• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.61-74
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• 2022

Recently, youth unemployment, especially the unemployment problem of university graduates, has emerged as a social problem. Unemployment of university graduates is both a pan-national issue and a university-level issue, and each university is making many efforts to increase the employment rate of graduates. In this study, we present a model that predicts employment availability of D-university graduates by utilizing Machine Learning. The variables used were analyzed using up to 138 personal information, admission information, bachelor's information, etc., but in order to reflect them in the future curriculum, only the data after admission works effectively, so by department / student. The proposal was limited to the recommended ability to improve the separate employment rate. In other words, since admission grades are indicators that cannot be improved due to individual efforts after enrollment, they were used to improve the degree of prediction of employment rate. In this research, we implemented a employment prediction model through analysis of the core ability of D-University, which reflects the university's philosophy, goals, human resources awards, etc., and machined the impact of the introduction of a new core ability prediction model on actual employment. Use learning to evaluate. Carried out. It is significant to establish a basis for improving the employment rate by applying the results of future research to the establishment of curriculums by department and guidance for student careers.

• Therapeutic Science for Rehabilitation
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• v.10 no.4
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• pp.7-24
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• 2021

Objective : This study examined the characteristics of the literature involving a single-subject research design among positive behavior support intervention studies to improve problem behavior in children with autism spectrum disorders and assess the quality level. Methods : This is a literature study, and the targets of analysis were nine single-subject research papers published between 2011 and 2020. The subject papers were analyzed by dividing them into general characteristics and the qualitative levels according to the content of the research method. Results : Analysis of analyzing the contents of the study showed that the subjects were preschool and elementary school-age children at the same ratio. Furthermore, the study design involved mostly the middle and multiple baseline designs among the behaviors. All papers presented social validity, intervention fidelity, and observer reliability. Problem behaviors included self-injury and aggression behaviors, disturbing behaviors, and seat break-away behaviors, while the most dependent variables were measured through partial interval recording. As a result of confirming the intervention effect, the effect was confirmed in intervention, maintenance, and generalization. All analysis studies showed high-quality levels. Conclusion : This study confirmed the content and qualitative level of the thesis that applied the single-subject research design among positive behavior support intervention studies for problem behaviors of children with autism spectrum disorders. Positive behavior support intervention, an evidence-based intervention for children with autism spectrum disorders, was confirmed an effective intervention for autism spectrum disorders.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.95-118
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• 2021

As the AI speaker business has risen significantly in recent years, the potential for numerous uses of AI speakers has gotten a lot of attention. Consumers have created an environment in which they can express and share their experiences with products through various channels, resulting in a large number of reviews that leave consumers with a variety of candid opinions about their experiences, which can be said to be very useful in analyzing consumers' thoughts. Using this review data, this study aimed to examine the factors driving the continued use of AI speakers. Above all, it was determined whether the seven characteristics associated with the intention to adopt AI identified in prior studies appear in consumer reviews. Based on customer review data on Amazon.com, text mining and social network analysis were utilized to examine Amazon eco-products. CONCOR analysis was used to classify words with similar connectivity locations, and Connection centrality analysis was used to classify the factors influencing the continuous use of AI speakers, focusing on the connectivity between words derived by classifying review data into positive and negative reviews. Consumers regarded personality and closeness as the most essential characteristics impacting the continued usage of AI speakers as a result of the favorable review survey. These two parameters had a strong correlation with other variables, and connectedness, in addition to the components established from prior studies, was a significant factor. Furthermore, additional negative review research revealed that recognition failures and compatibility are important problems that deter consumers from utilizing AI speakers. This study will give specific solutions for consumers to continue to utilize Amazon eco products based on the findings of the research.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.267-277
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• 2022

Achievement at university is recognized in a comprehensive sense as the level of qualitative change and development that students have embodied as a result of their experience in university education. Therefore, the academic achievement of university students will be given meaning in cooperation with the historical and social demands for diverse human resources such as creativity, leadership, and global ability, but it is practically an indicator of the outcome of university education. Measurement of academic achievement by such credits involves many problems, but in particular, standardization of academic achievement by credits based on evaluation methods, contents, and university rankings is a very difficult problem. In this study, we present a model that uses machine learning techniques to predict whether or not academic achievement is excellent for D-University graduates. The variables used were analyzed using up to 96 personal information and bachelor's information such as graduation year, department number, department name, etc., but when establishing a future education course, only the data after enrollment works effectively. Therefore, the items to be analyzed are limited to the recommended ability to improve the academic achievement of the department/student. In this research, we implemented an academic achievement prediction model through analysis of core abilities that reflect the philosophy, goals, human resources image, and utilized machine learning to affect the impact of the introduction of the prediction model on academic achievement. We plan to apply the results of future research to the establishment of curriculum and student guidance conducted in the department to establish a basis for improving academic achievement.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.203-210
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• 2022

The purpose of this study examines to what extent the multicultural youth's dual culture acceptance attitude is significantly affected by cultural adaptation stress and national identity using the data of the MAPS(Multicultural Adolescents Panel Study) conducted by the National Youth Policy Institute. The subject of the study was the first data of the second period of the MAPS, and 2,246 multicultural youth who were enrolled in the fourth grade of elementary school as of 2019 were used as analysis data. As a result of the study, it was found that the attitude to accept dual culture was significantly affected in the order of national identity and cultural adaptation stress. This means that the higher the national identity and the lower the cultural adaptation stress, the higher the attitude toward dual culture. On the other hand, as for the type of multicultural youth, it was found that international marriage families had the lowest attitude toward accepting dual culture. In terms of the size of the area where students live, large cities have the lowest dual cultural acceptance attitude. These results suggest that cultural adaptation stress, national identity, type of multicultural family, and area of residence act as major variables in multicultural youth's dual culture acceptance attitude.

• Journal of Korea Entertainment Industry Association
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• v.13 no.1
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• pp.99-109
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• 2019

The study was conducted to investigate the activities of working people in the sports club. The subject of this study was to take samples of workers who participated in the physical education system using the convenience sampling method. Out of a total of 400 questionnaires, 387 were used for research purposes, except for invalid or error questionnaires. Factor analysis and reliability tests were performed using IBM SPSS statistics Ver 21.0. Frequency analysis was conducted to explore the general characteristics of the study participants. An independent sample t-test ANOVA were conducted to verify differences among groups according to demographic characteristics, and a correlation analysis was conducted to examine the relationship between variables. Regression was performed to verify the effect of variable factors. The results of the study are as follows. First, there was no difference in wellness and job satisfaction according to gender. Second, there was no difference in wellness and job satisfaction according to sport. Third, there was a significant difference intellectual wellness according to age. In particular, 40s and 50s were higher than 60s and over. Fourth, there was a significant difference in social wellness according to activity duration. In particular, 1~2 years were higher than 3 years or more. Finally, If you look at the impact of working people's wellness lifestyle sports club activities on job satisfaction, the professional wellness lifestyle club activities showed significant influence on job satisfaction.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.105-116
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• 2023

As forest fires' scale has increased, they have become disasters that destroy not only forests but also property, human psychological balance, and even human lives. As a result, governmental support has become a crucial part of the forest fire restoration process. Quickly restoring victims' quality of life (QOL) from not only an ecological perspective but also from their human perspective has become an important goal. Therefore, through structural equation modeling, this study analyzed effects of government support, post-traumatic stress disorder (PTSD), and resilience on 195 Uljin and Samcheok forest fire victims' QOL. In the final research model, the total standardized effect on QOL of government support to PTSD and resilience was found to have significant effect (0.417). By path, the effect of government support on QOL through resilience was verified as 0.172. Examination of the path between latent variables revealed that resilience had the greatest influence on QOL, and government support had a significant effect, thus confirming that they were the main factors affecting QOL.

• Journal of Industrial Convergence
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• v.21 no.4
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• pp.133-143
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• 2023

The purpose of this study is to verify the mediating effect of depression on the effect of forest recreation satisfaction on psychological well-being of customers using forest recreation resources and provide basic data for improving psychological well-being. As for the analysis data, a survey was conducted on 450 customers using forest recreation resources, and the final 355 people were selected as subjects of the survey after removing non-response and insincere responses from 377 copies collected. For analysis, the SPSS WIN 23.0 and Amos 21.0 programs were used, and the mediating effect of depression was verified through descriptive statistical analysis, correlation analysis, and structural model of major variables. The study results showed, first, that forest recreation satisfaction had a negative(-) effect on depression. Second, depression was found to have a negative(-) effect on psychological well-being. Third, depression had a complete mediating effect in the relationship between forest recreation satisfaction and psychological well-being. Based on these results, it is meaningful in that programs and practical and policy suggestions were made to improve psychological well-being.

• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.231-263
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• 2022

The understanding and capability to utilize artificial intelligence (AI) incorporated technology has become a required basic skillset for the people living in today's information age, and various members of the university have also increasingly become aware of the need for AI education. Amidst such shifting societal demands, both domestic and international university libraries have recognized the users' need for educational content centered on AI, but a user-centered service that aims to provide personalized recommendations of digital AI educational content is yet to become available. It is critical while the demand for AI education amongst university students is progressively growing that university libraries acquire a clear understanding of user intention towards an AI educational content recommender system and the potential factors contributing to its success. This study intended to ascertain the factors affecting acceptance of such system, using the Extended Technology Acceptance Model with added variables - innovativeness, self-efficacy, social influence, system quality and task-technology fit - in addition to perceived usefulness, perceived ease of use, and intention to use. Quantitative research was conducted via online research surveys for university students, and quantitative research was conducted through written interviews of university librarians. Results show that all groups, regardless of gender, year, or major, have the intention to use the AI-related Educational Content Recommendation System, with the task suitability factor being the most dominant variant to affect use intention. University librarians have also expressed agreement about the necessity of the recommendation system, and presented budget and content quality issues as realistic restrictions of the aforementioned system.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.41-52
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• 2022

Although domestic public libraries achieved quantitative growth based on the 1st and 2nd comprehensive library development plans, there were some qualitative shortcomings, and various studies have been conducted to improve them. Most of the preceding studies have limitations in that they are limited to social and economic factors and statistical analysis. Therefore, in this study, by applying the spatiotemporal concept to quantitatively calculate the decrease in public library loan demand due to rainfall and heatwave, by clustering areas with high demand for book loan due to weather changes and areas where it is not, factors inside and outside public libraries and After the combination, changes in public library loan demand according to weather changes were analyzed. As a result of the analysis, there was a difference in the decrease due to the weather for each public library, and it was found that there were some differences depending on the characteristics and spatial location of the public library. Also, when the temperature was over 35℃, the decrease in book loan demand increased significantly. As internal factors, the number of seats, the number of books, and area were derived. As external factors, the public library access ramp, cafe, reading room, floating population in their teens, and floating population of women in their 30s/40s were analyzed as important variables. The results of this analysis are judged to contribute to the establishment of policies to promote the use of public libraries in consideration of the weather in a specific season, and also suggested limitations of the study.