• Journal of Digital Convergence
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• v.10 no.5
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• pp.1-6
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• 2012

This study is for using applications on smart devices at school class which designed by professor himself due to nonexistent of applications which related to textbook or course work even though fast developing smart devices and plenty of educational applications are in rapid ubiquitous environment. That is reason to make a learning environments of study course work anywhere at anytime and also make smooth communication between professor and learner with the smart devices advantages of being free of location and time. Also develop the application with the tools which the computer beginner can handle easily and quickly without contracting the work to commercial firms, it will lead to save money and time, be easily updated and modified from place of study, and increase the effectiveness and efficiency of study.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.383-390
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• 2014

In recent years, the convergence of IT and IT sightseeing tour has emerged as a fusion of academic disciplines in the future. Convergence study of social data analysis, raising the heat. Social Network Services (SNS) being utilized in many areas of marketing and to apply the case study is also increasing. This study is based u-smart tourist information systems for mobile learning content design. This is the pattern of things in the template library for things to increase the effectiveness of the learning content to mobile learning content to be converted to a. Design of mobile learning content using u-smart things smart phone app (App) and XMI to go through the design process of utilizing the heat. Future through the design process by implementing a mobile learning content to meet information quality tourist information content to create mobile learning content and learning things that can be content to live it up advantage.

• Journal of Korea Game Society
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• v.15 no.3
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• pp.79-86
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• 2015

Effective feedback plays a key role in education environments to motivate the students and to maintain their flow. However, there usually lacks in providing effective feedbacks in education environments due to an excessive number of students and insufficient class times. The purpose of this paper is to analyze the educatees' response on game like feedback using App. In this paper, Class123 App developed and published by BravePops was used. During one semester, Class123 App had been used in engineering class and the educatees' responses on game like feedbacks using Class123 App are analyzed. Statistical analysis results show that the feedbacks using Class123 App made positive effects to motivate the students. Especially, the positive feedbacks were more effective than the negative feedbacks.

• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.60-66
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• 2019

The purpose of this study was to compare the effect of educational smartphone app with the effect of learning using conventional paper material. We developed an educational app for nursing students to learn how to read blood pressure and how to take a pulse. Evaluated was the effect of the app-based education by measuring the short term memory (right after the education), the long term memory (a week later) and the satisfaction. 25 college nursing students participated for the experiment group using the app-based education and 25 for the control group using paper-based education. We applied for statistical analysis Fisher's exact test and Independent t-test. The satisfaction of the app user's appeared significantly higher than that of the paper material user's (t=2.322, p=0.024). The short term memory score was 0.23 points higher in the experimental group (6.46 points) than in the control group (6.23 points), which was not statistically significant (t =0.422, p =0.675). Similar result came for the long term memory (t=1.006, p=0.320). After adjusting for the effect of a college grade using ANCOVA, the effect on memory was significantly higher in the experiment group. There might be differences in learning ability between the experimental and the control groups.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.58-73
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• 2022

The purpose of this study is to construct a predictable estimation model that reflects the relationship between the variables of mobile app performance and to verify how app reviews affect app performance. In study 1 and 2, the relationship between app performance indicators was derived using correlation analysis and random forest regression estimation of machine learning, and app performance estimation modeling was performed. In study 3, sentiment scores for app reviews were by using sentiment analysis of text mining, and it was found that app review sentiment scores have an effect one lag ahead of the number of daily installations of apps when using multivariate time series analysis. By analyzing the dissatisfaction and needs raised by app performance indicators and reviews of apps, companies can improve their apps in a timely manner and derive the timing and direction of marketing promotions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.455-457
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• 2021

App is used on mobile devices such as smartphones and also has malicious code, which can be divided into normal and malicious depending on the presence or absence of hacking codes. Because there are many kind of malware, it is difficult to detect directly, we propose a method to detect malicious app using AI. Most of the existing methods are to detect malicious app by extracting features from malicious app. However, the number of types have increased exponentially, making it impossible to detect malicious code. Therefore, we would like to propose two more methods besides detecting malicious app by extracting features from most existing malicious app. The first method is to learn normal app to extract normal's features, as opposed to the existing method of learning malicious app and find abnormalities (malicious app). The second one is an 'ensemble technique' that combines the existing method with the first proposal. These two methods need to be studied so that they can be used in future mobile environment.

• The Journal of Korean Association of Computer Education
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• v.18 no.2
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• pp.1-9
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• 2015

Excessive cognitive burdens caused by learning grammar should be reduced to cultivate high-level thinking skills in students through programing education. To this end, various educational programing languages have been developed. In recent years, block-based App Inventor that can used in real life have been introduced. This study intends to suggest an educational environment in which programing can be utilized as a leading problem solving tool by designing and producing an app that can be easily used by students in their real life. In particular, given the developmental phase of elementary school students, specific operational activities are important. For this reason, an App Inventor that can be proposed to enable dynamic interactions with the real world based on various smartphone sensors during the process of programing has significance as an educational programing language for elementary school students. In this regard, this study designed App Inventor programing education for elementary school students, which can be used in their daily life. The results of applying the education in fifth graders showed its positive effects on learning programing. LT collaborative learning where the students cooperated with each other, the theme of learning, which enables the utilization of various smartphone sensors in real life, and the app inventor may have generated and sustained the students' interest and attention.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.211-213
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• 2022

Images in the textbooks influence the learning process. Students often see pictures before reading the text and these pictures can enhance the power of imagination of the students. The findings of some researches show that the images in textbooks can increase students' creativity. However, when learning major subjects, reading a textbook or looking at a picture alone may not be enough to understand the topics and completely realize the concepts. Studies show that viewers remember 95% of a message when watching a video than reading a text. If we can combine textbooks and videos, this teaching method is fantastic. The "TEXT + IMAGE + VIDEO (Animation)" concept could be more beneficial than ordinary ones. We tried to give our solution by using machine learning Image Classification. This paper covers the features, approaches and detailed objectives of our project. For now, we have developed the prototype of this project as a web app and it only works when accessed via smartphone. Once you have accessed the web app through your smartphone, the web app asks for access to use the camera. Suppose you bring your smartphone's camera closer to the picture in the textbook. It will then display the video related to the photo below.

• The Journal of Korean Association of Computer Education
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• v.16 no.4
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• pp.55-62
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• 2013

Most of the APP market today, it is biased in the field of games and entertainment. In contrast, market-share of the educational APP is very low. This phenomenon is due to two major problems. The first is a decrease in the reuse because of the test of simple pattern. The second is difficult to consider user-level range that was learned previously. In this case it is necessary for students to do additional effort. This paper, propose an educational intelligent educational APP to solve the problems described above and shows implementation results. This system analyzes the stored results that have been saved to determine the area of vulnerability. Time-based Re-validation module helps long-term memory of student. The proposed system in this way directly supports self-directed learning. Therefore, the students can be able to relearn weak area autonomously. It results in improved academic achievement.

• Journal of the Korea Institute of Building Construction
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• v.22 no.2
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• pp.219-228
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• 2022

In this study, to improve educational motivation and learning outcomes, a mobile app using game elements was developed, and the effect of its application in rebar work education was analyzed. Using the 4F(Figure out-Focus-Fun design-Finalize) process, which is a game development model, a mobile learning app for rebar work was developed that considers the characteristics of college students familiar with smartphone use, and the app was developed in a manner that utilizes game mechanics such as learning missions and points to stimulate a learner's interest and improve educational motivation. The results show that the proposed app for rebar work is positively evaluated in terms of interface style, perceived usefulness, perceived ease of use, perceived enjoyment, attitude toward using, and intention to use. Therefore, it can be concluded that using the learning game app for rebar work in classes can contribute to improving a learner's performance in various aspects.