• Hwankyungkyoyuk
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• v.7 no.1
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• pp.1-17
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• 1994

This study was performed to determine appropriate teaching-learning and evaluation methods for Environmental Studies. To promote the relevance of our study to the needs of the schools and concerned educational communities of environmental education, we reviewed related literature, conducted questionnaire surveys, interviewed related teachers and administrator, held meetings with experts, and field-tested our findings. For selecting and developing teaching-learning methods of Environmental Studies, findings of educational research in general are considered. moreover, principles of environmental education, general aim of environmental education, orientations of environmental education, and developmental stages of middle school students in educational psychology were attended. In addition, relevance to the purpose of the Environmental Studies curriculum, appropriateness for value inquiry as well as knowledge inquiry, small group centered class organization, social interaction centered teaching-learning process, regional environmental situation, significance of personal environment, evaluation methods of Environmental Studies, multi- and inter-disciplinary contents of the Environmental Studies textbook, suitability to the evaluation methods of Environmental Studies, and emphasis on the social interaction in teaching-learning process were regarded. It was learned the Environmental Studies can be taught most effectively in via of holding discussion sessions, conducting actual investigation, doing experiment-practice, doing games and plate, role-playing and carrying out simulation activities, and doing inquiry. These teaching-learning methods were field-tested and proved appropriate methods for the subject. For selecting and developing evaluation method of Environmental Studies, such principles and characteristics of Environmental Studies as objective domains stated in the Environmental Studies curriculum, diversity of teaching-learning organization, were appreciated. We categorized nine evaluation methods: the teacher may conduct questionnaire surveys, testings, interviews, non-participatory observations; they may evaluate student's experiment-practice performances, reports preparation ability, ability to establish a research project, the teacher may ask the students to conduct a self-evaluation, or reciprocal evaluation. To maximize the effect of these methods, we further developed an application system. It considered three variables, that is, evaluates, evaluation objectives domains, and evaluation agent, and showed how to choose the most appropriate methods and, when necessary, how to combine uses of different methods depending on these variables. A sample evaluation instrument made on the basis of this application system was developed and tested in the classes. The system proved effective. Pilot applications of the teaching-learning methods and evaluation method were made simultaneously; and the results and their implications are as follows. Discussion program was applied in a lesson dealing with the problems of waste disposal, in which students showed active participation and creative thinking. The evaluation method used in this lesson was a multiple-choice written test for knowledge and skills. It was shown that this evaluation method and device are effective in helping students' revision of the lesson and in stimulating their creative interpretations and responces. Pupils showed great interests in the actual investigation program, and this programme was proved to be effective in enhancing students' participation. However, it was also turned out that there must be pre-arranged plans for the objects, contents and procedures of survey if this program is to effective. In this lesson, non-participatory observation methods were used with a focus on the attitudes of students. A scaled reported in general description rather than in grade. Experiment-practice programme was adopted in a lesson for purifying contaminated water and in this lesson, instruction objectives were properly established, the teaching-learning process was clearly specified and students were highly motivated. On the other hand, however, it was difficult to control the class when some groups of students require more times to complete their experiment, and sometimes different results. As regards to evaluation, performance observation test were used for assessing skills and attitudes. If teachers use well-prepared Likert scale, evaluation of all groups within a reasonablely short period of time will be possible. The most effective and successful programme in therms of students' participation and enjoyment, was the 'ah-nah-bah-dah-market' program, which is kind of game of the flea market. For better organized program of this kind, however, are essential, In this program, students appraise their own attitudes and behavior by responding to a written questionnaire. In addition, students were asked to record any anecdotes relating to self-appraisal of changes on one's own attitudes and behaviours. Even after the lesson, students keep recording those changes on letters to herself. Role-playing and simulation game programme was applied to a case of 'NIMBY', in which students should decide where to located a refuse dumping ground. For this kind of programme to e successful, concepts and words used in the script should be appropriate for students' intellectual levels, and students should by adequately introduced into the objective and the procedures of the lessons. Written questionnaire was used to assess individual students' attitudes after the lesson, but in order to acquire information on the changes of students' attitudes and skills, pre-test may have to be made. Doing inquiry programme, in which advantages in which students actually investigated the environmental influence of the areas where school os located, had advantages in developing students' ability to study the environmental problems and to present the results of their studies. For this programme to be more efficient, areas of investigation should be clearly divided and alloted to each group so that repetition or overlap in areas of study and presentation be avoided, and complementary wok between groups bee enhanced. In this programme, teacher assessed students' knowledge and attitudes on the basis of reports prepared by each group. However, there were found some difficults in assessing students' attitudes and behaviours solely on the grounds of written report. Perhaps, using a scaled checklist assessing students' attitudes while their presentation could help to relieve the difficulties.

• Journal of vocational education research
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• v.37 no.5
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• pp.25-53
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• 2018

The purpose of this study is to find out the improvement plan through the satisfaction survey of the trainees involved in vocational training fraud preventive education. In order to do this, we conducted a satisfaction survey(4,263 persons) of 5,939 people who participated in the prevention education conducted by group education or e-learning in 2017. Finally we collected 4,237 effective responses data. Descriptive statistics and the regression analysis were conducted. The finding of the study were as follows. First, the education service quality(4.42), satisfaction level(4.44), understanding level(4.44) and help level(4.45) were significantly higher than those of participants in the preventive education 4 and above. Second, e-learning participants' perceived level of education service quality, satisfaction, comprehension, and help was higher in all variables than collective education's. Third, all of the sub-factors of preventive education service quality influenced satisfaction, understanding, and help in collective education and e-learning, respectively. In the collective education, the contents of education had the greatest influence, and in e-learning, the data composition had the greatest influence. Fourth, desirable education contents were cases of fraud training(70.7%), disposition regulations(47.9%), NCS course operation instructions(32.8%) and training management best practices(32.4%). Additional requirements also included the establishment of an in-depth course, the provision of anti-fraud education content for trainees, and screen switching and system stability that can be focused on e-learning. Therefore, this study suggests that first, it is necessary to activate e-learning for prevention education more, reflecting satisfaction of e-learning is higher than that of collective education. Second, it is necessary to diversify the content of preventive education and to provide it more abundantly, because it has the biggest influence in common with the satisfaction, understanding and help level of the preventive education. Third, education content next, the factors that have a relatively big influence on satisfaction are shown as delivery method and education place in the collective education. Therefore, it is necessary to prepare education place considering the assignment of instructor and convenience. Fourth, constructing data next, the factor that have a relatively great influence on understanding and help are found to be operator support, and more active operator support activities are required in e-learning. Fifth, it is required to delivery prevention activity for trainees participating in vocational training. Sixth, it is necessary to analyze the educational need to construct the contents of preventive education more systematically.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1633-1638
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• 2013

The mobile phone has now evolved into an effective multimedia devices to watch video content with your PC in addition to the calling features. Thus, the effectiveness of the video content streaming services smartphone will be available. And content should be able to deliver effectively. Be provided with textbook images and video of the speaker means that the effective content delivery. In this paper, we propose a integrated video management system that can be real-time VOD services on the Internet as input Multi-Source of audio-video, video content encoding system to meet the requirements of the above two.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.29-34
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• 2021

The real-time video education is used as an effective method of operating classes that replaces face-to-face education of instructors and learners in remote areas. However, the existing video call and video conferences system is mainly used, and this is effective in linguistic education because it focuses on lecture through video, but it is not utilized in other education. In this paper, we propose a design model of real-time video system that can improve the effectiveness of science curriculum and mathematics education by providing the functions that can be utilized during class by improving limitations of image - oriented image education.

• Communications of Mathematical Education
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• v.23 no.3
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• pp.823-848
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• 2009

In this paper, we try to find improved solutions for problems with general mathematics education courses. We suggest effective management strategies and teaching-learning methods by level-based classes with utilizing students survey and scholastic level assessment, and management of Mathematics Cafe and its homepage, and also setting example classes for assignments on the Webwork system and evaluating the class.

• Journal of IKEEE
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• v.8 no.2 s.15
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• pp.216-223
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• 2004

The customer's bulletin board is the important channel to get opinions from customers directly. The effective management of the bulletin board for the customer improves the reliance by providing the best replies and by accepting opinions of the customer and furthermore, that can raise the customer's reliance of the whole shopping mall is the important eCRM method. But, the present mostly customer's bulletin board is been replied without any classifying about many kinds of question. Consequently, The shopping mall should do systematic management of the best professional reply about many kinds of question. In order to resolve this problem, we implement a classifier called Naive Bayesian classifier is classified automatically bulletin board for eCRM of shopping mall.

• Journal of Korean Association for Spatial Structures
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• v.20 no.2
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• pp.51-58
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• 2020

Recently, deep learning that is the most popular and effective class of machine learning algorithms is widely applied to various industrial areas. A number of research on various topics about structural engineering was performed by using artificial neural networks, such as structural design optimization, vibration control and system identification etc. When nonlinear semi-active structural control devices are applied to building structure, a lot of computational effort is required to predict dynamic structural responses of finite element method (FEM) model for development of control algorithm. To solve this problem, an artificial neural network model was developed in this study. Among various deep learning algorithms, a recurrent neural network (RNN) was used to make the time history response prediction model. An RNN can retain state from one iteration to the next by using its own output as input for the next step. An eleven-story building structure with semi-active tuned mass damper (TMD) was used as an example structure. The semi-active TMD was composed of magnetorheological damper. Five historical earthquakes and five artificial ground motions were used as ground excitations for training of an RNN model. Another artificial ground motion that was not used for training was used for verification of the developed RNN model. Parametric studies on various hyper-parameters including number of hidden layers, sequence length, number of LSTM cells, etc. After appropriate training iteration of the RNN model with proper hyper-parameters, the RNN model for prediction of seismic responses of the building structure with semi-active TMD was developed. The developed RNN model can effectively provide very accurate seismic responses compared to the FEM model.

• Smart Structures and Systems
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• v.29 no.1
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• pp.77-91
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• 2022

Various monitoring systems have been implemented in civil infrastructure to ensure structural safety and integrity. In long-term monitoring, these systems generate a large amount of data, where anomalies are not unusual and can pose unique challenges for structural health monitoring applications, such as system identification and damage detection. Therefore, developing efficient techniques is quite essential to recognize the anomalies in monitoring data. In this study, several machine learning techniques are explored and implemented to detect and classify various types of data anomalies. A field dataset, which consists of one month long acceleration data obtained from a long-span cable-stayed bridge in China, is employed to examine the machine learning techniques for automated data anomaly detection. These techniques include the statistic-based pattern recognition network, spectrogram-based convolutional neural network, image-based time history convolutional neural network, image-based time-frequency hybrid convolution neural network (GoogLeNet), and proposed ensemble neural network model. The ensemble model deliberately combines different machine learning models to enhance anomaly classification performance. The results show that all these techniques can successfully detect and classify six types of data anomalies (i.e., missing, minor, outlier, square, trend, drift). Moreover, both image-based time history convolutional neural network and GoogLeNet are further investigated for the capability of autonomous online anomaly classification and found to effectively classify anomalies with decent performance. As seen in comparison with accuracy, the proposed ensemble neural network model outperforms the other three machine learning techniques. This study also evaluates the proposed ensemble neural network model to a blind test dataset. As found in the results, this ensemble model is effective for data anomaly detection and applicable for the signal characteristics changing over time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.495-509
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• 2020

This study is a theoretical research to explore ways to effectively learn AI in the age of intelligent information driven by artificial intelligence (hereinafter referred to as AI). The emphasis is on presenting a teaching method to make AI education accessible not only to students majoring in mathematics, statistics, or computer science, but also to other majors such as humanities and social sciences and the general public. Given the need for 'Explainable AI(XAI: eXplainable AI)' and 'the importance of storytelling for a sensible and intelligent machine(AI)' by Patrick Winston at the MIT AI Institute [33], we can find the significance of research on AI storytelling learning model. To this end, we discuss the possibility through a pilot study targeting general students of an university in Daegu. First, we introduce the AI storytelling(AI+ST) learning method[30], and review the educational goals, the system of contents, the learning methodology and the use of new AI tools in the method. Then, the results of the learners are compared and analyzed, focusing on research questions: 1) Can the AI+ST learning method complement algorithm-driven or developer-centered learning methods? 2) Whether the AI+ST learning method is effective for students and thus help them to develop their AI comprehension, interest and application skills.