• 한국과학교육학회지
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• 제27권6호
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• pp.497-509
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• 2007

Among many remedial approaches against the increasing unfavorableness toward school science, one of the prevalent findings studied by affective experts is that students' achievement in science and their attitude toward it has a relatively weak relationship. In contrast, cognitive experts assert that the conceptual change involves more than cognitive aspects, and may be influenced by affective factors such as beliefs, motivation, learning attitudes, and sociocultural contexts. The latter regards continuous conceptual change as leading to better student understanding of science with variables of students' attitude toward science. As an initial step toward illuminating the affective-cognitive learning aspects of science, the purpose of this study is to develop an instrument for analyzing the relationship between students' conceptual understanding and affective factors. Cognitive questionnaires from the database of distribution in students' misconceptions of physics (DMP project), and affective questionnaires from the Relevance of Science Education (ROSE project) are integrated into our instrument. The respondents are high school students in Okayama prefecture, Japan. Through the pilot test, the authors integrated attitude toward science (AS) and interest inventory (II) from ROSE into cognitive understanding (CD) from DMP. Statistical methodologies such as factor analysis and item total correlation theoretically discerned the effective sixty-three items from the two original item pools. Having discussed two validity issues, the authors suggest ongoing research associated with our affective-cognitive research perspective.

• Fisheries and Aquatic Sciences
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• 제25권3호
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• pp.151-157
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• 2022

Various approaches have been applied to transform aquaculture from a manual, labour-intensive industry to one dependent on automation technologies in the era of the fourth industrial revolution. Technologies associated with the monitoring of physical condition have successfully been applied in most aquafarm facilities; however, real-time biological monitoring systems that can observe fish condition and behaviour are still required. In this study, we used a video recorder placed on top of a fish tank to observe the swimming patterns of rock bream (Oplegnathus fasciatus), first one fish alone and then a group of five fish. Rock bream in the video samples were successfully identified using the you-only-look-once v3 algorithm, which is based on the Darknet-53 convolutional neural network. In addition to recordings of swimming behaviour under normal conditions, the swimming patterns of fish under abnormal conditions were recorded on adding an anaesthetic or lowering the salinity. The abnormal conditions led to changes in the velocity of movement (3.8 ± 0.6 cm/s) involving an initial rapid increase in speed (up to 16.5 ± 3.0 cm/s, upon 2-phenoxyethanol treatment) before the fish stopped moving, as well as changing from swimming upright to dying lying on their sides. Machine learning was applied to datasets consisting of normal or abnormal behaviour patterns, to evaluate the fish behaviour. The proposed algorithm showed a high accuracy (98.1%) in discriminating normal and abnormal rock bream behaviour. We conclude that artificial intelligence-based detection of abnormal behaviour can be applied to develop an automatic bio-management system for use in the aquaculture industry.

• 한국과학교육학회지
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• 제32권8호
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• pp.1295-1317
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• 2012

There has been disagreement on the importance of definitions in science education. Yager (1983) believes that one crisis in science education was due to the considerable emphasis upon the learning of definitions. Hobson (2004) disagrees with physics textbooks that do not provide general definition on energy. Some textbooks explain that "there is no completely satisfactory definition of energy" or they can only "struggle to define it." In general, imprecise definitions in textbooks (Bauman, 1992) and inaccuracies in definition provided by teachers (Galili & Lehavi, 2006) may cause alternative conceptions. Besides, there are at least four challenges in defining physical concepts: precision, circularity, context and completeness in knowledge. These definitional problems that have been discussed in The Feynman Lectures, may impede the learning of physical concepts. A meta-study approach is employed to examine about five hundreds journal papers that may discuss definitions in physics, problems in defining physical concepts and how they may result in alternative conceptions. These journal papers are mainly selected from journals such as American Journal of Physics, International Journal of Science Education, Journal of Research in Science Teaching, Physics Education, The Physics Teachers, and so on. There are also comparisons of definitions with definitions from textbooks, Dictionaries of Physics, and English Dictionaries. To understand the nature of alternative conception, Lee et al. (2010) have suggested a theoretical framework to describe the learning issues by synthesizing cognitive psychology and science education approaches. Taking it a step further, this study incorporates the challenges in semantics and epistemology, proposes that there are at least four variants of alternative conceptions. We may coin the term, 'alternative definitions', to refer to the commonly available definitions, which have these four problems in defining physics concepts. Based on this study, alternative definitions may result in at least four variants of alternative conceptions. Note that these four definitional problems or challenges in definitions cannot be easily resolved. Educators should be cognizant of the four variants of alternative conceptions which can arise from alternative definitions. The concepts of alternative definitions can be useful and possibly generalized to science education and beyond.

• 교육시설 논문지
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• 제24권6호
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• pp.11-18
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• 2017

Education facilities have much affect to make a good condition for the learning environment. Therefore, various approaches have been conducted to improve the physical, social and educational achievement. Especially, the physical aspect is very important to get rid of the building defect and improve the student their learning environment. For these, it needs to explain the performance and function of components and materials, which is linked with the deterioration degree. The deterioration degree is a imperative factor to make a decision whether the component would be repaired or not and to provide the repair scope of its component. In this paper, it aimed at making the deterioration degree model of roof proof under the hypothesis of which deterioration degree would be equal the repair cost at this time. Results of the study are shown that first, the $3^{rd}$ function is most proper to explain the deterioration degree model among 11 functions in view of resulted statistics. Second, the inflection of deterioration is shown at 15yr of the elementary school and 13yr of the middle and high school. This study has a limit of disclassification of the component or materials and it is, therefore, favorable to include the classification of waterproof material and work. These results would make a change from the breakdown maintenance to preventive maintenance and give a decent the learning environment for student.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.105-112
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• 2022

The development and spread of IT-technologies has raised interest in teaching programming pupils. The article deals with problems related to programming and ways to overcome them. The importance of programming skills is emphasized, as this process promotes the formation of algorithmic thinking of pupils. The authors determined the level of pupils' interest to programing learning depending on the age. The analysis has showed that the natural interest of younger pupils in programming is decreasing over the years and in the most productive period of its study is minimized. It is revealed that senior school pupils are characterized by low level of interest in the study of programming; lack of motivation; the presence of psychological blocks on their own abilities in the context of programming; law level of computer science understanding. To overcome these problems, we conducted the second stage of the experiment, which was based on a change in the approach to programing learning, which involved pupils of non-specialized classes of senior school (experimental group). During the study of programming, special attention was paid to the motivational and psychological component, as well as the use of game technologies and teamwork of pupils. The results of the pedagogical experiment on studying the effectiveness of teaching programming for pupils of nonspecialized classes are presented. Improvement of the results provided the use of social and cognitive motives; application of verbal and non-verbal, external and internal means; communicative attacks; stimulation and psychological setting; game techniques, independent work and reflection, teamwork. The positive effect of the implemented methods is shown by the results verified by the methods of mathematical statistics in the experimental and control groups of pupils.

• 정보처리학회논문지D
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• 제18D권5호
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• pp.329-338
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• 2011

문헌에서의 전문용어 인식 연구는 정보검색, 정보추출, 시맨틱 웹, 질의응답 분야 등의 연구를 위한 선행 연구로서, 지금까지 대부분 특정 분야, 특히 생의학 분야에서 집중되어 연구되어 왔다. 그러나 기존 연구들이 특정 도메인 또는 문헌 내부 통계 정보를 활용함으로써 범용적인 전문용어 인식에 한계점을 보여 왔기 때문에, 본 연구에서는 웹 검색 결과와 사전, 후보용어의 문형 특징 등을 활용하는 기계 학습 기반 범용 전문용어 인식 방법을 제안하였다. 제안한 방법을 문헌의 지역 통계 정보를 사용하는 방법(C-value)과 비교 실험하여 80.8%의 F-값으로 6.5%의 성능향상을 보였다. 다양한 응집도 자질들을 접목한 두 번째 실험에서는 Normalized Google Distance 방법과 접목한 방식이 F-값 81.8%의 성능으로 최고의 성능을 나타냈다. 기계 학습 방법으로는 로지스틱 회귀분석, C4.5, SVMs 등을 적용하였는데, 일반적으로 이진 분류에 좋은 성능을 보이는 SVMs과 로지스틱 회귀분석 방법보다 결정 트리 방식의 C4.5가 전반적으로 좋은 성능을 보였다.

• 한국비블리아학회지
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• 제29권3호
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• pp.209-228
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• 2018

본 연구는 고등학교 "국어" 교과서의 한 학기 한 권 읽기 학습활동을 분석하여 학교도서관과 협력 방안을 모색하는 것이다. 그동안 독서 활동은 교과 지식과 이원화되어 정규 교과 수업 시간 밖에서 이뤄지는 경우가 많았다. 한 학기 한 권 읽기는 "국어" 정규 수업 시간 내 이뤄지는 독서 활동으로, <읽기-생각나누기-표현하기>를 기본 모형으로 개발되었다. 하지만 실재 11종 "국어" 교과서 22개 유형의 한 권 읽기 학습활동을 분석한 결과, 한 권 읽기는 <도서 정하기-읽기-표현하기>로 실현되었다. 단계별 학교도서관과 협력방안으로, 도서 정하기 단계는 학교도서관을 대상 도서 검색 공간으로 활용하고, 읽기 단계는 독서전략을 추가, 보완해 독서일지를 재구성하며, 표현하기 단계는 기존 독후 프로그램을 함께 운영할 수 있다. 이와 같이 한 권 읽기의 단계별로 협력함으로써 학교도서관의 교육적 역할은 더욱 견고해질 수 있으리라 기대된다.

• 한국융합학회논문지
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• 제9권11호
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• pp.23-28
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• 2018

최근 존재하는 대부분의 관계 추출 모델은 언급 수준의 관계 추출 모델이다. 이들은 성능은 높지만, 장문의 텍스트에 존재하는 다수의 문장을 처리할 때, 문서 내에 주요 개체 및 여러 문장에 걸쳐서 표현되는 전역적 개체 관계를 파악하지 못한다. 그리고 이러한 높은 수준의 관계를 정의하지 못하는 것은 데이터의 올바른 정형화를 막는 중대한 문제이다. 이 논문에서는 이러한 문제를 해결하고 전역적 관계를 추출하기 위하여 외부 메모리 신경망 모델을 이용하는 새로운 방식의 전역관계 추출 모델을 제안한다. 제안하는 모델은 1차적으로는 단편적인 관계 추출을 실행한 뒤, 외부메모리 신경망을 이용하여 단편적인 관계들을 분석 및 종합하여 텍스트 전체로부터 전역적 관계들을 추출한다. 또한 제안된 모델은 외부 메모리를 통하여 전역적 관계 추출 외에도 주어와 목적어 생략이 잦은 한국어 관계 추출에도 뛰어난 성능을 보인다.

• Structural Engineering and Mechanics
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• 제83권3호
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.

• 한국멀티미디어학회논문지
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• 제23권12호
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• pp.1464-1475
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• 2020

Due to the spread of COVID-19, the online lecture has become more prevalent. However, it was found that a lot of students and professors are experiencing lack of communication. This study is therefore designed to improve interactive communication between professors and students in real-time online lectures. To do so, we explore deep learning approaches for automatic recognition of students' facial expressions and classification of their understanding into 3 classes (Understand / Neutral / Not Understand). We use 'BlazeFace' model for face detection and 'ResNet-GRU' model for facial expression recognition (FER). We name this entire process 'Degree of Understanding (DoU)' algorithm. DoU algorithm can analyze a multitude of students collectively and present the result in visualized statistics. To our knowledge, this study has great significance in that this is the first study offers the statistics of understanding in lectures using FER. As a result, the algorithm achieved rapid speed of 0.098sec/frame with high accuracy of 94.3% in CPU environment, demonstrating the potential to be applied to real-time online lectures. DoU Algorithm can be extended to various fields where facial expressions play important roles in communications such as interactions with hearing impaired people.