• Journal of Industrial Convergence
• /
• v.21 no.5
• /
• pp.1-13
• /
• 2023

Carbon neutrality is the concept of reducing greenhouse gases emitted by human activities and making actual emissions zero through removal of remaining gases. It is also called "Net-Zero" and "carbon zero". Korea has declared a "2050 Carbon Neutrality policy" to cope with the climate change crisis. Various carbon reduction legislative processes are underway. Since carbon neutrality requires changes in industrial technology, it is important to prepare a system for carbon zero. This paper aims to understand the status and trends of global carbon neutrality technology. Therefore, ROK's web platform "www.naver.com." was selected as the data collection scope. Korean online articles related to carbon neutrality were collected. Carbon neutrality technology trends were analyzed by future signal methodology and Word2Vec algorithm which is a neural network deep learning technology. As a result, technology advancement in the steel and petrochemical sectors, which are carbon over-release industries, was required. Investment feasibility in the electric vehicle sector and technology advancement were on the rise. It seems that the government's support for carbon neutrality and the creation of global technology infrastructure should be supported. In addition, it is urgent to cultivate human resources, and possible to confirm the need to prepare support policies for carbon neutrality.

• Journal of Digital Convergence
• /
• v.20 no.1
• /
• pp.33-39
• /
• 2022

This study aims to investigate the online class preference depending on students' gender and school level. To achieve this aim, the study conducted a survey on 4,803 elementary, middle, and high school students in 17 regions nationwide. The valid data of 4,524 were then analyzed using the Apriori algorithm to discern the associated patterns of the online class preference corresponding to their gender and school level. As a result, a total of 16 rules, including 7 from elementary school students, 4 from middle school students, and 5 from high school students were derived. To be specific, elementary school male students preferred software-based classes whereas elementary female students preferred maker-based classes. In the case of middle school, both male and female students preferred virtual experience-based classes. On the other hand, high school students had a higher preference for subject-specific lecture-based classes. The study findings can serve as empirical evidence for explaining the needs of online classes perceived by K-12 students. In addition, this study can be used as basic research to present and suggest areas of improvement for diversifying online classes. Future studies can further conduct in-depth analysis on the development of various online class activities and models, the design of online class platforms, and the female students' career motivation in the field of science and technology.

• Journal of The Korean Association For Science Education
• /
• v.43 no.3
• /
• pp.237-251
• /
• 2023

This study explores the possibility of automated scoring for scientific graph answers by designing an automated scoring model using convolutional neural networks and applying it to students' kinematics graph answers. The researchers prepared 2,200 answers, which were divided into 2,000 training data and 200 validation data. Additionally, 202 student answers were divided into 100 training data and 102 test data. First, in the process of designing an automated scoring model and validating its performance, the automated scoring model was optimized for graph image classification using the answer dataset prepared by the researchers. Next, the automated scoring model was trained using various types of training datasets, and it was used to score the student test dataset. The performance of the automated scoring model has been improved as the amount of training data increased in amount and diversity. Finally, compared to human scoring, the accuracy was 97.06%, the kappa coefficient was 0.957, and the weighted kappa coefficient was 0.968. On the other hand, in the case of answer types that were not included in the training data, the s coring was almos t identical among human s corers however, the automated scoring model performed inaccurately.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.4
• /
• pp.303-308
• /
• 2023

The purpose of this study is to provide a practical guide for establishing BSC that can be practically applied by SMEs. To this end, a case study was conducted to establish a performance evaluation system through a field-required Balanced Scorecard (BSC) for company J, a tent pole manufacturer, and to provide a management strategy system map. As a survey method, the requirements of the ordering organization were organized through a comparison of the BSC-related proposal requests in the first stage. The BSC establishment method was organized through the arrangement of the second stage result report. The 3rd stage BSC derived KPI indicators for SMEs for each of the 4 perspectives. A corporate vision was derived through a 4-step SWOT analysis. A strategy map was developed through 5-step field-required KPI, weight setting, and BSC. The 6-step final strategy system was also drawn up. As a result of the study, the four perspectives of the BSC were reconstructed by department. That is, the financial (financial) perspective is from the executives' perspective, the customer's perspective is from the sales department's perspective, the internal process perspective is from the design department/production quality department's perspective, and the learning/innovation perspective is from the management department's perspective. In addition, a total of 11 CSFs and a total of 49 KPIs of J company were derived. The limitation of the study is that the final strategy system through the company's BSC has only been carried out, and it needs to be linked with the company's compensation system in the future.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.4
• /
• pp.39-49
• /
• 2023

This study data were collected from 217 nursing students in J city to analyze major satisfaction and awareness of the importance of practice and performance of nursing students' practice at the public health center, and to identify improvement plans for the practice contents of the health center. The collected data was analyzed using SPSS WIN 25.0, and the research results showed that there was a positive correlation (r=.55, p<.001) between major satisfaction and public health center clinical practice performance, and the sub-factors of performance It showed positive correlation with all (r=.41~.54, p<.001). In particular, among the sub-factors, Internal growth through practice and Correlation with the actual application of theory were highly correlated (r=.54~.56, p<.001). In order to improve nursing students' satisfaction with their major, theoretical study should be preceded, and through area analysis, in order to obtain satisfaction through identity and internal growth of nursing students while practicing health center practice, practice instructors during health center practice Establish various networks, do our best to communicate smoothly with nursing students, and strive to present opinions through meetings with practice institutions before and after practice to improve the community health center practice environment. Also, nursing college students In order for the public health center practice to be carried out smoothly, practice guidance instructors drew improvement points that nursing college students need prior learning related to practice before practicing health center practice.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.4
• /
• pp.153-160
• /
• 2023

The process of verifying design concepts and ideas by producing real or equivalent model is essential in the product development process. Against this background, the purpose of this study is to consider the case of developing subjects that can systematically cultivate the ability to produce model from the basic stage to a certain level or higher, focusing on design engineering majors. As a theoretical consideration for this, prior studies related to making such as modeling or prototyping in related areas and majors such as industrial design are considered, followed by Bloom's revised taxonomy model and Hioshi Ishikawa's industrial design program as a methodological consideration for curriculum development. Finally, by applying this, we propose a new course that includes a lecture plan corresponding to the 16th week of learning, which is a general semester of university education. As a result of the study, it was confirmed that producing a physical model was still essential for the development of a new design, and accordingly, it was also necessary to establish a systematic curriculum suitable for the major area. Since the scope of this study extends to the development of subjects, in subsequent studies, it is necessary to consider the contents such as verification and reflection of the utility as competency education through actual application and suggestion of improved subject design.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.2
• /
• pp.357-366
• /
• 2023

In the purpose of this study, the college textbooks of self-narrative writing and examples of classroom practice are analyzed to find a way to educate it. The self- narrative writing subject with a learning of recognization, expression, and communication with oneself, emphasizes the necessity when they become college students through entrance exam-oriented education. The research methods are as follows. Firstly, three university textbooks which include a section on self-narrative writing were compared and analyzed. The analysis highlights the needs for a textbook covering self-narrative writing more extensively and comprehensively as what is offered by the existing textbooks is limited in facilitating students to fully develop the ability of self-reflection, which should be dealt as a long-term goal. Secondly, the current discussion on self-narrative writing and examples of real classroom practice were analyzed. It shows that a step-by-step approach is required to encourage the practice of deep self-reflection to be incorporated into writing. In addition, during the writing process, various correction and feedback activities should be carried out on a macro level and gradually while the communication and feedback should take place not only between a teacher and students, but also among students. As a result, it is expected that this study will help establish a teaching model of self-narrative writing by seeking complementary points and educational directions for self-narrative writing.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.471-480
• /
• 2023

The purpose of this study is to confirm the effect of recording online classes and real-time video classes on other behaviors, lecture satisfaction, and lecture flow in during the COVID-19 period. Data were collected and analysis using a structured questionnaire from May 20th to June 4th in 2021 for 550 nursing students in the D University. As a result of the study, it was found that there were more others behaviors in record online classes than in real-time online classes (t=-2.00, p=.046), lecture satisfaction(t=-1.54, p=.124) and lecture flow in real-time online classes it was higher in the record online classes (t=-.63, p=.529), but it was not statistically significant. However, the 2nd year students who participated in the two types of online classes showed statistically significantly higher lecture satisfaction (t=13.55, p=.000) and lecture flow(t=4.48, p=.004). And 4 th grade students of others behaviors was statistically significantly lower (t=4.68, p=.003). In the multiple regression analysis, the main factor affecting lecture flow was lecture satisfaction, and the explanatory power of the model was 55.1% in record online classes (F=128.49, p <.01), and in real-time classes 47.2%(F=77.24, p<.01). In the future, research should be conducted to confirm the difference between the two types of online classes of the same instructor and the difference in other things, lecture satisfaction, and class commitment that appear after applying learner-centered learning.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.2
• /
• pp.381-388
• /
• 2023

This thesis is purposed to develop a regional-customized education program selection model using big data analysis. Based on the literature review, the concepts and characteristics of big data and lifelong education are analyzed. In addition, this thesis presents how to collect the data for lifelong education and to use big data suitable for the characteristics of lifelong education. Based on these results, a regional- customized lifelong education program selection model is developed. The regional customized lifelong education program model is developed by the following six steps. The customized education program model proposed in this study has a high degree of flexibility in terms of practical use, as it can be utilized in real-time data provision methods such as the nationally approved Lifelong Learning Personal Status Survey without the need for analysis one year later, allowing for selective analysis and future predictions. It is clear that there is a significant need and value for big data in the education field. Furthermore, all programs used in the sample model are provided free of charge, and due to the programming nature, the community is actively engaged in exchanges, making it very easy to modify and improve for the development of a more complete education program model in the future.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.10
• /
• pp.133-153
• /
• 2023

In this paper, we propose a novel approach to investigating brain-signal measurement technology using Electroencephalography (EEG). Traditionally, researchers have combined EEG signals with bio-signals (BSs) to enhance the classification performance of emotional states. Our objective was to explore the synergistic effects of coupling EEG and BSs, and determine whether the combination of EEG+BS improves the classification accuracy of emotional states compared to using EEG alone or combining EEG with pseudo-random signals (PS) generated arbitrarily by random generators. Employing four feature extraction methods, we examined four combinations: EEG alone, EG+BS, EEG+BS+PS, and EEG+PS, utilizing data from two widely-used open datasets. Emotional states (task versus rest states) were classified using Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) classifiers. Our results revealed that when using the highest accuracy SVM-FFT, the average error rates of EEG+BS were 4.7% and 6.5% higher than those of EEG+PS and EEG alone, respectively. We also conducted a thorough analysis of EEG+BS by combining numerous PSs. The error rate of EEG+BS+PS displayed a V-shaped curve, initially decreasing due to the deep double descent phenomenon, followed by an increase attributed to the curse of dimensionality. Consequently, our findings suggest that the combination of EEG+BS may not always yield promising classification performance.