• Journal of Creative Information Culture
• /
• v.5 no.2
• /
• pp.135-143
• /
• 2019

In this study, the perceptions on SW education of K-12 students and teachers were surveyed and analyzed. At the primary school level, there was no significant difference in SW attitude based on school location. However, at the secondary level, students from metropolitan areas showed significantly higher SW attitude scores. In the case of gender, male students showed higher SW attitude scores both in primary and secondary schools. With regard to attitude differences based on prior experience of SW education, students with prior experience showed higher attitude scores in SW education in both primary and secondary schools. The awareness survey among teachers showed that both primary and secondary school teachers showed positive responses to SW education. For the successful induction of the SW education at K-12, four factors (participants, curriculum, teaching-learning method, and support from inside and outside of school) were highlighted.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.3
• /
• pp.193-198
• /
• 2023

We study a learner-customized lecture recommendation project using deep learning. Recommendation systems can be easily found on the web and apps, and examples using this feature include recommending feature videos by clicking users and advertising items in areas of interest to users on SNS. In this study, the sentence similarity Word2Vec was mainly used to filter twice, and the course was recommended through the Surprise library. With this system, it provides users with the desired classification of course data conveniently and conveniently. Surprise Library is a Python scikit-learn-based library that is conveniently used in recommendation systems. By analyzing the data, the system is implemented at a high speed, and deeper learning is used to implement more precise results through course steps. When a user enters a keyword of interest, similarity between the keyword and the course title is executed, and similarity with the extracted video data and voice text is executed, and the highest ranking video data is recommended through the Surprise Library.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.51-57
• /
• 2021

Quite a few elementary school teachers began to utilize AI technology in order to provide students with customized, intelligent information services in recent years. However, learning principles of AI may be as important as utilizing AI in everyday life because understanding principles of AI can empower them to buildup adaptability to changes in highly technological world. In the paper, 'Linear Regression Algorithm' is selected for teaching AI-based prediction system to solve real world problems suitable for elementary students. A simulation program written in Scratch was developed so that students can find a solution of linear regression model using the program. The paper shows that students have learned analyzing data as well as comparing the accuracy of the prediction model. Also, they have shown the ability to solve real world problems by finding suitable prediction models.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.151-154
• /
• 2021

Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study was analyzed for 21 papers in the March 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 305 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.326-327
• /
• 2021

Newly, big data utilization has been widely interested in a wide variety of industrial fields. Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study were analyzed for 29 papers in a specific journal. In the final analysis results, the most frequently mentioned keyword was "Research", which ranked first 743 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.20 no.4
• /
• pp.51-65
• /
• 2009

This study attempted to investigate users' information needs in an educational research library, which delivers web-based digital reference services to library users, by analyzing reference questions asked by remote users. A total of 242 questions from two electronic bulletin boards was examined in terms of 6 types of questions asked and 23 subareas of education. The study found that 56.1% of reference questions on the library bulletin board were pure reference questions in curriculum, textbooks and teaching & instruction. Suggestions for effective use of digital reference services were made: easy access to menu services, use of web forms, development of digital reference systems providing search functions and response functions.

• Journal of Korea Water Resources Association
• /
• v.56 no.5
• /
• pp.347-356
• /
• 2023

In Water Distribution Systems (WDSs), can abnormal hydraulic and water quality conditions such as red-water phenomenon and leakage occur. To restore them, data is generated through various meters data to predict and detect. However, in the case of leakage if difficult to detect unless direct exploration is performed. Among them, unreported leakage, are not seen visually and account for the most considerable volumes of leakage, which leads to economic loss. Bur direct exploration is limited through on site conditions such as securing professional manpower. In this paper, leakage volumes and location were randomly generated for the WDS, which was assumed to be calibrated, and it was detected through a deep learning model. For abnormal data generation, the leakage was simulated using the emitter coefficient, and leakage detection was successfully performed through the generated abnormal data and normal data.

• Journal of Internet of Things and Convergence
• /
• v.9 no.6
• /
• pp.51-56
• /
• 2023

Hand gesture recognition is an essential technology for the people who have difficulties using spoken language to communicate. Electromyogram (EMG), which is often utilized for hand gesture recognition, is expected to have difficulties in hand gesture recognition because its people's movements varies depending on prior postures, but the study on this subject is rare. In this study, we conducted tests to confirm if the prior postures affect on the accuracy of gesture recognition. Data were recorded from 20 subjects with different prior postures. We achieved average accuracies of 89.6% and 52.65% when the prior states between the training and test data were unique and different, respectively. The accuracy was increased when both prior states were considered, which confirmed the need to consider a variety of prior states in hand gesture recognition with EMG.

• Journal of The Korean Association For Science Education
• /
• v.28 no.6
• /
• pp.603-617
• /
• 2008

Inspired by the socio-cultural perspective on teaching and learning science, we have explored how the teacher and students interact with one another and develop meanings in science classrooms. Data came from four 10th grade science classrooms, and video recordings and verbatim transcripts of the lessons were analyzed. Focus of the analysis was on the participation structures as well as the possibility of developing the space for hybrid meaning making. The participation structures identified were mainly teacher-led, and students rarely took an active stance to initiate an opportunity for generating new meanings. However, some participation structures had the potential to develop a new discursive space in which hybrid meaning can be constructed through negotiation between participants. Implications for future research and more desirable educational practices were discussed based on the result.

• Journal of Korean Home Economics Education Association
• /
• v.18 no.2 s.40
• /
• pp.63-77
• /
• 2006

The Purpose of this study is to provide the basic data for the improvement or the contents or clothing curriculum in the 7th technology home economics of middle school. The standard of satisfaction of students' according to the detail domains and the standard of necessity and practical use and learners' patterns of activity task suggested in textbooks were evaluated. The ninth grade 169 boy students and 336 girl students in the national capital region were participated in this survey. According to the survey results, firstly, a dress domain got the highest relative importance(28.56%) while a clothes material domain took the lowest relative importance(8.07%) among various detail domains. Secondly, the standard of satisfaction according to each detail domain fell below the average. Generally girls' satisfaction for teaching was higher than boys'. Thirdly, a clothes material domain showed the lowest necessity for textbook contents according to detail domain and other domains showed above the average. The necessity for textbook contents appeared high for boy students rather than girl students. In addition, boy and girl students did not have interest in content relevance in textbook. Especially, they could not do well and understand experiments and practices in clothing section. Finally, The degree of utilization of the activity task ill textbooks was very low. Among various activity tasks, the learning by discovering and exploring were more utilized than cooperating learning.