• Journal of Korean Home Economics Education Association
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• v.23 no.3
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• pp.139-160
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• 2011

The purpose of this study is twofold: (i) to develop a teaching and learning plan and practical performance assessment tools for the improvement of teenager-parent communication and relationships as well as explore their effects on the communication in the everyday family life; and (ii) to find the underlying problems of teenager- parent communication through conversation analysis and to provide a improved dialogue model. We provided the experimental group with a performance task of communication training between teenagers and their parents in the real family situation while the control group practiced communication skills in a learning situation. However for both classes, before and after performance tasks were equally provided. The experimental group exhibited a longer conversation time with their parents, better communication skills, and higher degrees of relational satisfaction than the control group. Conversation analysis revealed that the experimental group reduced the use of blocking techniques in the teenager-parent conversations more than the control group, and all so raised the frequency of functional communications more than the control group. In both areas of communication in the experimental group was significantly improved, Most notably, a problem-solving case through no-lose conflict resolution methods was effective, succeeding by 70% in the e experimental group and 43.3% in the control group. Parents use blocking techniques like admonition, lecturing, blaming. sarcastic remarking, ordering and so forth, while teenagers use dispute, avoidance, blaming, and teasing in this order. The communication problems during the conversation process, teenagers' evasive and rebellious way of speaking instigates adverse communication responses from parents, so their conversation tends to unfold as ambiguous evasion opposed to: inquiring or evasion by short answers vs. ordering-preaching, or disputing vs. criticizing-making sarcastic, disputing vs. disputing-teaching, and criticizing vs. criticizing.

• Journal of the Korean Geographical Society
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• v.51 no.6
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• pp.893-914
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• 2016

This paper describes the development of an inquiry-based fieldwork program based on Yangdong village where students explore the ways that it can develop in a sustainable way. Important considerations in an inquiry-based fieldwork design include what the key inquiry questions should be, the geographical issues of fieldwork location, the potential roles of mobile technologies, design of learning activities and a final product, and the roles of a teacher. Student fieldwork activities, including mapping land-use changes at the building level, detecting what should be changed or remain the same, and conducting interview with residents to examine their perceptions of overall tourism impacts, are supported by mobile technologies (i.e., the Collector for ArcGIS and the Google Forms). Twenty one high school students participated in a field test of the program in February 2016, which allowed authors to evaluate the program. Students' pre-, in-, and post-fieldwork activities were observed and the data and final products which they gathered and producted were analyzed. The post-program survey indicated that the students deepened and expanded their understanding of Yangdong village and expressed their satisfaction with the program in general. Incorporating mobile technologies into inquiry-based geographical fieldwork can help students involved in collaborative problem solving and creative activities in real world settings and create a shareable multimodal product combining maps, photo, and text.

• Journal of Engineering Education Research
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• v.10 no.3
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• pp.21-37
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• 2007

The purpose of this study is to exploring the direction of woman engineering education by the analysis of learner's recognition. In order to investigate the direction of woman engineering education, the literature reviews were explored in the context of the human resource developmentand in the viewpoint of instructional technology. The survey results such as the learner's experience recognition of engineering education were analyzed and they were discussed by experts in the field of education, instructional technology, and engineering. From the analysis result of 399 students(man:206, woman:193) in P university, there were significant differences with man and woman to the factors of (a) understanding, (b) satisfaction, (c) motivation, (d) learning ability, (e) parents' expectation, (f) pleasure in the study, and (g) expectation grade. This study was suggesting the recommendations of woman engineering education in the viewpoints of cognition, emotion, motivation, environment and instructional strategy. The research results will show the cues of human resource development for women in the field of engineering education.

• 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 Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Korean Journal of Environment and Ecology
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• v.30 no.6
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• pp.1047-1056
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• 2016

This study aims to provide managerial implications for provincial parks through an analysis on visitors' characteristics and motivational factors. The information was collected by surveying 290 visitors. The survey questionnaire consisted of questions regarding visitors' socioeconomic characteristics, characteristics of their travel behavior, visitors' motivation to visit the park, and the degree of satisfaction derived from visiting the park. Results show that most respondents appeared not to collect any information on the park prior to their visit. It was also seen that most visitors do not visit other tourist sites nearby, and are not aware of the Gochang UNESCO biosphere, which indicates that Gochang-gun, which is responsible for park management, needs to make more efforts to promote the park. A factor analysis on the visitors' motivation to visit the park extracted three factors to visit the Seonunsan Provincial Park: 'to hike,' 'to experience and observe nature,' i.e., nature learning field trip and camping, and 'to build and nurture bonding with family and friends.' To examine the effect of these various motivational factors had on the visitors' satisfaction level upon visiting the park, we conducted a multiple regression analysis with the three extracted factors to visit the park and the respondents' socioeconomic characteristics as independent variables, and the degree of recommendation of visiting the park as a dependent variable. The result shows found that, of the three travel factors, only the 'hiking' factor statistically significantly affected the degree of recommendation of visiting the park. This result suggests that the Seonunsan Provincial Park only satisfied hikers and failed to meet the demands for nature experience and observation. It is therefore suggested that the park managers develop new experience-based tourism programs, such as guided tours conducted by professional eco-interpreters.

• Journal of Korean Home Economics Education Association
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• v.19 no.2
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• pp.1-12
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• 2007

This study analyzed the recognition and utilization regarding teacher's guidebook for middle school technology-home economics class in the 7th Educational Curriculum. The data were collected via e-mail to teachers teaching home economics in middle schools. These e-mail addresses were acquired from middle school web pages registered on the Educational Board. The 355 data were analyzed using the SPSS program. The results were as follows: First, teachers recognized highly the necessity of teacher's guidebook. However, as the actual guidebook was not adequately helpful, the overall degree of satisfaction was relatively low. Teachers utilizing guidebook had more positive recognition on teacher's guidebook than teachers who did not. And teachers majored in technology education thought teacher's guidebook more helpful compared with teachers majored in home economics education. Second, teachers referenced teacher's guidebook mostly for field practice guidance. Third, teachers who did not utilize teacher's guidebook used other reference materials such as Internet Web sites and audiovisual materials. They were most commonly used for the reason that the contents were ample and easy to access. Fourth, the followings were suggested to improve teacher's guidebook. The provision of learning contents that can be practically used in class, the various samples of teaching-learning method, the specified methods of planning and criteria for performance assessment, the adequate supplementations regarding textbook contents, and the improvement of the outward layout format of the guidebook.

• International Journal of Contents
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• v.10 no.1
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• pp.54-61
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• 2014

In this paper, we propose a pioneering concept of DPD(Disaster Prevention Design) to realize a securable society in the future. Features of danger in the future society are expected to be diverse, abrupt occurring, large scale, and complicated ways. Due to increment of dangers with their features of uncertainty, interactivity, complexity, and accumulation, human-oriented design concept naturally participates in activities to prevent our society against disasters effectively. We presented DPD is an essential design activity in order to cope with dangers expected in the future societies as well as realize securable environments. DPD is also an integrated design aids including preemptive protections, rapid preparing, recovery, and interactive cooperation. We also expect these activities of DPD is effective for generation of new values in the market, satisfaction of social needs, expansion of design industry, and a novel chance for development in the future society. Throughout this paper, we submit various aspects of DPD concepts including definition, classification, scope, necessity, strategy, influencing elements, process, and its principle. We expect these concepts will be the seed and/or basement of DPD research for the future works. For the direction of study for DPD in the future, we emphasize alarm system for preemptive protection rather than recovery strategy for the damage occurred. We also need to research about progressive prevention techniques and convergence with other areas of design. In order to transfer the concept of product design from facility-oriented mechanism to human-oriented one, we should develop new kinds of city basis facilities, public-sense design concepts referred to social weak-party, e-Learning content design preparing disasters, and virtual simulation design etc. On the other hand, we have to establish laws and regulations to force central and/or provincial governments to have these DPD strategies applying their regional properties. Modern design activities are expanding to UI(user interface) content design area overcoming the conventional design concept of product and/or service. In addition, designers are recognized as art directors or life stylists who will change the human life and create the social value. DPD can be divided into prevention design, preparedness design, response design, and recovery design. Five strategies for successful DPD are Precaution-oriented, Human-oriented, Sense-oriented, Legislation, and Environment Friendly Strategies.

• Journal of Oral Medicine and Pain
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• v.37 no.2
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• pp.93-105
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• 2012

Let me introduce a teaching method to improve practice capacity in dental laboratary work. I applied theories of layers of modeling and reflection constituting cognitive apprenticeship and peer tutoring to my class. At internet uploading a file showing a practice procedure a week before the class of a course, I let students preview it. During the class I demonstrated the practice procedure in front of students. A superior student and an inferior student paired according to the previous practice grade and a feedback between a peer tutor and a peer tutee was activated. Late in the class, a student self-evaluated his own practice result and had a check of a professor. Finally he compared his own practice result with that in the file uploaded at internet and reflected. This teaching method led to improvement in students' satisfaction and efficiency of learning.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.1-14
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• 2014

Both researchers and practitioners are showing an increased interested in interactive exhibition services. Interactive exhibition services are designed to directly respond to visitor responses in real time, so as to fully engage visitors' interest and enhance their satisfaction. In order to install an effective interactive exhibition service, it is essential to adopt intelligent technologies that enable accurate estimation of a visitor's emotional state from responses to exhibited stimulus. Studies undertaken so far have attempted to estimate the human emotional state, most of them doing so by gauging either facial expressions or audio responses. However, the most recent research suggests that, a multimodal approach that uses people's multiple responses simultaneously may lead to better estimation. Given this context, we propose a new multimodal emotional state estimation model that uses various responses including facial expressions, gestures, and movements measured by the Microsoft Kinect Sensor. In order to effectively handle a large amount of sensory data, we propose to use stratified sampling-based MRA (multiple regression analysis) as our estimation method. To validate the usefulness of the proposed model, we collected 602,599 responses and emotional state data with 274 variables from 15 people. When we applied our model to the data set, we found that our model estimated the levels of valence and arousal in the 10~15% error range. Since our proposed model is simple and stable, we expect that it will be applied not only in intelligent exhibition services, but also in other areas such as e-learning and personalized advertising.