• Journal of Engineering Education Research
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• v.11 no.4
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• pp.19-33
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• 2008

The purpose of this study is to find out the effects of the use of Chatting Method(with AI Chatting robot: Chatterbot) and Computer Interest Levels on Teaching & Learning. The major findings of the study are as follows. Firstly, the chatting activities using the chatterbot method and computer Interest Levels were not effective in the academic achievement. Secondly, the chatting activities using the chatterbot method and computer Interest Levels were effective in improving the learning motivation. Thirdly, According to the result of post-feedback analysis, the benefits of chatterbot method was 'the new', 'transcends time and space', 'drill and practice learning' and was some of the drawbacks 'response fixed', lack of emotional transactions. and the proposal 'PBL' was reached(1. strength: new experience, 2. weakness: be tired, 3. proposal: PBL approach). Fourthly, the relationship between the academic achievement, learning motivation, post-feedback was no correlation. Based on these results, the study suggests that the chatterbot method was need for multiple instructional design strategy.

• Annual Conference of KIPS
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• 2006.05a
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• pp.693-696
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• 2006

One of the most significant characteristics of JPEG 2000, the emerging still image standards, is the Region of Interest(ROI) coding. Until now, there have been many proposed ROI methods. However, all of these methods can not be applied completely in applications. In this paper, the ROI coding mechanisms in JPEG2000 is first outlined and the diversity of ROI coding methods is discussed in detail. Then a comparative selection about using a proper ROI method according to ROI applications' requirements is proposed. Finally the experimental results show that there are also several parameters that control the effectiveness of ROI coding, such as the codeblock size, ROI size, wavelet filter type, the number of wavelet decomposition levels, and ROI importance score.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.246-256
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• 2022

Recently, parents and teachers consider physical education as a minor subject for students in elementary and secondary schools. Physical education performance has become increasingly significant as parents and schools pay more attention to physical schooling. The sports mining with distribution analysis model considers different factors, including the games, comments, conversations, and connection made on numerous sports interests. Using different machine learning/deep learning approach, children's athletic and academic interests can be tracked over the course of their academic lives. There have been a number of studies that have focused on predicting the success of students in higher education. Sports interest prediction research at the secondary level is uncommon, but the secondary level is often used as a benchmark to describe students' educational development at higher levels. An Automated Student Interest Prediction on Sports Mining using DL Based Bi-directional Long Short-Term Memory model (BiLSTM) is presented in this article. Pre-processing of data, interest classification, and parameter tweaking are all the essential operations of the proposed model. Initially, data augmentation is used to expand the dataset's size. Secondly, a BiLSTM model is used to predict and classify user interests. Adagrad optimizer is employed for hyperparameter optimization. In order to test the model's performance, a dataset is used and the results are analysed using precision, recall, accuracy and F-measure. The proposed model achieved 95% accuracy on 400^th instances, where the existing techniques achieved 93.20% accuracy for the same. The proposed model achieved 95% of accuracy and precision for 60%-40% data, where the existing models achieved 93% for accuracy and precision.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.531-536
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• 2016

This study highlights the effectiveness of analyzing the feelings children have when interacting with robots in a dramatic play setting using augmented reality in Human Robot Interaction (HRI). Existing dramatic play activities using robots by QR-markers were edited, and their weaknesses have been corrected so that children could interact more effectively with robots. Additionally, children's levels of interest and engagement in dramatic play activities, the accuracy of robotic props, and the smartness of robots were analyzed throughout children's interactions during such activities using augmented reality. Younger participants were more likely to find robots interesting and intelligent, and participants with no previous experience with robots had relatively higher levels of interest in robots and tended to notice changes in robots' costumes.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.665-678
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• 2003

In this paper we suggest the new calibration estimator, which is called to the recalibration estimator, and its variance estimator using two-phase sampling technique according to the auxiliary information having strong correlation with the variable of interest under the unit nonresponse. In this unit nonresponse situation, an available information may exists at the level of whole population or the first-phase sample. The proposed recalibration estimator derives from the first and second phase weights respectively.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.169-180
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• 2016

In this paper, we propose a CT-SPI Model based on a physical computing for improving Computational Thinking(CT) for elementary students. This study analyzes the results obtained from applying the CT-SPI model to fourth-grade class. The model is designed to embrace the learning activities and CT elements for three different stages: System thinking, Prototyping and Interaction. For providing curriculum with CT-SPI model, physical SW educational module is developed, so that learners could focus on internalizing CT. The study results indicate that a learning satisfaction and a degree of learner interest improve significantly. Comprehensive CT capability assessment results in three levels show that the capability in lowest level (score is below 4 out of 10) has decreased by 46.6% but capability in highest level (over 7 out of 10) has increased by 20%.

• Journal of Engineering Education Research
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• v.26 no.1
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• pp.12-19
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• 2023

With the introduction of the accreditation of engineering programs in Korea, universities affiliated with the programs have opened introductory engineering design courses for first- or second-year students. Since these courses mainly aim at cultivating problem-solving skills through team projects, this type of classes has opened as face-to-face classes. However, from the beginning of 2020, online teaching was recommended or forced on universities due to the COVID-19 pandemic. Thus, effective design of online courses on introductory engineering design was inevitable during the period. In this paper, we introduce a case study of the course in the Department of Computer Science at S University in Fall 2021. Through concrete suggestions on project areas, selection of team members considering grade levels and interest, several systems for prevention of free riding, and carefully designed open-book exams, the course resulted in both high achievements and high satisfaction.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.159-166
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• 2023

Due to the aging workforce in the construction industry in South Korea, the accident rate has been increasing. The cognitive abilities of older workers are closely related to both safety incidents and labor productivity. Therefore, there is a need to improve cognitive abilities through personalized training based on cognitive assessment results, using cognitive training content, in order to enable safe performance in labor-intensive environments. The provided cognitive training content includes concentration, memory, oreintation, attention, and executive functions. Difficulty levels were applied to each content to enhance user engagement and interest. To stimulate interest and encourage active participation of the participants, the difficulty level was automatically adjusted based on feedback from the MMSE-DS results and content measurement data. Based on the accumulated data, individual training scenarios have been set differently to intensively improve insufficient cognitive skills, and cognitive training programs will be developed to reduce safety accidents at construction sites through measured data and research. Through such simple cognitive training, it is expected that the reduction of accidents in the aging construction workforce can lead to a decrease in the social costs associated with prolonged construction periods caused by accidents.

• Journal of the military operations research society of Korea
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• v.7 no.1
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• pp.118-138
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• 1981

In many response surface optimization problems for industrial processes, there are more than two responses of interest, and we want to find the optimal levels of the factors that influence the responses. This paper is to propose how to set up the desirability functions to find the optimum for a given set of data, and to propose how to analyse the data and the desirability functions to determine an optimal operating condition for the factors. To implement the proposed method in practice, a FORTRAN computer program was written and explained. Finally, an industrial example is illustrated to explain the proposed technique and the source list of the computer program is attached for the users.

• Journal of Fisheries and Marine Sciences Education
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• v.23 no.1
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• pp.92-104
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• 2011

Korea is a high level of ICT infrastructure Construction in the OECD's PISA 2006. However, the purpose using of ICT was analyzed for the sake of the interest. They have been emphasized a algorithm-based computer education in conference that it was attended by government, industry and university officials. We designed an algorithm curriculum by analyze a case in international ICT training courses and research. And we were proposed various methods, such as web-based contents, play-based programs, outdoor activities and educational programming language learning for algorithm learning at levels of elementary and middle school students.