• 공학교육연구
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• 제16권1호
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• pp.54-63
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• 2013

This study aims to investigate relationships among self-directed learning readiness [SDLR], prerequisite mathematics test score and achievement level in college mathematics. For this purpose, the adjusted SDLRS (self-directed learning readiness scale) of Guglielmino's model, the score of mathematics diagnostic assesment and first semester college mathematics score among 424 freshmen students of engineering department of D university in 2011 were used and analyzed. Research results are as follows: Firstly, freshmen of engineering department had average level of SDLR, though they showed relative low level of self-direction, passion and time control ability. Secondly, considering SDLR with the mathematics diagnostic assesment score (3 groups: high, middle, low), there were no statistically significant differences. Thirdly, concerning SDLR according to the achievement level in college mathematics, a group which acquired good achievement showed higher level of SDLR compared with middle or lowachievement group. Differences among three groups were statistically significant. Lastly, there were affirmative relationships between SDLR, mathematics diagnostic assesment score and achievement in college mathematics. Furthermore, mathematics diagnostic assesment score and achievement level in college mathematics were found to be the most closely related. Based on the results, we suggest strategies to elevate SDLR of engineering department students and improve their achievement in college mathematics.

• 공학교육연구
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• 제22권4호
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• pp.22-31
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• 2019

This study aims to elucidate the relationship between physics and mathematics to predict achievement for the college level of engineering courses. For the last 4 years, more than 3,000 engineering college freshmen of this study took the diagnostic tests on three subjects, which were physics, mathematics, and chemistry before enrollment. We studied how strongly these diagnostic scores can predict each general college course grades. The correlation between the physics diagnostic scores and the course grades in physics was .264, which was significantly lower than the correlation between the mathematics scores and the physics grades, .311. This stronger prediction of the mathematical diagnostic scores for the general course grades was not found when predicting the grades in chemistry. We therefore conclude that mathematical preparation can unexpectedly predict future achievement in physics better than physics preparation due to the academic interrelationships between mathematics and physics.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제12권1호
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• pp.27-37
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• 2008

A test as a form of diagnostic of algorithm and logic abilities is considered. Such test for measuring abilities and achievements of talented children has been designed and used at the Kharkiv Regional Olympiad in Informatics. Quality of the test and its items is analyzed. Correlation between the test results of children and their success in creating mathematical models, designing of complicated algorithms and translating these algorithms into computer programs is discussed.

• 대한수학교육학회지:수학교육학연구
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• 제20권2호
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• pp.103-119
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• 2010

이 연구에서는, 초등학교 1, 2학년을 대상으로 개발된 다문화가정 학생 대상 언어 인지 진단도구를 적용한 결과를 분석하여, 수학 영역에서의 다문화가정 학생반응의 주요 특징을 찾고 수학교육에 유의한 시사점을 찾고자 하였다. 결론적으로, 1학년보다 2학년에서 미도달 비율이 높았으며, 다문화가정 학생 중 미도달 비율도 1학년보다 2학년에서 높게 나타났다. 도형과 측정 영역보다는 수와 연산 영역에서 미도달 비율이 높게 나타났으며, 다문화가정 학생 중 미도달 비율도 수와 연산 영역에서 높았다. 문장제 해결에서 어려움이 나타났으며, 난이도가 있는 수학적 내용과 수학적 사고로 인한 어려움이 상대적으로 높게 나타났다. 다문화가정 학생들의 여러 약점을 고려하여, 도형 영역에서 시각적 정보와 언어적 정보를 균형감 있게 다룰 수 있도록 지도해야 하며, 무정의용어를 신중하게 사용해야 하며, 교재 구성, 평가 문항 작성, 실제 교실 수업 등에서 언어적 요인이 학습에 미치는 영향을 충분히 고려해야 할 것이다.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제25권3호
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• pp.593-606
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• 2011

2008학년도 대전 소재 C 대학교 공과대학 신입학생 전체에 대하여 미분적분학 기초학력진단평가를 실시하였다. 그 결과 보충지도가 필요하다고 판단되는 하위 13%의 학생들에게 1 2학기 동안 수준별 기초보충수업을 실시하였으며, 기초보충수업을 받은 학생들이 그렇지 않은 학생들에 비하여 학기말 성적에서 유의미하게 높은 성취도증가를 보였다. 특히 대학입학전형 방법의 다양화에 따라 고등학교에서 미분적분학을 이수하지 않고 입학한 학생들의 경우에서도 보충학습을 통하여 정규미적분학 수업을 따라 갈 수 있는 기초와 동기를 부여하였다. 본 논문은 미분적분학 학습 부진 공대 신입생들에게 학기별 다양한 형태의 수준별 보충수업을 실시한 후 성취도를 분석하였으며, 그 형태에 따른 효과를 알아보았고, 이를 바탕으로 향후 공과대학에서 수학 성적 부진 학생들에 대한 성취도 향상 프로그램을 제안하였다.

• Communications for Statistical Applications and Methods
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• 제23권3호
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• pp.231-239
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• 2016

A graphical diagnostic method based on multiple case deletions in a regression context is introduced by using the sampling distribution of the difference between two least squares estimators with and without multiple cases. Principal components analysis plays a key role in deriving this diagnostic method. Multiple case deletions of test statistic are also considered when a new observation is fitted to a given regression model. The result is useful for detecting influential observations in econometric data analysis, for example in checking whether the consumption pattern at a later time is the same as the one found before or not, as well as for investigating the influence of cases in the usual regression model. An illustrative example is given.

• 한국수학교육학회지시리즈C:초등수학교육
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• 제9권2호
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• pp.89-105
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• 2005

The purposes of this study were to develop an effective teaching material for slow learners in mathematics and to investigate its effect. To achieve the first goal, several pre-used teaching material and the 7th national curriculum for elementary school mathematics were analyzed to set up a framework fur developing new teaching material. Using these developed framework and curriculum data, 370 units of lesson were developed from the 3rd grade to the 6th grade. To investigate the effect of the material, 3 slow learners (2 from the 5th and 1 from the 6th grade) were selected through diagnostic tests. Then supplementary lessons were administered after school to relieve their disability accordingly for seven months. During the lessons(lasted about 40 minutes), teacher observed the subjects in detail and .judged the teaming sequence and the learning pace. Through this observation and the test administered after the treatment, several conclusions were drawn as follow: First, the supplementary lessons using the developed teaching material helped slow learners understand mathematics and solve problems. Especially, the test scores gained on formative evaluation became higher. This might be caused by the material that enabled to relieve the disablement and the teaching method that aimed to give a meaningful mathematical experience. Second, the supplementary lessons affected positively to the affective domain of the slow learners. They convinced themselves to their mathematical ability and became active in their mathematics class. This was observed by researcher and the class teacher in their lessons. Positive attitude toward mathematics and their ability is quite important for mathematics learning especially fur slow learners in mathematics.

• Journal of the Korean Data and Information Science Society
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• 제21권6호
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• pp.1203-1209
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• 2010

한국정보화진흥원에서는 2002년 개발한 한국형 인터넷 중독 진단척도를 사용하여 인터넷 중독 실태를 매년 발표하고 예방을 위해 노력하고 있다. 그러나 인터넷사용이 급증함에 따라 정보화의 역기능도 증가하고 있으며 특히 인터넷 중독의 폐해가 우려되고 있는 실정이다. 본 연구에서는 인터넷 중독 자가진단 소형척도를 제안하고자한다. 대학생들을 대상으로 킴벌리영척도와 한국형진단척도를 적용하여 인터넷 중독을 진단한 자료를 분석한다. 두 척도의 신뢰성과 타당성을 검토한 결과 한국형진단척도에서 요인타당도가 있음으로, 이를 이용하여 소형척도를 개발한다. 요인타당도의 요인적재값과 변수선택법을 이용하여 선택한 소형척도들을 비교 분석한다. 분할표와 감마 연관성측도를 이용하여 소형척도와 기존의 척도들과의 일치성을 비교하고, 소형척도들의 신뢰성과 타당성을 조사한다.

• 한국수학교육학회지시리즈C:초등수학교육
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• 제14권3호
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• pp.237-259
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• 2011

수학 학습장애는 정상적인 수학적 역량 획득을 저해하는 학습 장애의 한 유형으로, 아동, 청소년의 5- 10% 정도가 겪는 학습 장애의 한 분야이다. 현재 수학학습장애를 진단하기 위하여 기초학력평가나 표준화된 검사가 사용되고 있다. 검사 결과를 토대로 아동의 사전지식을 파악하고, 취약한 영역을 찾는 것 역시 중요하다. 본 연구는 수학학습장애의 유형을 파악하고, 중재의 출발점을 알려줄 수 있는 포괄적인 진단 검사가 포함해야 하는 구성요소를 찾는 것을 목표로 하고 있다. 이를 위하여 신경심리학적 이론에 근거하여 수학학습에 영향을 주는 기본적인 인지적 요인들을 찾고, 관련되어 활성화 되는 두뇌 영역과 그들의 세부적 기능을 살펴본다. 또 수학학습장애 아동의 신경심리학적 특징을 살펴 본 다음 수학학습장애의 유형을 분류한다. 그 결과를 바탕으로 교육현장에서 사용될 수 있는 심층 진단 검사의 개발을 위한 기초연구를 수행하고자 한다.

• Korean Journal of Radiology
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• 제22권4호
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• pp.612-623
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• 2021

Objective: To evaluate the diagnostic performance of a deep learning algorithm for the automated detection of developmental dysplasia of the hip (DDH) on anteroposterior (AP) radiographs. Materials and Methods: Of 2601 hip AP radiographs, 5076 cropped unilateral hip joint images were used to construct a dataset that was further divided into training (80%), validation (10%), or test sets (10%). Three radiologists were asked to label the hip images as normal or DDH. To investigate the diagnostic performance of the deep learning algorithm, we calculated the receiver operating characteristics (ROC), precision-recall curve (PRC) plots, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) and compared them with the performance of radiologists with different levels of experience. Results: The area under the ROC plot generated by the deep learning algorithm and radiologists was 0.988 and 0.988-0.919, respectively. The area under the PRC plot generated by the deep learning algorithm and radiologists was 0.973 and 0.618-0.958, respectively. The sensitivity, specificity, PPV, and NPV of the proposed deep learning algorithm were 98.0, 98.1, 84.5, and 99.8%, respectively. There was no significant difference in the diagnosis of DDH by the algorithm and the radiologist with experience in pediatric radiology (p = 0.180). However, the proposed model showed higher sensitivity, specificity, and PPV, compared to the radiologist without experience in pediatric radiology (p < 0.001). Conclusion: The proposed deep learning algorithm provided an accurate diagnosis of DDH on hip radiographs, which was comparable to the diagnosis by an experienced radiologist.