• Journal of Digital Convergence
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• v.19 no.4
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• pp.291-303
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• 2021

The study tried to examine the characteristics of transcription culture on YouTube through narrative analysis methods. The study found five meaningful features in YouTube's transcription culture. YouTube's transcription culture was first characterized by efficient writing and learning skills. Second, there was a characteristic of a transcription to read and understand text more deeply. Third, it had the characteristics of five strategies to advance my writing. Fourth, YouTubers had time to self-heal and comfort through transcription. Fifth, YouTube's transcription culture has expanded and developed into left-handed writing and digital writing. The characteristics of these YouTubers' transcription culture are expected to enrich the transcription culture that has been handed down for many years.

• Journal of People, Plants, and Environment
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• v.23 no.3
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• pp.321-332
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• 2020

Background and objective: The concept of 'money' in the numbers and operations domain is a fundamentally necessary domain of economic life. This study was conducted to examine the effects of a horticulture-mathematics integration program on mathematical attitude and money calculating ability of high school students with intellectual disabilities. Methods: We analyzed the changes in the mathematical attitude and money calculating ability of students with mild intellectual disabilities in S special school in the city of D, Republic of Korea, with 12 students in the control group and 12 students in the experimental group, from August 27 to October 29, 2019. Results: The results of the comparison showed no statistically significant changes in the three items of mathematical attitude for the control group, while the experimental group, which took part in the horticulture-mathematics integration program, showed statistically significant differences across all three items, such as self-concept about the subject (p = .003), attitude toward the subject (p = .004), and study habit related to the subject (p = .012). The horticulture-mathematics integration program, which was developed by integrating horticultural activities and the mathematics curriculum, used plants and horticultural activities to provide students with positive experiences in mathematics. These included the sense of closeness, curiosity, interest, attention, and enjoyment, leading to positive changes in mathematical attitude. In terms of money calculating ability, both the control group and experimental group showed statistical differences across the three items, but the experimental group showed greater degrees of increase, 15.0 or more, in the scores compared to the control group. Conclusion: These results suggest that utilizing horticultural materials as a part of purchase learning programs with elements of money calculation chapters in the mathematics curriculum could lead to the improvement of students' ability in money calculation. These positive changes are thought to be related to the high degrees of interest in horticulture among students, which led to active participation in the program and enabled the simple and repeated purchase activities in the program to generate positive changes in the money calculation ability of the students.

• Smart Structures and Systems
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• v.30 no.6
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• pp.601-612
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• 2022

The prediction of structural mechanical behaviors is vital important to early perceive the abnormal conditions and avoid the occurrence of disasters. Especially for underground engineering, complex geological conditions make the structure more prone to disasters. Aiming at solving the problems existing in previous studies, such as incomplete consideration factors and can only predict the continuous performance, the deep attention fused temporal convolution network (DATCN) is proposed in this paper to predict the spatial mechanical behaviors of structure, which integrates both the temporal effect and spatial effect and realize the cross-time prediction. The temporal convolution network (TCN) and self-attention mechanism are employed to learn the temporal correlation of each monitoring point and the spatial correlation among different points, respectively. Then, the predicted result obtained from DATCN is compared with that obtained from some classical baselines, including SVR, LR, MLP, and RNNs. Also, the parameters involved in DATCN are discussed to optimize the prediction ability. The prediction result demonstrates that the proposed DATCN model outperforms the state-of-the-art baselines. The prediction accuracy of DATCN model after 24 hours reaches 90 percent. Also, the performance in last 14 hours plays a domain role to predict the short-term behaviors of the structure. As a study case, the proposed model is applied in an underwater shield tunnel to predict the stress variation of concrete segments in space.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.41-46
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• 2023

Recently, big data analysis can use various techniques according to the development of machine learning. Big data collected in reality lacks an automated refining technique for the same or similar terms based on semantic analysis of the relationship between words. Since most of the big data is described in general sentences, it is difficult to understand the meaning and terms of the sentences. To solve these problems, it is necessary to understand the morphological analysis and meaning of sentences. Accordingly, NLP, a technique for analyzing natural language, can understand the word's relationship and sentences. Among the NLP techniques, the transformer has been proposed as a way to solve the disadvantages of RNN by using self-attention composed of an encoder-decoder structure of seq2seq. In this paper, transformers are used as a way to form associations between words in order to understand the words and phrases of sentences extracted from big data.

• Human Ecology Research
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• v.60 no.1
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• pp.1-20
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• 2022

This paper presents a social network analysis of changes in Home Economics education content loaded on YouTube before and after the outbreak of COVID-19. From January 1, 2008 to June 30, 2021, a basic analysis was conducted of 761 Home Economics education videos loaded on YouTube, using NetMiner 4.3 to analyze important keywords and the centrality of video titles and full texts. Before COVID-19, there were 164 Home Economics education videos posted on YouTube, increasing significantly to 597 following the emergence of the pandemic. In both periods, there was more middle school content than high school content. The content in the child-family field was the most, and the main keywords were youth and family. Before COVID-19, a performance evaluation indicated that the proportion of student content was high, whereas after the outbreak of the disease, teacher content increased significantly due to the effect of distance learning. However, compared with video use, the self-expression and participation of users were lower in both periods. The centrality analysis indicated that in the title, 'family' exhibited a high degree of both centrality and eigenvector centrality over the entire period. Degree centrality of the video title was found to be high in the order of class, online, family, management, etc. after the outbreak of COVID-19, and the connection of keywords was strong overall. Eigenvector centrality indicated that career, search, life, and design were influential keywords before COVID-19, while class, youth, online, and development were influential keywords after COVID-19.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.85-93
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• 2021

The government is pursuing plans to create new e-government services. In terms of improving business procedures, dBrain (finance), e-people (personnel), and Onnara (electronic payment and business management) have achieved considerable results, and are currently making efforts to improve existing administrative services using newly emerged ICT. Among them, this paper attempted to study whether self-learning-based intelligent administrative services are efficient in the work process of public officials promoting actual work and affect their continued use. Based on individual perceptions and attitudes toward advanced ICTs such as AI, big data, and blockchain, public officials' influences on administrative services were identified and verified using UTAUT variables. They believe that the establishment and introduction of innovative administrative services can be used more efficiently, and they have high expectations for the use and provision of services as ICT develops. In the future, a model will be also applied to citizens

• The Journal of Korean Academic Society of Nursing Education
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• v.27 no.4
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• pp.436-446
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• 2021

Purpose: The purpose of this study was to identify the influences of nursing students perfectionism tendencies and their perception of instructor caring on incivility experienced by nursing students during clinical practice. Methods: A descriptive correlational study was conducted. The participants were 244 nursing students from five universities in B city. Data were analyzed using an independent t-test, ANOVA, Pearson's correlation coefficient, Scheffé test and a stepwise regression analysis. Results: The mean score for incivility in nursing students was 2.61 out of 5 points. The explanatory power of the model for incivility was in nursing students 52.8% of the variance in training in student's university hospital (𝛽=-.15, p=.002), total period of clinical practice (𝛽=.17, p<.001), confidence through caring (𝛽=-.23, p<.001), respectful sharing (𝛽=-.15, p=.005), supportive learning climate (𝛽=-.15, p=.005), self-oriented perfectionism (𝛽=.14, p=.004), and socially prescribed perfectionism (𝛽=.18, p<.001). Conclusion: The research results suggest that instructor caring is an important factor in regard to the incivility of nursing students. Organizational efforts and institutional devices will be needed to improve the incivility in clinical environments. By communicating with students and showing them respect, clinical nurses will help nursing students cope with incivility and recognize the clinical practice education environment positively.

• Journal of Christian Education in Korea
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• v.69
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• pp.105-137
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• 2022

This paper is to study the characteristics of outdoor wilderness education and the impacts of outdoor wilderness experience on the participants in higher education. The first part of this paper addresses the common components of outdoor wilderness programs: adventure or self-discovery in disequilibrium, small groups for accountability in a temporary community, problem solving processes for decision making in real situations, solo time for integration in solitude, and leadership styles and role of the trip leaders. These elements of outdoor wilderness programs help the participants to achieve their goals according to its mission. The second part of this paper divides outdoor wilderness programs into three categories according to the objectives and outcomes of outdoor wilderness education: orientation programs for incoming students, personal leadership development programs, and professional training programs. The impacts of outdoor wilderness experiences on the participants of different programs in higher education were reviewed. Then guidelines for spiritual formation prorgams were proposed for Christian educators who are involved in wilderness programs in higher education to develop their practical wilderness experiences into holistic development programs according to its mission and goals.

• Journal of Korean Academy of Nursing
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• v.52 no.6
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• pp.564-581
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• 2022

Purpose: This study aimed to evaluate the validity and reliability of the Korean version of the Readiness for Practice Survey (K-RPS). Method: The English Readiness for Practice Survey was translated into Korean using the Translation, Review, Adjudication, Pretesting, and Documentation (TRAPD) method. Secondary data analysis was performed using the dataset from the New Nurse e-Cohort study (Panel 2020) in South Korea. This study used a nationally representative sample of 812 senior nursing students. Exploratory and confirmatory factor analyses were also conducted. Convergent validity within the items and discriminant validity between factors were assessed to evaluate construct validity. Construct validity for hypothesis testing was evaluated using convergent and discriminant validity. Ordinary α was used to assess reliability. Results: The K-RPS comprises 20 items examining four factors: clinical problem solving, learning experience, professional responsibilities, and professional preparation. Although the convergent validity of the items was successfully verified, discriminant validity between the factors was not. The K-RPS construct validity was verified using a bi-factor model (CMIN/DF 2.20, RMSEA .06, TLI .97, CFI .97, and PGFI .59). The K-RPS was significantly correlated with self-esteem (r = .43, p < .001) and anxiety about clinical practicum (r = - .50, p < .001). Internal consistency was reliable based on an ordinary α of .88. Conclusion: The K-RPS is both valid and reliable and can be used as a standardized Korean version of the Readiness for Practice measurement tool.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.167-176
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• 2023

In this paper, we designed and implemented a graph assessment module that can evaluate graphs in an programming assessment system based on text and numbers. The assessment method of the graph assessment module is self-evaluation that outputs two graphs generated by codes submitted by learners and by answers, automatic-evaluation that converts each graph image into an array, and gives feedback if it is wrong. The data used to generate the graph can be inputted directly or used from external data, and the method of generatng graph that can be evaluated is MATLAB style in matplotlib, and the graph shape that can be evaluated is presented in mathematics and curriculum. Through expert review, it was confirmed that the content elements of the assessment module, the possibility of learning, and the validity of the learner's needs were met. The graph assessment module developed in this study has expanded the evaluation area of the programming automatic asssessment system and is expected to help students learn data visualization.