• Journal of Practical Engineering Education
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• v.16 no.3_spc
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• pp.297-308
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• 2024

This study explored the application of the NFT-based Learn-and-Earn model in metaverse vocational education and training. Through expert interviews, Delphi analysis, and AHP analysis, the study evaluated considerations and importance of L&E model operation, NFT technology application, course history and certification management, teaching media copyright management, and platform-related issues. Based on the results, the study suggested the need for performance measurement, infrastructure establishment, institutional arrangement, and ethical issue response when utilizing the L&E model.

• Knowledge Management Research
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• v.23 no.4
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• pp.233-250
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• 2022

This paper aims to verify how the knowledge sharing culture of hotel companies affects psychological ownership awareness and organization citizenship behavior through knowledge sharing of millennials and generation Z employees. It also assumed that two types of knowledge, such as tacit knowledge and explicit knowledge, would have the effect of controlling knowledge sharing culture and knowledge sharing. This paper collected data from 138 employees working in hotels in the metropolitan area. As a result of the empirical analysis, it was found that the knowledge sharing culture of hotel companies influenced knowledge sharing. In addition, it was confirmed that it had a positive effect on psychological ownership and organizational citizenship behavior. In the case of hotel companies, it was found that the tacit knowledge was more effective in inducing knowledge sharing among employees that the explicit knowledge. If a company provides a knowledge-sharing culture using various forms of tacit knowledge strategies, it is expected to increase the organizational citizenship behavior and psychological ownership of MZ generation employees.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.285-301
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• 2023

Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

• Information Systems Review
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• v.25 no.4
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• pp.89-112
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• 2023

In March 2020, as it was declared a COVID-19 pandemic, various quarantine measures were taken. Accordingly, many changes have occurred in the tourism and hospitality industries. In particular, quarantine guidelines, such as the introduction of non-face-to-face services and social distancing, were implemented in the restaurant industry. For decades, research on restaurant attributes has emphasized the importance of three attributes: atmosphere, service quality, and food quality. Nevertheless, to the best of our knowledge, research on restaurant attributes considering the COVID-19 situation is insufficient. To respond to this call, this study attempted an exploratory approach to classify new restaurant attributes based on understanding environmental changes. This study considered 31,115 online reviews registered in Naverplace as an analysis unit, with 475 general restaurants located in Euljiro, Seoul. Further, we attempted to classify restaurant attributes by clustering words within online reviews through TF-IDF and LDA topic modeling techniques. As a result of the analysis, the factors of "prevention of infectious diseases" were derived as new attributes of restaurants in the context of COVID-19 situations, along with the atmosphere, service quality, and food quality. This study is of academic significance by expanding the literature of existing restaurant attributes in that it categorized the three attributes presented by existing restaurant attributes and further presented new attributes. Moreover, the analysis results have led to the formulation of practical recommendations, considering both the operational aspects of restaurants and policy implications.

• Knowledge Management Research
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• v.25 no.2
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• pp.135-153
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• 2024

With the recent emergence of smart tourist cities, premium mobility is being considered an important means of transportation in the tourism. However, there has been insufficient research conducted on the experience of premium mobility among its users. Accordingly, this study used CIT to analyze the components of the user experience of customers who used premium mobility. In order to specifically identify the factors that make up the premium mobility experience, 366 cases of satisfaction and 13 cases of dissatisfaction were collected through a total of 273 online surveys. As a result of the study, based on the customer's experience using premium mobility, CIT was applied to derive 6 categories and 9 sub-factors that constitute the perception of premium mobility. In particular, this study is different from existing studies in that convenience was added as a new category out of the 6 categories, and wide ride comfort and high price were derived as new sub-factors among the 9 sub-factors. Because of this, it has academic significance. Therefore, if scales suitable for quantitative research are developed based on the derived constructs, they could be widely applied to various topics related to premium mobility in the tourism field.

• Journal of The Korean Association of Information Education
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• v.26 no.1
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• pp.65-73
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• 2022

In this study, by using Entry text model learning, educational contents for artificial intelligence education of elementary school students are developed and applied to actual classes. Based on the elementary and secondary artificial intelligence content table, the achievement standards of practical software education and artificial intelligence education will be reconstructed.. Among text, images, and sounds capable of machine learning, "production of emotion recognition programs using text model learning" will be selected as the educational content, which can be easily understood while reducing data preparation time for elementary school students. Entry artificial intelligence is selected as an education platform to develop artificial intelligence education contents that create emotion recognition programs using text model learning and apply them to actual elementary school classes. Based on the contents of this study, As a result of class application, students showed positive responses and interest in the entry AI class. it is suggested that quantitative research on the effectiveness of classes for elementary school students is necessary as a follow-up study.

• Journal of The Korean Association of Information Education
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• v.26 no.2
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• pp.129-140
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• 2022

Our society is undergoing rapid changes due to COVID-19, and in particular, online learning using digital technology is being tried in various forms in the educational field. A change has occurred. However, the limitations of distance learning, such as reduced learning immersion in non-face-to-face educational situations, lack of interaction between teachers and learners, and lower basic academic ability, are constantly being raised, and an appropriate educational strategy is needed to solve these problems. This study focused on the concept of 'Metaverse' based on the interaction between the virtual world and the real world, and tried to verify the effectiveness of educational activities based on it. In detail, we propose an educational framework for realizing flipped learning in the Metaverse Virtual Classroom, and a frame developed by measuring the learning immersion of a single group with a teaching/learning program developed based on this. The effectiveness of the work was verified. When the metaverse platform-based flip learning framework and education program proposed in this study were applied, it was confirmed that learners' immersion in learning was improved.

• Journal of The Korean Association of Information Education
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• v.24 no.6
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• pp.585-596
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• 2020

The purpose of this study is to examine effects of maker education for high-school students on attitude toward software education, creative problem solving, and computational thinking. The program was designed to develop an artificial intelligence robot using mBlock and Arduino and implemented at a maker space. We analyzed 19 students among 20 who participated in the program, the result of paired t-test indicated significant increase in all variables. Also, we performed a multiple regression analysis to investigate predictors of perceived achievement and satisfaction. The finding demonstrated an initial attitude toward software education was found to be the significant predictor of perceived achievement and satisfaction. With the results, we confirmed maker education enhances attitude toward software education, creative problem solving, and computational thinking. Lastly, we discussed the implications and limitations and suggested the direction for future research.

• Journal of the Korean School Mathematics Society
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• v.25 no.4
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• pp.397-422
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• 2022

The purpose of this study was to explore the possibilities of using the Metaverse in mathematics education. The use of the Metaverse started for commercial purposes, and now its use is expanding to all areas, including education. For this study, the researcher analyzed preceding studies related to the Metaverse and the domestic Metaverse platforms for mathematics education in Korea. As a result of the study, the use of Metaverse for mathematics education is still in its beginning stage, and most of the content is limited to mathematical games. However, there are a lot of opportunities and possibilities for mathematics education with Metaverse, and we need to develop the Metaverse platforms specialized for mathematics education with high-quality mathematics content. The researcher suggested to build infrastructure and operate a national level educational Metaverse platform, develop math-specific Metaverse platforms and mathematical content based on field-tested research on the use of the Metaverse platforms. The researcher also emphasized the necessity of teacher education programs for teachers to strengthen the utilization capacity of the Metaverse for mathematics education.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.167-173
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• 2021

The purpose of this study is to discuss the types of algorithms and data categories in AI education for elementary school students. The study surveyed 11 pre-elementary teachers after providing education and practice on various data, artificial intelligence algorithm, and AI education platform for 15 weeks. The categories of data and algorithms considering the elementary school level, and educational tools were presented, and their suitability was analyzed. Through the questionnaire, it was concluded that it is most suitable for the teacher to select and preprocess data in advance according to the purpose of the class, and the classification and prediction algorithms are suitable for elementary AI education. In addition, it was confirmed that Entry is most suitable as an AI educational tool, and materials that explain mathematical knowledge are needed to educate the concept of learning of AI. This study is meaningful in that it specifically presents the categories of algorithms and data with in AI education for elementary school students, and analyzes the need for related mathematics education and appropriate AI educational tools.