• Journal of radiological science and technology
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• v.46 no.1
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• pp.53-61
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• 2023

The aim of this study analyzed the important level (IL) and understanding level (UL) including the Borich's need for students preparing of the national examination for radiological technologists at online open chatting room. A total of 254 survey were collected from a total of 1,016 students who used open chatting room from December 13 to December 16, 2022. A general characteristics were the age, gender, curriculum (3 or 4 years), grade and area. The IL, UL, learning satisfaction (LS), learning achievement (LA) and intention to continue using (ICU) were analyzed by using the 5 point Likert scale. There was no significant difference the LS, LA, and ICU according to general characteristics (p>0.05). There was a statistically significant difference a total of sixteen subjects based on the t-test results of the response values from the IL and UL (p<0.05). The total of ten subjects with the highest priority in the Locus for Focus models were the Ultrasonography, Human anatomy, Magnetic resonance imaging, Radiation therapy, Cardiovascular and intervention, Computed tomography, Human physiology, Radiographic imaging, Fluroscopic radiography, and Nuclear medicine) that the Borich's need was also the same as the top 10 ranked subjects. The LS (4.23±0.72), LA (4.18±0.73), and ICU (4.15±0.78) for open chatting room were high. This study identified the subjects most needed by college students by the Borich's need analysis. First, it is necessary to provide intensive education on subjects with high scores that are most needed by college students. Second, it is necessary to improve the teaching method for subjects with low need and low level of understanding.

• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.446-457
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• 2016

The purpose of the study was to understand the various aspects of learning experiences of Korean university students on K-MOOC. Analyses on the major motivation of the enrollment in a certain MOOC class, the actual learning experiences in the class and the perception of the achievement of the class were the three main foci of the current study. The study employed inductive content analysis as a major analysis tool. Reflective journals from 94 students who enrolled in K-MOOC classes were collected and analyzed at the end of the semester. The result of this study indicated that most of students selected the specific K-MOOC classes based on their general interests on the topics the class offered. Other factors such as intellectual curiosity, practical reasons for their study or work and popularity were also influential on the selection of MOOC classes. Watching videos, taking quizzes and taking tests were the three major sources of the students' satisfaction. Most students felt that K-MOOC is technically satisfactory. However, some students reported on simple errors and absence of advanced functions in the platform. Students perceived positively on their academic achievements of obtaining knowledge(remembering and understanding), attitudes (receiving), and skills through K-MOOC. This study ultimately showed a new awareness of learning experiences around K-MOOC from the perspective of the students. Future research is needed to understand the relationships between the students' learning experience and the students' performance in MOOC classes.

• Journal of Industrial Convergence
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• v.19 no.1
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• pp.117-127
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• 2021

The purpose of this study was to identify the relationship between social support, academic self-efficacy, and learning agility on intention of academic dropout among nursing students. Data collection was conducted online surveys from November 9 to 27, 2020. The 363 students were conveniently sampled from the school of nursing in K-do in Korea. The contents of the self-reported questionnaire included social support, academic self-efficacy, learning agility, intention of academic dropout. As a result, The score of each variables were like this: social support 4.32, academic self-efficacy 3.66, learning agility 3.40, intention of academic dropout 2.08. The factors that affecting intention of academic dropout among nursing students are academic self-efficacy, learning agility, satisfaction on major, perceived mental health status, grade in score and grade, which explained 30.4% of the variances. Therefore in order to lower the intention of dropping out of nursing students, it is considered that the development of programs considering individual characteristics and systematic support are necessary.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.367-376
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• 2022

In this study, the user experience was analyzed from the learner's point of view, focusing on the metaverse platform 'Spatial'. SUS(System Usability Scale) was used to evaluate the usability of the metaverse platform 'Spatial' in a college class, and the Magnitude estimation technique was used to evaluate the immersion and satisfaction with the class. In addition, a questionnaire survey was used to collect user experience opinions on the use of 'Spatial' as a teaching tool. Looking at the usability evaluation results of the 'Spatial' system, the students evaluated the usability, immersion, and satisfaction quite positively. Looking at the user experience of metaverse platform 'Spatial', it was found that students highly valued Metaverse as an educational tool that can provide a place for many people to gather and communicate even in a non-face-to-face space. Compared to other online platforms, metaverse has advantages in ease of use, interaction, immersion, and interest. In particular, in addition to keyboard, touch, and display, interaction using the five senses such as voice, motion, and gaze was recognized as a great advantage. On the other hand, it was found that high openness, freedom, and interest factors can both promote learning and inhibit learning. Nevertheless, it is judged that the metaverse platform 'Spatial' can be effectively applied in college classes because it enables various interactions between instructor and learner or between learner and learner.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of KIISE:Software and Applications
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• v.34 no.6
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• pp.539-548
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• 2007

Mobile content adaptation is a technology of effectively representing the contents originally built for the desktop PC on wireless mobile devices. Previous approaches for Web content adaptation are mostly device-dependent. Also, the content transformation to suit to a smaller device is done manually. Furthermore, the same contents are provided to different users regardless of their individual preferences. As a result, the user has difficulty in selecting relevant information from a heavy volume of contents since the context information related to the content is not provided. To resolve these problems, this paper proposes an enhanced method of Web content adaptation for mobile devices. In our system, the process of Web content adaptation consists of 4 stages including block filtering, block title extraction, block content summarization, and personalization through learning. Learning is initiated when the user selects the full content menu from the content summary page. As a result of learning, personalization is realized by showing the information for the relevant block at the top of the content list. A series of experiments are performed to evaluate the content adaptation for a number of Web sites including online newspapers. The results of evaluation are satisfactory, both in block filtering accuracy and in user satisfaction by personalization.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.397-408
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• 2020

This study conducted a focus group interview with 15 college freshman from J college to find out their experiences in non-face-to-face lectures with COVID-19. The contents of the interview were recorded and conducted, and the meaning was analyzed according to the focus group interview procedure through repeated listening. Components were 'Operation of non-face-to-face lectures in unprepared situations', 'Loss of orientation in lectures and departure from learning', 'One way listening', 'The convenience of taking a lectures'. The experience of 'Operating non-face-to-face lectures in unprepared situations' included the start of mixed non-face-to-face lectures, cumbersome and inconvenient online systems, and the demand for tuition refunds. The experience of 'Loss of orientation in lectures and departure from learning' has experienced difficulty in concentrating on lectures, Deficiency in the degree of recognition of learning content, and burden of assignments and exams. The experience of 'One way listening' has experienced lack of interaction between professors and learners and non reflection of liveliness in the field. Finally, participants experienced satisfaction with being able to lectures and repeat lectures at anytime and anywhere they wanted with the convenience of taking lectures. Based on this study, participants called for improvements in the quality lecture contents and interaction between professors and learners, and it is thought that universities will need administrative and financial support and education design and system construction to construct high-quality lecture contents.

• The Journal of Korean Association of Computer Education
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• v.21 no.4
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• pp.1-10
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• 2018

Block programming environment, which is represented by Scratch in elementary and middle school programming education, is suitable for learner's characteristics and cognitive level, and is recommended not only for beginners. Transference to the text programming environment after the block programming is essential for understanding the data processing process, understanding the accuracy and efficiency aspects of algorithms, and creating SW activity. In addition, it is presented step by step in the programming curriculum. In this study, developed WithBlock the online evaluation system for the purpose of transference from a block programming to a text programming environment. The developed system can solve the same algorithm problem in both block and text programming environment, and it can be used for elementary and secondary programming education by automatically scoring the written code and providing immediate feedback. In order to applicable to programming education in elementary and secondary surveyed the usability, learning possibility, interest and satisfaction of WithBlock. The results of the survey showed that it can be used for programming education.

• Journal of Engineering Education Research
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• v.24 no.6
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• pp.3-19
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• 2021

This study aimed to introduce a case study of a basic engineering design course using the ENACT model for fostering social responsibility of engineers, and to investigate the educational effects of the course. Since the ENACT model was designed to encourage STEM college students to pursue responsible problem solving based on their understanding of socioscientific issues, we assumed that it would be beneficial for engineering students to foster their social responsibility as well as their understanding of science/engineering-related issues. A total of 49 engineering students who enrolled in the course participated in the study. Data included students' course artifacts, reflection papers, and responses to survey questionnaires. Results indicated that the students became more aware of nature of science and technology after the program, and began to solve the problems while considering the views of multiple stakeholders. They highly valued the experience of communicating with others as engaging in the civic activities. They also expressed high satisfaction and feeling of achievement on the course learning. We expect the ENACT model to be an effective teaching guideline that fosters the social responsibility of engineering students and furthermore, engineering ethics.

• Journal of the Korean Society of Food Culture
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• v.27 no.6
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• pp.666-676
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• 2012

The purpose of this study was to propose effective marketing communication strategies for overseas Korean restaurants through a multilateral comparison analysis of American, Chinese, and Japanese consumers' attitudes towards communication media and Korean restaurants. The survey was written in English, Chinese, and Japanese, with guideline for surveyors, and conducted using both online and offline methods. Samples were collected from five major cities - Los Angeles, New York, Tokyo, Beijing and Shanghai, which are the foothold for the globalization of Korean food. When it comes to attitudes towards communication media, word-of-mouth showed a high mean value, indicating it as the most useful and reliable media recognized by consumers who visited Korean restaurants. Furthermore, the necessity of recognizing the importance of visual communication in the physical environment of Korean restaurants and specialized websites, featuring restaurants and gourmet food, was observed. Consumers in all three nations chose word-of-mouth as the most useful and reliable media for learning about Korean restaurants. In addition, American consumers highly depended on signage and restaurant exteriors. Chinese consumers highly recognized the usefulness and reliability of offline media, such as newspapers, magazines, and events, while Japanese consumers considered online media, such as gourmet websites, blogs and social networks, as useful and reliable sources. A significantly positive attitude and high value was observed in all who had visited Korean restaurants. American and Japanese consumers had a significantly higher rate of intention to visit Korean restaurants in the future and to tell others about their satisfaction with Korean restaurants. Meanwhile, the average rate of prior preference for Korean restaurants (when choosing restaurants) was the lowest in all three countries. This study is useful for both the Korean government and food enterprises abroad to plan and develop marketing communication strategies properly for overseas Korean restaurants.