• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.229-240
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• 2005

This study described the application of constructivism and information technology for teaching simple random sampling. We considered more student's participation, more interaction, and more flow in their introductory statistics class. In addition, we presented a web-based teaching and learning system for simple random sampling to demonstrate.

• Knowledge Management Research
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• v.25 no.1
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• pp.155-172
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• 2024

This study investigates the effectiveness of foreign language learning through diverse treatments in virtual settings, particularly by differentiating virtual environments with three textual enhancement techniques. A 2 × 3 mixed-factorial design was used, treating virtual environments as within-subject factors and textual enhancement techniques as between-subject factors. Participants experienced two videos, each in different virtual learning environments with one of the random textual enhancement techniques. The results showed that the interaction between different virtual environments and textual enhancement techniques had a statistically significant impact on presence among groups. In examining main effects of virtual environments, significant differences were observed in flow and attitude toward pre-post learning. Also, main effects of textual enhancements notably influenced flow, intention to use, learning satisfaction, and learning confidence. This study highlights the potential of Metaverse in foreign language learning, suggesting that learner experiences and effects vary with different virtual environments.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.39-39
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• 2020

Low-flow 하천에서의 최저수위를 나타내는 지표이다. 일반적으로 유황곡선의 갈수량(Q355)를 대표적으로 사용한다. Low-flow는 물 공급 관리 및 계획, 관개용수, 생태계등 다양한 분야에 영향을 미친다. 이러한 Low-flow를 산정하기 위해서는 충분한 기간의 유량자료가 필요하다. 하지만 국토의 70%가 산지지형으로 구성되어 있는 우리나라의 경우 국가하천과 1급하천을 제외한 산지유역은 수위관측소가 부재하거나 결측으로 인해 자료가 충분하지 않아 Low-flow분석에 한계가 있다. 이에 과거에는 미계측지역의 갈수량을 예측하기 위해서 다중회귀분석, ARIMA 모형 등 다양한 기법을 사용하였지만, 최근들어 머신러닝 모형의 수요가 증가하고 있다. 이에 본 연구에서는 새로운 패러다임에 맞는 머신러닝 기법인 DNN기법을 사용하고자 한다. DNN기법은 ANN기법의 단점인 학습과정에서 최적 매개변수값을 찾기 어렵고, 학습시간이 느린 단점을 보완한 방법이다. 따라서 본연구에서는 머신러닝 기법인 DNN기법을 통해 미계측지역에 적용 가능한 지역화 Low-flow indices를 산정하고자 한다. 먼저, Low-flow에 영향을 미치는 인자들을 수집하고 인자들간의 상관분석, 다중공선성 분석을 통해 통계적으로 유의한 변수를 선정하여, 머신러닝 모형에 입력자료를 구축하였다. 또한 기존의 갈수량 예측기법인 다중회귀분석 결과와 비교하여 머신러닝 기법의 효용성을 검토하였다.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.167-177
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• 2019

The enhancement of national competitiveness in future society is the discovery and training of excellent SW convergence gifted. In order to cultivate these SW convergence gifted, reinforcing competence of teachers in charge should be made first. Therefore, in this paper, artificial intelligence education contents, one of the core technologies of the 4th Industrial Revolution era, were developed to reinforcing competence of SW convergence gifted teachers. After setting the direction of artificial intelligence education content, we constructed educational content suitable for secondary SW convergence gifted education, and designed and developed it in detail. The composition of artificial intelligence education content consists of machine learning and tensor flow understanding, linear regression machine learning implementation for numerical prediction, and multiple linear regression-based price prediction machine learning implementations. The developed educational contents were verified by experts with qualitative aspects. In the future, we expect that the educational content of artificial intelligence proposed in this paper will be useful for strengthening the ability of SW convergence gifted teachers.

• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.57-64
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• 2021

In this paper, we propose a device that can control the primary control surface of an aircraft by recognizing speech commands. The speech command consists of 19 commands, and a learning model is constructed based on a total of 2,500 datasets. The training model is composed of a CNN model using the Sequential library of the TensorFlow-based Keras model, and the speech file used for training uses the MFCC algorithm to extract features. The learning model consists of two convolution layers for feature recognition and Fully Connected Layer for classification consists of two dense layers. The accuracy of the validation dataset was 98.4%, and the performance evaluation of the test dataset showed an accuracy of 97.6%. In addition, it was confirmed that the operation was performed normally by designing and implementing a Raspberry Pi-based control device. In the future, it can be used as a virtual training environment in the field of voice recognition automatic flight and aviation maintenance.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1099-1104
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• 2020

In order to provide various types of application services based on the Internet, it is ideal to guarantee the quality of service(QoS) for each flow. However, realizing these ideas is not an easy task.. It is effective to classify multiple flows having the same or similar service quality requirements into same group, and to provide service quality for each group. The queue management mechanism in the router plays a very important role in order to efficiently transmit data and to support differentiated quality of service for each service. In order to efficiently support various multimedia services, an intelligent and adaptive queue management mechanism is required. This paper proposes an intelligent queue management mechanism based on deep reinforcement learning that decides whether to deliver packets for each group based on the traffic information of each flow group flowing in for a certain period of time and the current network state information.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.119-128
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• 2023

This study was conducted to present an alternative instructional model through natural experience activities by developing a natural experience activity program that can learn and feel how to recognize and act on nature based on flow learning. In order to achieve the purpose of the study, a nature experience program, which consists of four stages of meeting nature, exploring nature, playing with nature and sharing emotions, was developed based on the main procedures of each stage of the ADDlE instructional design model. Through the research process, activities and precautions for each stage of the nature experience activity program were presented, and major educational implications were discussed based on the developed program. The nature experience program developed through the study can provide teachers with a basic direction for nature experience activities along with changing their perception of how to do nature experience activities, and infants are expected to become learners who freely feel, experience nature and make up their own knowledge through the nature experience program.

• Journal of The Korean Association of Information Education
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• v.24 no.6
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• pp.539-550
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• 2020

This study establishes the scientific basis for the use of digital learning materials through the education-neurological research method and derives implications for education based on education-neurological understandings. The main findings of the education-neurological analysis of digital learning materials are as follows: First, various sensory stimuli go through multiple sensory neurons and deep sections of the upper sphere and make possible the cooperative processing of information. Second, indirect experience from digital learning materials helps students understand the learning contents vividly through the mirror neuron system. Third, positive emotions originating from digital learning materials promote functions of dopamine, the reticular activating system, frontal-striatal circuit, cerebrum cortex. Based on the findings, the study suggests the following educational implications. First of all, when selecting digital learning materials, teachers should consider expression forms, learning contents, the flow of classes, and the adverse effects of digital learning materials. Next, it is effective to utilize digital learning materials in the lecture for provoking curiosity and enjoyment, maintaining interest and effort, and reviewing what students learned.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.327-340
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• 2022

This study applied effective playful learning to increase the learning motivation of non-CS major students to help them achieve learning and to successfully operate online SW liberal arts classes for 560 students. As a result of analyzing the students' reflection journals, most of the students accepted the 'white radish' of dialect names as fun playful learning in the process of learning local variables and global variables. And they were surprised and amazed at discovering unexpected contents in our SW class. It was found that they experienced delight in learning, learning-flow, confidence, and intrinsic motivation. In the final term exam at the end of the semester, it was confirmed that the correct rate of 92% for questions related to local and global variables was higher than the average rate of other questions' correctness of 67.1%.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.3
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• pp.255-272
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• 2023

This study sought implications for further revitalizing student-centered classes by measuring and analyzing the effects of the operation of major courses applying blended learning for library and information sicence (LIS) students on learning immersion, result achievement, and learning satisfaction. The results are as follows: First, as a result of comparative analysis between the pre and post scores of learning immersion, result achievement, and academic satisfaction after operating the blended learning class, the average score of the post-survey was high. Second, among the factors of learning immersion, significant results were found in academic reasons, academic concentration, interest, and control. In particular, the effect of academic concentration and control was high. Third, among the factors of outcome achievement, significant results were found in achievement motivation, satisfaction, relationship utilization ability, and class attitude. The effect of satisfaction and relationship utilization ability was particularly high. Fourth, both general satisfaction and learning-related satisfaction were very effective in academic satisfaction factors. In sum, it was found that the operation of major courses applying blended learning was effective for LIS students.