• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.325-333
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• 2019

This study was conducted to investigate the factors affecting satisfaction and dissatisfaction of e-learning learner students using Kano model and Timko's customer satisfaction coefficient. The results of the analysis showed that firstly, the students are highly satisfied when it is convenient to learn visually and audibly, when the students can ask questions at any time, and when the professor was interested in the students. Second, the rational criteria and accurate evaluation of grades and assignments were confirmed as factors that should be satisfied. Third, unlike the results of the basic study that the students use e-learning due to the convenience of learning time and learning space and the ease of learning process, it is no longer an attractive factor to use e-learning. The results of this study suggest that it is possible to present effective directions for the development of e-learning education and strategic application of each factor classified by the two-dimensional recognition method.

• Journal of Engineering Education Research
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• v.19 no.5
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• pp.3-12
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• 2016

This paper aims to apply two ways of student evaluation, i.e. peer- and self-evaluation to TBL(team based learning) class and to explore the difference between two evaluations by gender and grade as well as their relationships, and finally to provide an explanation for the improvement of evaluation ways in TBL class. There has been much research about TBL and its related factors. However, according to the examination of both domestic and overseas researches concerning the application of peer- and self-evaluation to TBL class, few studies have focused on them in terms of the engineering curriculum. This study was conducted with 251 engineering students at P University, and peer- and self-evaluation in TBL class have been measured. Our findings show that firstly, there were significant grade differences in self-evaluation of engineering students. Second, there were no significant gender and grade differences in peer-evaluation. Third, we found a significant correlation between the two factors, self- and peer-evaluation. Also there was a significant correlation among variables of subcategories. Based on these findings, it is expected to provide an explanation for the application of peer- and self-evaluation in TBL class and will be useful for the improvement plans of the related courses in engineering school.

• The Journal of Korean Association of Computer Education
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• v.11 no.6
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• pp.65-76
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• 2008

Since Cyber Home Learning is an e-learning system promoted with policy goals of reducing private tutoring costs, solving gaps among regions, and improving scholastic attainments, preceding researches to verify its effects have been developed of evaluation standards focused on achievement of its policy goals rather than educational goals. The evaluation standards suggested in preceding researches have limitations in clearly reviewing Cyber Home Learning's effects by teaching-learning activities factors and Cyber Home Learning's improvement related to teaching-learning activities. Therefore, an evaluation model capable of analyzing effects of Cyber Home Learning from pedagogical aspect is required. The goal of this paper is to design pedagogical evaluation model according to teaching-learning activities factors and analyze effects of Cyber Home Learning. For the goal, researches from Korea and abroad related to Cyber Home Learning have been examined, pedagogical evaluation model was designed according to teaching-learning activities factors, and the model was then experimented through survey and in-depth interview on students who used Cyber Home Learning. It is expected that results of this paper can be used as a basic data to improve quality of Cyber Home Learning service for teaching-learning activities, and will contribute to establishment of more developmental Cyber Home Learning policy in the future.

• International Journal of Contents
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• v.5 no.1
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• pp.51-55
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• 2009

In this paper, we present a structure of personalized e-Learning system to study for a test formalized by uniform multiple-choice using on/off line mixed estimations as is the case of Driver :s License Test in Korea. Using the system a candidate can study toward the license through the Internet (and/or mobile instruments) within the personalized concept based on IRT(item response theory). The system accurately estimates user's ability parameter and dynamically offers optimal evaluation problems and learning contents according to the estimated ability so that the user can take possession of the license in shorter time. In order to establish the personalized e-Learning concepts, we build up 3 databases and 2 agents in this system. Content DB maintains learning contents for studying toward the license as the shape of objects separated by concept-unit. Item-bank DB manages items with their parameters such as difficulties, discriminations, and guessing factors, which are firmly related to the learning contents in Content DB through the concept of object parameters. User profile DB maintains users' status information, item responses, and ability parameters. With these DB formations, Interface agent processes user ID, password, status information, and various queries generated by learners. In addition, it hooks up user's item response with Selection & Feedback agent. On the other hand, Selection & Feedback agent offers problems and content objects according to the corresponding user's ability parameter, and re-estimates the ability parameter to activate dynamic personalized learning situation and so forth.

• The Journal of the Korea Contents Association
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• v.11 no.9
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• pp.524-535
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• 2011

For success in E-learning, support from a learning environment that enables learners to perform self-directed learning more effectively is assumed. However, most existing e-learning systems do not maximize the improvement in learners' self-regulated learning ability because they only partially accommodate factors that can facilitate self-directed learning. In this paper, a web-based e-learning system is designed and proposed that enables support of an enhanced self-directed learning environment by providing various learning methods, evaluation methods, learning content levels, and strategies for learning motivation in various conditions, and synthetically reflecting them. To validate the effectiveness of the proposed system, it was applied to the subject of data structures in a university course, and an online survey was conducted with the students. The results indicated that the proposed system can support a learning environment in which students can perform more effective self-directed learning, enhancing their learning ability.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.499-510
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• 2022

This study examines the reporting factors of crime against business in Korea and proposes a corresponding predictive model using machine learning. While many previous studies focused on the individual factors of theft victims, there is a lack of evidence on the reporting factors of crime against a business that serves the public good as opposed to those that protect private property. Therefore, we proposed a crime prevention model for the willingness factor of theft reporting in businesses. This study used data collected through the 2015 Commercial Crime Damage Survey conducted by the Korea Institute for Criminal Policy. It analyzed data from 834 businesses that had experienced theft during a 2016 crime investigation. The data showed a problem with unbalanced classes. To solve this problem, we jointly applied the Synthetic Minority Over Sampling Technique and the Tomek link techniques to the training data. Two prediction models were implemented. One was a statistical model using logistic regression and elastic net. The other involved a support vector machine model, tree-based machine learning models (e.g., random forest, extreme gradient boosting), and a stacking model. As a result, the features of theft price, invasion, and remedy, which are known to have significant effects on reporting theft offences, can be predicted as determinants of such offences in companies. Finally, we verified and compared the proposed predictive models using several popular metrics. Based on our evaluation of the importance of the features used in each model, we suggest a more accurate criterion for predicting var.

• The Journal of Korean Association of Computer Education
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• v.10 no.6
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• pp.61-68
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• 2007

The Cyber Home Learning System(CHLS) is a representative, nationwide e-learning system specially for G1-12 in Korea. It was launched at 16 MPOE in 2005 and has been evolved through every year-its evaluation and sharing best practices. In terms of evaluation, learners' satisfaction is one of essential and indispensable factors to improve CHLS. In this research, evaluation criteria on learners's satisfaction were developed, and also, the developed evaluation criteria were verified through the process of item goodness analysis and item characteristic analysis. These evaluation criteria are expected to contribute to analysing learners' satisfaction more objectively and quantitatively.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.108-115
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• 2020

Blended learning is a teaching method utilizing all the advantages in 'on and off-line' learning circumstances in order to enhance the learning effect and efficiency, more than the simple use of online factors in the classroom education. In this paper, we present the realization and simulation of algorithm for the realtime evaluation of low-grade and high-grade subjects in order to implement smart e-learning system, considering a lecture intelligibility. In order to grasp the levels of student's intelligibility, we simulated a function that automatically summarizes the study contents of class given by a lecturer. Especially, in administrator mode of smart e-learning system, we suggested and simulated a system in order to help the lecturer to easily manage the student's grades, and we have provided software to tell the student's intelligibility of lecture, analyzed the rate of incorrect answers, automatic judgment of lecture intelligibility and judge the weakest subject.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.316-324
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• 2005

e-Learning has been mushrooming with wide range of teaming groups from pedagogy to andragogy As e-teaming opportunities increase, many people raise question about whether e-teaming show positive teaming effects. The related research emphasized that e-learning would be a failure in terms of understanding of e-Learners and activating intuitive teaming activities from learner's long-term memory span. The e-teaming strategies based on the traditional classroom and resulted boring and ineffective teaming outcomes, should be changed to provide authentic and effective teaming results. This paper analyzed that how learners have received e-Learning for the last few years from the research and explained what could be the failing aspects in e-Learning. To be successful, e-loaming should consider the e-learner's individualized teaming style and thinking patterns. When considering of various e-Learning components, the quality of e-teaming should not be focused on any specific single factor, but develop every individual factor to be integrated into high level of quality. In conclusion, this paper suggest that it is needed new understandings of e-Loaming and e-Learner. Also the e-Learning strategies should be examined throughly whether they are on the side of learners and realized how they learn from e-Learning. Finally, we should add enormous imagination into e-loaming for next generation because new generation's teaming patterns significantly differ from their parent's generation.

• Journal of Korean Neurosurgical Society
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• v.67 no.1
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• pp.60-72
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• 2024

Objective : Recently, robotic-assisted spine surgery (RASS) has been considered a minimally invasive and relatively accurate method. In total, 495 robotic-assisted pedicle screw fixation (RAPSF) procedures were attempted on 100 patients during a 14-month period. The current study aimed to analyze the accuracy, potential risk factors, and learning curve of RAPSF. Methods : This retrospective study evaluated the position of RAPSF using the Gertzbein and Robbins scale (GRS). The accuracy was analyzed using the ratio of the clinically acceptable group (GRS grades A and B), the dissatisfying group (GRS grades C, D, and E), and the Surgical Evaluation Assistant program. The RAPSF was divided into the no-breached group (GRS grade A) and breached group (GRS grades B, C, D, and E), and the potential risk factors of RAPSF were evaluated. The learning curve was analyzed by changes in robot-used time per screw and the occurrence tendency of breached and failed screws according to case accumulation. Results : The clinically acceptable group in RAPSF was 98.12%. In the analysis using the Surgical Evaluation Assistant program, the tip offset was 2.37±1.89 mm, the tail offset was 3.09±1.90 mm, and the angular offset was 3.72°±2.72°. In the analysis of potential risk factors, the difference in screw fixation level (p=0.009) and segmental distance between the tracker and the instrumented level (p=0.001) between the no-breached and breached group were statistically significant, but not for the other factors. The mean difference between the no-breach and breach groups was statistically significant in terms of pedicle width (p<0.001) and tail offset (p=0.042). In the learning curve analysis, the occurrence of breached and failed screws and the robot-used time per screw screws showed a significant decreasing trend. Conclusion : In the current study, RAPSF was highly accurate and the specific potential risk factors were not identified. However, pedicle width was presumed to be related to breached screw. Meanwhile, the robot-used time per screw and the incidence of breached and failed screws decreased with the learning curve.