• Journal of Digital Convergence
• /
• v.16 no.3
• /
• pp.27-35
• /
• 2018

The purpose of this study is to design smart learning based extracurricular program of the university and to analyze the effect of core competencies. This program was formed by 10 teams with S and K University in Seoul, and run a daily camp format to use smart devices and apps. As a result, the participating students, communication skill, self-directed and creativity increased significantly. In addition, the educational effects of this program was positive changes in the areas of 'communication', 'self-directed', 'cooperative learning', 'problem solving' in the focus group interview. And the students responded that the use of smart devices and apps help to immerse in the program and increase their interest. The purpose of this study is to suggest new models and implications for the extracurricular program. In the future, we hope to develop the various smart learning based extracurricular programs for enhancing the competencies.

• Journal of Digital Convergence
• /
• v.16 no.7
• /
• pp.213-222
• /
• 2018

The purpose of the study is to promote the expansion of educational environment and students' competence through the application of smart learning. In G University in 2017, 118 freshmen in the department of Chemical-bio engineering who were taking Calculus I class were divided into 2 groups of experimental and control group. The study analyzed the effect of the various learning experience using educational technology and the interaction in the class through SNS on students' visual understanding and academic achievement. The result shows that the students' academic achievement and satisfaction in the experimental group were higher than those in the control group. This verifies the potential of smart learning in the field of mathematics in the tertiary level and suggests strategies for high quality smart learning.

• The Journal of the Convergence on Culture Technology
• /
• v.6 no.4
• /
• pp.797-802
• /
• 2020

Over the past few years, smart devices, including smartphones, have been continuously required by users based on portability. The performance is improving. Ubiquitous computing environment and sensor network are also improved. Due to various network connection technologies, mobile terminals are widely used. Smart terminals need technology to make energy monitoring more detailed for more stable operation during use. The smart terminal which is light in small size generates the power shortage problem due to the various multimedia task among the terminal operation. Various estimation hardwares have been developed to prevent such situation in advance and to operate stable terminals. However, the method and performance of estimating the remaining amount are not relatively good. In this paper, we propose a method for estimating the remaining amount of smart terminals. The Capacity Estimation of lithium ion cells for stable operation was estimated based on machine learning. Learning the characteristics of lithium ion cells in use, not the existing hardware estimation method, through a map learning algorithm using machine learning technique The optimized results are estimated and applied.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.3
• /
• pp.7-14
• /
• 2021

The emergence of the automated smart grid has become an essential device for responding to these problems and is bringing progress toward a smart grid-based society. Smart grid is a new paradigm that enables two-way communication between electricity suppliers and consumers. Smart grids have emerged due to engineers' initiatives to make the power grid more stable, reliable, efficient and safe. Smart grids create opportunities for electricity consumers to play a greater role in electricity use and motivate them to use electricity wisely and efficiently. Therefore, this study focuses on power demand management through machine learning. In relation to demand forecasting using machine learning, various machine learning models are currently introduced and applied, and a systematic approach is required. In particular, the GP learning model has advantages over other learning models in terms of general consumption prediction and data visualization, but is strongly influenced by data independence when it comes to prediction of smart meter data.

• Journal of Korean Elementary Science Education
• /
• v.37 no.1
• /
• pp.66-79
• /
• 2018

The purpose of this study is to explore how pre-service elementary teachers perceive and use smart learning environments. For this purpose, 23 pre-service elementary teachers who took theory and practice in a science education course were asked to develop lesson materials using smart tools and make a self-report questionnaire. These data were categorized in an instructional, exploratory, and interactive approach, depending on how they guided students to access knowledge and information. As a result of the study, pre-service teachers perceived the smart tools as the exploratory and interactive learning tools to be used for students to actively search for and interact with data and knowledge. But in developing lesson materials, they usually used the smart tools for resource sharing and communication in the instructional manner. In conclusion, the gap between their perception of smart tools and lesson materials, and the educational implications will be discussed.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.8
• /
• pp.5232-5239
• /
• 2015

The purpose of this study is to examine university student's awareness and utilization plan of Smart Learning of the university education. For this purpose, a needs analysis is performed through a survey of 345 university students. Through the survey, first, students of media devices, including the average daily usage time of four hours at the most common smart devices, the intended use was used SNS, games and entertainment, datebook, and more. Second, the benefits of the smart learning, which students learn to recognize the challenges and reducing the burden most common obstacle was the difficulty in immersion classes. Third, the demand for university education smart learning, the most common opinion about the classroom building. On the basis of the above research findings, the utilization plans are proposed.

• Journal of Internet Computing and Services
• /
• v.16 no.6
• /
• pp.123-131
• /
• 2015

Recently the development of ICT has a big impact on education field, and diffusion of smart devices has brought new education paradigm. Since people has an opportunity to use various contents anytime and communicate in an interactive way, the method of learning has changing. In 2011, Korean government has established the smart education promotion plan to be a first mover in the paradigm shift from e-learning to smart learning. Especially, government aimed to improve the quality of learning materials and method in public schools, and also to decrease the high expenditure on private education. However, the achievement of smart education policy has not emerged yet, and the refinement of smart learning policy and strategy is essential at this moment. Therefore, the purpose of this study is to propose the successful strategies for smart learning in public education. First, this study explores the status of public education and smart learning environment in Korea. Then, it derives the key success factors through SWOT(Strength, Weakness, Opportunity, Threat) analysis, and suggests strategic priorities through AHP(Analytic Hierarchy Priority) method. The interview and survey were conducted with total 20 teachers, who works in public schools. As a results, focusing on weakness-threat(WT) strategy is the most prior goal for public education, to activate the smart learning. As sub-factors, promoting the education programs for teachers($W_2$), which is still a weakness, appeared as the most important factor to be improved. The second sub-factor with high priority was an efficient optimizing the capability of new learning method($S_4$), which is a strength of systematic public education environment. The third sub-factor with high priority was the extension of limited government support($T_4$), which could be a threat to other public schools with no financial support. In other words, the results implicate that government institution factors should be considered with high priority to make invisible achievement in smart learning. This study is significant as an initial approach with strategic perspective for public education. While the limitation of this study is that survey and interview were conducted with only teachers. Accordingly, the future study needs to be analyzed in effectiveness and feasibility, by considering perspectives from field experts and policy makers.

• Smart Media Journal
• /
• v.8 no.1
• /
• pp.74-81
• /
• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.6
• /
• pp.631-636
• /
• 2019

In recently, various kinds of services utilizing the location information of the user's smart phone have appeared. Based on this trend, we designed a new type of learning assistant system that utilizes geofencing technology, which is a field of location information technology. This system identifies the location of the classroom using the location information of learner's the smart phone and automatically provides the necessary learning contents to the learner's smart phone when the learner enters the classroom set as the virtual fence area while carrying the smart phone respectively. Our system provides learning contents in a form similar to the form of a message or a mobile coupon and learners are used to such mobile service environments very much. So the use of learning contents provided by our system is expected to help improve the learning effect of learners.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.10a
• /
• pp.960-963
• /
• 2013

By the rapid development ICTs, education is entering into a smart learning. Learners are put down the paper book, are learning by using a various smart devices, and at this moment emerged that learning system each of which contains numerous platforms. Platform-specific systems require a lot of time and money to applicable to heterogeneous platforms, and This phenomenon is exacerbated if system has a lot of learning contents. Learning system that supports cross-platform is needed for reduce the unnecessary waste of resources and provide effective learning content. In order to achieve this, the research must be preceded by a database model that numerous of existing learning content can be integrated without any unnecessary redundant. In this paper, suggests Ontology-based metadata model that can be integrate existing learning content as an alternative to database, and through this, Design and Implementation of smart learning system that support Heterogeneous platforms.