
• /
• v.38 no.1
• /
• pp.133-143
• /
• 2014

The purpose of this study is to analyze elementary school teachers' perception on application of STEAM education. For this study, a survey was administered to 80 primary teachers. The result showed as follows: First, even though, elementary school teachers have known about the meaning and aims of the STEAM education in detail, they often took a neutral attitude toward the actual teaching method. In addition, they take a negative attitude toward having the gathering. Second, only a few elementary school teachers prepared and used the teaching materials related to the STEAM education in class and teach students the concept based on the STEAM education. Only a few elementary school teachers said that they used the developed modules. However, the demand, developing the modules, was extremely high. This result means that the easy and available modules should be developed to establish the STEAM education. Third, only a few elementary school teachers applied the subject, activity, and estimation related to the STEAM education in actual class. Forth, even though, after applying, there much be the positive affects, most elementary school teachers could not recognize the positive affects. At the same time, elementary school teachers suggested the curriculum should be reorganized for students to connect between the results of the STEAM education and the contents of the textbook, and the easy and available program should be developed and spread, also. The attitude of elementary school teachers toward the application of the STEAM education was normally negative. Therefore, it is needed to include more STEAM related contents in the science textbooks and to develop various STEAM education materials and circulate them as well as to establish adequate teaching and assessment methods for STEAM education.

• Journal of Science Education
• /
• v.36 no.1
• /
• pp.153-165
• /
• 2012

This study investigated the frequent mistakes and the causes of the alternative conceptions in the animal classification by using the questionnaire and interview with the middle school students (N=300). As results, some students have difficulties classifying suggested animals into vertebrates or invertebrates : snakes (31.7%), shrimps (28.3%), turtles (25.6%), frogs (24.7%), and starfish (10.7%) in order of precedence. These errors seemed to be caused by intuitive thinking over characteristics of physical motions and appearance of suggested animals, wrong inference from comparing to features of familiar animals and the lack of observation experience of the vertebrate backbone. Furthermore, the results showed that relatively many students made a mistake classifying subgroup members of vertebrates such as classifying salamanders into the class Reptilia (45.3%) and turtles into Amphibia (40.3%). It is likely that those errors are affected by ambiguousness of classification terminology (e.g. the term of Amphibia) and weak ability in relating the physiological and ecological feature to standard of classification feature. In addition, sociocultural factors could influence animal classification as 'bat in birds', 'whale in fish, and 'penguin in mammals'. The present study implied that teaching and learning animal classification may require an appropriate guide focused on activities to explore major characteristics used for the animal classification standard through providing more chances of animal observation rather than the cramming method of learning induced by technical memorizing.