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.
Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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v.7
no.5
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pp.369-379
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2017
The purpose of this study was to improve an university tutoring program qualitatively, evaluating and analyzing the case of tutoring program that students attended in order to strengthen their learning competences through CIPP(Context-Input-Process-Product). To do this, a tutoring survey with satisfaction survey was carried out for 90 students who participated in the final reporting meeting among those who joined the tutoring program at the second semester of 2016 year at the B university. In addition, a tutor interim checking workshop was held for the 49 tutors and qualitative analyses were carried out on the reflection papers submitted by students who were involved in the tutoring program. Tutoring program assessments were carried out in terms of several steps and their view points. They were the necessity of tutoring program for the context evaluation, the appropriacy of human-material resources and program planning for the input evaluation, the teaching and learning activity for the process evaluation and the influence, effectiveness, sustainability, transferability for the product evaluation. Survey results showed that the average scores were presented 4.05 for the context evaluation, 3.88 for the input evaluation, 4.08 for the process evaluation and 3.92 for the product evaluation respectively. Similar analysis results were represented from the tutor workshops and the reflection paper analysis results. Learners were satisfied with all the evaluation items, scoring more than the average level. However, it was necessary for the evaluation items that were rated low range to improve the program through detail modification plans.
The purpose of this study was to investigate students' problem solving process based on the model of IDEAL if they learn to solve word problems of simultaneous linear equations through structure-representation instruction. The problem solving model of IDEAL is followed by stages; identifying problems(I), defining problems(D), exploring alternative approaches(E), acting on a plan(A). 160 second-grade students of middle schools participated in a study was classified into those of (a) a control group receiving no explicit instruction of structure-representation in word problem solving, and (b) a group receiving structure-representation instruction followed by IDEAL. As a result of this study, a structure-representation instruction improved word-problem solving performance and the students taught by the structure-representation approach discriminate more sharply equivalent problem, isomorphic problem and similar problem than the students of a control group. Also, students of the group instructed by structure-representation approach have less errors in understanding contexts and using data, in transferring mathematical symbol from internal learning relation of word problem and in setting up an equation than the students of a control group. Especially, this study shows that the model of direct transformation and the model of structure-schema in students' problem solving process of I and D stages.
Journal of the Korea Society of Computer and Information
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v.28
no.4
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pp.31-39
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2023
In this paper, we propose an Internal/External Knowledge Distillation (IEKD), which utilizes both external correlations between feature maps of heterogeneous models and internal correlations between feature maps of the same model for transferring knowledge from a teacher model to a student model. To achieve this, we transform feature maps into a sequence format and extract new feature maps suitable for knowledge distillation by considering internal and external correlations through a transformer. We can learn both internal and external correlations by distilling the extracted feature maps and improve the accuracy of the student model by utilizing the extracted feature maps with feature matching. To demonstrate the effectiveness of our proposed knowledge distillation method, we achieved 76.23% Top-1 image classification accuracy on the CIFAR-100 dataset with the "ResNet-32×4/VGG-8" teacher and student combination and outperformed the state-of-the-art KD methods.
Journal of the Korea Society of Computer and Information
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v.17
no.10
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pp.185-192
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2012
Call Center requires an ability of agents a lot more than face-to-face contact due to being achieved communication by non face-to face channel for contact with customers. In order to improve the ability of agents, Call Center carries out various educational training according to their work experience and function and with the accomplishment of educational training, Call Center is going to fulfill to develop its quality of counseling and productivity. On the other hand, due to investment of a lot of time and budget to educational training, it is needed to grasp and manage about its effectiveness that how helpful the training is for performance of work-site operations through evaluation of educational training. Having Seen researches about evaluation of educational training until these days, most researches have mainstream to measure satisfaction and a level of learning or degree that how the learning transfers to actions. It is found that a research about an entire evaluation model should be required. This study aims to investigate effectiveness of Call Center educational training from the level of recognition by reflecting Kirkpatrick's the four levels of learning evaluation. By the four levels, reaction, learning, behavior and results, the study found out a connection with standards of evaluation about each levels. In addition, by using structural equation modeling, it was examined goodness of fit about the entire model. Furthermore, by an alternative model, considering a direct relation between a factor of reaction and behavior, it was compared and examined goodness of fit of overall model of the study model and the alternative one.
Plant diseases and pests affect the growth of various plants, so it is very important to identify pests at an early stage. Although many machine learning (ML) models have already been used for the inspection and classification of plant pests, advances in deep learning (DL), a subset of machine learning, have led to many advances in this field of research. In this study, disease and pest inspection of abnormal crops and maturity classification were performed for normal crops using YOLOX detector and MobileNet classifier. Through this method, various plant pest features can be effectively extracted. For the experiment, image datasets of various resolutions related to strawberries, peppers, and tomatoes were prepared and used for plant pest classification. According to the experimental results, it was confirmed that the average test accuracy was 84% and the maturity classification accuracy was 83.91% in images with complex background conditions. This model was able to effectively detect 6 diseases of 3 plants and classify the maturity of each plant in natural conditions.
The purpose of this study is to examine the effect of violin learning as to enhance the attention span and impulsiveness of children with Attention Deficit Hyperactivity Disorder(ADHD). Three children with ADHD, grade 2, 3, 4 were selected to participate in the research. A total of 15 session were given during 8 week time span, including a final performance session. For measurement, Korean-Child Behavior Checklist(K-CBCL), Home Situation Questionnaire-Revised (HSQ-R), Conners Teacher Rating Scale-Revised (CTRS-R) were administered before and after the implementation. Other behavioral checklist were used to record inappropriate or interruptive behaviors. The results showed that violin learning has increased attention span and reduced impulsive behaviors of all three children with ADHD. Along with these changes, the identified inappropriate behaviors reduced as sessions progressed. Also the changes observed within the music environment were generalized to non-music environment, such as family and school. These results also indicate that violin can be a therapeutic medium used in music therapy setting to bring positive changes for children with ADHD problems.
Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.
Journal of the Korea Academia-Industrial cooperation Society
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v.21
no.2
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pp.335-344
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2020
This study compared the structures and changes of help network between pre-service secondary teachers and pre-journalists who participated in the class related to network analysis to seek ways to activate a professional learning community. For this study, we used Exponential Random Graph Models (ERGM) based on ties as being interdependent and not conventional regression models requiring assumptions of independence between observations. The analysis subjects were 43 pre-service secondary teachers and 29 pre-journalists who responded both early and late in the help network survey. The main results were as follows. First, full models with network structural terms were better than simple models with no structural terms. Second, the effect of transitivity was not statistically significant in the pre-service secondary teachers' network. However, it was statistically significant in the pre-journalists' network. Third, there were effects of reciprocity, indegree popularity, and outdegree activity in the early help network of pre-service secondary teachers. On the contrary, there were only the positive effects of reciprocity and the negative effect of outdegree activity in the late network. Finally, this study demonstrated the possibility in educational fields' application of network structural effects and provided limitations and directions for future research.
Kim, Youngshin;Park, Ae-Ryeon;Lim, Soo-min;Jeng, Jae-Hoon;Kim, Soo-Wan;Song, Ha-Young
Journal of Science Education
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v.33
no.1
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pp.69-76
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2009
Probabilistic reasoning and combinational reasoning are essential to build a logical thinking and a process of thinking dealing with everyday life as well as scientific knowledge. This research aims at finding the optimal period to teach reasoning to the students who haven't developed probabilistic reasoning and combinational reasoning. The treatment program was performed for 20 students from each grade who couldn't develop two parts of reasoning. The treatment program using baduk stones and cards was performed repeatedly, focusing on the specific activities. After four weeks of treatment program, the test to check the development of probabilistic reasoning and combinational reasoning was performed again and the changes of reasoning development were identified. After giving treatment program for reasoning development, 15.0%, 25.0% and 40.0% of improvement in the 4th, the 5th, the 6th graders respectively were shown. With regard to the combinational reasoning, the results showed the improvement of 20.0% in the 4th grades, 25.0% in the 5th graders and 63.2% in the 6th graders. As a result of research in the above, students, who were not formed probabilistic reasoning and combinational reasoning, could be known to be enhanced through learning, but to fail to be formed the qualitative change like the cognitive development. It is expected that this research can contribute to the improvement of students' cognitive level and there would be more active researches in different fields to improve the cognitive level of the 6th graders who are in their optimal periods to learn two parts of reasoning.
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