• The Journal of the Korea Contents Association
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• v.13 no.10
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• pp.584-593
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• 2013

The purpose of this research is to analyze students' perception of smart learning focusing on its definitions, roles and values in distance higher education. In the online survey, 1,950 students of 'A' open university were participated. The results show that the students viewed the smart learning to be more 'absorbing', 'interactive' and 'collaborative' than the existing e-learning, as it compiles their experiences into learning. However, the respondents' perceptions of smart learning varied among different age groups: more students in their 40s and 50s responded that smart learning was 'customized', 'humanlike', 'interactive', 'comfortable', 'stable', 'familiar', 'unstressful', and 'practical' than students in their 20s and 30s, and they tend to view the main feature of smart learning to be the compilation of learner experiences.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.10
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• pp.397-402
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• 2019

Accurately predicting cancer prognosis to provide appropriate treatment strategies for patients is one of the critical challenges in bioinformatics. Many researches have suggested machine learning models to predict patients' outcomes based on their gene expression data. Gene expression data is high-dimensional numerical data containing about 17,000 genes, so traditional researches used feature selection or dimensionality reduction approaches to elevate the performance of prognostic prediction models. These approaches, however, have an issue of making it difficult for the predictive models to grasp any biological interaction between the selected genes because feature selection and model training stages are performed independently. In this paper, we propose a novel two-dimensional image formatting approach for gene expression data to achieve feature selection and prognostic prediction effectively. Node2Vec is exploited to integrate biological interaction network and gene expression data and a convolutional neural network learns the integrated two-dimensional gene expression image data and predicts cancer prognosis. We evaluated our proposed model through double cross-validation and confirmed superior prognostic prediction accuracy to traditional machine learning models based on raw gene expression data. As our proposed approach is able to improve prediction models without loss of information caused by feature selection steps, we expect this will contribute to development of personalized medicine.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.43-50
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• 2020

The purpose of this study is to examine the case of constructing information and communication facilities in daycare centers and to propose an educational environment that can foster young talents who can lead the era of the fourth industrial revolution. In particular, after COVID19, a method was proposed to create an information and communication environment suitable for children to receive personalized education, and to create an environment for experiential education if possible, and at the same time to enable averaging of customized learning. Since there has been no research on information and communication facilities in daycare centers, we intend to place significance on starting, and in the future, to foster creative and contextual children, we will reduce the movement of teachers through smart speakers and mobile devices, and tailor the educational environment through AI data. I think that the design of the daycare center should be changed in the direction of making the product. To this end, the CM role of information and communication supervision is needed, and it is hoped that it will become a design standard for daycare centers after COVID19 by developing research on daycare centers.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.33-39
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• 2019

Edutech, which combines education and information technology, is in the spotlight. Core technologies of the 4th Industrial Revolution have been actively used in education. Students use an AI-based learning platform to self-diagnose their needs. And get personalized training online with a cloud learning platform. Recently, a new educational medium called smart speaker that combines artificial intelligence technology and voice recognition technology has emerged and provides various educational services. The purpose of this study is to suggest a way to use smart speaker educationally to overcome the limitation of existing education. To this end, the concept and characteristics of smart speakers were analyzed, and the implications were derived by analyzing the contents provided by smart speakers. Also, the problem of using smart speaker was considered.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.171-176
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• 2022

With the recent development of deep learning technology, the areas of recommendation systems have also diversified. This paper studied algorithms to improve the learning rate and studied the significance results according to words through comparison with the performance characteristics of the Word2Vec model. The problem recommendation algorithm was implemented with the values expressed through the reflection of meaning and similarity test between texts, which are characteristics of the Word2Vec model. Through Word2Vec's learning results, problem recommendations were conducted using text similarity values, and problems with high similarity can be recommended. In the experimental process, it was seen that the accuracy decreased with the quantitative amount of data, and it was confirmed that the larger the amount of data in the data set, the higher the accuracy.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.59-66
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• 2022

This research conducted a study classifying gender of speakers by analyzing feature vectors extracted from the voice data. The study provides convenience in automatically recognizing gender of customers without manual classification process when they request any service via voice such as phone call. Furthermore, it is significant that this study can analyze frequently requested services for each gender after gender classification using a learning model and offer customized recommendation services according to the analysis. Based on the voice data of males and females excluding blank spaces, the study extracts feature vectors from each data using MFCC(Mel Frequency Cepstral Coefficient) and utilizes SVM(Support Vector Machine) models to conduct machine learning. As a result of gender classification of voice data using a learning model, the gender recognition rate was 94%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.1042-1048
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• 2017

Recently rapid changes in the industrial environment require new talents in companies. Flipped learning is drawing attention as an effective teaching-learning method. The existing traditional lecture teaching-learning method have various problems that the dropout rates of the student is high and the creative problem solving ability is hindered. In the case of the IT engineering college, most of the major theoretical courses require prior learning of the prerequisite coursework subjects. Therefore, effective teaching-learning methods must be developed to improve student participation and academic achievement. This paper proposes the flipped learning model consisting of five sets that combine the flipped learning and practice to improve student motivation and self - directed learning. Also, this paper analyzes the learning effect by applying it to the algorithm lecture of computer engineering and presents problem and utilization plan according to the result.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.400-409
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• 2021

Training, unlike education in holistic perspective, not only affects individual's potential of work competencies such as knowledge and technology, but also affects the job performance in organizational perspective. The effectiveness of training for civil servants who participated in mock jury trial learning of Suwon-si was verified using CIPP model. Participants valued the significance of the process of training rather than the conclusion that draws a certain solution, and based on the comparison and analysis of pre·post evaluations, the educational effect of mock trial training and its utilization at work in the future was higher than before the training, proving its effectiveness. In terms of the implications of training programs in addition to the program planner's evaluation, participant constitution in consideration of sex or employment period is needed for learning interaction among various learners, and information acquisition training on various local issues and conflict situations, as well as the combination of deliberation learning, are needed. in addition, it may be supplemented through customized conflict management raining related to pending projects for the effectiveness of training.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.111-119
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• 2022

This study examined the relationship of self-directed learning ability, teaching presence, learning flow and academic achievement of nursing students in non-face-to-face class. Data were collected through self reported structured questionnaire in 146 nursing students from June 19 to 20, 2021. Data were analyzed using SPSS/WIN 23.0. As a result this study, academic achievement was positively correlated with self-directed learning ability, teaching presence and learning flow. As result regression analysis, learning flow, self-directed learning ability and teaching presence explained 67% of the academic achievement in nursing students. Therefore, based on this study it will be more effective to improve academic achievement of instructional design and customized instructional methods that can improve self-directed learning ability, teaching reality and learning commitment are applied together in non-face-to-face classes.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.379-392
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• 2021

In recent years, vocational training has shifted away from lectures and practice-oriented methods in light of rising demand for project-based classes in which trainees can produce results while simultaneously receiving feedbacks from field experts from the industry. Therefore, this study aims to suggest a salient role of the project-based classes of enterprise-customized training programs, which private vocational training institutions regard as vital, by identifying demands from trainees or the actual beneficiaries of these programs. To this end, a written survey of the trainees' perception of the enterprise-customized training programs was conducted along with a qualitative analysis of open-ended questions. Specifically, we analyzed the overall satisfaction level of these classes, their contribution to employment, degree of meeting the expectations, and areas for improvements to ultimately derive significant implications.