• Journal of Practical Engineering Education
• /
• v.13 no.2
• /
• pp.243-249
• /
• 2021

It has been determined the 6 core competencies of our university students. Among them, it was judged that the student's convergence thinking ability and self-development ability were insufficient. To enforce the two insufficient abilities, an engineering-related major collage course was newly established in the form of an intensive coursework. The course was conducted as a shared curriculum between division/departments. For each of the first and second semesters in the 2020, 54 students from two completion groups (Department of Electrical and Electronic Control Engineering; 26, Optical Engineering; 28) were the subjects of the survey, the survey results of 20 common questions were comprehensively analyzed. As the result, more than 75% of the respondents were positive about free online learning at any time and place. And if additional interactive activities and team teaching method are reinforced during recorded audio and video contents learning material, It is confirmed that the attempted intensive course can maximize the learning effect.

• The Mathematical Education
• /
• v.60 no.1
• /
• pp.61-76
• /
• 2021

The purpose of this study is to analyze the errors and difficulties which pre-service secondary teachers shows during the task modification in consideration of the cognitive demand and to provide significant implications to the pre-service teacher education program related to the modification of the mathematical tasks. In the pursuit of this purpose, tasks were selected from perpendicular bisector units and 24 pre-service teachers were asked to modify the tasks to higher and lower level tasks. After the modification activities, opportunities for reflection and modification were provided. The findings from analysis are as follows. Pre-service teachers had a difficulty to distinguish between PNC tasks and PWC tasks. Also, We identified the interference phenomena that pre-service teachers depended on the apparent elements of the task. Pre-service teachers showed a tendency to overlook the learning objectives and learning hierarchy during the task modification, and to focus on some types of task modification. However, pre-service teachers were able to have meaningful learning opportunities and extend the category of tools to technology including Geogebra through self-reflection and correction activities on task modification. The above results were summed up and we presented the implications to the task modification program in the pre-service secondary teacher education.

• Journal of Digital Convergence
• /
• v.19 no.6
• /
• pp.213-223
• /
• 2021

In this study, a smartphone utilization system was designed to explore ways to use smartphones owned by more than 95% of Korean teenagers in school classes. First, the necessary functions were selected based on the factors related to adolescents and the factors of distraction, dependence, motivation, and cooperation in the preceding studies on the use of smartphone classes, and then three versions of the application were composed according to the educational roles of students, teachers, and parents. By using these applications, students can learn self-study, motivate learning, and actively interact, teachers can be more closely with students and facilitate lessons while giving detailed feedback, and parents can check the student's safe learning using smartphones. It is hoped that this measure will help to increase the educational effect by activating the use of smartphones in school classes.

• Journal of the Korean Institute of Gas
• /
• v.24 no.6
• /
• pp.91-97
• /
• 2020

Lithium-ion batteries (LIBs) have a longer lifespan, higher energy density, and lower self-discharge rates than other batteries, therefore, they are preferred as an Energy Storage System (ESS). However, during years 2017-2019, 28 ESS fire accidents occurred in Korea, and accurate capacity estimation of LIB is essential to ensure safety and reliability during operations. In this study, data-driven modeling that predicts capacity changes according to the charging cycle of LIB was conducted, and developed models were compared their performance for the selection of the optimal machine learning model, which includes the Decision Tree, Ensemble Learning Method, Support Vector Regression, and Gaussian Process Regression (GPR). For model training, lithium battery test data provided by NASA was used, and GPR showed the best prediction performance. Based on this study, we will develop an enhanced LIB capacity prediction and remaining useful life estimation model through additional data training, and improve the performance of anomaly detection and monitoring during operations, enabling safe and stable ESS operations.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.32 no.1
• /
• pp.267-293
• /
• 2021

This study is aimed at analyzing the achievement criteria of cross-curricular Learning themes that can be linked to curriculums, and developing and applying the career reading programs focusing on the school library. For these purposes, first, a class model was designed in connection with reading education programs through cross-curricular Learning themes of 2015 revised curriculum. Second, the career reading classes in the areas of self-understanding, career exploration and career design have been held through a career reading class model for 137 middle school students in 5 classes for one semester. Third, the data to evaluate the career reading for the analysis of the study was constructed, and the qualitative study was conducted through of anecdotal records, multilateral observation on checklists and the analysis of action research. Lastly but not least, the materials regarding the list of books focusing on the career reading storytelling and the career mentor in a type of interests were presented, and the career reading education activities at the school field were suggested.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.3
• /
• pp.93-102
• /
• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• Human Ecology Research
• /
• v.61 no.1
• /
• pp.15-28
• /
• 2023

The aim of this study was to develop, implement, and evaluate the use of Artificial Intelligence in the prevention of violence among middle-school students. The sample for this study consisted of 20 first-year middle-school students who participated in theme selection activities in a free semester program as part of their home economics studies. The data for the study consisted of nine class observation logs, four group activity outputs, 30 class results, an online survey, and in-depth interviews with three students. A program called "R.U.OK" was developed by setting problematic situation for school violence prevention linked to the contents of the Home Economics Education(HEE) curriculum. After the program was implemented, the survey on the students' class satisfaction content elements, with AI-based learning activities and PBL and interest, displayed high points, with an average of 4.0 or higher. Our qualitative analysis produced four significant results. First, students' concerns about school violence had increased and they showed a change in attitude, having more empathy with friends and more interest in their surroundings. Second, digital and AI literacy had improved, and students' interest in digital media learning had increased. Third, there had been an improvement in problem-solving ability in terms of being able to think more critically and independently. Fourth, the results also demonstrated that there had been a positive effect on self-direction and an improved capacity for teamwork. This study was significant in demonstrating the effectiveness of a program for the prevention of school violence based on the use of digital technology in the educational environment.

• Korean Journal of Culture and Social Issue
• /
• v.14 no.1_spc
• /
• pp.47-62
• /
• 2008

The 'education panic' is one of the most phenomenal social issue in the current Korean society. The explanations of it until now, however, are rather superficial in a way that they only describe apparent facts and its seriousness, rendering further examination of the psychological motivation of parents who are the protagonist of education panic necessary. With 548 elementary, middle, and highschool students and their parents, the present study has investigated the impact of parents' past experience of 'han', regret, and learning effect regarding education on their parenting style as well as on their children's academic experience. The result revealed that parents' learning effect was related with more affective/autonomous parenting style and reasonable expectation for their children's educational career. On the contrary, parents' 'han' and regret indicated relationship with hostile and controlling parenting style and also with blind intention toward their children's educational career. The negative emotions also seemed to increase their children's academic stress, and lower academic self-efficacy. Such results suggest that the extraordinary education panic in Korea is more than a simple quantitative matter of intensity. The psychological basis and motivation of the people included, a much more quantitative information, should be taken into account.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.6
• /
• pp.919-928
• /
• 2023

Deep learning technology is used in various fields such as self-driving cars, image creation, and virtual voice implementation, and deep learning accelerators have been developed for high-speed operation in hardware devices. However, several side channel attacks that recover secret information inside the accelerator using side-channel information generated when the deep learning accelerator operates have been recently researched. In this paper, we implemented a DNN(Deep Neural Network)-based MNIST digit classifier on a microprocessor and attempted a correlation power analysis attack to confirm that the weights of deep learning accelerator could be sufficiently recovered. In addition, to counter these power analysis attacks, we proposed a Node-CUT shuffling method that applies the principle of misalignment at the time of power measurement. It was confirmed through experiments that the proposed countermeasure can effectively defend against side-channel attacks, and that the additional calculation amount is reduced by more than 1/3 compared to using the Fisher-Yates shuffling method.

• Korean Medical Education Review
• /
• v.25 no.3
• /
• pp.212-228
• /
• 2023

Systems thinking, a linking domain of health systems science (HSS), is an approach that investigates specific problems from a holistic perspective. It supports improving patients' health, fulfilling their health needs, and anticipating issues that threaten patient safety within the healthcare system. It also helps solve problems through critical thinking and ref lection. This study aimed to develop an curriculum on systems thinking, explore the effectiveness of the course, and investigate the applicability of HSS education at individual universities. In this study, the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model was utilized to design, develop, implement, and evaluate an elective course on systems thinking. In the design process, learning outcomes and goals were developed, and educational content, teaching-learning methods, and student evaluation methods were linked. In the development process, class materials and evaluation materials were prepared. In the implementation process, the course was implemented, and the evaluation process analyzed the results of learning performance and curriculum assessments. The evaluation found the following results. First, the students in the study realized the importance of systems thinking and experienced the need for systems thinking through non-medical and medical situations. Second, the students were very satisfied with the learning activities in the course (mean=4.84), and the results of the self-competence evaluation, conducted before and after the course, also showed a significant improvement. This study confirmed the effectiveness of the elective course, and its results can serve as a reference for developing an HSS curriculum.