• Title/Summary/Keyword: 학습자료 부족

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Analysis of Pre-service Secondary Chemistry Teachers' Uses of Teacher's Guide in Planning Lessons (중등 예비화학교사의 수업 계획에서 교사용 지도서의 활용 방식 분석)

  • Yang, Chanho;Song, Nayoon;Kim, Minhwan;Noh, Taehee
    • Journal of The Korean Association For Science Education
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    • v.36 no.4
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    • pp.681-691
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    • 2016
  • In this study, we investigated pre-service secondary chemistry teachers' use of teacher's guide in planning lessons. Eleven pre-service teachers at a college of education in Seoul participated in this study. Textbooks and teacher's guide books including various teaching materials were provided. Pre-service teachers used teacher's guide while they planned two lessons, which were a lecture and an instruction using science teaching model. A semi-structured interview was conducted. All of the teaching-learning materials and interviews were analyzed. The analyses of the results revealed that most pre-service teachers followed each lesson presented in teacher's guide, but they did not consider the structure of the whole unit and science curriculum. There were some cases that the exemplary lesson planning in teacher's guide helped them to select science teaching model. They modified the questions of textbook activity in planning their lecture. On the other hand, they modified the activity to fit each stage of the model in planning their instruction using science teaching models. Most pre-service teachers constructed their own worksheets by applying the materials of the teacher's guide. They recognized the components of assessment by considering exemplary lesson planning from the teacher's guide, and created questions by modifying the content of textbooks and teacher's guide books including various teaching materials. However, the questions which they made were limited in context of knowledge. They evaluated that introductory questions were not of interest to students, and modified or added new materials. Educational implications of these findings are discussed.

Construction of a Bark Dataset for Automatic Tree Identification and Developing a Convolutional Neural Network-based Tree Species Identification Model (수목 동정을 위한 수피 분류 데이터셋 구축과 합성곱 신경망 기반 53개 수종의 동정 모델 개발)

  • Kim, Tae Kyung;Baek, Gyu Heon;Kim, Hyun Seok
    • Journal of Korean Society of Forest Science
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    • v.110 no.2
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    • pp.155-164
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    • 2021
  • Many studies have been conducted on developing automatic plant identification algorithms using machine learning to various plant features, such as leaves and flowers. Unlike other plant characteristics, barks show only little change regardless of the season and are maintained for a long period. Nevertheless, barks show a complex shape with a large variation depending on the environment, and there are insufficient materials that can be utilized to train algorithms. Here, in addition to the previously published bark image dataset, BarkNet v.1.0, images of barks were collected, and a dataset consisting of 53 tree species that can be easily observed in Korea was presented. A convolutional neural network (CNN) was trained and tested on the dataset, and the factors that interfere with the model's performance were identified. For CNN architecture, VGG-16 and 19 were utilized. As a result, VGG-16 achieved 90.41% and VGG-19 achieved 92.62% accuracy. When tested on new tree images that do not exist in the original dataset but belong to the same genus or family, it was confirmed that more than 80% of cases were successfully identified as the same genus or family. Meanwhile, it was found that the model tended to misclassify when there were distracting features in the image, including leaves, mosses, and knots. In these cases, we propose that random cropping and classification by majority votes are valid for improving possible errors in training and inferences.

Academic Warning Students' Learning Behavior Type Exploration (학사경고 대학생의 학습행동 유형 탐색)

  • Hyun, Yong-Chan;Hong, Seung-Hee;Park, Jung-Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.12
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    • pp.819-825
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    • 2020
  • This study explored the possibility of psychological testing as a way to proactively support underachieving students. Among the four-year college students that participated in our study, 43 students who participated in the academic warning support program for the second semester of 2019 and 30 students who had no academic warning experience used the data from the study personality type test. For data analysis, technical statistics, t-test, and correlation analysis were performed using jambi 1.1.9.0 to obtain the Pearson correlation. Studies have shown that the two classes of students differ in their learning behavior patterns. A student with a bachelor's degree warning scored high in the rest of the class, except for rebelliousness, perfection, mixed thoughts, hard work, satisfaction, single-mindedness and type satisfaction. This can be seen as a factor in the psychological conflict, such as the discrepancy between what one likes and what one studies, and lack of available support. It has been confirmed that psychology, emotional parts and economic support are needed as well as learning skills. In addition, this study is expected to provide basic data for proper preemptive support in schools, such as the prevention of dropouts and counseling programs.

A Study on the interracially Married Female Immigrant's Adaptation of Multi-cultural Families : Qualitative Methods (여성결혼이민자가 경험하는 다문화가족 적응에 관한 연구 -T시를 중심으로-)

  • Han, Sang-Young
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.11
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    • pp.5066-5075
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    • 2012
  • The purpose of this study was to offer a foundation of developing the more qualitative and individual nursing-intervention strategy for allowing married female immigrants and their children of multi-cultural families to possibly grow and develop as a Korean without discrimination and prejudice in Korean society. Period of data collection in this study was from April 2010 to May 2011. Subjects of this study are totally 13 married female immigrants of multi-cultural families who have preschool children of dwelling in T city. Data analysis is qualitative research that applied Spradley(1990)'s culture-descriptive method. The results were as follows : The common elements, which are shown in married female immigrants, children, and family members of multi-cultural families, were indicated to "social prejudice", "exclusive family atmosphere", "economic difficulty", "coexistent different culture".

A Recognition Analysis of Elementary Teachers for Software Education of 2015 Revised Korea Curriculum (2015 개정 교육과정의 소프트웨어 교육에 대한 초등 교사들의 인식 분석)

  • Kim, Kapsu
    • Journal of The Korean Association of Information Education
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    • v.20 no.1
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    • pp.47-56
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    • 2016
  • In order to nurture creative talent in the 21st century knowledge-based society in elementary education software is carried from the year 2018. The educational content and achievement standards to conduct a software education had been made in the 2015. In this study, the recognition of educational software for elementary school teachers 199 people is investigated. Findings are as follows. Elementary education is the first software required, and is lacking in 17 hours. Second, the idea of a common training software education, teaching and learning methods, evaluation methods, how to develop information materials. Third, lower cognitive development and educational materials for the teaching methods appropriate for understanding, achievement standards for achievement standards. Therefore, should allow teacher training teaching materials development, assessment methods, teaching methods suitable for the achievement standards available to all teachers throughout the school know.

A Study on the Major Perception of Nursing Freshmen (간호학과 신입생의 전공 인식에 관한 연구)

  • Jung Hyo Ju
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.145-151
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    • 2023
  • This study was attempted to provide basic data for the development of the nursing major curriculum and the admission strategy for attracting new students by identifying the perception of the nursing major among freshmen in the nursing department. Participants in this study were 40 freshmen who agreed to participate in the study among freshmen in the department of nursing who completed self-exploration, a required liberal arts course for freshmen opened in the first semester of 2021. Data collection was a study diary written by participants after 15 weeks of class, and the traditional content analysis method suggested by Heieh and Shannon was applied to data analysis. As a result of the study, three themes were derived: 'motivation for entering the nursing major', 'value of the nursing major', and 'obstacles to the nursing major'. Therefore, colleges and departments need to strengthen their entrance examination strategies to develop and conduct field trip programs for experiential departments linked to middle and high schools and It is necessary to solve the difficulties in taking major courses by providing subject and extracurricular programs targeting students who lack basic learning ability.

Development of River Water Level Prediction Model Based on Artificial Intelligence for Independent Flood Alert (독립적 하천홍수경보를 위한 인공지능기반 하천수위예측모형 개발)

  • Kim, Sooyoung;Kim, Hyung-Jun;Kim, Boram;Yoon, Kwang Seok
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.328-328
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    • 2021
  • 최근 전 지구적인 기후변화의 영향은 강우량의 집중을 야기하며 홍수피해의 규모를 증가시키는 영향을 끼친다. 특히, 아세안 국가들은 해수면 상승, 태풍 및 집중호우에 의한 침수피해 빈발로 최소 2,000만명이 영향을 받고 있다. 국내의 홍수예보모형을 수출하여 아세안 국가에 구축하고 있으나 통신 시설이 불안정하여 중앙제어 방식의 기존의 홍수예보시스템만으로는 긴급상황에 대한 대처가 부족할 수 있다. 따라서 본 연구에서는 하나의 관측소에서 수위, 강우의 관측과 홍수예측, 경보까지 한번에 가능한 관측소를 개발하기 위해 관측된 수위와 강우자료를 활용하여 인공지능기반의 하천수위예측 모형을 개발하였다. 목표 리드타임은 30분에서 6시간으로 설정하였으며 모형은 Tensorflow로 구축하였다. 시계열 자료의 예측에 적합한 LSTM 기법을 적용하였다. 연구의 대상지역은 건설연의 계측시험유역인 설마천유역으로 하였으며 학습에는 2009년부터 2020년까지의 10분 단위 수위 및 강우량자료를 활용하였다. 연구결과 설마천 유역은 규모가 작고 도달시간이 짧아 1시간 후 예측까지는 높은 정확도를 나타냈으나 3시간 이상의 예측결과는 다소 낮게 평가되었다. 다만, 비상상황에서 통신이 두절된 상황에서 위급하게 대피를 위해 홍수경보를 발령하는데는 활용이 가능 할 것으로 판단된다.

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A Study on Atmospheric Data Anomaly Detection Algorithm based on Unsupervised Learning Using Adversarial Generative Neural Network (적대적 생성 신경망을 활용한 비지도 학습 기반의 대기 자료 이상 탐지 알고리즘 연구)

  • Yang, Ho-Jun;Lee, Seon-Woo;Lee, Mun-Hyung;Kim, Jong-Gu;Choi, Jung-Mu;Shin, Yu-mi;Lee, Seok-Chae;Kwon, Jang-Woo;Park, Ji-Hoon;Jung, Dong-Hee;Shin, Hye-Jung
    • Journal of Convergence for Information Technology
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    • v.12 no.4
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    • pp.260-269
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    • 2022
  • In this paper, We propose an anomaly detection model using deep neural network to automate the identification of outliers of the national air pollution measurement network data that is previously performed by experts. We generated training data by analyzing missing values and outliers of weather data provided by the Institute of Environmental Research and based on the BeatGAN model of the unsupervised learning method, we propose a new model by changing the kernel structure, adding the convolutional filter layer and the transposed convolutional filter layer to improve anomaly detection performance. In addition, by utilizing the generative features of the proposed model to implement and apply a retraining algorithm that generates new data and uses it for training, it was confirmed that the proposed model had the highest performance compared to the original BeatGAN models and other unsupervised learning model like Iforest and One Class SVM. Through this study, it was possible to suggest a method to improve the anomaly detection performance of proposed model while avoiding overfitting without additional cost in situations where training data are insufficient due to various factors such as sensor abnormalities and inspections in actual industrial sites.

An Exploration of Science Teachers' NOS-PCK: Focus on Science Inquiry Experiment (과학교사의 과학의 본성 수업에 대한 교과교육학 지식(NOS-PCK) 탐색 -과학탐구실험을 중심으로-)

  • Kim, Minhwan;Shin, Haemin;Noh, Taehee
    • Journal of The Korean Association For Science Education
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    • v.40 no.4
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    • pp.399-413
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    • 2020
  • In this study, we analyzed science teachers' NOS-PCK in Science Inquiry Experiment lessons. Four science teachers in charge of Science Inquiry Experiment in high schools located in the Seoul metropolitan area participated in the study. NOS Lessons were observed, all of the teaching-learning materials were collected, and semi-structured interviews were conducted. All the collected data were analyzed according to five factors of NOS-PCK. As a result of the study, their understanding and consideration of the curriculum related to NOS were insufficient in some cases. They thought that given inquiry activities or textbook composition was not effective for NOS teaching so that they actively reconstructed the curriculum. In terms of teaching strategies, their lessons were close to explicit approaches. However reflective approaches were generally lacking. They were neglected in evaluating NOS for reasons that views of NOS are individually subjective or that NOS is not an area of cognitive learning. They guessed the state of students by relying on their own experiences rather than based on evaluation results. They recognized a specific aspect of values of NOS learning. And intention to teach NOS played an important role throughout their classes. Based on the above results, we discuss some ways to improve the professionalism of science teachers for NOS teaching.

A study on program development to improve learning competencies of major courses for Chinese students in Korea (중국인 유학생의 전공학습역량 향상을 위한 교육 프로그램 개발 연구)

  • Im, Che-Ri;NING, LI XU;Park, Yoon-Hee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.6
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    • pp.389-402
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    • 2020
  • This study aimed to develop an educational program for improving the learning competencies of major courses for Chinese graduate students who account for more than 70% of international students in Korea. In this study, the program was developed using Caffarella and Daffron's interactive model. Due to the internationalization of education, the number of foreigners who study in Korea for degree courses has already exceeded 100,000, but the dropout rate has increased due to the maladjustment to university life. More specifically, they face difficulties in academic achievement because of a lack of understanding lecture contents, conducting research, and presenting in class. Therefore, this study surveyed the Chinese students in the graduate course to identify the difficulties and needs in their study of major courses and to reflect those needs (major knowledge, communication, assignment writing, and presentation) in program development. This study focused on developing an educational program for improving their learning competencies of major courses rather than simply improving Korean language skills or adapting to university life. The results of the study are expected to help Chinese Graduate students perform well in their major course studies and make their study abroad successful.