• Title/Summary/Keyword: 수준 분류

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Verification of Validity on the Manual Ability Classification System in Children With Spastic Cerebral Palsy (경직형 뇌성마비 아동의 손 기능 분류 체계의 타당도 검증)

  • Park, Eun-Young
    • The Journal of the Korea Contents Association
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    • v.10 no.1
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    • pp.317-324
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    • 2010
  • The purpose of this study was to examine the validity of the Manual Ability Classification System (MACS) by analysing of relation between MACS and Jebsen-Talyor Hand Function Test. The concurrent validity was examined by calculation of correlation between MACS and Jabsen-Talyor Hand Function test and the discriminant validity was examined by measurement of hand function difference according to MACS level. For this, eighty-one children with spastic cerebral palsy were employed in this study. The children were evaluated by using the MACS and Jebsen-Taylor Hand Function Test for their hand function. There were a significant correlation between the MACS and Hand function (r = .870, p < .05). The good correlation between the MACS and subtest of Jabsen-Talyor Hand function (p < .05). The hand function according to the MACS level were different significantly (p < .05). The MACS is valid classification system for assessment of hand function of children with cerebral palsy. The MACS in practice will provide usefulness for assessment of hand function in children with spastic cerebral palsy.

패키지 소프트웨어 품질평가모형 개발 및 적용에 관한 연구

  • 이국철;이성현
    • Proceedings of the Korea Database Society Conference
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    • 1999.10a
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    • pp.143-152
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    • 1999
  • 세계 소프트웨어 시장의 급속한 성장과 함께 선진국들은 자국에 유리한 소프트웨어 품질표준을 만들어 이를 국제 표준에 반영하고, 외국 소프트웨어에 대한 진입 규제의 수단으로 활용하고 있다. 또한 전자상거래의 발달로 인해 디지털 상품인 소프트웨어는 전자상거래를 통한 거래가 쉬운 이점을 가지고 있는 상황에서 아직 우리나라에서는 패키지 소프트웨어에 관한 품질모형 개발에 관한 연구가 다소 미흡한 실정이다. 본 연구에서는 기존 국내외 소프트웨어 품질평가모형을 도출하고, 그 평가모형을 바탕으로 전자상거래에서 활용 가능한 패키지 소프트웨어만을 대상으로 품질평가모형을 개발하였다. 그리고 평가모형을 적용하기에 앞서 소프트웨어 개발 업체를 대상으로 설문조사를 실시하여 품질평가모형에 대한 실증분석을 하였다. 실증분석은 현재 개발업체가 취급하고 있는 제품에 대한 종류와 개발업체에서 평가받기를 원하는 제품의 종류, 그리고 평가대상이 될 수 있는 패키지 소프트웨어 제품의 경쟁력 수준과 관련하여 선진국의 제품과 비교하여 5점 척도로 조사하였다. 그리고 소프트웨어 개발자 입장에서 품질평가 항목별로 중요도를 조사하였으며 분석결과를 토대로 품질평가모형의 적용 대상을 선정하였다. 적용대상 제품은 모두 14개로 각각의 제품들을 게임, OA, 통신, ERP, 4GL, OS 소프트웨어로 분류하고 제품에 대한 평가는 개발자(개발경력 3년 이상)와 일반사용자로 분류하여 평가를 실시하였다. 그리고 각 제품분야별로 평가항목에 대한 가중치를 전문가 집단에 의뢰하여 적용하였다. 평가방법은 각각의 제품에 대한 평가점수를 1점부터 5점까지 나누어 평가결과를 평균값으로 나타냈으며, 평가결과에 대해 여러 가지 방법으로 분석하였다. 첫째, 동종제품간 평가분석을 통하여 각각의 제품을 비교하였으며, 둘째 소프트웨어 종류별 평가로 제품을 응용소프트웨어, 응용개발도구, 시스템 소프트웨어로 분류하여 평균값으로 비교하였다. 셋째, 국내외 제품별 평가분석으로 전체 제품을 국내제품과 국외제품으로 분류하여 비교하였으며, 마지막으로 총괄분석을 통해 가중치를 적용하여 전 제품의 점수를 비교하였다. 여기에서는 각 제품의 평균점수에 대한 차이를 95%의 유의수준으로 T-Test를 실시하였다.

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A Compare of 'Understanding' in Backward design and Taxonomy of Educational Objectives in Informatics (정보과 수업 설계에서 백워드 디자인의 '이해'와 교육목표분류학의 6단계 비교 분석)

  • Kim, JaMee;Lee, WonGyu
    • The Journal of Korean Association of Computer Education
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    • v.22 no.3
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    • pp.25-35
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    • 2019
  • The backward design suggested in the 2015 revised curriculum takes into consideration the consistency between a goal and its evaluation, and emphasizes the essence of knowledge. However, the method for designing lesson plans is different from those of the past and, as a result, teachers in the field have experienced some difficulty in applying the design. Accordingly, this study was aimed at examining the differences between the taxonomy of educational objectives with which teachers are familiar and the viewpoint of informatics. The result of the analysis indicated no difference when applying the hierarchy of the six-sided view of the concept of understanding, of which teachers felt some difficulty in terms of applying the backward design. However, the analysis did show some similarity to the hierarchy of the six levels suggested in the taxonomy of the educational objectives. In general, when a new theory is suggested, it is very difficult for it to be accepted and applied. This study holds significance in that it suggests that a new theory must be accepted on the basis of sufficient analysis along with the necessity of efforts to be dedicated in order to increase its applicability.

A Study on the PBL-based AI Education for Computational Thinking (컴퓨팅 사고력 향상을 위한 문제 중심학습 기반 인공지능 교육 방안)

  • Choi, Min-Seong;Choi, Bong-Jun
    • Journal of the Institute of Convergence Signal Processing
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    • v.22 no.3
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    • pp.110-115
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    • 2021
  • With the era of the 4th Industrial Revolution, education on artificial intelligence is one of the important topics. However, since existing education is aimed at knowledge, it is not suitable for developing the active problem-solving ability and AI utilization ability required by artificial intelligence education. To solve this problem, we proposes PBL-based education method in which learners learn in the process of solving the presented problem. The problem presented to the learner is a completed project. This project consists of three types: a classification model, the training data of the classification model, and the block code to be executed according to the classified result. The project works, but each component is designed to perform a low level of operation. In order to solve this problem, the learners can expect to improve their computational thinking skills by finding problems in the project through testing, finding solutions through discussion, and improving to a higher level of operation.

Automatic Classification of Academic Articles Using BERT Model Based on Deep Learning (딥러닝 기반의 BERT 모델을 활용한 학술 문헌 자동분류)

  • Kim, In hu;Kim, Seong hee
    • Journal of the Korean Society for information Management
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    • v.39 no.3
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    • pp.293-310
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    • 2022
  • In this study, we analyzed the performance of the BERT-based document classification model by automatically classifying documents in the field of library and information science based on the KoBERT. For this purpose, abstract data of 5,357 papers in 7 journals in the field of library and information science were analyzed and evaluated for any difference in the performance of automatic classification according to the size of the learned data. As performance evaluation scales, precision, recall, and F scale were used. As a result of the evaluation, subject areas with large amounts of data and high quality showed a high level of performance with an F scale of 90% or more. On the other hand, if the data quality was low, the similarity with other subject areas was high, and there were few features that were clearly distinguished thematically, a meaningful high-level performance evaluation could not be derived. This study is expected to be used as basic data to suggest the possibility of using a pre-trained learning model to automatically classify the academic documents.

Friedewald-Estimated Versus Directly Measured LDL-Cholesterol: KNHANES 2009-2010 (LDL-콜레스테롤의 Friedewald 계산값과 실측값 비교: 국민건강영양조사 2009-2010)

  • Jang, Sungok;Lee, Jongseok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.8
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    • pp.5492-5500
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    • 2015
  • Low-density lipoprotein cholesterol (LDL-C) is a major modifiable risk factor for cardio- cerebrovascular disease. In clinical practice, however, it is primarily calculated using the Friedewald formula as a cost-effective method. The aim of this study was to compare Friedewald-estimated and directly measured LDL-C values and assess the concordance in guideline LDL-C risk classification between the two methods. The data were derived from the 2009 and 2010 Korea National Health and Nutrition Survey (KNHANES). Analysis was done for 4,319 subjects with lipid panels-total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), directly measured LDL-C using an enzymatic homogeneous assay, and triglycerides (TG). For subjects with TG lower than 400 mg/dL, Friedewald-estimated and directly measured LDL-C were highly correlated (r = 0.958, p < 0.001) and overall concordance was 82.7%. As TG increased, overall concordance decreased. Overall concordance was 85.4% at TG lower than 150 mg/dL; 78.2% at TG of 150-199 mg/dL; and 71.4% at TG of 200-399 mg/dL. The Friedewld equation tended to overestimate LDL-C when TG are of < 150 mg/dL; however, underestimate LDL-C when TG are of ${\geq}150mg/dL$. As a result, Friedewald estimation misclassified 382 subjects (9.1%) in a higher category versus 348 subjects (8.3%) in a lower category. Our findings suggest that overestimation of LDL-C by the Friedewald formula can be a great problem as well as underestimation.

Improving the Performance of SVM Text Categorization with Inter-document Similarities (문헌간 유사도를 이용한 SVM 분류기의 문헌분류성능 향상에 관한 연구)

  • Lee, Jae-Yun
    • Journal of the Korean Society for information Management
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    • v.22 no.3 s.57
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    • pp.261-287
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    • 2005
  • The purpose of this paper is to explore the ways to improve the performance of SVM (Support Vector Machines) text classifier using inter-document similarities. SVMs are powerful machine learning systems, which are considered as the state-of-the-art technique for automatic document classification. In this paper text categorization via SVMs approach based on feature representation with document vectors is suggested. In this approach, document vectors instead of index terms are used as features, and vector similarities instead of term weights are used as feature values. Experiments show that SVM classifier with document vector features can improve the document classification performance. For the sake of run-time efficiency, two methods are developed: One is to select document vector features, and the other is to use category centroid vector features instead. Experiments on these two methods show that we can get improved performance with small vector feature set than the performance of conventional methods with index term features.

A divide-oversampling and conquer algorithm based support vector machine for massive and highly imbalanced data (불균형의 대용량 범주형 자료에 대한 분할-과대추출 정복 서포트 벡터 머신)

  • Bang, Sungwan;Kim, Jaeoh
    • The Korean Journal of Applied Statistics
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    • v.35 no.2
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    • pp.177-188
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    • 2022
  • The support vector machine (SVM) has been successfully applied to various classification areas with a high level of classification accuracy. However, it is infeasible to use the SVM in analyzing massive data because of its significant computational problems. When analyzing imbalanced data with different class sizes, furthermore, the classification accuracy of SVM in minority class may drop significantly because its classifier could be biased toward the majority class. To overcome such a problem, we propose the DOC-SVM method, which uses divide-oversampling and conquers techniques. The proposed DOC-SVM divides the majority class into a few subsets and applies an oversampling technique to the minority class in order to produce the balanced subsets. And then the DOC-SVM obtains the final classifier by aggregating all SVM classifiers obtained from the balanced subsets. Simulation studies are presented to demonstrate the satisfactory performance of the proposed method.

In-Depth & Supplementary Differentiated Curriculum for Social Studies based on Cooperative Learning (협동학습에 기반한 사회과를 위한 심화·보충형 수준별 교육)

  • Chae, Jung-Bo;Kang, Oh-Han;Song, Hee-Heon
    • The Journal of Korean Association of Computer Education
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    • v.8 no.6
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    • pp.45-53
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    • 2005
  • In this paper, we propose an improved method of differentiated curriculum in social studies class that can be immediately used in the class. There are two major reasons that differentiated curriculum has not been applied to actual educational programs. One reason is the inefficient progress of differentiated curriculum derived from students' self-study based on individual projects and teacher's excessive investment of time in the development and management of individual researches. The other attribute is the difficulty in distinguishing students' academic level due to the lake of distinct criteria, because students are classified into merely two groups, in-depth group and supplementary class. To cope with these problems, we adopted a cooperative learning to enhance the educational effect of students of the similar level. Experimental results validate that the proposed method is effective in the course of social studies.

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The Effects of Learner's Metacognition and Scaffolding Types on Problem Solving Process in Web-based PBL (웹기반 PBL에서 학습자의 메타인지와 스캐폴딩 유형이 문제해결과정에 미치는 효과)

  • Jeon, Hee-Jeong
    • The Journal of the Korea Contents Association
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    • v.7 no.2
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    • pp.161-169
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    • 2007
  • This study examines the effects of learner's metacognition and scaffolding types on problem solving processes by examined 49 undergraduates to identify effective scaffolding type in Web-based PBL. This study classifies problem solving processes as defining the problem, developing solutions, making selections and justifications for the Proposed solution(s), and monitoring the solution. Moreover, it classifies scaffolding types as subject-related scaffolding and process-related scaffolding. As a result, the upper metacognition group showed higher performance only in monitoring solutions than the lower metacognioon group. This study also showed that offered scaffolding effects are not statistically significant. However, the lower metacognition group showed higher performance when subject-related scaffolding was offered and the upper metacognition group showed higher performance when process-related scaffolding was offered in making selections and justifications for the proposed solution(s) and monitoring solution. This study, based on the result of research, can partially verify the effects of learner's metacognition on problem solving processes and interaction effects between scaffolding and metacogniton in Web-based PBL.