• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.9
• /
• pp.6027-6035
• /
• 2015

The purpose of this study was to examine influential factors for the transition to college life and career identity of nursing students and what changes social support from parents brought about to them by academic year. The subjects in this study were 542 selected students who majored in nursing in four-year universities located in Seoul and the provinces. A self-administered survey was conducted to find out their general characteristics, social support from fathers and mothers, college adjustment and career identity. A hierarchical regression analysis was made to determine how social support from parents affected the college adjustment and career identity of the nursing students. Social support from parents had an impact on their college adjustment and career identity. The factors that affected college adjustment were academic year, satisfaction level with major and emotional support from mothers, and the factors that impacted on career identity were academic year, satisfaction level with major and informative support from fathers. In order to facilitate the college adjustment of nursing students, professors should try to develop efficient learning methods, meet with parents to inform them of the necessity of social support, share information on the major field of study and learning methods, and provide an opportunity for students to communicate with graduates or students who are years ahead of them in college so that they could have a better understanding of majoring in nursing.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.10C
• /
• pp.1007-1012
• /
• 2003

In order to accelerate the convergence speed of the conventional BP algorithm, constrained optimization techniques are applied to the BP algorithm. First, the noise-constrained least mean square algorithm and the zero noise-constrained LMS algorithm are applied (designated the NCBP and ZNCBP algorithms, respectively). These methods involve an important assumption: the filter or the receiver in the NCBP algorithm must know the noise variance. By means of extension and generalization of these algorithms, the authors derive an adaptive error-constrained BP algorithm, in which the error variance is estimated. This is achieved by modifying the error function of the conventional BP algorithm using Lagrangian multipliers. The convergence speeds of the proposed algorithms are 20 to 30 times faster than those of the conventional BP algorithm, and are faster than or almost the same as that achieved with a conventional linear adaptive filter using an LMS algorithm.

• Journal of Digital Convergence
• /
• v.15 no.7
• /
• pp.329-342
• /
• 2017

This study investigates convergent influence on Self Factors(SF), Stress Factors(STF), Resilience & Control Factors(RCF), Test Anxiety(TA), Learning Flow(LF) and academic burnout among Health College Students in TOEIC class(HCST). The survey was administered to 291 HCST from 1 college located in J area during the period from April 3, 2017 to April 14, 2017. The structured self-administered questionaries were used. With the analysis of covariance structure, we could confirm relationship among the six factors such as SF, STF, RCF, TA, LF and academic burnout. The results of the study indicate that the efforts, to manage these factors, are required to decrease the academic burnout of HCST. Squared multiple correlations, which explain the academic burnout related with the stress from economic pressure and job seeking, test anxiety, learning flow and self factors, were 98.8%. The results are expected to be useful for the development of TOEIC learning curriculum and course to decrease the academic burnout of HCST. In the following study, the analysis about additional factors of influence on academic burnout will be needed.

• Journal of the Korean Society of Earth Science Education
• /
• v.9 no.2
• /
• pp.123-138
• /
• 2016

The purpose of this study is to examine the effects of applying the Question-Answer Relationship (QAR)strategy on the attitude toward science of the elementary fifth grade students whose learning styles have beenidentified. The population of the study constitutes the total of 97 elementary fifth grade students who wereassigned into a comparison (n=48) or experimental group (n=49). To understandhow the QAR strategy potentially influencedscientific attitude, both groups were surveyedin the areas of scientific attitude before and after the experiment. TheKolb's Test was used to identifythe students' learning stylein the experimental group. According tothe learners' learning style, the results have been compared and analyzed. The results of this study are as follows:First, the findings revealed a significant difference in the experimental group students' attitude toward sciencecompared to the comparison group. Second, four learning styles were identified among the studentsin theexperimental group: a) Accommodators (46.9%), b) Convergers (24.5%), c) Divergers (20.4%), and d) Assimilator (8.2%). Following the data analysis, there was no meaningful statistical difference between four groups oflearning styles with respect to their scientific attitude.Applyingthe QAR strategy in a science class seemed toimprove the accommodators, convergers, and divergers' scientific attitude positively.

• 교육공학연구
• /
• v.33 no.4
• /
• pp.1001-1024
• /
• 2017

Flipped classroom has used widely in university in that its unique structure can facilitate learners' higher-thinking skills and promote competencies. Learners are expected to extend knowledge through performing online and offline, but they have difficulty in understanding their roles and specific behaviors to achieve the learning goals in the flipped learning. Therefore, a guidance for students has been required to support learners' mastery learning. The purpose of this study is to identify successful learners' characteristics in terms of "competency". For this, three-phased competency modeling was employed. In Phase I, Behavioral Event Interviews were conducted with eight learners of the flipped classroom. In Phase II for identifying competencies and developing a competency model, the data was coded, followed by testing reliability of the coding. Based on the meaning codes, competencies and behavioral indexes were developed. The final competencies consist of learning orientation, learning management, feedback seeking, peer interaction, and knowledge extension. In Phase III, validation of the competency model was conducted by explanatory factor analysis. As last, competencies were aligned by the two-phase of the flipped classroom. The finding will be used as the guidance for the learners and instructors in the flipped classroom.

• Journal of the Korean Society of Radiology
• /
• v.3 no.1
• /
• pp.29-39
• /
• 2009

In this paper has proposed to the recognition of the disease on medical images using neural network. The neural network is constructed as three-layers of the input-layer, the hidden-layer and the output-layer. The training method applied for the recognition of disease region is adaptive error back-propagation. The low-frequency region analyzed by DWT are expressed by matrix. The coefficient-values of the characteristic polynomial applied are n+1. The normalized maximum value +1 and minimum value -1 in the range of tangent-sigmoid transfer function are applied to be use as the input vector of the neural network. To prove the validity of the proposed methods used in the experiment with a simulation experiment, the input medical image recognition rate the evaluation of areas of disease. As a result of the experiment, the characteristic polynomial coefficient of low-frequency area matrix, conversed to 4 level DWT, was proved to be optimum to be applied to the feature parameter. As for the number of training, it was marked fewest in 0.01 of learning coefficient and 0.95 of momentum, when the adaptive error back-propagation was learned by inputting standardized feature parameter into organized neural network. As to the training result when the learning coefficient was 0.01, and momentum was 0.95, it was 100% recognized in fifty-five times of the stomach image, fifty-five times of the chest image, forty-six times of the CT image, fifty-five times of ultrasonogram, and one hundred fifty-seven times of angiogram.

• Journal of Korean Home Economics Education Association
• /
• v.18 no.2 s.40
• /
• pp.15-27
• /
• 2006

The purpose of this research was to develop and analyze the effects of ICT based teaching learning process plans for 'Designing My Home' unit of Technology Home Economics subject in High School. The seven housing contents were selected from 8 textbooks and 8 teaching resources at the analyses stage. A specific homepage(ieduhome.cafe.com) was built to utilize the eight ICT teaching learning process plan as well as many other resources at the planning & development stages. The number of 68 highschool students have participated for the application stage during September 4-26, 2003 and the same number have studied the same contents through regular teaching learning plans as a comparison group. Experimental groups have significantly more increased in the knowledge and understanding of the housing contents than have comparison groups. The same results occurred in the interests in Home Economics, Housing, and Internet utilized study. The Design reports were not statistically differed between two groups based on the objective evaluation criteria. The results of this study generally supported previous research and showed that the In teaching learning plans were more effective in various aspects than were the regular plans.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2010.05a
• /
• pp.1159-1163
• /
• 2010

최근의 극심한 기상이변으로 인하여 발생되는 유출량의 예측에 관한 사항은 치수 이수는 물론 방재의 측면에서도 역시 매우 중요한 관심사로 부각되고 있다. 강우-유출 관계는 유역의 수많은 시 공간적 변수들에 의해 영향을 받기 때문에 매우 복잡하여 예측하기 힘든 요소이다. 과거에는 추계학적 예측모형이나 확정론적 예측모형 혹은 경험적 모형 등을 사용하여 유출량을 예측하였으나 최근에는 인공신경망과 퍼지모형 그리고 유전자 알고리즘과 같은 인공지능기반의 모형들이 많이 사용되고 있다. 하지만 유출량을 예측하고자 할 때 학습자료 및 검정자료로써 사용되는 유출량은 수위-유량 관계곡선식으로부터 구하는 경우가 대부분으로 이렇게 유도된 유출량의 경우 오차가 크기 때문에 그 신뢰성에 문제가 있을 것으로 판단된다. 따라서 본 논문에서는 선행우량 및 수위자료로부터 단시간 수위예측에 관해 연구하였다. 신경망은 과거자료의 입 출력 패턴에서 정보를 추출하여 지식으로 보유하고, 이를 근거로 새로운 상황에 대한 해답을 제시하도록 하는 인공지능분야의 학습기법으로 인간이 과거의 경험과 훈련으로 지식을 축적하듯이 시스템의 입 출력에 의하여 연결강도를 최적화함으로서 모형의 구조를 스스로 조직화하기 때문에 모형의 구조에 적합한 최적 매개변수를 추정할 수 있다. 따라서 정확한 예측이 어려운 하천수위를 과거의 자료로 부터 학습된 신경망의 수학적 알고리즘을 통해 유출량의 예측에 적용할 수 있을 것이다. 유전자 알고리즘은 적자생존의 생물학 원리에 바탕을 둔 최적화 기법중의 하나로 자연계의 생명체 중 환경에 잘 적응한 개체가 좀 더 많은 자손을 남길 수 있다는 자연선택 과정과 유전자의 변화를 통해서 좋은 방향으로 발전해 나간다는 자연 진화의 과정인 자연계의 유전자 메커니즘에 바탕을 둔 탐색 알고리즘이다. 즉, 자연계의 유전과 진화 메커니즘을 공학적으로 모델화함으로써 잠재적인 해의 후보들을 모아 군집을 형성한 뒤 서로간의 교배 혹은 변이를 통해서 최적 해를 찾는 계산 모델이다. 따라서 본 연구에서는 인공신경망의 가중치를 유전자 알고리즘에 의해 최적화시킨후 오류역전파알고리즘에 의해 신경망의 학습을 진행하는 모형으로 감천유역의 선산수위표지점의 수위를 1시간~6시간까지 예측하였다.

• The Journal of the Korea Contents Association
• /
• v.18 no.7
• /
• pp.272-281
• /
• 2018

The purpose of this study was to examine the influence of an academic tutoring program on interpersonal relationships, self- directed learning capability and academic self-efficacy. The research question posed in this study was whether an academic tutoring program would affect interpersonal relationships, self-directed learning capability and academic self-efficacy. To address the research question, a self-administered survey was conducted to gather data on 214 students who participated in an academic tutoring program during a semester from September 4 to November 10, 2017. The findings of the study were as follows: After their participation in the tutoring program, there was a little decrease in self-directed learning capability and personal learning orientation, and they made progress in interpersonal relationships and academic self-efficacy. By gender, there was the greatest improvement in interpersonal relationships as well after their participation in the tutoring program. By academic year and motivation for participation, they showed the best improvement in interpersonal relationships as well, followed by academic self-efficacy. In other words, it could be said that the parts which the tutoring program brought about the biggest change to and worked best on were interpersonal relationships and academic self-efficacy. In conclusion, the improvement of interpersonal relationships and academic self-efficacy could boost not only the school adjustment of students but their academic levels and then eventually prevent them from dropping out. Therefore this program seems to be one of outstanding learning programs that could make a contribution to the stable management and qualitative competitiveness of universities.

• Journal of the Korea Computer Industry Society
• /
• v.2 no.3
• /
• pp.377-388
• /
• 2001

Software metrics provide effective methods for characterizing software. Metrics have traditionally been composed through the definition of an equation, but this approach restricted within a full understanding of every interrelationships among the parameters. This paper use fuzzy logic system that is capable of uniformly approximating any nonlinear function and applying cognitive psychology theory. First of all, we extract multiple regression equation from the factors of 12 software complexity metrics collected from Java programs. We apply cognitive psychology theory in program volume factor, and then measure program volume complexity to execute fuzzy learning. This approach is sound, thus serving as the groundwork for further exploration into the analysis and design of software metrics.