• Journal of Digital Convergence
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• v.13 no.3
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• pp.11-18
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• 2015

After entering a convergence era, South Korea Government has enacted and announced the Standard Contract on the e-Learning Content Development Project, a year and eight months has passed. Nevertheless, there has been continued still the unjust and unreasonable contract practices issues raised by project owner in the e-Learning industry. This study investigated application status of the Standard Contract via FGI and questionnaires and suggested its improvement alternative. This study analyzed that the Standard Contract has not taken root at all in ordering of the e-Learning content development project and not reaped the effect. This study presented alternatives such as mandatory application of the Standard Contract, education and outreach, introduction of the monitoring system, certification system implementation, granting of additional points in the evaluation of agencies and CEO and etc. to that standard contract is settled as the government's intentions and objectives in the e-Learning industry field.

• The Journal of Korean Academic Society of Nursing Education
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• v.18 no.2
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• pp.268-275
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• 2012

Purpose: The purpose of this study was to implement and evaluate the learning contracts based self-directed learning in a final clinical placement for senior nursing students. Methods: This study was a case study and 82 senior nursing students at a university participated in a learning contract based practice placement. Data were collected from written learning contracts and questionnaires after a clinical practice. Results: The students' learning needs were knowledge, clinical skills, and attitudes frequently encountered in a ward in which clinical skills were most common. The students' formulated learning contracts were varied but most of them were basic and simple. A self-directed clinical course was beneficial and a satisfactory experience to senior students. There was an increase in the students' motivation in learning, confidence in own capability, and satisfaction with the use of the learning contract. Conclusion: Self-directed clinical practicum would result in a degree of attitude change in the students. This study suggests that learning contract based self-directed clinical practice is effective to improve learning satisfaction, confidence in own capability, and competency.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.195-201
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• 2022

For a efficient distance education environment, the need for correct problem recommendation guides considering the learner's exact learning pattern is increasing. In this paper, we study block chain based smart contract technology to suggest a method for presenting the optimal problem recommendation path for individual learners based on the data given by situational weights to the problem patterns of learners collected in the distance education environment. For the performance evaluation of this study, the learning satisfaction with the existing similar learning environment, the usefulness of the problem recommendation guide, and the learner data processing speed were analyzed. Through this study, it was confirmed that the learning satisfaction improved by more than 15% and the learning data processing speed was improved by more than 20% compared to the existing learning environment.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.19-28
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• 2005

A web-based instructor-learner system has changed the form into a learner-centered environment. Especially a self-regulated learning which is a self-leading and a positive learning, is an ideal learning, and the interest on it is more increasing. In this research, learners can organize the individualized course based on the learner's demand and learning level after making a contract process with the system, The self-regulated learning system which can recognize a learning status and result by analyzed data, and which can lead to a learning goal effectively by establishing a learning strategy, is designed and implemented. The proposed system provides the learner-centered learning environment which can process the differentiated and flexible individualized-teaming service considering an individual characteristic.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.199-208
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• 2023

Performance analysis for work-learning dual system has been mainly conducted from the perspective of diagnosing the effectiveness of policies at the macro level. This study aims to analyze issues in organizational management of the work-learning dual system training center by conducting an analysis focusing on the organizational performance of the work-learning dual system training center's employees. As a result of the analysis, it was confirmed that the perception and attitude of employees toward the work-learning dual training center differed depending on the type of work-learning dual system and the type of employment contract. Among the types of work-learning dual system, overall, in the case of IPP, the organizational performance of employees was low, while the apprenticeship was relatively high. As for the type of employment contract, the need for institutional improvement has been derived, especially for the project contract workers.

• Journal of the Korean Home Economics Association
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• v.42 no.12 s.202
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• pp.123-140
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• 2004

The purpose of this study was to explore the unfairness of adhesion contracts for internet contents service. The internet contents were classified into six types of avatar, learning, download, e-book and movie internet sites. The adhesion contracts of internet contents service were collected in 60 internet sites. The unfairness of the adhesion contract was reviewed under the adhesion contract regulation act. The major results were as follows. First, the obligation of clear statement, explanation, and delivery was not observed completely. Second, many articles of adhesion contract were unfair and they especially violated articles 7 and 9. Therefore, the standard adhesion contract system for internet content service should be enforced and self-regulation of information service providers is needed.

• The Journal of Information Systems
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• v.30 no.2
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• pp.105-126
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• 2021

Purpose The purpose of this study is to implement a optimal machine learning model about the cancellation prediction performance in car sales business. It is to apply the data set of accumulated contract, cancellation, and sales information in sales support system(SFA) which is commonly used for sales, customers and inventory management by imported car dealers, to several machine learning models and predict performance of cancellation. Design/methodology/approach This study extracts 29,073 contracts, cancellations, and sales data from 2015 to 2020 accumulated in the sales support system(SFA) for imported car dealers and uses the analysis program Python Jupiter notebook in order to perform data pre-processing, verification, and modeling that is applying and learning to Machine learning model after then the final result was predicted using new data. Findings This study confirmed that cancellation prediction is possible by applying car purchase contract information to machine learning models. It proved the possibility of developing and utilizing a generalized predictive model by using data of imported car sales system with machine learning technology. It can reduce and prevent the sales failure as caring the potential lost customer intensively and it lead to increase sales revenue by predicting the cancellation possibility of individual customers.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.201-207
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• 2021

Deep learning, a type of machine learning, performs learning while changing the weights as it progresses through each learning process. Tensor Flow and Keras provide the results of the end of the learning in graph form. Thus, If an error occurs, the result must be discarded. Consequently, existing technologies provide a function to roll back learning results, but the rollback function is limited to results up to five times. Moreover, they applied the concept of MLOps to track the deep learning process, but no rollback capability is provided. In this paper, we construct a system that manages the intermediate value of the learning process by blockchain to record the intermediate learning process and can rollback in the event of an error. To perform the functions of blockchain, the deep learning process and the rollback of learning results are designed to work by writing Smart Contracts. Performance evaluation shows that, when evaluating the rollback function of the existing deep learning method, the proposed method has a 100% recovery rate, compared to the existing technique, which reduces the recovery rate after 6 times, down to 10% when 50 times. In addition, when using Smart Contract in Ethereum blockchain, it is confirmed that 1.57 million won is continuously consumed per block creation.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.57-66
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• 2022

Claims and disputes are major causes of cost and schedule overruns in the construction business. In order to manage claims and disputes effectively, it is necessary to analyze various types of contract documents punctually and accurately. Since volume of such documents is so vast, analyzing them in a timely manner is practically very challenging. Recently developed approaches such as artificial intelligence (AI), machine learning algorithms, and natural language processing (NLP) have been applied to various topics in the field of construction contract and claim management. Based on the systematic literature review, this paper analyzed the goals, methodologies, and application results of such approaches. AI methods applied to construction contract management are classified into several categories. This study identified possibilities and limitations of the application of such approaches. This study contributes to providing the directions for how such approaches should be applied to contract management for future studies, which will eventually lead to more effective management of claims and disputes.

• Knowledge Management Research
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• v.17 no.2
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• pp.205-229
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• 2016

Owing to the current economic downturn, one of the most important goals of the organizations who are actively involved in Information Technology Outsourcing (ITO) is the cost efficiency. We focus on supplier firm's domain understanding to make the cost efficiency; therefore, we examine how the disadvantages from lower domain knowledges affect outsourcing performance moderated by outsourcing ratio and knowledge change environments. That is, if clients can endure disadvantage from service providers' lower domain knowledge, they can achieve cost efficiency by choosing lower domain knowledge suppliers with less expensive cost. To examine performance gap depending on the environments, we applied 'A Learning Model of IT Outsourcing' which is suggested by previous literature. As a result, we suggest five strategies for clients to contract with suppliers which have lower domain knowledge: (1) Prepare the strategy to endure disadvantages from the early stage. (2) Make the strategy depending on outsourcing ratio. (3) Knowledge transfer between organizations is important. (4) Make a short-term contract if they do not have good environments for organizational learning. (5) Client's knowledge change environments are more important than those of supplier's. Finally, we offer various implications for clients and suppliers in IT outsourcing.