• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

• Journal of the Korean Society for information Management
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• v.40 no.3
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• pp.245-271
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• 2023

The purpose of this study was to assess the perception of e-book subscription services among the digitally native generation in their twenties, who have a high e-book usage rate. This study employed a mixed-methods approach, combining survey responses and usability testing. It aimed to assess the awareness and usage of e-book subscription services among university students in their twenties, a demographic known for their high utilization of electronic devices and e-books. The survey was conducted among 202 university students, and the responses were categorized and examined based on whether they were users or non-users. As a result of the survey, I found there is different awareness of e-book between users and non-users, on the other hand, convenience and portability are the strong point of e-books for users and non-users commonly also. Usability testing was performed on a group of 10 university students in their twenties who had not previously used the 'Millies Library' application, which is renowned as the most widely-used e-book platform. Following the experiment, participants expressed positive feedback regarding various optional features, convenience, design, and cost-effectiveness. However, they also had negative reactions concerning touch errors, malfunctions, functional practicality, a lack of interest, system issues, and the absence of a library.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.101-106
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• 2023

In this busy world actually stress is continuously grow up in research and monitoring social websites. The social interaction is a process by which people act and react in relation with each other like play, fight, dance we can find social interactions. In this we find social structure means maintain the relationships among peoples and group of peoples. Its a limit and depends on its behavior. Because relationships established on expectations of every one involve depending on social network. There is lot of difference between emotional pain and physical pain. When you feel stress on physical body we all feel with tensions, stress on physical consequences, physical effects on our health. When we work on social network websites, developments or any research related information retrieving etc. our brain is going into stress. Actually by social network interactions like watching movies, online shopping, online marketing, online business here we observe sentiment analysis of movie reviews and feedback of customers either positive/negative. In movies there we can observe peoples reaction with each other it depends on actions in film like fights, dances, dialogues, content. Here we can analysis of stress on brain different actions of movie reviews. All these movie review analysis and stress on brain can calculated by machine learning techniques. Actually in target oriented business, the persons who are working in marketing always their brain in stress condition their emotional conditions are different at different times. In this paper how does brain deal with stress management. In software industries when developers are work at home, connected with clients in online work they gone under stress. And their emotional levels and stress levels always changes regarding work communication. In this paper we represent emotional intelligence with stress based analysis using machine learning techniques in social networks. It is ability of the person to be aware on your own emotions or feeling as well as feelings or emotions of the others use this awareness to manage self and your relationships. social interactions is not only about you its about every one can interacting and their expectations too. It about maintaining performance. Performance is sociological understanding how people can interact and a key to know analysis of social interactions. It is always to maintain successful interactions and inline expectations. That is to satisfy the audience. So people careful to control all of these and maintain impression management.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.25-32
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• 2022

The purpose of this study was conducted to develop adult distance literacy education program and verify its effects. The program was developed through the examination on factors affecting online literacy education and necessary analysis and feedback. Pre- and post-tests analyzing the effects of distance literacy education measuring academic understanding factor, learner satisfaction and satisfactory levels on the academic were administered to 49 adult literacy learners before and after a distance literacy education course. Also, this paper try to explore learners who participated in distance literacy education experience, change and that meaning. The results of the content analysis on the program are summarized as follows. First, there were statistically significant differences regarding academic understanding factor, learner satisfaction and perceived learning outcome satisfaction variables since distance literacy education program which is based on ARCS model start. In addition, learners were satisfied with replaying the learning videos several times, and the improved ability to use smart devices. But they expressed regrets about not being able to go to school and the difficulty of using the devices. It means that distance literacy education based on the ARCS model draw a positive learning conclusion. On the basis of these results, suggestions for further research were discussed.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.9
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• pp.429-442
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• 2017

This study was performed to investigate and analyze users' needs for m-health based prevention and intervention programs that are intended to improve the awareness of metabolic syndrome and promote health behaviors of college students. A questionnaire survey was conducted to 200 college students of 2 university in D city. Data were analyzed using descriptive statistics, t-tests, chi-square test with the SPSS Version 20.0. The result showed that users wanted customization of prescriptions and accurate measurement of health applications, and provided a positive feedback on information exchange between those who manage their health. The most preferred content was proper exercise methods, and the preferred gamification factors were goal-setting, compensation, and competition. The optimal price for wearable devices was between 10,000 to 50,000 won, and calorie consumption function was also preferred. Although users with experiences of wearable devices and health apps had a higher knowledge score pertaining to metabolic syndrome, there was no significant difference in the overall score. Concerning the health behaviors associated with lifestyles, individuals without the experiences of wearable devices and health apps showed a remarkably lower score. The research has a significance that it investigated and analyzed the contents needed for the development of effective moblie health based prevention and intervention programs targeting the population in their early adulthood. Therefore, based on the findings, we propose a rich and concrete follow-up study on the needs and characteristics of different user types by collecting a population with experiences of wearable devices, and a development of differentiated mobile health based prevention and intervention programs.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.687-692
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• 2023

We analyze the accuracy of emotion analysis of natural language processing deep learning model and propose to use it for emotional content development. After looking at the outline of the GPT-3 model, about 6,000 pieces of dialogue data provided by Aihub were input to 9 emotion categories: 'joy', 'sadness', 'fear', 'anger', 'disgust', and 'surprise'. ', 'interest', 'boredom', and 'pain'. Performance evaluation was conducted using the evaluation indices of accuracy, precision, recall, and F1-score, which are evaluation methods for natural language processing models. As a result of the emotion analysis, the accuracy was over 91%, and in the case of precision, 'fear' and 'pain' showed low values. In the case of reproducibility, a low value was shown in negative emotions, and in the case of 'disgust' in particular, an error appeared due to the lack of data. In the case of previous studies, emotion analysis was mainly used only for polarity analysis divided into positive, negative, and neutral, and there was a limitation in that it was used only in the feedback stage due to its nature. We expand emotion analysis into 9 categories and suggest its use in the development of emotional content considering it from the planning stage. It is expected that more accurate results can be obtained if emotion analysis is performed by additionally collecting more diverse daily conversations through follow-up research.

• The Mathematical Education
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• v.62 no.1
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• pp.57-78
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• 2023

Students' engagement in lessons not only determines the direction and result of the lessons, but also affects academic achievement and continuity of follow-up learning. In order to provide implications related to teaching strategies for encouraging students' engagement in elementary mathematics lessons, this study implemented lessons for middle-low achieving fifth graders using open-ended tasks and analyzed characteristics of students' engagement in the light of the framework descripors developed based on previous research. As a result of the analysis, the students showed behavioral engagement in voluntarily answering teacher's questions or enduring difficulties and performing tasks until the end, emotional engagement in actively expressing their pleasure by clapping, standing up and the feelings with regard to the topics of lessons and the tasks, cognitive engagement in using real-life examples or their prior knowledge to solve the tasks, and social engagement in helping friends, telling their ideas to others and asking for friends' opinions to create collaborative ideas. This result suggested that lessons using open-ended tasks could encourage elementary students' engagement. In addition, this research presented the potential significance of teacher's support and positive feedback to students' responses, teaching methods of group activities and discussions, strategies of presenting tasks such as the board game while implementing the lessons using open-ended tasks.

• 한국노년학
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• v.32 no.2
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• pp.559-576
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• 2012

This research aims to address the effect of Guided Autobiography(GAB) on ego-integrity, depression and life-satisfaction in the elderly and to investigate psychological changes and experiences on the senior subject. 20 subjects participated weekly autobiography writing sessions in a senior academy in the S city for 13 weeks. In this research, we carried out examination on ego-integrity, depression test, and life-satisfaction survey were performed before and after the writing sessions for a quantitative analysis, which was later investigated through a 'corresponding sample T-test'. Based on the results of the above mentioned tests, the qualitative analysis was conducted through an individual sessions with 5 selected participants. The results of this research are summarized as following. First, ego-integrity showed satisfactorily meaningful difference between pre- and post-GAB writing. The participants recollected the past repent and revisited unresolved issues in their lives. The subjects were able to accept these past misdemeanors and appreciate their lives. GAB indeed helped improving ego-integrity. Second, the hypothesis that GAB writing will help decrease depression was accepted. 2-page weekly writing assignments enabled the participants think of joyful moments in their past, and showed decrease the symptoms of depression. Third, this study revealed that GAB writing improved life- satisfaction. The participants learned to express gratitude and peace in their mind. The happy feeling and optimistic thoughts enhanced their satisfaction of life in turn. In addition, it turned out that the effects of GAB were more drastic in group sessions than in individual writings. Interpersonal interactions in group sessions encouraged the exchange of positive feedback, thereby helping them reflect themselves positively.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.44-53
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• 2022

The purpose of this study is to plan and develop contents for training social skills using robots for elementary school students. Seven functions (guiding activity, providing reinforcement, guiding students behavior, team setting, presenting team order, timer setting, and checking scores) were developed by analyzing functions that robots can take charge of in the training contents. A total of 8 sessions of social skills training contents were developed by selecting social skills required for academic achievement and social interaction of elementary school students. The lesson consisted of providing positive and negative examples, modeling, role-playing, providing feedback on performance, and encouraging generalization stages using effective strategies for acquiring social skills. After developing social skills training contents using robots for elementary school students, so-called Friendly Friends (FF), a satisfaction survey was conducted on the field application of contents and participating students and teachers to examine the acceptance pattern. As a result, it was found that the participating students and teachers were satisfied with the contents. Finally, the meaning and the expected effects of the 'FF (Friendly Friends)' contents were discussed, and also, the matters to be considered when developing social skills training contents using robots in the future were suggested.

• Science of Emotion and Sensibility
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• v.27 no.2
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• pp.69-80
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• 2024

The COVID-19 pandemic highlighted the importance of remote education, yet the adoption rate of AI in the educational sector remains relatively low, and studies into learners' familiarity with using AI learning robots are scarce. In response, this study analyzes the factors influencing users' familiarity with AI learning robots in a smart learning environment tailored to the untact era. To this end, social big data analysis was used to examine changes in public perception and the frequency of mentions of smart learning and AI learning robots. The results showed that positive perceptions of smart learning significantly outweigh negative ones, reflecting the convenience and improved accessibility that technology brings to education. However, there is also a considerable negative perception attached to smartphone use, which is interpreted as reflecting concerns that smartphones may disrupt learning and bring other negative aspects of technology dependence. These results indicate mixed social concerns and expectations regarding the educational use of smart learning and AI technologies. The effective introduction and use of AI learning robots, especially in smart learning environments, necessitate considering these social perceptions. This study provides foundational data for the effective implementation and use of AI learning robots in smart learning environments and suggests the need for approaches that primarily consider users' familiarity and social perceptions in the development of educational technologies.