• The Journal of Korean Philosophical History
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• no.38
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• pp.63-96
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• 2013

$L{\ddot{u}}Zuqian$(呂祖謙) was one of the famous philosophers during the Southern Song period, and is called one of DongNamSanXian(東南三賢) together with ZhuXi(朱熹) and ZhangShi(張?). With his profound knowledge transmitted and uphold by JiaXue(家學), $L{\ddot{u}}Zuqian$(呂祖謙) established his learning system, interacting with scholars of those days. Principally, $L{\ddot{u}}Zuqian$(呂祖謙)'s XinLun(心論) was based on Mengzi(孟子)' theory of LiangXin(良心) and BenXin(本心). $L{\ddot{u}}Zuqian$(呂祖謙) explained the meaning of such a conscience through ChuXin(初心) and Inner NeiXin(內心). According to $L{\ddot{u}}Zuqian$(呂祖謙), ChuXin(初心) arouses when one encounters external things, and this one's intention enables us to make the right judgments over the outside objects. NeiXin(內心) means LiangXin(良心) and BenXin(本心) that recovered the ability of moral awareness. The important significances of $L{\ddot{u}}Zuqian$(呂祖謙)'s XinLun(心論) are XinWai WuDao(心外無道), and XinWaiWuTian(心外無天). Through these, $L{\ddot{u}}Zuqian$(呂祖謙) emphasized that Tian(天), Dao(道), and Li(理) are one. $L{\ddot{u}}Zuqian$(呂祖謙) arranged a meeting of EHuSi(鵝湖寺), and exerted efforts to negotiate the academic differences between ZhuXi(朱熹) and LuJiuyuan(陸九淵). However, compared with LuJiuyuan(陸九淵) who asserted FaMingBenXin(發明本心), $L{\ddot{u}}Zuqian$(呂祖謙) put the emphasis on DaoWenXue(道問學) with self-awareness of conscience. Meanwhile, $L{\ddot{u}}Zuqian$(呂祖謙) valued much of Jing(敬) like ZhuXi(朱熹). But, to $L{\ddot{u}}Zuqian$(呂祖謙), Jing(敬) meant WuJianDuan(無間斷) of ChunYiBuZa(純一不雜) DaoDeXin(道德心), and implied the same as Cheng(誠). $L{\ddot{u}}Zuqian$(呂祖謙) stressed the reading and pursuit of study, however, he also asserted that Li(理) could be understood and realized through self-awareness of one's mind and its reflection, and working without interruption. $L{\ddot{u}}Zuqian$(呂祖謙)'s academic tradition of the XinXueDe XueFeng(心學的 學風), which reveals through compromise and confrontation with ZhuXi(朱熹), can be said that it will have a significant meaning of idealism of dispute in the Southern Song period.

• Journal of The Korean Association For Science Education
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• v.42 no.4
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• pp.417-428
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• 2022

This study analyzed the frequency and level of scientific practices presented in secondary science textbooks. A total of 1,378 student activities presented in 14 middle school science textbooks and 5 high school integrated science textbooks were analyzed, using the definition and level of scientific practice suggested in the NGSS. Findings show that most student activities focus on three practices. Compared to the textbooks for the previous science curriculum, the practice of 'obtaining, evaluating, and communicating information' was more emphasized, reflecting societal changes due to ICT development. However, the practice of 'asking a question', which can be an important element of student-led science learning, was still rarely found in textbooks, and 'developing and using models', 'using math and computational thinking' and 'arguing based on evidence' were not addressed much. The practices were mostly elementary school level except for the practice of 'constructing explanations'. Such repeated exposures to a few and low level of practices mean that many future citizens would be led to a naïve understanding of science. The findings imply that it is necessary to emphasize various practices tailored to the level of students. In the upcoming revision of the science curriculum, it is necessary to provide the definition of practices that are not currently specified and the expected level of each practice so that the curriculum can provide sufficient guidance for textbook writing. These efforts should be supported by benchmarking of overseas science curriculum and research that explore students' ability and teachers' understanding of scientific practices.

• Journal of The Korean Association For Science Education
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• v.28 no.1
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• pp.1-14
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• 2008

The image of science is one of the recurrent topics in science education research. In particular, we believe that students' images of Doing-Science-Well could be used for identifying not only students' perceived goals of science learning, but also practical guidelines of effective science teaching. In this study, the students' images of Doing-Science-Well were investigated with the following two research questions: (i) what are student's images of Doing-Science-Well?; (ii) in what contexts do students perceive that someone is doing science well? Thirty seven students in a high school in Seoul, Korea were asked to write their personal experiences by which they realized that someone was doing science well. The main results of the study are the following: Firstly, the images of Doing-Science-Well could be categorized into 'Einstein type', 'Socrates type', 'MacGyver type' and six more types. Secondly, with regard to contexts, students tended to realize that somebody is doing science well in terms of two kinds of contexts: 4 physical contexts and 6 psychological contexts. The findings led us to develop a frame of judging Doing-Science-Well, which combines the types and two kinds of contexts. The frame illustrates the multiplicity of the images of Doing-Science-Well.

• Journal of Science Education
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• v.47 no.3
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• pp.238-250
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• 2023

This study aims to explore the effect of an appropriate technology program related to water acquisition and purification on scientific attitudes and creative problem-solving skills in elementary school students. Thus, this study developed a learning program related to the appropriate technology composed of 8 sessions, and some were for exploring water acquisition-related scientific principles and the appropriated technology of Warka Tower, and the others were for conducting water purification-related inquiry experiments, such as Life Straw and Drinkable Book, and the last two sessions were for presenting practical tasks through creative ideas and designs and carrying out the relevant campaign activities. For research subjects, this study selected 51 students from two sixth-grade classes, and after modifying the scientific attitude questionnaire and the creative problem-solving skill questionnaire fit for the environment and situation, this study conducted a paired-sample t-test by applying both the questionnaires before and after this program. In addition, while looking into the correlation between scientific attitudes and creative problem-solving skills, based on the post-test results, this study examined relationships between sub-domains perceived by the students after this program was applied. The results can be summarized as below. Out of all the scientific attitudes, curiosity, openness, cooperation, and creativity showed statistically significant results with an increase in the average value when their overall averages of the pre-test were compared with those of the post-test. With creative problem-solving skills, the domain of mastering a specific area and the domain of divergent thinking showed statistically significant results. The correlation analysis results showed that cooperation out of the scientific attitudes had a significant correlation with all the domains of creative problem-solving skills, especially showing the highest correlation coefficient with such sub-domains as critical and logical thinking. All the four domains of creative problem-solving skills showed a number of significant correlations with the sub-domains of scientific attitudes. Through the research results above, this study has several implications on how and where to apply such appropriate technology-related topics in the future and various responses from students.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.434-441
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• 2023

Determining the size or area of a plant's leaves is an important factor in predicting plant growth and improving the productivity of indoor farms. In this study, we developed a convolutional neural network (CNN)-based model to accurately predict the length and width of lettuce leaves using photographs of the leaves. A callback function was applied to overcome data limitations and overfitting problems, and K-fold cross-validation was used to improve the generalization ability of the model. In addition, ImageDataGenerator function was used to increase the diversity of training data through data augmentation. To compare model performance, we evaluated pre-trained models such as VGG16, Resnet152, and NASNetMobile. As a result, NASNetMobile showed the highest performance, especially in width prediction, with an R_squared value of 0.9436, and RMSE of 0.5659. In length prediction, the R_squared value was 0.9537, and RMSE of 0.8713. The optimized model adopted the NASNetMobile architecture, the RMSprop optimization tool, the MSE loss functions, and the ELU activation functions. The training time of the model averaged 73 minutes per Epoch, and it took the model an average of 0.29 seconds to process a single lettuce leaf photo. In this study, we developed a CNN-based model to predict the leaf length and leaf width of plants in indoor farms, which is expected to enable rapid and accurate assessment of plant growth status by simply taking images. It is also expected to contribute to increasing the productivity and resource efficiency of farms by taking appropriate agricultural measures such as adjusting nutrient solution in real time.

• Korean Journal of Culture and Social Issue
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• v.12 no.5_spc
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• pp.81-98
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• 2006

The objective of this research is to do a cultural comparison on the daily lives of the children of Korea, Japan and China. To achieve this objective, the questionnares were distributed to the 2940 mothers of children from the ages of 3 to 6 in the countries of Korea, Japan and China. The target audience consisted of 941 mothers living in Seoul and Kyunggi area for Korea, 1007 mothers living in Tokyo for Japan, and 992 mothers living in Beijing for China. As a result of the research, we found out that firstly, although children in general got up anytime between 7:00am to 9:00am and went to bed between 8:00pm and 11:00pm, 61.5% of the Korean children went to bed after 10pm and 16.8% after 11pm. Besides that, we found that compared to 3.51% of Korean children who got up before 6am, 13.41% of Japanese children and 17.24% of Chinese children got up before 6:00am. So we could see that the Korean children got up later and went to bed later than their Japanese and Chinese counterpart. This pattern could also be seen in the average rising time and bed time. Korean children went to bed at 10:00pm and woke up at 7:75am whereas the Japanese children went to bed at 9:28pm and woke up at 7:39am, and the Chinese children went to bed at 9:05pm and woke up at 7:05am. The average sleeping hours for Japanese children was 10.12 hours, 9.50 hours for the Chinese and 9.75 hours for the Korean. As a result, we could see that the Korean children went to bed later, got up later and slept fewer hours than their Japanese and Chinese counterparts. Also, since the rising time and bedtime of the Korean children was later than those of the Chinese and Japanese counterparts, the former s' breakfast and dinner time was also much later. Secondly, we looked at the time children went off to and came back from institutes such as kindergarten and child care centers. The Chinese were earliest at going with average attendance at 7:83am, the Japanese came next at 8:59am and the Korean children were last at 8:90am, whereas the Japanese came first in coming back home at 3:36pm, Korean next at 3:91pm and the Chinese last at 5:46pm. Next when we looked at the hours spent at the kindergartens and child care centers, Japan spent 6.76 hours, Korea 7.01 hours and China spent the longest hours with 9.63 hours. Excluding China where all preschool institutes are centralized into kindergartens, we nest looked at time children went to and came back from the institutes as well as the time spent there. In the case of kindergarten, there was not much difference but in the case of child care centers, the Japanese children went to the child care centers mach earlier and came home later than the Korean children. Also, the time spent at the child care center was much longer for the Japanese than the Korean children. This fact coincides with the Korean mothers' number one wish to the kindergartens and child care centers i.e. for the institutes to prolong their school hours. Thus, the time spent at child care centers for Korea was 7.75 hours, 9.39 hours for Japan and 9.63 hours for China. The time for Korea was comparatively much shorter than that of Japan and China but if we consider the fact that 50% of the target audience was working mothers, we could easily presume that the working parents who usually use the child care centers would want the child care centers to prolong the hours looked after their children. Besides this, the next most wanted wish mothers have towards the child care centers and kindergartens was for those institutes to "look after their children when sick". This item showed high marks in all three countries, and the marks in Korea was especially higher when compared to Japan and China. Thirdly, we looked at the private extracurricular activities of the children. We found that 72.6% of the Korean children, 61.7% of the Japanese children, and 64.6% of the Chinese children were doing private extracurricular activities after attending kindergarten or day care centers. Amongst the private extracurricular activities done by Korean children, the most popular one was worksheet with 51.9% of the children doing it. Drawing (15.20%) and English (11.6%) came next. Swimming (21.95%) was the most popular activity for Japan, with English (17.48%), music (15,79%) and sports (14.70%) coming next. For China, art (30.95%) was first with English (22.08%) and music (19.96%) following next. All three countries had English as the most popular activity related to art and physical activities after school hours, but the rate for worksheet studies was much higher for Korea compared to Japan China. The reason Koreans universally use worksheet in because the parents who buy the worksheet are mothers who have easy access to advertisement or salespeople selling those products. The price is also relatively cheap, the worksheet helps the children to grow the basic learning ability in preparation for elementary school, and it is thought to help the children to build the habit of studying everyday. Not only that but it is estimated that the worksheet education is being conducted because parents can share the responsibility of the children's learning with the worksheet-teacher who make home visits. Looking at the expenses spent on private extracurricular activities as compared to income, we found that China spent 5% of income for activities outside of regular education, Korea 3% and Japan 2%. Fourthly, we looked at the amount of time children spent on using multimedia. The majority of the children in Korea, Japan and China watch television almost every day. In terms of video games, the Japanese children played the games the most, with Korea and China following next. The Korean children used the computer the most, with Japan and China next. The Korean children used about 21.17% of their daily time on computers which is much more than the Japanese who used 20.62% of their time 3 or 4 times a week, or the Chinese. The Chinese children were found to use considerably less time on multimedia compared to the Korean of Japanese.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.