• Journal of radiological science and technology
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• v.44 no.2
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• pp.123-131
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• 2021

In this study, safety education contents for medical radiation workers were produced based on Mixed Reality(MR). Currently, safety training for radiation workers is based on theory. This is insufficient in terms of worker satisfaction and efficiency. To address this, we created ICT(Information and Communication Technologies)-based MR radiation worker safety education content. The expected effect of Mixed Reality worker safety education content is that education is possible without space and time constraints, realistic education is possible without on-site training, and interaction between images is possible through reality-based 3D images, enabling self-directed learning Is that. In addition, learning in a virtual space expressed through HMD(Head Mounted Display) is expected to make education more enjoyable and increase concentration, thereby increasing the efficiency of education. A quantitative evaluation was conducted by an accredited institution and a qualitative evaluation was performed on users, which received excellent evaluation. The MR safety education conducted in this study is expected to be of great help to the education of medical radiation workers, and is expected to develop into a new educational paradigm as online education in accordance with Corona 19 progresses.

• Korean Journal of Childcare and Education
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• v.16 no.6
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• pp.253-272
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• 2020

Objective: This study aimed to analyze the counseling contents of daycare center teachers by using text mining and semantic network analysis methods to find the necessary support directions for daycare teachers and to improve the quality of child-care. Methods: Five hundred thirteen cases of counseling recorded on the open bulletin board of online counseling (Naver Bands for Nursery Teacher Counseling) were collected, and frequency analysis, centrality solidarity analysis, and machine learning-based topic analysis were conducted using the NetMiner4.3 program. Results: First, 'teacher-to-child ratio' was highest in the frequency. Second, 'colleagues' were all high in all centrality analysis. Third, machine learning-based topical analysis shows that the topics were categorized as subjects about 'childcare and education', 'working environment that supports professional development' and 'working condition', and among them, 'first-time teacher concerns' accounted for 44% of the total counseling content. Conclusion/Implications: This study implied that it is necessary to provide high-quality child-care and education to infants by lowering the 'teacher-to-child ratio', and a systematic program is needed to help improve effective communication skills in interpersonal relationships such as between parents, fellow teachers, and principals. In addition, self-development and efforts to improve teachers expertise should be prioritized in order to improve infant care quality and quality of teachers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1534-1538
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• 2020

Smart farming education service focuses on the dissemination of farming information that is the farming knowledge, farming skill, and farmer's experiences and knowhow, etc. This farming information is supposed from current activities, farming product and from the experience of farmer on the field. If the information is not available, or if available and not in a form that is amenable to being brought to the end producer then the process stalls at this point. The core component of the automation process for smart farming education service is the creation of a data store which will be a repository for the information of the smart farming education. The farming sector will benefit immensely from the implementation of farming data in farming contents repository which will serve as the knowledge base for the smart farming education service.

• The Journal of Economics, Marketing and Management
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• v.7 no.1
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• pp.26-38
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• 2019

Purpose - This paper is to review recent literature, by conducting a thorough investigation of the limitations and implications for future research on work-life balance with the focus and linkages between work-life balance practices, machine learning and emotional intelligence, work-life conflict, the correlations between work-life enrichment and work-life balance practices, the relationships between employee job satisfaction and work-life balance, the links between work-life balance and the managerial support. Research design, data, and methodology - The paper will further detail linkages between work-life balance and organizational performance outcomes productivity and innovation. Previous literatures have paid attentions to the link of HR practices and organizational outcomes such as productivity, flexibility, and financial performance, but the understanding needs to be extended to involve innovation performance. Dealing with employees' emotions using different machine learning techniques is one of the phenomenal researches in today's world. Here, we examine how far the employees are conscious of their own self and found the ideas and views of an individual about themselves and others. Without proper knowledge about their personality it will be very difficult for an individual to manage their own emotions. This study also aims at finding out the individual abilities to manage their emotions in order to perform well. Conclusions - A theoretical conceptual framework has been built by integrating the existing literature to explain a number of factors which are closely associated with work-life balance. The conceptual model illustrates how the work-life balance interplays with performance and interrelates with the aforementioned factors.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.220-224
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• 2022

The teacher is considered the cornerstone of the educational process; the quality of education is linked mainly to teachers who perform such a necessary process. The shift in pedagogical thinking has led to progress in looking at the teacher's roles; he is no longer transferring knowledge to learners, but instead, he has become a mentor, a mediator, a planner, an intellect, and a leader. If we analyze these missions from the perspective of mental habits, we will see that they require the teacher to develop the skills of perseverance, listening comprehension, thinking flexibly, controlling emotions, self-confidence, communication skills, and other essential skills. The current research verifies the effectiveness of an instructional program based on web quests in developing habits of the mind of English language students. The study employed a quasi-experimental design. The sample consisted of 46 male students representing two classes. They were assigned randomly into an experimental group (n=24) and a control group (n=22). They were undergraduate students majoring in the English language. The findings showed a statistically significant difference in the mean scores of the experimental and control groups favoring the experimental group. The study concludes with some recommendations to differentiate teaching techniques in EFL classrooms.

• Journal of Engineering Education Research
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• v.25 no.5
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• pp.68-74
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• 2022

The purpose of this study was to develop an infographic-based STEAM program for high school students and test its effectiveness. In this study, we converged high school 'art' education with 'Korean language' and 'mathematics.' The program was divided into four phases. The effectiveness of the program was analyzed by conducting matched pair t-test for 377 students at a girl's high school in Seoul before and after the program. The study found that the students' self-concept on mathematics and their attitude towards choosing science and engineering career showed significant increases after the program. By connecting high school courses through data visualization based on cognitive information design, findings from this study suggest that our infographic-based STEAM program should be implemented more frequently at high schools.

• Korean Medical Education Review
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• v.25 no.2
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• pp.114-118
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• 2023

Multiple cohorts (e.g., current students and graduates) were formed to collect information on the entire educational process from admission to graduation regarding students' educational performances at Kosin University College of Medicine. Data that had already been collected and analyzed by different committees for different purposes were grouped into a more systematic and comprehensive system called the cohort system, enabling the necessary data to be collected promptly and analyzed in accordance with the purpose of providing meaningful information in each area of the educational process. Therefore, comprehensive cohort data that can be used for mission statement revision, curriculum development and improvement, student counseling, and student selection were established and utilized. The cohort data were collected from performance evaluation indicators including self-evaluation surveys, evaluation tools for learning outcomes, academic achievement, results of the Korean Medical Licensing Examination, and career placement. Based on the results obtained by analyzing cohort data, a comprehensive cohort report has been published. The data analyzed through the cohort were reported to each committee and used in various ways. Currently, however, only some data have been analyzed and used. In the future, after complete data collection, the cohort data can be used as meaningful basic data for achieving the institution's mission and educational goals, developing and improving the curriculum, counseling students, and selecting students through the analysis of learning performance data from student admission to graduation and after graduation.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.4
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• pp.427-439
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• 2023

Purpose: This study aimed to evaluate the effects of a nursing education program for hyperglycemia patient care using standardized patients. Methods: This study used a nonequivalent control group pre-test and post-test non-synchronized design. A total of 50 senior university nursing students who had completed an adult nursing course participated in this study (experimental group, n=24; control group, n=26). This nursing education program was developed according to the stages of analysis, design, development, implementation, and evaluation. The collected data were analyzed using χ² -test, Fisher's exact test, independent t-test, paired t-test, and repeated measure ANOVA. Results: Significant differences were shown between the experimental and control groups in clinical performance ability (F=277.41, p<.001), communication skills (F=47.18, p<.001), self-efficacy (F=3.81, p=.031), and learning satisfaction (t=2.25, p=.033). Problem-solving ability was not statistically significant between the groups. Conclusion: The nursing education program for hyperglycemia patient care using standardized patients was effective in improving nursing students' clinical performance ability, communication skills, and learning satisfaction. Therefore, it is proposed that the education program developed in this study be used as part of an education program to enhance nursing students' abilities in caring for hyperglycemia patients.

• Smart Structures and Systems
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• v.32 no.6
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• pp.359-369
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• 2023

Servo-motor driven uniaxial shake tables have been widely used for education and research purposes in earthquake engineering. These shake tables are mostly displacement-controlled by a digital proportional-integral-derivative (PID) controller; however, accurate reproduction of acceleration time histories is not guaranteed. In this study, a control strategy is proposed and verified for uniaxial shake tables driven by a servo-motor. This strategy incorporates a deep-learning algorithm named Long Short-Term Memory (LSTM) network into a displacement PID feedback controller. The LSTM controller is trained by using a large number of experimental data of a self-made servo-motor driven uniaxial shake table. After the training is completed, the LSTM controller is implemented for directly generating the command voltage for the servo motor to drive the shake table. Meanwhile, a displacement PID controller is tuned and implemented close to the LSTM controller to prevent the shake table from permanent drift. The control strategy is named the LSTM-PID control scheme. Experimental results demonstrate that the proposed LSTM-PID improves the acceleration tracking performance of the uniaxial shake table for both bare condition and loaded condition with a slender specimen.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.142-148
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• 2023

In Modern days, Self-driving for modern people is an absolute necessity for transportation and many other reasons. Additionally, after the outbreak of COVID-19, driving by oneself is preferred over other means of transportation for the prevention of infection. However, due to the constant exposure to stressful situations and chronic fatigue one experiences from the work or the traffic to and from it, modern drivers often drive under drowsiness which can lead to serious accidents and fatality. To address this problem, we propose a drowsy driving prevention learning model which detects a driver's state of drowsiness. Furthermore, a method to sound a warning message after drowsiness detection is also presented. This is to use MoveNet to quickly and accurately extract the keypoints of the body of the driver and Dense Neural Network(DNN) to train on real-time driving behaviors, which then immediately warns if an abnormal drowsy posture is detected. With this method, we expect reduction in traffic accident and enhancement in overall traffic safety.