• International journal of advanced smart convergence
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• v.10 no.2
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• pp.201-208
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• 2021

Recently, artificial intelligence(AI) has been used throughout society, and social interest in it is increasing. Accordingly, the necessity of AI education is becoming a big topic in the education field. As a response to this trend, the Korean education authorities have also announced plans for AI education, and various studies have been performed in academic field to revitalize AI education in the future. However, the curriculum research on what differentiates AI education from existing SW education and what and how to train AI is still in its infancy. In this paper, Therefore, we focused on the experiences of elementary school students in solving problems in their own lives, and developed a teaching-learning model based on design-based research so that students can design a problem-solving process and experience the process of feedback. We applied the developed teaching-learning model to the problem-solving process and confirmed that it increased students' understanding and satisfaction with AI education.

• Educational Technology International
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• v.13 no.1
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• pp.175-205
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• 2012

The current study investigated whether SNS such as Twitter can be an assisting tool to compensate the limitations of online learning from social-affective and cognitive perspectives. Such limitations include low level of motivation to participate, feeling of isolation, rare exchanges of ideas and feedback from peers or instructors. This paper reports findings from a research study on the use of Twitter in online learning in Higher Education. Survey and subsequent interviews were conducted to examine students' perceptions about the cognitive and social-affective aspects of their participation in Twitter activities. Some of the challenges and potentials in integrating Twitter into online course are also addressed. It can be concluded that Twitter contributes not only to building close relationships among peers and instructors but also to opening a communication channel that can extend cognitive potentials.

• Research in Mathematical Education
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• v.27 no.1
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• pp.111-127
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• 2024

There is an increasing concern in the United States regarding the workforce's ability to maintain a competitive position in the global economy. This has led to an increased interest in effective science, technology, engineering, and mathematics (STEM) education. The purpose of this study was to investigate the effect of STEM project-based learning (PBL) on students' self-regulation and motivation to learn. Secondary students (n = 60) participated in a STEM summer camp in which STEM PBL was utilized. Results showed that students increased their self-regulation skills (t = 2.83, df = 59, p = .004) and motivation (t = 2.25, df = 59, p =.004), with Cohen's d effect sizes of 0.395 and 0.404, respectively. Student-centered learning and peer collaboration while solving real-world problems were likely the greatest contributing factors to the outcomes. Educators should utilize the results to provide opportunities for students to experience STEM PBL.

• Journal of Korean Library and Information Science Society
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• v.44 no.2
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• pp.27-50
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• 2013

In this study, a smart Learning instruction model for school library was developed in terms of library instruction. Based on ADDIE model and ASSURE model, this model is organized considering the characteristics of school library, including facilities, materials, human resources, information problem solving process, collaborative teaching and blended learning, and utilizing smart devices. The entire procedure of this model is as follows: "establishment of instructional objectives${\rightarrow}$learner analysis${\rightarrow}$analyzing the learning environment${\rightarrow}$analyzing the learning task${\rightarrow}$instructional process design${\rightarrow}$developing instructional tool${\rightarrow}$instruction${\rightarrow}$evaluation". In addition, an instructional practice is provided for actual experience of smart Learning in school libraries.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.95-100
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• 2021

This paper introduces model-based meta reinforcement learning as a control for the manipulator of an underwater construction robot. Model-based meta reinforcement learning updates the model fast using recent experience in a real application and transfers the model to model predictive control which computes control inputs of the manipulator to reach the target position. The simulation environment for model-based meta reinforcement learning is established using MuJoCo and Gazebo. The real environment of manipulator control for underwater construction robot is set to deal with model uncertainties.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.382-386
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• 2009

Online or sequential learning is one of the most basic and powerful method to train neuron network, and it has been widely used in disease detection, weather prediction and other realistic classification problem. At present, there are many algorithms in this area, such as MRAN, GAP-RBFN, OS-ELM, SVM and SMC-RBF. Among them, SMC-RBF has the best performance; it has less number of hidden neurons, and best efficiency. However, all the existing algorithms use signal normal distribution as kernel function, which means the output of the kernel function is same at the different direction. In this paper, we use multi-variable normal distribution as kernel function, and derive EKF learning formulas for multi-variable normal distribution kernel function. From the result of the experience, we can deduct that the proposed method has better efficiency performance, and not sensitive to the data sequence.

• Electronics and Telecommunications Trends
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• v.34 no.6
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• pp.71-86
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• 2019

The unprecedented demands of mobile communication networks by the rapid rising popularity of mobile applications and services require future networks to support the exploding mobile traffic volumes, the real time extraction of fine-rained analytics, and the agile management of network resources, so as to maximize user experience. To fulfill these needs, research on the use of emerging deep learning techniques in future mobile systems has recently emerged; as such, this study deals with deep learning based mobile communication research activities. A thorough survey of the literature, conference, and workshops on deep learning for mobile communication networks is conducted. Finally, concluding remarks describe the major future research directions in this field.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.334-349
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• 2022

The effectiveness of Wi-Fi networks is greatly influenced by the optimization of contention window (CW) parameters. Unfortunately, the conventional approach employed by IEEE 802.11 wireless networks is not scalable enough to sustain consistent performance for the increasing number of stations. Yet, it is still the default when accessing channels for single-users of 802.11 transmissions. Recently, there has been a spike in attempts to enhance network performance using a machine learning (ML) technique known as reinforcement learning (RL). Its advantage is interacting with the surrounding environment and making decisions based on its own experience. Deep RL (DRL) uses deep neural networks (DNN) to deal with more complex environments (such as continuous state spaces or actions spaces) and to get optimum rewards. As a result, we present a new approach of CW control mechanism, which is termed as contention window threshold (CW_Threshold). It uses the DRL principle to define the threshold value and learn optimal settings under various network scenarios. We demonstrate our proposed method, known as a smart exponential-threshold-linear backoff algorithm with a deep Q-learning network (SETL-DQN). The simulation results show that our proposed SETL-DQN algorithm can effectively improve the throughput and reduce the collision rates.

• Journal of Korean society of Dental Hygiene
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• v.21 no.4
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• pp.467-479
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• 2021

Objectives: The purpose of this study was to investigate the awareness of the performance and necessity of oral health promotion activities and seek ways to revitalize the professional role of dental hygienists in oral healthcare for the efficient oral care of the elderly. Methods: Eighty-five dental hygienists in charge of oral health promotion projects at public health centers and 38 dental hygienists in network dental clinical trials were investigated for their learning experience, performance experience, feasibility, and necessity of dental hygienists for general and oral health service items for the elderly. The collected data were analyzed using frequency analysis, chi-square test, and Mann-Whitney U test. Results: The degree of performance possibility according to the learning experience and performance experience of the dental hygienist for the whole body and oral health promotion activity items for the elderly showed that the degree of performance possibility was higher among those with experience compared to the non-experienced person, and it was statistically significantly higher (p<0.05). Conclusions: The dental hygienist's professional oral health service is a necessary system to improve practical knowledge and skills and to provide a wide range of professional oral health services for the elderly.

• The Journal of Korean Academic Society of Nursing Education
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• v.3
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• pp.34-45
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• 1997

Aspects of nursing student's clinical experiences are anxiety provoking. High anxiety may contribute to decreased learning. The purpose of this study was to identify the level of anxiety and potentially anxiety-producing clinical experience, the relation between the level of anxiety and their Trait-Anxiety and State-Anxiety. Finally, it is aimed at getting preparing data for guidance of students which can enhance learning effect of students for clinical experience. The samples of this study were 36 junior students(1 semester experience) and 44 senior students (3 semester experience) from Junior College of Nursing in Seoul on September 1996. The tools of this study were two kinds ; questionare of Spielberg' STAI measuring State and Trait-Anxiety, and author's for measuring the level of Anxiety producing situations and 10cm visual analogue scale was also used for measuring self stated level of anxiety on clinical setting. The collected data were analyzed by SPSS using percentage, t-test, ANOVA and Pearson correlation coefficient. The results of this study were as follows : 1. The self perception of anxiety level was 4.3/10cm and the level of anxiety in clinical setting situations was 3.5/5. 2. Among 20 questions for perception of anxiety-producing situations in the clinical setting. 'deficit of nursing knowledge' was the highest item(4.18), 'vagueness of role'(4.11), 'lack of nursing skill'(4.00), 'evaluation by faculty'(4.00) 'fear of making mistakes'(3.81) 'initial clinical experience on a unit'(3.76) 'initial application of nursing knowledge'(3.74) in turn. 3. The level of State-anxiety of senior students was higher than junior's (p=0.005)and the level of Trait-Anxiety of insufficient interpersonal relationship and unhealthy students were higher than others (p=0.015) There was no differences according to the student's grade in level of anxiety. 4. Both of self-stated anxiety and situationa anxiety of unhealthy students were high (p=0.007, p=0.000) and the level of self-stated anxiety of unsatisfied students for selection major and clinical experience were high (p=0.050, p=0.009). 5. Self-stated anxiety and situation anxiety (p=0.0000), self-stated- anxiety and Trait-anxiety(p=0.003), situation anxiety and Trait-anxiety(p=0.004), and Trait-anxiety and state-anxiety(p=0.000) of the students were interrelated. By the above conclusion, the nursing students still feel anxiety on clinical experience and on making a mistake due to the lack of their nursing knowledge and skill. And the students are afraid of the faculties' evaluation. In addition, the students who are not healthy and have not sufficiently interpersonal relationship feel more anxiety. But, since there was no difference significantly between each grade, we think it is needed that further study on the same topic in large samples. And, we have to equip the students with much nursing knowledge and philosophy apparently before the students have clinical experience. Finally, the faculty have to reduce the students' anxiety by making a climate of acceptance in clinical setting with good personality.