• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.387-403
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• 2021

The purpose of this study is to design a community-based career education app for college students. Currently, career education in universities has various problems. First, career education is not systemized, second, satisfaction of participating students is not high, and third, competency-based career education is not conducted. Designing a community-based career education app for college students will solve the problem of lack of college career education instructors and increase the satisfaction of students participating in career education. To this end, core values were derived through the results of demand surveys, literature analysis, and network text analysis for college students, and a prototype of the app was devised according to the design of the rapid prototype. The career education program to be used in the app was designed by dividing online and offline activities so that university students can execute them in units of learning communities. Through the first and second usability evaluation and expert evaluation, the final prototype was designed and the app screen was designed.

• Journal of the Korean School Mathematics Society
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• v.25 no.2
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• pp.195-224
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• 2022

In this study, pre-service mathematics teachers cultivated technology content teaching knowledge (TPACK) in the regular curriculum of the College of Education. The course was designed to enhance pre-service teachers' mathematical communication skills by using an application, which is a mobile mathematics learning content for the development of group creativity of high school students. The educational program to improve mathematics teaching expertise using the application for group creativity expression consists of pre-education, goal setting, planning, teaching at school, and evaluation. In this process, pre-service teachers evaluated technology tools. They also wrote a task dialogue, lesson play, reflective journal, and lesson plan to guide high school students to develop group creativity in both app activities. As a result of the educational program, pre-service mathematics teachers cultivated TPACK and enhanced their mathematical communication skills with high school students to develop group creativity.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.669-678
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• 2023

The aim of this study is to explore 'how is ICT being used in social work education and are they effective?' In order to answer the questions, a content analysis was conducted. Three academic databases, DBPIA, Kiss, EBSCO were searched to look for the articles that investigated ICT and social work education between Jan. 2016 and July, 2022. No study was found from DBPIA and Kiss. Based on inclusion criteria, thirteen articles were selected from EBSCO. Those articles were analyzed following 9 analytic themes: Country, Undergraduate or Graduate Student, Pedagogical Theory, Course Goal, Course Content, Evaluation Method, Outcome, Applied Software or Program. As results of the study, the platforms primarily used for social work education were VR, Second Life, PeopleSIM, course-tailored Applications. In addition, the following was illustrated as effectiveness of ICT in social work education; immersiveness, course satisfaction, improved knowledge, etc. Study limitations and recommendations of future applications were also discussed.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.228-236
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• 2020

As of March 2020, this study divided the applications for young children installed on Android-based smart-phones in Korea into top and bottom groups according to review scores, and selected 30 applications each, conducted content analysis and application evaluation, and looked at differences between groups. Through this, by providing objective information on the smart-phone application for young children, it is intended to help parents and early childhood education professionals select high-quality applications, and to present ideas and directions for developing applications suitable for development to application developers. As a result of application content analysis, only data presentation type, simulation type, and game type were found in all the top and bottom groups as for the application type. There was a difference in order. In the case of app purchase cost, the top group in the review score was evenly distributed from the low price to the high price of 100,000 won or more, while the bottom group had few high-priced applications. On the other hand, as a result of application evaluation, a significant difference was found in the entire evaluation score, including all functional elements and all content elements, between the top and bottom groups of the review score. In the case of detailed sub-factors, significant differences were shown in all factors except 'technicality' of functional elements.

• Journal of Service Research and Studies
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• v.12 no.1
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• pp.36-48
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• 2022

As the use of smartphones has rapidly increased due to the development of digital technology, the expansion of smartphones, and the COVID-19 incident, dependence on smartphones and the Internet is emerging as a serious social problem. As one of the solutions to the smartphone overdependence problem, the government and companies are releasing smartphone overdependence prevention applications. However, research on the effectiveness of smartphone overdependence prevention applications is insufficient. Therefore, this study selects 25 applications serviced in Korea as analysis targets and evaluates smartphone overdependence prevention applications in terms of function and service using the FGI survey method to identify problems and propose improvements. In the function evaluation, the functions of blocking illegal/harmful apps/websites, limiting smartphone usage time, and monitoring smartphone usage status are provided in most applications, so satisfaction scores are also highly evaluated. However, functions such as location check, smombie prevention, and body camphishing prevention served by some applications are evaluated low due to poor performance and poor accuracy. Classified by service provider, government-providing applications need to accurately perform functions and improve convenience of use. Mobile-Carrier-providing applications need to improve connectivity with other carriers and compatibility with other smart devices like smartphone, tablet, etc. Other private enterprise-providing applications need to open AS channels such as customer service centre and chatbot to improve service.

• Information Systems Review
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• v.23 no.1
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• pp.93-113
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• 2021

Service orientation and customer orientation are recognized as important success factors in service companies. However, these constructs are evaluated through self-diagnosis within the service company based on service delivery experience. For this reason, Fintech companies that provide financial services based on non-face-to-face channels such as mobile APP have limitations in evaluating their service orientation and customer orientation. Therefore, in this study, the perceived customer orientation is conceptualized so that service orientation and customer orientation can be evaluated through customer evaluation. In addition, the antecedents and consequences of the perceived customer orientation based on the technology acceptance model were demonstrated. As a result, it was confirmed the mediating effect of perceived customer orientation in the relationship between perceived ease of use and usefulness and customer's continuous use intention and word of mouth intention. This study laid the foundation for the Fintech companies that provide all financial services throughout non-face-to-face to measure their service orientation and customer orientation through customer evaluation and utilize them in establishing service operation strategies.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.35-40
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• 2024

In this paper, we validate the practicality of the OnePIC app implemented in the previous study by analyzing the execution and storage performance. The OnePIC app is a camera app that allows you to get a photo with a desired focus after taking photos focused on various places. To evaluate performance, we analyzed distance focus shooting time and object focus shooting time in detail. The performance evaluation was measured on actual smartphone. Distance focus shooting time for 5 photos was around 0.84 seconds, the object detection time was around 0.19 seconds regardless of the number of objects and object focus shooting time for 5 photos was around 4.84 seconds. When we compared the size of a single All-in-JPEG file that stores multi-focus photos to the size of the JPEG files stored individually, there was no significant benefit in storage space because the All-in-JPEG file size was subtly reduced. However, All-in-JPEG has the great advantage of managing multi-focus photos. Finally, we conclude that the OnePIC app is practical in terms of shooting time, photo storage size, and management.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.835-844
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• 2018

Recently, as the number of smartphone users has been increasing worldwide, various services such as electronic payment, internet use, and financial settlement are being used as a smartphone. In addition, researches for home appliance control and automobile control using smartphone are conducted. As such, smartphone users can enjoy a more convenient life, but by hacking smartphones, tapping texts and conversations on smartphones, tracking location through spy apps, DDoS attacks using smartphones, and malicious apps When a message is received at a specific telephone number when using a micropayment, the corresponding text message is transmitted to a remote server, thereby increasing the risk of leakage of personal information and the like. Therefore, in this paper, we define the risk factors of the smartphone that are caused by the internal and external environmental, physical, contents (apps) of the smartphone through the smartphone that we use in real life, We propose a method to check vulnerability of smartphone security solution such as CC evaluation and the most effective response technique for each risk of smartphone by defining the technique.

• Journal of Korean Library and Information Science Society
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• v.54 no.2
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• pp.23-42
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• 2023

The library tour program is a new type of cultural program that was first introduced and operated by J City, and library tourists travel to specialized libraries in the city according to a set course and experience various experiences. This study aims to build a customized course recommendation model that considers the characteristics of individual participants in addition to the existing fixed group travel format so that more users can enjoy the opportunity to participate in library tours. To this end, the characteristics of library travelers were categorized to establish traveler personas, and library evaluation items and evaluation criteria were established accordingly. We selected 22 libraries targeted by the library travel program and measured library data through actual visits. Based on the collected data, we derived the characteristics of suitable libraries and developed a persona-based library tour course recommendation model using a decision tree algorithm. To demonstrate the feasibility of the proposed recommendation model, we build a mobile application mockup, and conducted user evaluations with actual library users to identify satisfaction and improvements to the developed model.