• Journal of Korean Elementary Science Education
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• v.25 no.spc5
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• pp.495-506
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• 2007

This study investigated the differences in learning activity preferences according to different thinking styles between gifted and average students. A cluster analysis procedure was performed to classify students on the basis of thinking styles. Two clusters of different thinking styles were deduced: the gifted group with a high level thinking style (cluster 1), and the average group with a low level thinking style (cluster 2). The gifted group (cluster 1) preferred projects, simulations, discussions and game activities to other types of loaming activities. Gifted students and average students also were clustered into each three unique subgroups with respect to levels and patterns in thinking styles, and these subgroups also showed different learning preferences. The clusters of gifted students included the self-regulated learning type (cluster a), cooperative-learning type (cluster b), and the passive-learning type (cluster c). The clusters of average students included the independent learning type (cluster i), no-preference learning type(cluster ii), and the no-motivation & teacher-directed learning type (cluster iii). Theses clusters indicated significant differences not only in thinking styles but also in terms of preferences regarding learning activities. Theses findings are discussed in terms of their educational implications.

• Journal of Korean Elementary Science Education
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• v.33 no.4
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• pp.724-735
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• 2014

The purpose of this study was to confirm correlation between elementary school students' VARK Learning styles test and Scientific Communication Skills through VARK questionnaire (version 7.3) for Youngers and Scientific Communication Skills Test. The subjects were 99 in 6th grade students of an elementary school located in Gyeonggi-do, Korea. The results of this study were as follows: 64% of the students had multiple learning styles, but only 36% of the students preferred a single mode of information presentation. Among students had a single mode preference, the aural ("A") was the highest unimodal preference. Among "V(visual)" mode, "A" mode, "R(read/write)" mode, and "K(kinesthetic)" mode, "A" mode was the commonest learning mode which students had. In Scientific Communication Skills Test, students' overall average was 26.19p [scientific explanation type (11.85p), scientific insistence type (14.34p)]. Girls' scores were higher than boys in scientific explanation type, but not in scientific insistence type. The scores by communication forms were Text (5.67p), Number (6.87p), Table (6.15p), and Picture (7.49p). Girls' scores were higher than boys in Text and Picture forms but not in Number and Table forms. In result of correlation analysis (Spearman's rho) between VARK Learning Styles and the types & forms of Scientific Communication Skills, there were common correlation in "Read/write (R) learning style-Scientific insistence type", "Read/write (R) learning style-Grounds of Scientific insistence", "Read/write (R) learning style-Description of Scientific explanation", and "R learning style-Text form".

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.443-450
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• 2005

In this paper, we propose an intelligent model lot extraction of the web user's preference and present the results of evaluation. For this purpose, we analyze shortcomings of current information retrieval engine being used and reflect preference weights on learner. As it doesn't depend on frequency of each word but intelligently learns patterns of user behavior, the mechanism Provides the appropriate set of results about user's questions. Then, we propose the concept of preference trend and its considerations and present an algorithm for extracting preference with examples. Also, we design an intelligent model for extraction of behavior patterns and propose HTML index and process of intelligent learning for preference decision. Finally, we validate the proposed model by comparing estimated results(after applying the Preference) of document ranking measurement.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.645-654
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• 2019

The purpose of this study was to collect and analyze personal bio data and social network services (SNS) data, derive user preference and user life pattern, and propose intuitive and precise user modeling. This study not only tried to conduct eye tracking experiments using various smart devices to be the ground of the recommendation system considering the attribute of smart devices, but also derived classification preference by analyzing eye tracking data of collected bio data and SNS data. In addition, this study intended to combine and analyze preference of the common classification of the two types of data, derive final preference by each smart device, and based on user life pattern extracted from final preference and collected bio data (amount of activity, sleep), draw the similarity between users using Pearson correlation coefficient. Through derivation of preference considering the attribute of smart devices, it could be found that users would be influenced by smart devices. With user modeling using user behavior pattern, eye tracking, and user preference, this study tried to contribute to the research on the recommendation system that should precisely reflect user tendency.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.716-720
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• 2006

Fuzzy sets are good for abstracting and unifying information using natural language like terms. However, fuzzy sets embody vagueness and users may have different attitude to the vagueness, each user may choose difference one as the best among several fuzzy values. In this paper, we develop a method teaming a user's, preference on fuzzy values and select one which fits to his preference. Users' preferences are modeled with artificial neural networks. We gather learning data from users by asking to choose the best from two fuzzy values in several representative cases of comparing two fuzzy sets. In order to establish tile representative comparing cases, we enumerate more than 600 cases and cluster them into several groups. Neural networks ate trained with the users' answer and the given two fuzzy values in each case. Experiments show that the proposed method produces outputs closet to users' preference than other methods.

• Korea Science and Art Forum
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• v.21
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• pp.437-449
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• 2015

The research aims to verify the effects of preference for science and self-directed learning ability of the science puppet show program that the researcher has developed as a STEAM education model. The results for conducting the survey with the same questionnaire before and after the program targeting the students showed that the science puppet show had effects on increasing the science related assignment performance will of the behavioral will among the three sub-dimensions including emotional respond, value cognition and behavioral will, but there was no effect on overall aspects of science preference. It can be interpreted as reflecting the characteristics of the scientific talents who already have a high level of preference for science. In addition, the three sub-dimensions including the cognitive regulation, motivational regulation and behavioral regulation had effects on the self-directed learning ability. Especially it had great effects on the directed learning ability of cognitive regulation, learning motivation of motivational regulation, tool application of behavioral regulation, and cooperation capacity which were greater for female students than male students. It is judged that the three-staged science puppet show program including the 'content integrating stage' that the students integrate the curriculum contents, 'integrated mission stage' of solving the visualization, auralization and performance missions by themselves, and 'process integration stage' of making the stage piece all together.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.243-248
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• 2018

The most important factor for collaborative learning to be effective is the selection of tools that constitute groups. Grouping is to facilitate collaborative learning, learners form groups based on various characteristics. If a group of students fails to form properly due to the selection of the wrong tools, problems can arise where complaints from students can lead to lectures and the effects of learning. In this paper, we have implemented a group of configuration tools that considered improving learning effects and diagnosing bulling tendency. We have proposed a group composition tool that can take into consideration the learning effect and also diagnose the tendency of the bullring by constructing the group according to the teacher's preference by inputting the class preference and the student's grade through the sociometry survey. We expect that the teacher will be able to grasp the students' friendship in advance and cope with the bulling that can happen in the class, as well as the cooperative learning that can lead the class to improve the learning effect.

• Asia-Pacific Journal of Business
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• v.3 no.1
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• pp.1-9
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• 2012

The Index of Learning Styles (ILS) instrument based on the Felder-Silverman Learning Style Model was used to determine distribution of learning styles of 125 South Korean business students enrolled in a South Korean institution of higher education. Results show that greater proportion of South Korean business students surveyed in this study prefer sensing over intuitive, visual over verbal, reflective over active, and global over sequential learning styles. The majority of business students have a balanced learning style in all four dimensions of the Felder-Silverman model. Among the students that do not have a balanced learning style, students with sensing, visual, reflective, and global learning styles dominate. Gender difference in learning style preference was not statistically significant for any of the four dimensions.

• Journal of Korean Elementary Science Education
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• v.33 no.3
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• pp.427-438
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• 2014

In this study, we explored the factors related with preference for and participation in science-related activities of elementary school students. We developed a questionnaire to measure the characteristics of students such as motivation toward science learning, science aspiration, family science orientation, parental educational level and occupation, and the degrees of preference and participation of science-related activities. The questionnaire was administered to about 400 fourth graders in Seoul. The results revealed that the students with higher motivation toward science learning and/or science aspiration preferred and participated more in most activities. It was also found that parental educational level and occupation did not make an appreciable difference in preference and participation. The students who perceived their parents to be science-oriented, however, preferred and participated more in most activities. These results may offer practical implications for effective uses of both school and out-of-school science activities in elementary science education.

• The Mathematical Education
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• v.55 no.1
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• pp.129-145
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• 2016

The purpose of this study was to research and compare teachers' preferences for 'Great Math Class' by region and gender. The research was conducted on 261 high school math teachers by using non-probability sampling. As the results of the study, regional preference had no statistically significant difference in all four factors of 'Great Math Class' while gender preference had statistically significant difference only in the factor of teaching (methods) and learning methods. Both region and gender had statistically significant positive (+) relationship with preference for all four factors. This implies that it is necessary to consider socio-cultural factors rather than teachers' perception on class for regional differences in academic achievements in mathematics.