• Journal of the Korean Society for Library and Information Science
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• v.50 no.2
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• pp.25-45
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• 2016

This study investigates how high school students with low academic achievement seek and use information. Participants were seven US students in an American Literature and Composition course of the $11^{th}$ grade Remedial Education Program who completed a class project that required comprehensive information seeking and use. Data were collected through comprehensive observation and individual interviews with each student, the teacher, and two library media specialists. Additionally, we gathered and analyzed the instructions the teacher and the two library media specialists provided and all documents each student produced to complete the class project. The process of data analysis was supported by QSR NVivo. The findings of the study implied that students experienced cognitive and affective challenges for their information seeking and use required for the tasks and suggested that technological and individual conferencing would motivate the students to continue their information seeking and use. We then conclude the study with some important implications that can be used as a basis for designing information literacy instructions for students with low academic achievement.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.66-71
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• 2006

Lately teaching-learning system on the web site offers broad educational environment without any restriction of time and place to the teachers and learners. Using a web site in music education turned out to be effective. It provokes learner's interest and guides self-directed learning. Therefore, on this research, the web site for self-directed learning in music subject was designed and embodied as an assistant material of learning which is suitable for learner's level and demand As a result of using the web site in music class, there are some responses of students. First, there were 27 students positive responses$(79.4\%)$ of 34 students in the learning effect of the web site, and 25 students$(73.5\%)$ of 34 showed their will to use the web site continually if it is modified and supplemented. Second, some students answered that using this program in Diagnosis Evaluation and Formative Test could have an instant result, which was used for the material of feedback. Third, there was a positive evaluation of helping self-directed learning.

• Journal of Practical Engineering Education
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• v.11 no.1
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• pp.75-86
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• 2019

Globally, the change in higher education is gradually moving toward a trend that seeks a change in innovative higher education through the revitalization of digital-based education. Accordingly, this study designed a customized education model based on e-learning that can be used in undergraduate education and development of lifelong vocational skills. The use of online learning platforms and the expansion of education are major factors that change the overall higher education system as the form and content of curriculum changes around the world. In order to establish a customized education model using online learning platform, this study analyzed major overseas advanced education cases and selected the basic direction of customized learning as personalized learning, competency based learning, and training for talents leading the 4th Industrial Revolution. Then, FGI was conducted for undergraduate and lifelong vocational ability development experts. As a result, a customized education model using an online learning platform was derived from a degree-type model available in undergraduate education and a non-degree-type model available in the field of lifelong vocational ability development, and each operation strategy was suggested.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.111-128
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• 2016

The purpose of this study was to analyze domestic research trends of social learning in higher education, and find out educational implications with regard to the effectiveness of social learning. The 63 articles on social learning were finally analyzed, which were published in KCI journals. The results are as follows: Firstly, in respect of research contents, the research area of utilization and the survey methods were most frequently used in those studies. Secondly, as to the use of SNS, the analyzed studies were centralized on Facebook and Formal Structured Learning. Thirdly, as for the effectiveness of SNS, the experimental studies showed that social learning has an effective impact on the learning outcomes, learning processes, and learners' characteristics. In addition, survey studies most frequently set the independent variables as learners' characteristics and the dependent variables as participation, satisfaction, and academic achievement. This research has a significance in terms of verifying the educational implications of social learning, and providing the preliminary data to facilitate the performance for the effective social learning.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.115-126
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• 2021

The purpose of this study is to closely analyze the case of blended-learning in order to provide a diverse and flexible learning environment while maintaining the nature of face-to-face classes, and to identify the learning environment that supports blended-learning in each class step and the educational experience of students. The experience and satisfaction of blended learning were investigated in various ways: course evaluation, LMS activity evaluation, and questionnaire before and after the class. As a result, the blended-learning is better than the traditional face-to-face classes, in providing real-time feedback, opportunities for various interactions, and textual conversations, anytime and anywhere. In addition, as a result of the preliminary survey, as a measure to solve the opinion that concentration was reduced due to problems such as networks and felt uncomfortable in the communication part, the theory and lectures of the design practice class were conducted non-face-to-face. The individual Q&A and feedback were conducted face-to-face and non-face-to-face. As a result of the follow-up survey, it was found that concentration and efficiency could be improved. This opens up possibilities for active use of the online environment in design practice classes.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.105-126
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• 2023

The domestic used car market continues to grow along with the used car online platform service. The used car online platform service discloses vehicle specifications, accident history, inspection history, and detailed options to service consumers. Most of the preceding studies were predictions of used car prices using vehicle specifications and some options for vehicles. As a result of the study, it was confirmed that there was a nonlinear relationship between used car prices and some specification variables. Accordingly, the researchers tried to solve the nonlinear problem by executing a Machine Learning model. In common, the Regression based Machine Learning model had the advantage of knowing the actual influence and direction of variables, but there was a disadvantage of low Cost Function figures compared to the Decision Tree based Machine Learning model. This study attempted to predict used car prices of six domestic brands by utilizing both vehicle specifications and vehicle options. Through this, we tried to collect the advantages of the two types of Machine Learning models. To this end, we sequentially conducted a regression based Machine Learning model and a decision tree based Machine Learning model. As a result of the analysis, the practical influence and direction of each brand variable, and the best tree based Machine Learning model were selected. The implications of this study are as follows. It will help buyers and sellers who use used car online platform services to predict approximate used car prices. And it is hoped that it will help solve the problem caused by information inequality among users of the used car online platform service.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.871-884
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• 2021

The purpose of this study was to determine ways to increase efficiency in constructing and verifying artificial intelligence learning data on land cover using aerial and satellite images, and in applying the data to AI learning algorithms. To this end, multi-resolution datasets of 0.51 m and 10 m each for 8 categories of land cover were constructed using high-resolution aerial images and satellite images obtained from Sentinel-2 satellites. Furthermore, fine data (a total of 17,000 pieces) and coarse data (a total of 33,000 pieces) were simultaneously constructed to achieve the following two goals: precise detection of land cover changes and the establishment of large-scale learning datasets. To secure the accuracy of the learning data, the verification was performed in three steps, which included data refining, annotation, and sampling. The learning data that wasfinally verified was applied to the semantic segmentation algorithms U-Net and DeeplabV3+, and the results were analyzed. Based on the analysis, the average accuracy for land cover based on aerial imagery was 77.8% for U-Net and 76.3% for Deeplab V3+, while for land cover based on satellite imagery it was 91.4% for U-Net and 85.8% for Deeplab V3+. The artificial intelligence learning datasets on land cover constructed using high-resolution aerial and satellite images in this study can be used as reference data to help classify land cover and identify relevant changes. Therefore, it is expected that this study's findings can be used in the future in various fields of artificial intelligence studying land cover in constructing an artificial intelligence learning dataset on land cover of the whole of Korea.

• East Asian mathematical journal
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• v.32 no.4
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• pp.425-441
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• 2016

In this study, we focused on the graphing calculator to support the activity-oriented mathematics instruction with considering the accessibility of technology. The purpose of this study was to investigate the direction of the education of mathematics teachers. For this, we gave the teacher training for mathematics using graphing calculators for secondary mathematics teachers, and then examined the recognition for that of teachers. Teacher training of the graphing calculator was carried out three times in two years, we conducted a survey immediately at the time that has passed and after the 8 months or more after the training. As a result, we have obtained the suggestions of the advantages of using a graphing calculator in the learning mathematics, the difficulties of use of the graphing calculator in the classroom and the form of teacher training they want.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.52-63
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• 1995

A neuro-fuzzy algorithm is presented for nuclear reactor power control in a pressurized water reactor. Automatic reacotr power control is complicated by the use of control rods because of highly nonlinear dynamics in the axial power shape. Thus, manual shaped controls are usually employed even for the limited capability during the power maneuvers. In an attempt to achieve automatic shape control, a neuro-fuzzy approach is considered because fuzzy algorithms are good at various aspects of operator's knowledge representation while neural networks are efficinet structures capable of learning from experience and adaptation to a changing nuclear core state. In the proposed neuro-fuzzy control scheme, the rule base is formulated based ona multi-input multi-output system and the dynamic back-propagation is used for learning. The neuro-fuzzy powere control algorithm has been tested using simulation fesponses of a Korean standard pressurized water reactor. The results illustrate that the proposed control algorithm would be a parctical strategy for automatic nuclear reactor power control.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.257-267
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• 2009

This paper presents a training method for neural networks and the employment of MSE (mean scare error) values as the basis of a decision regarding the identity claim of a speaker in a recurrent neural networks based speaker verification system. Recurrent neural networks (RNNs) are employed to capture temporally dynamic characteristics of speech signal. In the process of supervised learning for RNNs, target outputs are automatically generated and the generated target outputs are made to represent the temporal variation of input speech sounds. To increase the capability of discriminating between the true speaker and an impostor, a discriminative training method for RNNs is presented. This paper shows the use and the effectiveness of the MSE value, which is obtained from the Euclidean distance between the target outputs and the outputs of networks for test speech sounds of a speaker, as the basis of speaker verification. In terms of equal error rates, results of experiments, which have been performed using the Korean speech database, show that the proposed speaker verification system exhibits better performance than a conventional hidden Markov model based speaker verification system.