• Industry Promotion Research
• /
• v.2 no.2
• /
• pp.31-44
• /
• 2017

This study is to investigate the relationship between the communication type recognized by members of organization and the learning transfer climate in the organization, and when it comes to the type of communications within organization set as independent variable, four variables such as communication with supervisor, media quality communication, and organizational outlook communication were proposed and regarding learning transfer climate which is a dependent variable, four sub-parameters such as supervisor support, colleague support, transfer opportunity and organizational compensation recognition were selected. 116 copies of the statistical data excluding statistically insignificant surveys were used for 150 participants who participated in the 2015 core competency curriculum for SMEs and 3 months have passed, in order to achieve this study's objective. Meanwhile, the research hypothesis was verified with the collected data through frequency analysis, factor analysis, reliability verification, technical statistical analysis, and simple and multiple regression analysis by using the statistical package program of SPSS 20.0. Results of this study have shown that firstly, communication with supervisor, media quality communication, and organizational outlook communication all showed a positive (+) significant influence on the superior support in the influence relationship between communication type in organization and supervisor support which is learning transfer climate. Secondly, communication type in organization doesn't appear to affect colleague support of learning transfer climate. Thirdly, communication with supervisor, media quality communication, and organizational outlook except for communication with colleagues have shown a positive (+) influence on transfer opportunity in the influence relationship between communication type in organization and transfer opportunity of learning transfer climate. Lastly, communication with supervisor and communication on organizational outlook showed positive(+) influence in the influence relationship between communication type in organization and organizational compensation recognition of learning transfer climate.

• Journal of Digital Convergence
• /
• v.13 no.11
• /
• pp.119-132
• /
• 2015

This study empirically examined which factors facilitate or disturb the learning and practical knowledge transfer in consulting and which factors have most powerful influence on the learning and transfer of consulting knowledge. Analysing 160 data collected from FTA origin managers in export companies, the study findings show the ambiguity(-), complexity(+), consulting competences(+), intervention design and delivery(+), self-efficacy(+) and government subsidies(+) significantly affected on Client's learning, while consultant's expertise(+), consulting involvement(+), transfer culture(+) significantly affected on consulting knowledge transfer, respectively. It showed that consulting competence and causal ambiguity have an greater influence on learning while consultant's expertise has a greater influence on consulting knowledge transfer, respectively. The findings implicate that consulting success depends on rather consultant's factors(consultant's expertise and consulting competence) than client's input factors. To succeed in consulting project, it is important that the consultants effectively develop and apply consulting methods & tools as shared interfaces between consultant and client.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.14 no.6
• /
• pp.287-294
• /
• 2019

With the automation of production lines in the manufacturing industry, the importance of real-time fault diagnosis of facility is increasing. In this paper, we propose a fault diagnosis algorithm of LM (Linear Motion)-guide based on deep learning using vibration signals. Generally, in order to guarantee the performance of the deep learning, it is necessary to have a sufficient amount of data, but in a manufacturing industry, it is often difficult to obtain enough data due to physical and time constraints. To solve this problem, we propose a convolutional neural networks (CNN) model based on transfer learning. In addition, the spectrogram image is input to the CNN to reflect the frequency characteristic of the vibration signals with time. The performance of fault diagnosis according to various load condition and transfer learning method was compared and evaluated by experiments. The results showed that the proposed algorithm exhibited an excellent performance.

• Journal of The Korean Association For Science Education
• /
• v.37 no.6
• /
• pp.993-1003
• /
• 2017

Teachers expect team-based project learning to help students develop collaborative and real-world problem solving skills. In practice, however, students tend to solve problems with simple division of labor, and there is a tendency that learning transfer does not occur in solving problems. The purpose of this study is to develop a collaborative learning model based on the transactive memory system (TMS) and to verify its effectiveness. The collaborative learning model based on the TMS is composed of three stages. The first stage is developing TMS. In this stage, the students learn physics concepts and make knowledge about the expertise of group members through peer instruction. The second stage, activating TMS, is building trust through solving well-defined problems for developing near-transfer. And in the third stage, applying TMS, the students solve an ill-defined problem based on real-world context for practicing far-transfer. Based on this model, a 15-week program including two projects on geometric optics and sound waves was developed and applied to 60 college students. The data for five weeks of one project were collected and analyzed. As a result, the TMS of the experimental group with the TMS-based collaborative learning model improved stepwise. Whereas, the difference between the first week and the last week was statistically significant, while the TMS change of the comparison group using the general project learning model was not significant. Also, the experimental group showed that the learning transfer occurred better in the project than the comparison group. A collaborative learning model based on TMS can be used to learn how students gain synergy through collaboration and how students collaboratively transfer the learned concepts in problem solving.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.4
• /
• pp.2093-2108
• /
• 2017

In this paper, we describe a novel method for recognizing human actions from different views via view knowledge transfer. Our approach is characterized by two aspects: 1) We propose a unsupervised topic transfer model (TTM) to model two view-dependent vocabularies, where the original bag of visual words (BoVW) representation can be transferred into a bag of topics (BoT) representation. The higher-level BoT features, which can be shared across views, can connect action models for different views. 2) Our features make it possible to obtain a discriminative model of action under one view and categorize actions in another view. We tested our approach on the IXMAS data set, and the results are promising, given such a simple approach. In addition, we also demonstrate a supervised topic transfer model (STTM), which can combine transfer feature learning and discriminative classifier learning into one framework.

• The Journal of Korean Association of Computer Education
• /
• v.20 no.6
• /
• pp.61-69
• /
• 2017

The Goal of SW education is to improve computational thinking. Especially, non computer majors need to apply computational thinking to their problem solving in their fields after computational thinking class. In this paper, we verified what factors affect the improvement of computational thinking through mixed research method after teaching computational thinking to non major students. Also, we analysed the characteristics of initial learning transfer of computational thinking, and establish the reason about he validity and justification for non major in SW education. The result shows learning satisfaction, learning transfer motivation, and self-CT efficacy affect the perception about improvement of computational thinking. Also, we found that there is application of computational thinking was coming up with problem solving process because the initial learning transfer process of computational thinking has characteristics about concepts and practices of it in programming steps. The effectiveness and learning transfer process of computational thinking for non majors will give the validity and justification to teach SW education for all students.

• The Journal of Asian Finance, Economics and Business
• /
• v.6 no.1
• /
• pp.9-19
• /
• 2019

A recent survey of Australian directors conducted by the Financial Reporting Council found that directors require a detailed understanding of technical accounting issues. With the aim of understanding learner difficulties in learning and applying higher learning material relevant to directors, this study explores the transfer pricing topic taught as a case presentation in an undergraduate accounting program at an Australian university. Before intervention with improvements, this study invited 25 students to take part in the study after they had learned the topic and been given one week to understand it. By adopting a transfer pricing problem presented in their essential reading and interviewing those students to gain further insights, the study found that learners experienced conceptual difficulties at various stages in attempting to learn. Intervention to ease learning difficulties was addressed through instructor training. The intervention improvements included using guided workbooks to develop a better understanding of concepts among learners, and representing the problem at hand with diagrams. After intervention with improvements, this study repeated the same procedures with 25 students who had not taken part in the previous study and found that interventions increased the learning. Results have implications for most directors, who are novices to the detailed technical accounting issues of transfer pricing.

• PNF and Movement
• /
• v.11 no.2
• /
• pp.77-85
• /
• 2013

Purpose : The purpose of this study is to investigate the effects school business hospital-based integrated health education on learning transfer factor and level. Methods : This study conducted a questionnaire survey of 60 students at D college using metastatic diagnostic tool who took the integrated health education curriculum, statistical analysis utilized the SPSS 17.0 for window version. Results : On comparison of the details 5 clauses, 29 questions using LTSI, this study found that the integrated health education based on the school business hospital is effective for learning transfer. Conclusion : What the integrated health education based on clinic practice system at D college to overcome the limitations of health and medical line is effective for learning transfer and it will be useful to cultivate professional.

• Nuclear Engineering and Technology
• /
• v.54 no.6
• /
• pp.2297-2310
• /
• 2022

A condensation heat transfer model is essential to accurately predict the performance of the passive containment cooling system (PCCS) during an accident in an advanced light water reactor. However, most of existing models tend to predict condensation heat transfer very well for a specific range of thermal-hydraulic conditions. In this study, a new correlation for condensation heat transfer coefficient (HTC) is presented using machine learning technique. To secure sufficient training data, a large number of pseudo data were produced by using ten existing condensation models. Then, a neural network model was developed, consisting of a fully connected layer and a convolutional neural network (CNN) algorithm, DenseNet. Based on the hold-out cross-validation, the neural network was trained and validated against the pseudo data. Thereafter, it was evaluated using the experimental data, which were not used for training. The machine learning model predicted better results than the existing models. It was also confirmed through a parametric study that the machine learning model presents continuous and physical HTCs for various thermal-hydraulic conditions. By reflecting the effects of individual variables obtained from the parametric analysis, a new correlation was proposed. It yielded better results for almost all experimental conditions than the ten existing models.

• Education of Primary School Mathematics
• /
• v.3 no.1
• /
• pp.37-45
• /
• 1999

This paper investigates the comparative effectiveness of two kinds of instructional methods in transfer of mathematics learning: one based on the situated cognition, ie. situated learning and the other based on traditional learning. Two classes of second graders studied the instruction about 3-digit addition and subtraction. After that, they completed two written tests and a real situation test. As a result. no significant differences were found between the two group's performance on the written test 1 and real situation test. But the situated learning group performed significantly better on the performance of story problem than traditional group. This result indicated that the situated learning made improvement in transfer of mathematic loaming. As a result of interviews with 12 children, the situated loaming group's children were able to use contextual resources in solving real situation as well as story problems.