• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.05a
• /
• pp.1396-1399
• /
• 2007

컴퓨터의 보급이 보편화 되면서 컴퓨터 보유 가정이 기하급수적으로 증가되고 있다. 이로 인하여 컴퓨터로 할 수 있는 일이 늘어나고, 활용분야 역시 다양해지고 있다. 특히 과거의 교수-학습 방법과는 달리 최근에 많은 분야에서 연구되고 있는 E-러닝, ICT, 컴퓨터 활용, 인터넷 등을 접목하여 학생들의 협동심과 책임감을 요하는 협동학습에 적용하고자 하는 연구가 진행 중이다. 그런데, 협동학습의 집단은 크게 인문계열, 실업계열 고등학생 집단과 중학생 집단으로 분류한다. 따라서 본 논문에서는 컴퓨터를 활용하는 정도와 이용시간 등을 학습에 얼마만큼 도움이 되는지 분석하고, 계열별로 집단을 구분하여 학생들의 집단에서 개인의 적극성과 참여정도에 대한 영향이 집단 전체에 미치는 파급효과를 분석한다. 마지막으로 학업성취에 대한 학생들의 성적차이의 관점을 분석하고, 성별에 따른 학업성취도 차이, 주변 환경에 따른 영향력의 정도, 협동학습의 결과 학업성취도의 변화를 평가한다.

• Journal of Digital Convergence
• /
• v.19 no.10
• /
• pp.295-301
• /
• 2021

Individual mental fatigue not only reduces cognitive ability and work performance, but also becomes a major factor in large and small accidents occurring in daily life. In this paper, a CNN model for EEG-based mental fatigue discrimination was proposed. To this end, EEG in the resting state and task state were collected and applied to the proposed CNN model, and then the model performance was analyzed. All subjects who participated in the experiment were right-handed male students attending university, with and average age of 25.5 years. Spectral analysis was performed on the measured EEG in each state, and the performance of the CNN model was compared and analyzed using the raw EEG, absolute power, and relative power as input data of the CNN model. As a result, the relative power of the occipital lobe position in the alpha band showed the best performance. The model accuracy is 85.6% for training data, 78.5% for validation, and 95.7% for test data. The proposed model can be applied to the development of an automated system for mental fatigue detection.

• Journal of Information Management
• /
• v.38 no.3
• /
• pp.137-160
• /
• 2007

The purpose of this study is to examine the meaning and status of the current service of academic libraries in the aspect of its supporting roles for academic courses. The research methods include an examination of model cases from the U.S.A. and Hong Kong and also an electronic questionnaire survey of 32 academic libraries in Korea(67% response rate). With the result of the research analysis, this study aimed to provide optimal administrative plans in e-learning environment.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.12
• /
• pp.3005-3012
• /
• 2014

Massive Open Online Courses(MOOC), originally started from United States, have recently received a great deal of attention all over the world. MOOC means free online courses that anyone can attend anytime. In Korea, KERIS(Korea Education and Research Information Service) and some universities provide various MOOC services. The purpose of this paper is to present current status and improvement suggestions of MOOC. We first introduce the formal definition and history of MOOC, then discuss current status of MOOC services in Korea and other countries. We finally present improvement suggestions that include induction of active participation for universities, value creation for campus, development of revenue model, providing motivation to students for finishing courses, development of LMS(Learning Management System), securing well-trained lecturers, translation of lecture materials, ensuring quality of authentification system of MOOC services.

• Education of Primary School Mathematics
• /
• v.18 no.3
• /
• pp.217-234
• /
• 2015

Computer technology and internet environment have been adapted to teaching and learning in Korean educational context. However, there are several problematic areas in operating web site for teaching and learning mathematics. This study aims to investigate the operating system, such as designing web site, contents information, and contents connection of NRICH web site that has been operated as a part of 'Millennium Mathematics Project' of Cambridge University since 1997. Based on these categories, this study also gives the implications for how to develop theme-centered contents, accumulation of continuous and long-term data, induction of user's participation, and various cooperation project.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.1
• /
• pp.29-34
• /
• 2021

The real-time video education is used as an effective method of operating classes that replaces face-to-face education of instructors and learners in remote areas. However, the existing video call and video conferences system is mainly used, and this is effective in linguistic education because it focuses on lecture through video, but it is not utilized in other education. In this paper, we propose a design model of real-time video system that can improve the effectiveness of science curriculum and mathematics education by providing the functions that can be utilized during class by improving limitations of image - oriented image education.

• Journal of Korea Society of Industrial Information Systems
• /
• v.29 no.1
• /
• pp.135-144
• /
• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.

• Journal of Convergence for Information Technology
• /
• v.12 no.5
• /
• pp.139-149
• /
• 2022

The purpose of this study is to develop and analyze the effects of an educational program that can cultivate artificial intelligence(AI) convergence education competency for future education and enhance students' understanding of pre-service teachers. For this end, an AI convergence education program using Machine Learning for Kids and Scratch 3 was developed for 15 weeks under the theme of classifying the state of matter. The developed program were treated by K University pre-service teachers who participated voluntarily. As a result, pre-service teachers were able to metaphorically understand the learning process of students through understanding of machine learning training process. In addition, the pre-post t-test result of AI teaching efficacy showed a statistically significant improvement with t=-7.137 (p<.000). Therefore, it is suggested that the AI convergence education program developed in this study can help to increase the understanding of the pre-service teacher's students in an indirect way other than practice teaching, and can contribute to foster AI education competency.

• Journal of The Korean Association of Information Education
• /
• v.18 no.1
• /
• pp.75-87
• /
• 2014

The purpose of this study was to investigate the educational usefulness, problems of smartpad-based instruction in elementary school based on qualitative research. To accomplish the purpose of the study, D elementary school in metropolitan area, two classes of digital textbook model school for seven years, were selected as the classes for observation. Six fourth and fifth graders and their teachers were interviewed and their 10 lessons were used for analyzing teaching and learning activities in smartpad-based instruction. The results of the study, 'Facilitating collaboration and interaction', 'effective use of various resource and SNS', 'improving concentrativeness', 'shortening waiting time' were identified as main educational usefulness. 'Lack of learning supporting tools', 'focusing on function rather than learning contents', 'low learning effectiveness', 'interference of flow' were presented as problems in using smartpad in classroom. Finally, some practical tasks for effective application of smartpad-based instruction were recommended.

• Journal of Navigation and Port Research
• /
• v.48 no.1
• /
• pp.27-33
• /
• 2024

Following the COVID-19 pandemic, congestion within container terminals has led to a significant increase in waiting time and turnaround time for external trucks, resulting in a severe inefficiency in gate-in and gate-out operations. In response, port authorities have implemented a Vehicle Booking System (VBS) for external trucks. It is currently in a pilot operation. However, due to issues such as information sharing among stakeholders and lukewarm participation from container transport entities, its improvement effects are not pronounced. Therefore, this study proposed a deep learning-based predictive model for external trucks turnaround time as a foundational dataset for addressing problems of waiting time for external trucks' turnaround time. We experimented with the presented predictive model using actual operational data from a container terminal, verifying its predictive accuracy by comparing it with real data. Results confirmed that the proposed predictive model exhibited a high level of accuracy in its predictions.