• Korean Medical Education Review
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• v.17 no.1
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• pp.33-38
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• 2015

During the education reform in 2009, the Catholic University of Korea College of Medicine (CUMC) adopted body systems as the basis for structuring basic medical education. After running the new program for 5 years, we need to evaluate the program by comparing it with nationwide standards. This study was designed to evaluate the coverage of our basic medical education program by comparing it with the assessment items of the medical licensing examination for physicians in the Republic of Korea. We built a relational database populated with 3,017 learning outcomes from all the courses on basic medical education. We tagged each learning outcome according to 2 criteria: 206 physician encounters and 9 outcome domains. A majority of the learning outcomes were in the domains of 'knowledge' and 'critical thinking'. In addition, we repeated the categorization process with 584 assessment items of the medical licensing examination in the Republic of Korea and compared them with the categorization results of the learning outcomes. Among the 206 physician encounters, we found that outcomes on family violence and sexual violence were missing in the learning outcomes of CUMC. Eighty-two physician encounters were associated with more than one outcome domain, and 96 physician encounters were covered in more than one course. Twenty-one physician encounters were repeated in 5 or more courses and 34 physician encounters had outcomes categorized into 3 or more domains. Thus, we showed that the 2-way categorization could be applied to the comparison and evaluation of two different education formats.

• Journal of The Korean Association For Science Education
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• v.40 no.3
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• pp.291-305
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• 2020

The purpose of this study is to examine whether and how the features of performance assessments implemented during integrated science classes are related to teachers' PCK. We observed and video recorded four high school teachers' performance assessment practices, interviewed them, and surveyed their PCK. An analysis of the data shows that the teachers' performance assessment practices differed in terms of assessment of process, diagnosis of student learning progress, feedback, degree of classroom interactions, and use of assessment criteria. In particular, the opportunities for students to participate in assessment actively and use of assessment for learning varied across teachers. Also, relational patterns among science teaching orientations, PCK and performance assessment practices were found. When a teacher aimed at teaching for both academic learning and scientific literacy, sophisticated PCK was shown and assessment practices were complex accordingly. When scientific literacy was emphasized PCK highlighted experiential learning and assessments were not clearly distinguished from learning activities. In contrast, when academic achievement was emphasized traditional teaching strategies and assessments were highlighted. Based on these findings a number of topics for professional development are suggested including strategies for students' active engagement in assessment, use and development of specific assessment criteria, strategies for assessing performance qualities, and intuitive assessment competency development. Further research topics are also suggested.

• The Mathematical Education
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• v.39 no.2
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• pp.151-166
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• 2000

The purpose of this study is to understand what two models of SOLO taxonomy and van Hiele theory suggest and find out what relation there is between the category system of the SOLO taxonomy and the thinking level of the van Hiele theory. The van Hiele theory describes in line of ranking level so that it may increase the teaching effects by putting together a class, which takes into consideration the students thoughts. The SOLO taxonomy focused on the response mode of the students rather than the thinking level or the developmental stage of them to pursuit the method that can describe the students understanding in depth quality-wise. Although the SOLO taxonomy and the van Hiele model seem to have different form and character from outside in terms of their goals, a closer examination reveals that the two stances have much in common and that the models are complementary. Although the van Hiele placed more focus on the thoughts, because the conclusion was based on the students responses, the van Hiele theory can be interpreted within the structure identified in the SOLO model. In this study, we have tried to understand how the response structure form the SOLO taxonomy and the thinking level of the van Hiele theory are related, based on the studies of Pegg and Davery1998). If you briefly look at them, there are following corresponding relation between the SOLO taxonomy and the van Hiele theory. a) The relational level(R) in iconic moe is van Hiele level 1. b) The multisturctural level(M$_2$) in the second cycle of concrete-symbolic mode is van Hiel level 2. c) The relation level(R$_2$) in the second cycle of concrete-symbolic mode is van Hiele level 3. d) The unistructural level(U$_2$) in the second cycle of formal mode is van Hiele level 4. e) The postformal mode is van Hiele levle 5. Though it would be difficult to conclude that these correspondences were perfectly done, if you look at their relation, you can see that the learning process of the students were not carried out uniformly. Therefore, by studying the students response structure, using the SOLO taxonomy, and identifying the learning cycle and understand the geometrical concept more in depth.

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.598-605
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• 2018

Behavior awareness is a technology that recognizes human behavior through data and can be used in applications such as risk behavior through video surveillance systems. Conventional behavior recognition algorithms have been performed using the 2D camera image device or multi-mode sensor or multi-view or 3D equipment. When two-dimensional data was used, the recognition rate was low in the behavior recognition of the three-dimensional space, and other methods were difficult due to the complicated equipment configuration and the expensive additional equipment. In this paper, we propose a method of recognizing human behavior using only CCTV images without additional equipment using only RGB and depth information. First, the skeleton extraction algorithm is applied to extract points of joints and body parts. We apply the equations to transform the vector including the displacement vector and the relational vector, and study the continuous vector data through the RNN model. As a result of applying the learned model to various data sets and confirming the accuracy of the behavior recognition, the performance similar to that of the existing algorithm using the 3D information can be verified only by the 2D information.

• Journal of Korean Academy of Nursing
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• v.17 no.2
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• pp.153-161
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• 1987

This descriptive-correlational study was conducted to recognize the relational between the Perceived social support and stress in pregnant women. The subject were comprised of 154 patients who were at 24 weeks over, and data were collected by way of questionnairs at K-university hospital in Seoul during 23 days (November 21, 1986 to December 13, 1986). The result of this study may be summerized as follows. 1) The degrees of the support from situation perceived by pregnant women were: the minimal 20 feints, the maximal 61 points and the mean 40.42 feints. 2) The degrees of stress perceived by pregnant women were: the minimal 32 points, the maximal 109 points and the mean 65.49 points. 3) The results of hypotheses were: the first hypothesis was not supported that the higher the degree of social support from situation perceived by pregnant women, the lower that of stress(r= -0.01129, p=0.8895) the second was supported that the higher the degree if support perceived indirectly by pregnant women, the lower that of stress(r= -0.23832, p=0.0029). the third was supported that the higher the degree of support perceived directly by pregnant women, the lower that of stress. (r= -0.36019, p=0.0001) 4) The fourth shows that in the relationships between the characteristics of socio-popualtion and obstetrics and the degree of social support, there was significant difference; i) the support from situation differs in learning (t= -2.178, p<.05), and satisfaction of marriage (F=5.06, p<.01) ii) the support perceived indirectly differs in learning (t= -3.065, p<.01), month of pregnant(F= 2.78, p <.05), satisfaction of marriage (F=20.08, p<.001) and forms of family (t=2.11, p<.05) iii) the support perceived directly differs in satisfaction of marriage (F=21.00, p <.001) and forms of family (t=2.11, p<.05) 5) the fifth shows that in the relationship between the characteristics of sociopopulation and obstetrics and stress, the degree of satisfaction of marriage only shows the significant statistical difference(F= 0.40, p<.01) 6) The sixth shows that the factor affecting the stress of pregnant women was the support perceived directly and its explanatory power was 12.9%.

• Journal of Elementary Mathematics Education in Korea
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• v.23 no.3
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• pp.273-288
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• 2019

This study focuses on understanding proportionality, in particular, what constitutes relational understanding of a:b=c:d, which is called proportional expression. The meanings of a:b=c:d are analyzed and some suggestions are offered for improving the teaching and learning of it. The equation a:b=c:d has three different meanings. First, it represents two different structures in one proportional situation. Second, it represents a common structure in two different proportional situations. Finally, it represents a number or a quantity underlying in different proportional situations. It is important to choose and use a unit flexibly to understand the first and the second meanings of a:b=c:d, Double strip diagram and double number line are useful to visualize the meanings of a:b=c:d. In addition, what a number or a quantity in the third meaning of a:b=c:d refers to in proportional situations should be emphasized in teaching and learning of a:b=c:d.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.329-338
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• 2013

Purpose: This study was to identify the types of subjectivity on PBL experience of freshmen in nursing students. Method: This study is exploratory research through Q methodology. From 102 Q populations, we selected 31 Q sorting was done by 25 of P sample. When the Q sorting is completed on nine point scale, we interviewed participants and documented their responses. The data was analyzed by using QUNAL program. Result: The result of the study showed 4 types. Four factors provided an explanation for 71.6% of total variances, and these four factors were analyzed and categorized as four types. We named type 1 as [positive pressure], type 2 as [relational friendly], type 3 as [creative benefit], type 4 as [paticipatory development]. Conclusion: In this study, PBL was valuable experience and recognized as a variety of perspectives for freshmen in nursing students. These findings indicate we suggest that planning of strategy for efficient operation on PBL was reflected above results.

• Journal of the Economic Geographical Society of Korea
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• v.4 no.1
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• pp.19-35
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• 2001

This paper is concerned with the relationships between large firms with global reaches in their markets and subcontracting firms, mostly small and medium-sized firms. It then attempts to focus in more detail on the dynamic relational dimensions between the two. In doing so, we draw upon the secondary data and the results of interviewing survey with some senior managers. The empirical study shows that the localisation of subcontracting networks have been increasingly reinforced thanks to the increasing tendency of vertical disintegration by LC. However, it is identified that there is a tendency that local subcontractors are specialised in producing relatively low value-added and low technology-intensive electronic parts/components. Based on these results, the author suggests the implications of regional economic development in the context of innovation and learning.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.477-482
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• 2016

As being the advanced analytics indispensable on big data for agile decision-making and tactical planning in enterprises, distributed processing platforms, such as Hadoop and Spark which distribute and handle the large volume of data on multiple nodes, receive great attention in the field. In Spark platform stack, Spark SQL unveiled recently to make Spark able to support distributed processing framework based on SQL. However, Spark SQL cannot effectively handle advanced analytics that involves machine learning and graph processing in terms of iterative tasks and task allocations. Motivated by these issues, this paper proposes the design of SQL-based big data optimal processing engine and processing framework to support advanced analytics in Spark environments. Big data optimal processing engines copes with complex SQL queries that involves multiple parameters and join, aggregation and sorting operations in distributed/parallel manner and the proposing framework optimizes machine learning process in terms of relational operations.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.521-526
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• 2016

As on-line informal text data have massive in its volume and have unstructured characteristics in nature, there are limitations in applying traditional relational data model technologies for data storage and data analysis jobs. Moreover, using dynamically generating massive social data, social user's real-time reaction analysis tasks is hard to accomplish. In the paper, to capture easily the semantics of massive and informal on-line documents with unsupervised learning mechanism, we design and implement automatic topic extraction systems according to the mass of the words that consists a document. The input data set to the proposed system are generated first, using N-gram algorithm to build multiple words to capture the meaning of the sentences precisely, and Hadoop and Spark (In-memory distributed computing framework) are adopted to run topic model. In the experiment phases, TB level input data are processed for data preprocessing and proposed topic extraction steps are applied. We conclude that the proposed system shows good performance in extracting meaningful topics in time as the intermediate results come from main memories directly instead of an HDD reading.