• Journal of Engineering Education Research
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• v.16 no.1
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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.

• Journal of Engineering Education Research
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• v.22 no.4
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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.

• Research in Mathematical Education
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• v.12 no.1
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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.

• Journal of Educational Research in Mathematics
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• v.20 no.2
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• pp.103-119
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• 2010

This study aims to figure out the characteristics of the mathematical ability of multicultural Korean elementary school learners. This was done by analyzing the results of a mathematics diagnostic test given to multicultural Korean first and second year elementary school students. The findings of this study mainly support the following three. First, it was indicated that, regardless of whether the students are multicultural or not, more second-year students had difficulty in understanding mathematics than the first-year students. Specifically, a higher percentage of second-year students were below the reference point (cut-off point) than was the case in the first-year learners, which pattern of the overall Korean students was consistent with that of multicultural Koreans. Second, concerning the sub-fields of mathematics, higher proportion of the students fell below the cut-off point in 'numbers and arithmetics' area than in 'measure and geometry,' which pattern was again the same with the multicultural students. Third, it was implied that, in addition to mathematically more complex questions, linguistically complex sentential representations contributed to increasing the difficulty of the test items. It is suggested that care be taken to enhance linguistic processing and to employ well-defined terms.

• Communications of Mathematical Education
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• v.25 no.3
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• pp.593-606
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• 2011

We carried out mathematics diagnostic tests for all first year engineering students at C University in Daejeon in 2008, covering precalculus and basic calculus. Then we divided into two classes such as regular and supplementary classes. The supplementary class students are lower 13% students. Then we gave extra classes for these students to support their basic and elementary calculus skills. As a result, these supplementary students received a meaningful accomplishment at the final exam. This paper analyzes the results and effects of various types of supplementary classes such as education by level, and proposes some strategies to enhance mathematics learning, particularly for under achieving first year engineering students.

• Communications for Statistical Applications and Methods
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• v.23 no.3
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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.

• Education of Primary School Mathematics
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• v.9 no.2 s.18
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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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• v.21 no.6
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• pp.1203-1209
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• 2010

Internet addiction is a serious social problem in information society. The purpose of this study is to develope a small diagnostic scale in order to detect internet addiction easily. The reliability and validity of K-scale and Kimberly Young-scale is investigated. Five small diagnostic scale is suggested by factor analysis and regression. The comparision of these small scale is established by correlation coefficient, chi-square test, gamma value of concordance in contingency table. In view of reliability and validity, we suggest a small diagnostic scale. The results of this study may be useful to detect internet addiction by oneself.

• Education of Primary School Mathematics
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• v.14 no.3
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• pp.237-259
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• 2011

Mathematics learning disabilities is a specific learning disorder affecting the normal acquisition of arithmetic and spatial skills. Reported prevalence rates range from 5 to 10 percent and show high rates of comorbid disabilities, such as dyslexia and ADHD. In this study, the characteristics and the causes of this disorder has been examined. The core cause of mathematics learning disabilities is not clear yet: it can come from general cognitive problems, or disorder of innate intuitive number module could be the cause. Recently, researchers try to subdivide mathematics learning disabilities as (1) semantic/memory type, (2) procedural/skill type, (3) visuospatial type, and (4) reasoning type. Each subtype is related to specific brain areas subserving mathematical cognition. Based on these findings, the author has performed a basic research to develop grade specific diagnostic tests: number processing test and math word problems for lower grades and comprehensive math knowledge tests for the upper grades. The results should help teachers to find out prior knowledge, specific weaknesses of students, and plan personalized intervention program. The author suggest diagnostic tests are organized into 6 components. They are number sense, conceptual knowledge, arithmetic facts retrieval, procedural skills, mathematical reasoning/word problem solving, and visuospatial perception tests. This grouping will also help the examiner to figure out the processing time for each component.

• Korean Journal of Radiology
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• v.22 no.4
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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.