• Educational Technology International
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• v.11 no.2
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• pp.43-75
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• 2010

The purpose of this study is to identify patterns of learner behaviors, conflicting and facilitating factors during collaborative work in an online learning community(OLC). This study further seeks to investigate the difference of learner behaviors between high- and low-performing groups, and conflicting and facilitating factors. The online postings from four groups(19 students) in the spring semester(study 1) and six groups(24 students) in the fall semester(study 2) were analyzed. A coding scheme was generated based on constant comparison using the qualitative data analysis tool, NVivo. The analysis identified 7 categories of learner behaviors in both studies. Among the seven categories, information seeking and co-construction were most frequently observed in both studies. One evident difference between the high- and low-performing groups was that the high-performing groups revealed more incidents of learner behaviors in both studies. In addition, six categories of conflicting factors and five categories of facilitating factors were emerged in both studies. The inefficiency of work category was one of the most frequently observed categories in both studies. Interestingly, the high-performing groups showed more incidents of conflicting factors than the low-performing groups. This study revealed two different types of conflicting factors and there is a need for different moderating strategies depending on its type. Based on the results of the study, effective design strategies for an OLC to facilitate active learning were suggested.

• Safety and Health at Work
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• v.6 no.3
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• pp.211-217
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• 2015

Background: E-learning-based programs have recently been introduced to the occupational safety and health (OSH) education for migrant workers in Korea. The purpose of this study was to investigate how the factors related to migrant workers' backgrounds and the instructional design affect the migrant workers' satisfaction with e-learning-based OSH education. Methods: The data were collected from the surveys of 300 migrant workers who had participated in an OSH education program. Independent sample t test and one-way analysis of variance were conducted to examine differences in the degree of learning satisfaction using background variables. In addition, correlation analysis and multiple regression analysis were conducted to examine relationships between the instructional design variables and the degree of learning satisfaction. Results: There was no significant difference in the degree of learning satisfaction by gender, age, level of education, number of employees, or type of occupation, except for nationality. Among the instructional design variables, "learning content" (${\beta}=0.344$, p < 0.001) affected the degree of learning satisfaction most significantly, followed by "motivation to learn" (${\beta}=0.293$, p < 0.001), "interactions with learners and instructors" (${\beta}=0.149$, p < 0.01), and "previous experience related to e-learning" (${\beta}=0.095$, p < 0.05). "Learning environment" had no significant influence on the degree of learning satisfaction. Conclusion: E-learning-based OSH education for migrant workers may be an effective way to increase their safety knowledge and behavior if the accuracy, credibility, and novelty of learning content; strategies to promote learners' motivation to learn; and interactions with learners and instructors are systematically applied during the development and implementation of e-learning programs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.83-93
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• 2019

The purpose of this study is to suggest implications for maximizing the effectiveness and efficiency of IPP work-learning by studying the effects of the personal characteristics of trainees and firm's field teacher on trainees' employability. The following conclusions were drawn by verifying the causal relationship between factors based on a questionnaire (157 copies) distributed to 200 trainees (learning workers) of 9 universities participating in IPP work-learning training. First, in order to increase the employability of IPP trainees, it is necessary to select trainees with strong core competencies and failure tolerance by verifying individual characteristics of trainees. Secondly, companies should appoint senior staff with strong leadership and teaching capacity as corporate field teachers, and corporate field teacher training institutions should reinforce the training to improve their leadership. Third, work-learning companies should be selected as those with high social integration and absorption capacity, and those companies should try to build an organizational culture of acquiring and learning new technologies. The results of this study are expected to contribute to enhancing the effectiveness of work-learning training by establishing a training system that can systematically select trainees and participating companies and enhance the training capacity of companies and field teachers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.446-465
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• 2015

In this modern era of technology and information, e-learning approach has become an integral part of teaching and learning using modern technologies. There are different variations or classification of e-learning approaches. One of notable approaches is Personal Learning Environment (PLE). In a PLE system, the contents are presented to the user in a personalized manner (according to the user's needs and wants). The problem arises when a new user enters the system, and due to the lack of information about the new user's needs and wants, the system fails to recommend him/her the personalized e-learning contents accurately. This phenomenon is known as cold-start problem. In order to address this issue, existing researches propose different approaches for recommendation such as preference profile, user ratings and tagging recommendations. In this research paper, the implementation of a novel interaction-based approach is presented. The interaction-based approach improves the recommendation accuracy for the new-user cold-start problem by integrating preferences profile and tagging recommendation and utilizing the interaction among users and system. This research work takes leverage of the interaction of a new user with the PLE system and generates recommendation for the new user, both implicitly and explicitly, thus solving new-user cold-start problem. The result shows the improvement of 31.57% in Precision, 18.29% in Recall and 8.8% in F1-measure.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.233-244
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• 2023

Although artificial intelligence and machine learning technologies have been used in various fields, problems with personal information protection have arisen based on centralized data collection and processing. Federated learning has been proposed to solve this problem. Federated learning is a process in which clients who own data in a distributed data environment learn a model using their own data and collectively create an artificial intelligence model by centrally collecting learning results. Unlike the centralized method, Federated learning has the advantage of not having to send the client's data to the central server. In this paper, we quantitatively present the performance improvement when federated learning is applied using the building change detection learning data. As a result, it has been confirmed that the performance when federated learning was applied was about 29% higher on average than the performance when it was not applied. As a future work, we plan to propose a method that can effectively reduce the number of federated learning rounds to improve the convergence time of federated learning.

• Journal of Engineering Education Research
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• v.12 no.4
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• pp.142-149
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• 2009

This paper deals with the analysis and comparison between on the course of a conventional engineering design (typically project-based learning) and a new engineering design (introduced PBL model to conventional engineering design). The purpose of the study is to identify and prove the effect of PBL model on the course with a new teaching-learning. In the result of t-test, there were significant statistics in the creative problem solving and self-directed learning ability, but no significant statistics in the team work and communication skill ability. Also the average of factors of the problem-based strategy is higher than those of the project-based strategy. In the problem-based strategy, the team work has the most influential on the satisfactory of the course. However in the project-based strategy, the comprehension of given product has the most influential on the satisfactory. Finally, this study has proved the effect of PBL on the course engineering design.

• Current Optics and Photonics
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• v.8 no.3
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• pp.239-245
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• 2024

This paper proposes single logarithmic amplification (single-LA) and deep learning (DL)-based fixed-threshold on-off keying (OOK) detection for free-space optical (FSO) communication. Multilevel LAs (MLAs) can be used to mitigate intensity fluctuations in the received OOK signal by their nonlinear gain characteristics; however, it is ineffective in the case of high scintillation, owing to degradation of the OOK signal's extinction ratio. Therefore, a DL technique is applied to realize effective scintillation compensation in single-LA applications. Fully connected (FC) networks and fully connected neural networks (FCNN), which have nonlinear modeling characteristics, are deployed in this work. The performance of the proposed method is evaluated through simulations under various scintillation effects. Simulation results show that the proposed method outperforms the conventional adaptive-threshold-decision, single-LA-based, MLA-based, FC-based, and FCNN-based OOK detection techniques.

• The Journal of Korean Association of Computer Education
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• v.11 no.6
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• pp.95-102
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• 2008

In this paper through the implementation of cooperative learning using SDG, education puzzle actually applies to computer training. SDG(Single Display Groupware) which one computer display have a multi-input devices can work as a collaborative system. Learners are performing together through SDG-based cooperative learning system. SDG cooperative learning with a multi-input device is superior to traditional learning with individual. We have implementation of the puzzle game with this fact. This system through effective education and raising their children's education participation rate will be able to do.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.671-679
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• 2023

This study aims to establish an evaluation model by quantifying the evaluation index as a follow-up study to the development of evaluation index for work-study parallel learning companies. An evaluation model was established by verifying the 2nd level components based on the quantitative factors of the learning company, the qualitative factors, the competency factors of the person in charge, and the competency factors of the learning workers, which are the highest-level components derived from previous study. For the evaluation of a learning company, an AHP survey was conducted with experts in charge of the company consulting to derive important factors that determine the quality of on-site education and training, and the evaluation model of the learning company was completed and grouped by calculating the weight between evaluation items proceeded. Work-study parallel program was promoted as a key policy to resolve the mismatch between industrial sites and school education and realize a competency-centered society, and as of December 2022, 16,664 companies participated in the training. Learning companies play a very important role as education and training supply organizations that conduct field training. It is expected that the support and consulting plan for each level of learning companies according to the evaluation model presented in this study will be used as basic data to improve the quality of work-study parallel program.

• The Journal of Korean Association of Computer Education
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• v.14 no.6
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• pp.53-64
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• 2011

This paper proposes and evaluates empirically a new recommendation method in order to improve the learning achievement of learners using case-based method. In this paper, we first carried out a survey targeting teachers who work currently in Gyeongbuk area, and constructed learning cases depending on critical factors of learning. We next recommended differentiated learning methods to learners classifying according to learning cases by achievement level through this survey. The students of a middle school took part in the experiment in order to evaluate empirically the proposed learning cases. The students were divided into three groups by their achievement level and three separate learning cases were applied to each group. The weights among learning improvement elements applying to each group were added through the survey result of teachers. The experiment using the proposed case-based recommendation method showed that the learning achievement of learners is improved considerably compared to the previous one.