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

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.487-494
• /
• 2023

The purpose of this study was to examine the relationship between self-directed learning readiness, stress coping, and academic resilience among freshman nursing students, and investigate the impact of self-directed learning readiness and stress coping on academic resilience. Data were collected from March 15 to March 26, 2022, using 205 questionnaires that were analyzed using SPSS/WIN 25.0. The results showed that the average self-directed learning readiness score of the participants was 2.61, the average stress coping score was 2.14, and the average academic resilience score was 2.36. Academic resilience was found to be positively correlated with self-directed learning readiness (r=.573, p<.001), problem-focused coping (r=.305, p<.001), seeks social support coping (r=.321, p<.001), and hopeful thought coping (r=.344, p<.001). The variables that affected academic resilience were self-directed learning readiness (β=.498, p<.001), seeks social support coping (β=.203, p=.001), and major satisfaction (β=.117, p=0.034), and these variables explained 44.8% of the variance in academic resilience. Therefore, to enhance academic resilience among nursing students, it is necessary to develop programs that improve self-directed learning readiness and promote active stress coping strategies.

• Journal of Digital Convergence
• /
• v.10 no.8
• /
• pp.341-346
• /
• 2012

This paper reports the findings of research into the effect of flow experience and internet addiction on e-learning participation. The total number of access, playing time of contents and lag time (time between content upload and first access) were investigated as e-learning participation by analyzing web log data. The paper also examines the relationship between academic achievement and e-learning participation. The results suggest that the flow experience significantly correlates with all variables related with e-learning participation and internet addiction significantly correlates with lag time. It is found that female students significantly access more, longer and have shorter lag time than their male counterparts. It also suggest total number of access, lag time and gender difference have significant effect on academic achievement.

• Journal of Digital Convergence
• /
• v.15 no.5
• /
• pp.189-195
• /
• 2017

The pursuit of independent self-development in adolescence and the development of self-identity are related to their adaptation in social life. In Korea, too, college is the place where graduates from high school go to advance in society. The purpose of study is to investigate the relationship between self - identity and college life in university students. First, self - identity has a positive effect on academic adjustment. Specifically, goal orientation has a positive effect on academic adjustment. Second, self - identity has a positive effect on emotional adjustment. In detail, self-acceptance, future confidence, and goal orientation were found to affect emotional adaptation. Finally, self - identity did not affect university satisfaction.

• Journal of Digital Convergence
• /
• v.14 no.9
• /
• pp.301-308
• /
• 2016

Writing high-quality papers and publishing them at prestigious academic journals would be something that every scholar strives for. This study made a network with nine academic journals in South Korea in the field of public administration and public policy and analyzed the influence of academic journals through social network analysis. Using centrality measures, such as degree centrality, beta centrality, and eigenvector centrality, this study found that Korean Public Administration Review has the highest influence on the journal network, followed by Korean Public Studies Review. However, different choice of centrality measure led to different ranking of journals in terms of their influence.

• The Journal of Economics, Marketing and Management
• /
• v.10 no.6
• /
• pp.1-7
• /
• 2022

Purpose: The purpose of this study is identifying the research trends of degree papers related to the beauty industry and providing information which can contribute to the development of the domestic beauty industry and the direction of various research about beauty industry. Research design, data and methodology: This study used 154 academic papers and 189 academic papers with English abstracts out of 299 academic papers. All of these papers were found by searching for the keyword "beauty industry" in ScienceON on August 15, 2022. For the analysis, BERTopic and LDA (Latent Dirichlet Allocation) analysis were conducted using Python 3.7. Also, OLS regression analysis was conducted to understand the annual increase and decrease trend of each topic derived with trend analysis. Results: As a result of word frequency analysis, the frequency of satisfaction, management, behavior, and service was found to be high. In addition, it was found that 'service', 'satisfaction' and 'customer' were frequently associated with program and relationship in the word co-occurrence frequency analysis. As a result of topic modeling, six topics were derived: 'Beauty shop', 'Health education', 'Cosmetics', 'Customer satisfaction', 'Beauty education', and 'Beauty business'. The trend analysis result of each topic confirmed that 'Beauty education' and 'Health education' are getting more attention as time goes by. Conclusions: The future studies must resolve the extreme polarization between the structure of the small beauty industry and beauty stores. Furthermore, the researches have to direct various ways to create the performance of internal personnel. The ways to maximize product capabilities such as competitive cosmetics and brands are also needed attentions.

• Asia pacific journal of information systems
• /
• v.29 no.4
• /
• pp.615-643
• /
• 2019

Now is the time for IS scholars to demonstrate the added value of academic theory through its integration with text mining, clearly outline how to implement this for text mining experts outside of the academic field, and move towards establishing this integration as a standard practice. Therefore, in this study we develop a systematic theory-based text-mining framework (TTMF), and illustrate the use and benefits of TTMF by conducting a text-mining project in an actual business case evaluating and improving hotel service quality using a large volume of actual user-generated reviews. A total of 61,304 sentences extracted from actual customer reviews were successfully allocated to SERVQUAL dimensions, and the pragmatic validity of our model was tested by the OLS regression analysis results between the sentiment scores of each SERVQUAL dimension and customer satisfaction (star rates), and showed significant relationships. As a post-hoc analysis, the results of the co-occurrence analysis to define the root causes of positive and negative service quality perceptions and provide action plans to implement improvements were reported.

• Journal of Digital Convergence
• /
• v.22 no.2
• /
• pp.1-9
• /
• 2024

The purpose of this study is to verify whether companies residing in industry-academic convergence zones designated by the government are achieving policy goals and to seek policy implications and directions for improvement through analysis. For the study, business activities targeting resident companies were divided into infrastructure, business content, management, and system aspects, and business performance indicators, resident company satisfaction surveys, and differences in sales increase between resident companies and non-resident companies were analyzed through t-test. Based on statistical analysis results, performance indicators, and corporate survey analysis results, we track joint industry-academia R&D projects to maximize the effectiveness for companies, develop and operate human resources management for teams, and provide financial support for ordinances of metropolitan local governments. Improvements such as stipulation, antenna facilities at the corporate research center, and improvement of the researcher's residential environment were suggested. This study is the first to quantitatively verify policy performance targeting companies residing in industry-academic convergence zones, a large-scale government project, and future follow-up research is needed, including analysis of policy effects based on various variables such as employment indicators and corporate financial indicators.

• Proceedings of the Technology Innovation Conference
• /
• 1997.12a
• /
• pp.70-88
• /
• 1997

Recently, the interdisciplinary linkage between engineering and social science has received an increasing attention as an emerging education discipline. Due to intrinsic complexity of innovation process and heterogeneity of disciplinary nature, however there exists little, if not no, effort to draw a common framework in terms of educational scope and contents of the new subject. This paper presents a number of criteria and guidelines for building up new educational framework by integrating engineering subject and social science subject. Specifically, three neo-disciplines, technology policy, technology management, and economics of technology are considered since it is postulated that the forementioned disciplines have established academic identity and fundamental structure By nature, this paper is an exploratory and seminal one. It is not the purpose of this paper to provide a concrete table of contents of educational material. Instead, it merely brings up a discussion topic for the wide audience of academic arena, leaving the gradual consensus and convergence as future task.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
• /
• v.67
• /
• pp.233-253
• /
• 2015

The cooperation among industry, academy and government is the main factor for world leading trade country. In particular, many papers and research is greatly helpful for finding the needs of industry and establishing strategies. Academic activities have significantly contributed the development of trade. In recent time, the approach based on complexity, convergence and consilience in increasing in academic fields for more mutual understanding and exchange of ideas. For this reason, joint research is necessary in trade. In this research, author can find not only the trend of joint research but also the centrality of trade researchers in the excellent journals in Korea by use of Social Network Analysis.