• 공학교육연구
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• 제16권2호
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• pp.11-23
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• 2013

The main purpose of this study was to examine the mediating effect of participation motivation of continuing professional development between the level of organizational learning transfer climate and learning transfer. In the analysis of the relationship among the level of the organizational learning transfer climate, learning transfer and participation motivation of CPD, organizational learning transfer climate had indirect influence on learning transfer through participation motivation of CPD. Based upon the findings of this study, several suggestions were made to improve professional engineers' participation and learning transfer in CPD and implement future research on professional engineer's CPD.

• 전기전자학회논문지
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• 제23권4호
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• pp.1408-1414
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• 2019

전이학습을 수행한 심층 인공신경망을 압축센싱 심혈관 자기공명영상에 적용하였다. 전이학습은 선행학습 신경망의 구조나 필터 커널, 가중치를 현재의 학습이나 응용에 활용하는 방법이다. 전이학습은 학습 속도를 향상시키고, 학습 데이터가 제한적일 때 신경망의 일반화에 도움이 된다. 8명의 건강한 지원자가 참여한 심장 자기공명영상 실험에서 전이학습을 수행한 신경망은 단독학습 신경망에 비해 학습시간이 5배 이상 단축되었다. 시험 데이터에 대해서도 전이학습을 수행한 신경망은 전이학습을 수행하지 않은 신경망에 비하여 낮은 정규화 평균제곱오차와 향상된 재구성 영상화질을 보였다.

• 기본간호학회지
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• 제22권3호
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• pp.297-307
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• 2015

Purpose: The purpose of this study was to identify the learning style, learning efficacy, transfer of learning, and confidence in performance competence of Core Basic Nursing Skills (CBNS) and factors influencing confidence in performance competence of CBNS by nursing students. Methods: A descriptive study design was used. Participants were 148 nursing students. Data were analyzed using SPSS 20.0 for descriptive statistics, ANCOVA, correlation and regression. Results: Learning styles of the participants were assimilator 33.11%, accommodator 26.35%, diverger 23.65%, and converger 16.89%. Learning efficacy was significantly different according to learning styles, however, transfer of learning and confidence in performance competence of CBNS were not significantly different according to learning styles. Confidence in performance competence of CBNS positively correlated with transfer of learning and learning efficacy. Transfer of learning was a significant predictor of confidence in performance competence of CBNS. Conclusion: The findings of this study indicate that transfer of learning influences confidence in performance competence of CBNS. Thus, nursing faculty should develop educational strategies to enhance and improve transfer of learning, and development of effective confidence in performance competence of CBNS programs.

• Asian Journal of Innovation and Policy
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• 제7권2호
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• pp.310-337
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• 2018

Adoption of mobile learning (m-learning) is not new in Malaysian oil and gas industry, with heavy investment into research and development to train the workers. Nevertheless, the low application of learnt skills on the job remains an emergent research area where there is a missing link on the effects of m-learning and effective organisational learning and implication on its training transfer. The result of this quantitative research revealed that all variables in m-learning were found to have a positive relationship with the effective organisational learning, and there is evidence of training transfer as a mediator of the relationship between self-directed learning, training design, work environment and effective organisational learning. However, there were some discrepancies in the extend of training transfer between trainee characteristics and organisational learning. As such, some important issues emerged which challenge the importance of evaluating workers' readiness and transfer for a successful implementation of m-learning towards developing effective organisational learning.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.165-165
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• 2023

Streamflow prediction is a critical task in water resources management and essential for planning and decision-making purposes. However, the streamflow prediction is challenging due to the complexity and non-linear nature of hydrological processes. The transfer learning is a powerful technique that enables a model to transfer knowledge from a source domain to a target domain, improving model performance with limited data in the target domain. In this study, we apply the transfer learning using the Informer model, which is a state-of-the-art deep learning model for streamflow prediction. The model was trained on a large-scale hydrological dataset in the source basin and then fine-tuned using a smaller dataset available in the target basin to predict the streamflow in the target basin. The results demonstrate that transfer learning using the Informer model significantly outperforms the traditional machine learning models and even other deep learning models for streamflow prediction, especially when the target domain has limited data. Moreover, the results indicate the effectiveness of streamflow prediction when knowledge transfer is used to improve the generalizability of hydrologic models in data-sparse regions.

• 한국정보시스템학회지:정보시스템연구
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• 제15권2호
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• pp.1-29
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• 2006

The recent development of IT, consolidation of communication and multimedia technology have brought enormous changes in many organizations. Theses changes are enabling the new educational opportunities such as distance teaming and virtual class room. Recently, e-Learning has grown rapidly in business training field, In the context of companies, e-Learning has merits in terms of access convenience, costs reduction self-directed learning, reciprocity, and flexibility. In this regard, the primary purpose of this study is to investigate which factors of e-Learning influence the effectiveness of education and transfer of loaming in business organizations. Based on the prior studies of the education and business training field, research model and research hypotheses were developed. Factors studied in this paper were as follows: 1) learners' characteristics, 2) organizational support and 3) system environments. The results of our study are as follows. (1) Motivation perceived usefulness in Learner factors had an significant influence on both learning effectiveness and transfer of teaming, whereas Ability, expectation had an influence on transfer of teaming. (2) Support from peer, support from supervisor in Organization factors had an significant influence on both Loaming effectiveness and transfer of teaming, whereas support from organization had influence on learning effectiveness. (3) Appropriate contents in system circumstance had an significant influence on both teaming effectiveness and transfer of teaming, whereas interface design had an influence on learning effectiveness.

• 한국멀티미디어학회논문지
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• 제21권10호
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• pp.1195-1202
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• 2018

Artificial neural network is widely used for its excellent performance and implementability. However, traditional neural network needs to learn the system from scratch, with the addition of new input data, the variation of the observation environment, or the change in the form of input/output data. To resolve such a problem, the technique of transfer learning has been proposed. Transfer learning constructs a newly developed target system partially updating existing system and hence provides much more efficient learning process. Until now, transfer learning is mainly studied in the field of image processing and is not yet widely employed in acoustic data processing. In this paper, focusing on the scalability of transfer learning, we apply the concept of transfer learning to the problem of guitar chord classification and evaluate its performance. For this purpose, we build a target system of convolutional neutral network (CNN) based 48 guitar chords classification system by applying the concept of transfer learning to a source system of CNN based 24 guitar chords classification system. We show that the system with transfer learning has performance similar to that of conventional system, but it requires only half the learning time.

• 지식경영연구
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• 제9권4호
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• pp.1-16
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• 2008

The purpose of the present study is to explain the effects of academic self-efficacy, self-regulated learning and online task value on academic achievement and learning transfer in corporate cyber education. 202 students who completed S corporate's cyber courses in 2007 and responded to all survey participated in this study. A hypothetical model was proposed, which was composed of academic self-efficacy, online task value and self-regulated learning factors as prediction variables, and learning transfer as well as academic achievement factors as outcome variables. The results of this study through regression analysis as follows. First, learners' academic self-efficacy, self-regulated learning and online task value predict learners' academic achievement significantly. Second, except for academic self-efficacy, learners' self-regulated learning and online task value predict on learners' learning transfer significantly. Third, academic achievement plays a role as mediating value in predicting academic achievement by online task. It implies that learners' academic self-efficacy, online task value and self-regulated learning which predict learners' academic achievement and learning transfer should be considered in developing strategies for the design and operation of cyber courses.

• 한국콘텐츠학회논문지
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• 제13권8호
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• pp.482-489
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• 2013

본 연구는 일개 대학에서 e-Learning 수업을 듣고 있는 간호학과 학생 239명을 대상으로 학습전이 인식수준과 만족도에 영향을 미치는 e-Learning 교수설계 변인을 밝히고자 시행된 서술적 조사연구이다. 그 결과, 대상자의 학습전이 인식수준에 영향을 미치는 도입의 하부영역은 학습상황 및 방향제시, 학습자 초기 동기화로 나타났으며, 이는 41%의 설명력이 있었다(F=81.16, p<.001). 대상자의 학습전이 인식수준에 영향을 미치는 학습객체의 하부영역은 동기화, 학습목적 일치, 접근성, 피드백 및 적합으로 나타났으며, 이는 46%의 설명력이 있었다(F=50.69, p<.001). 대상자의 만족도에 영향을 미치는 도입의 하부영역은 학습상황 및 방향제시, 학습자 초기 동기화로 나타났으며, 이는 33%의 설명력이 있었다(F=59.32, p<.001). 대상자의 만족도에 영향을 미치는 학습객체의 하부영역은 동기화, 표현설계, 상호작용 유용성, 피드백 및 적합, 학습목적 일치, 콘텐츠 품질로 나타났으며, 이는 52%의 설명력이 있었다(F=43.93, p<.001). 이를 통해 대학 e-Learning 프로그램의 교수설계 요인이 학습자의 학습전이와 만족도에 영향을 미치고 있다는 것을 알 수 있었다. 이는 e-Learning 프로그램 교수설계 전략을 개발하기 위한 기초자료로서 활용될 수 있을 것이다.

• 한국직업건강간호학회지
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• 제29권4호
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• pp.354-362
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• 2020

Purpose: This study aimed to define and clarify learning transfer in nursing. Methods: This study used a hybrid model to analyze the concept of learning transfer in nursing through three phases. For the theoretical phase, learning transfer attributes were identified through a scoping literature review. In the fieldwork phase, in-depth focus group interviews were conducted to develop attributes. Purposive sampling was performed with ten participants(five nursing students, two nurses, three nursing faculty members). In the analysis phase, the attributes and final analysis of learning transfer in nursing were extracted and integrated from the previous two phases. Results: According to the analysis, learning transfer was represented in two dimensions with eight attributes. The development of competency dimension had three attributes: 1) theory acquisition, nursing skills, professional attitude, 2) integration, and 3) analysis competency. The competency change dimension had five attributes: 1) appropriateness in patient care, 2) proficiency in patient care, 3) satisfaction, 4) achievement, and 5) confidence. Conclusion: The concept analysis might provide a basic understanding of learning transfer, a development framework toward a measurement of nursing learning transfer and effective educational nursing strategies.