• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1353-1358
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• 2015

The creative economy is the industrialization era, the information age, knowledge-based economy, linking the new economic paradigm. The core words of the creative economy are stand for creativity, innovation, consumer protection and utilization of intellectual property. Creative ideas are combined with software technology will make innovative ecosystem-based structured market such as Apple, Google, Facebook. Intangible assets attributable to creativity than ever before in human history that is important as the economic value. In addition, innovative ideas, creativity and economic growth beyond the knowledge and information society is required. Because the core has a fusion of science and technology, industry, culture and industry convergence, various genres of creative activity support, and cultural and high-tech fusion industries, such as content creation and job creation through economic traction is needed. In this study, we analyze the case of the US Smithsonian Institution proposes the direction of Science Museum in creative workforce.

• Journal of Practical Engineering Education
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• v.11 no.1
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• pp.87-103
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• 2019

The purpose of this study is to examine the factors affecting the intention of smart device internet usage from the perspective of lifelong learning of elderly people. Survey was conducted for understanding the factors affecting the internet usage intention of smart devices with 150 elderly people who visited the Gwangju Senior Technology Center (GSTC). The empirical results show that the perceived economic value and practical value of the elderly have a significant effect on the intention of utilizing the Internet of Smart Device. Although the moderating effect of the individual innovation of the elderly is not significant, Participation in social activities significantly moderated the relationship between perceived value and intention to use internet. In addition, the elderly expected that the quality of life would be improved via the use of smart devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.978-984
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• 2020

In this study, the correlation between sports records and weather data was analyzed using the big data analysis method. To this end, data was collected by API and crawling, data was processed, statistics were performed, and data visualization was performed. The subject of this study was a player who entered the regular at-bat among outfielders in the 2019 KBO League. In addition, meteorological data were analyzed by using the unpleasant index and above 70 and below 70. As a result of the study, in the various hitting indicators, which are the records that pitchers intervene, the higher the unpleasant index, the better the outfielder's record, but pitchers, walks, pitches, pitching success rates, pitches per turn, pitches per game From the records of the back, it was found that the outfielder made the pitcher difficult. It is expected that this study will help the development of the sports data industry and the performance of baseball players, baseball teams, and coaching staff.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.49-59
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• 2022

This study was conducted to develop a teaching competency scales customized for teaching programs conducted by Center for Teaching & Learning at A University. To achieve this purpose, a preliminary study was set up, which consists of three competency groups (basic competency, practice competency, innovation competency) and 26 learning competency factors through a review of previous studies. In order to verify the reliability and validity of the provisional teaching competency scales, an online survey was conducted on A university teachers in September 2020, The collected questionnaire data were organized and exploratory factor analysis and confirmatory factor analysis were conducted. As a result of exploratory factor analysis, 26 teaching competency was reduced to 17. As a result of the confirmatory factor analysis, the model was found to be good, Also, as a result of analyzing the construct reliability and AVE of the confirmed teaching competency factors, all 17 factors showed a good level of .7 or more. The teaching competency scales developed through this study can be used as basic data for performance evaluation and development of new programs of CTL teaching program.

• Journal of Industrial Convergence
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• v.21 no.3
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• pp.195-202
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• 2023

This study analyzes the results of a survey based on classes conducted in the field to understand the educational needs of learners, and reflects the elements necessary for SW education. In this study, various experimental elements according to learning motivation and learning achievement were constructed and designed through previous studies. As a survey applied to this study, experimental elements in three categories: Faculty Competences(FC), Learner Competences(LC), and Educational Conditions(EC) were analyzed by primary area and secondary major, respectively. As a result of analyzing CT-based SW education by area, the development of educational materials, understanding of lectures, and teaching methods showed high satisfaction, while communication with students, difficulty of lectures, and the number of students were relatively low. The results of the analysis by major were found to be more difficult and less interesting in the humanities than in the engineering field. In this study, Based on these statistical results proposes the need for non-major SW education to improve into an interesting curriculum for effective liberal arts education in the future in terms of enhancing learners' problem-solving skills.

• Journal of Practical Engineering Education
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• v.12 no.1
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• pp.213-230
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• 2020

Until now, various educational budgets, facilities, and programs have been put into school education, but the results have not been clearly evaluated. This study presents a model to analyze the effectiveness of educational support for students in high schools across the country. In this model, we first use EM cluster analysis to make clusters with similar inputs for school operation, and then calculate the relative efficiency in each cluster by using Network DEA analysis. The Network DEA analysis has a two-stage structure where the first stage uses six inputs in terms of school infrastructure to generate outputs such as the number of academic persistence. In the Network DEA analysis, the second stage uses 10 inputs in terms of school programs to generate outputs such as the number of enrollees to higher learning and the number of employees and per capita usage of library as the connection variable. Based on the efficiency analysis results, Tier analysis is performed by applying the Euclidean distance to select targets for benchmarking. In this study, we applied the model to analyze the efficiency of educational support by collecting data regarding student education support in general and vocational high school nationwide. The stepwise benchmarking method proposed that the target be selected for efficiency improvement step by step, taking into account inefficient school elements to complement the problem of the choice of benchmarking targets. Based on this study, it is expected that schools with low efficiency of educational support for students will be used as basic data for stepwise benchmarking for efficient operation of educational support for students.

• Journal of Engineering Education Research
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• v.14 no.2
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• pp.3-12
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• 2011

The purpose of this study is to understand the campus life of engineering transfer students, to devise a means for increasing their participation in the ABEEK, and to assist them to have the satisfactory campus lives through researching the satisfaction level and the campus life adaptation of transfer students. We conducted a survey targeting 193 engineering transfer students of K university and D university. The study shows that most transfer students were accepted into college through a general screening process, their grades are likely to be lower than those of the previous college, however, they tend to be satisfactory with the current campus life, and the rate of participation in the ABEEK is low. Therefore university officials need to work hard to raise the rate of the participation in the ABEEK track and the campus life adaptation of transfer students. Moreover, the male transfer students tend to be more satisfactory than the female students, and students with higher grades in the previous college are likely to show higher adaptation than those with lower grades. Therefore we should make effort to increase the satisfaction of transfer students and need to accommodate the programs for the female transfer students more positively.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.11-19
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• 2020

In recent years, college students have emerged as the main players in Chinese innovation and start-ups. Based on the TPB theory, this paper introduced the start-up education variables and established the influence model of start-up education for university students in China on the motivation of start-up. In this paper, a questionnaire containing five variables, including behavior attitude, subjective norms, perceived behavior control, entrepreneurship education and entrepreneurial intention, was investigated for students from six universities in Jilin Province, China, and statistical analysis was carried out using SPSS23.0. The study found that the entrepreneurship education of college students had the greatest impact on entrepreneurial intentions compared to the three elements of planned behavioral theory: behavioral attitudes, subjective norms and perceived behavioral control. This paper has a guiding significance in strengthening start-up education in universities. This study was conducted only for students from six universities in Jilin Province, China, and the scope of the study needs to be expanded throughout China in order to generalize the research results.

• 대한공업교육학회지
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• v.35 no.2
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• pp.124-139
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• 2010

This study has its purpose of researching on the relevant variables which affect the attitude toward engineering science and brain dominance for the department of engineering students. The results of this study are as follows: First, the department of engineering students' attitude toward engineering science has shown the order of cognitive element (3.73), definitional element (3.05) and behavioral element (2.86), and in the actual context it is considered that it is necessary to establish a teaching-learning strategy which can reinforce the behavioral elements such as experiments and practices as well as can improve engineering-related cognitive ability. Second, the attitudes toward engineering science according to their brain dominance thinking (Type A: analyst, Type B: Administrator, Type C: Cooperator, and Type D: Jointer) have no significant difference, but the students of Type A who have the characteristics of 7 analyzing thinking have shown high academic accomplishment. Based on these results of study, it is necessary to make a change of the current teaching-learning stratery in accordance with the types of thinking of the students from the teaching-learning perspective. In particular, in order to develop the weak dominance properties and thinking type of individual learners, the change in teacher's recognition that the teacher's teaching-learning strategy and practice is important has to take precedence.

• Journal of Engineering Education Research
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• v.11 no.4
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• pp.64-75
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• 2008

The purpose of the study was to verify reliability and validity of SDLRS instrument and to prove up possibility of usage as an evaluation method for evaluating life-long learning. Literature review and survey were used to accomplish objectives of the study. 218 students in department of mechanical engineering of A university at Gyunggi province were responded for SDLRS(Guglielmino, 1977) instrument. Data were analyzed using descriptive statistics, factor analysis, t-test, and ANOVA test. 58 items in original version instrument were converted to 23 items. There were 7 factors for assessing the self-directed learning readiness according to this measurement scale with a total variance of about 58%. The total reliability of the final 23 items was $\alpha$. The final 7 factors consisted of love for learning, openness for learning, self-perception, basic learning function and independence, acceptance of responsibility for learning, leadership and future directivity, and creativity and exploration. The result of SDLRS analysis according to individual background, there were significant statistically in the grade, period of employment in industry, entering graduate school or not, and GPA, but no significant statistically in sexual difference, employment in industry or not, final academic level of parent, and income level of the family. In the future, final instrument will be needed to check in the respect of correlation with another ability and skill influencing on life-long learning, and more study will be done for developing life-long learning.