• Journal of the Korean School Mathematics Society
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• v.10 no.3
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• pp.323-340
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• 2007

This study set out to analyze the learning types that most students were engaged in after school, to review the efficiency of private education through academic institutions or tutoring, and to examine the directions in the after-school learning in math under the current system. It also aimed to analyze the impacts of those after-school learning activities on school classes and to suggest some plans to help public education get back on the track. In the study the after-school learning activities in the math subject were categorized into taking classes at academic institutions, tutoring, and autonomous learning. The grades of the subject students were compared and analyzed for three semesters to find the directions right for the school classes.

• Knowledge Management Research
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• v.18 no.4
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• pp.31-62
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• 2017

It found that employee silence negatively impacts both organizations and their employees as shown in findings from many studies and recently there has been a growing interest in it. Silence is described as intentionally withholding job-related ideas, information, concerns, and opinions. Employee silence may decrease organizational change and innovation and reduce employee learning motivation and knowledge sharing engagement as well. The purpose of this study is to examine the relationships among silence motivations, perceived silence climate, and employee silence; the relationships among employee silence, learning inertia and knowledge sharing disengagement; the mediating role of employee silence between antecedents of employee silence and consequences additionally. The results that analyzed using data from 225 employees in 42 organizations are as follows. First, the impact of silence motivation and perceived silence climate on employee silence are positively significant. Second, the influence of defensive silence motivation on the acquiescent and relational silence motivation is positively significant. Third, the influence of employee silence on learning inertia and knowledge sharing disengagement is positively significant. Forth, employee silence mediates the relationship between silence motivation and perceived silence climate and learning inertia and knowledge sharing disengagement. These results suggest that employee silence is another strong expression and message for organizations to try to establish a learning organization from the perspective of knowledge management.

• Journal of Distribution Science
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• v.21 no.7
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• pp.33-40
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• 2023

Purpose: Higher Order Thinking Skills is one of the important aspects in education that must be mastered by the students in order to be qualified in competing at international level. Success in mastering HOTS among the students is always linked to preparation of a good and conducive learning environment. However, does this connection impacts the students' HOTS achievement? Therefore, this research is carried out in order to evaluate the relationship between HOTS and learning environment with the main focus on Accounting Principle Elective Subject (MPEI PP). Research design, data and methodology: Research in the form of correlation is implied in this study and it involves 59 Form 5 students that has learned all syllabus in Form 4's MPEI PP. Results: Evaluation of HOTS level is based on Taxonomy Bloom that covers applying skill, analysing skill, evaluating skill, and creating skill. Result from data analysis found that there is a very weak correlation (r = 0.02) between the two variables with regression equation of average grade point = 75.023 + (-.273) Learning Environment. Conclusion: Thus, a non-significant relationship between HOTS and learning environment is successfully proven through correlation and regression statistical analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.2062-2073
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• 2014

Relationship learning is very important to grow and develop interorganization. Greatly to ours regret, relationship learning study have left unexplored with regard to interfirm's relationship. The purpose of this study is to analyze the effects of relationship benefits on relationship learning and cooperation of buyer-seller in food material industries. We collected statistically usable data from 228 questionnaire respondents who deal with food firms and analyzed them with SPSS 20.0 and Amos to achieve research's goals. Analysis results revealed that, first, relational benefits of economical benefits and psychological benefit had impacts on relationship learning between buyer and seller in food material channel market. Second, the survey found that relationship learning has impact on collaboration. Third, on the other hand, relationship benefits of social benefits had no effect relationship learning. Summary and strategy implication will be mention in conclusion.

• Journal of Information Technology Applications and Management
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• v.14 no.2
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• pp.27-47
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• 2007

In an effort to apply IT to practices of learning, universities are trying to implement e-Learning systems and expanding the extent of their usage. Nowadays, e-Learning systems are not only used for conducting web-based distance learning, but also used for supporting traditional classes education by encouraging communication and information sharing between instructors and learners or among the learners. There is relatively lack of studies on the exploitation of e-Learning systems in the traditional classes, in comparison with a distance education. Specifically, howe-Learning systems could support the traditional class and/or which benefits e-Learning systems could offer in the classes are among the important issues. In this study, we suggest that e-Learning systems would be the rich media to communicate and exchange information among people who participate in a class. We derive key variables like media richness and media experience from Media Richness Theory and from Channel Expansion Theory. Moreover, Media usefulness and Satisfaction of a learner with e-Learning system is drawn from the literature on IS success. We examine the effects of perceived media richness, media usefulness, and media experience on leaner's satisfaction with e-Learning systems. In addition, we also investigate learner's media usefulness perception which is positively related to media richness and media experience. Finally, learner's experience with e-Learning systems affects perceived media richness. Based on the results of an empirical test. we first suggest that perceived media richness with e-Learning systems contributes to increase media usefulness and satisfaction of a learner. Second, media experience is an important predictor of media richness and media usefulness perception. Consequently, the result can support Channel Expansion Theory. Finally, media usefulness perception affects learner's satisfaction with e-Learning systems.

• Journal of Korean Elementary Science Education
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• v.28 no.3
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• pp.340-351
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• 2009

The purpose of this study was to investigate the effect of case-based learning program on three elementary students' scientific problem solving and attitudes in science class. For this study, case-based learning program was designed for bridging students' scientific knowledge and their personal experiences in real life through 4 stages: understanding the problem, planning for problem solving, conducting problem solving, and making conclusion. This study was carried out through 17 lessons of 4th grade for 6 weeks. The data was collected through close observation on three students in two groups in a class. The results include that cased-based learning program showed overall positive effects on the elementary students' scientific problem solving and attitudes in class. In particular, it turned out that the continuous emphasis of real world examples in case-based learning had powerful impacts on students' problem solving abtsity, motivation, and participation in classroom activities. The key factors to successful problem solving in school science was discussed.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.57-65
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• 2020

At present, the existing virus recognition systems usually use signature approach to detect malicious executable files, but these methods often fail to detect new and invisible malware. At the same time, some methods try to use more general features to detect malware, and achieve some success. Moreover, machine learning-based approaches are applied to detect malware, which depend on features extracted from malicious codes. However, the different distribution of features oftraining and testing datasets also impacts the effectiveness of the detection models. And the generation oflabeled datasets need to spend a significant amount time, which degrades the performance of the learning method. In this paper, we use transfer learning to detect new and previously unseen malware. We first extract the features of Portable Executable (PE) files, then combine transfer learning training model with KNN approachto detect the new and unseen malware. We also evaluate the detection performance of a classifier in terms of precision, recall, F1, and so on. The experimental results demonstrate that proposed method with high detection rates andcan be anticipated to carry out as well in the real-world environment.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.833-852
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• 2019

In real time applications, due to their effective cost and small size, wireless networks play an important role in receiving particular data and transmitting it to a base station for analysis, a process that can be easily deployed. Due to various internal and external factors, networks can change dynamically, which impacts the localisation of nodes, delays, routing mechanisms, geographical coverage, cross-layer design, the quality of links, fault detection, and quality of service, among others. Conventional methods were programmed, for static networks which made it difficult for networks to respond dynamically. Here, machine learning strategies can be applied for dynamic networks effecting self-learning and developing tools to react quickly and efficiently, with less human intervention and reprogramming. In this paper, we present a wireless networks survey based on different machine learning algorithms and network lifetime parameters, and include the advantages and drawbacks of such a system. Furthermore, we present learning algorithms and techniques for congestion, synchronisation, energy harvesting, and for scheduling mobile sinks. Finally, we present a statistical evaluation of the survey, the motive for choosing specific techniques to deal with wireless network problems, and a brief discussion on the challenges inherent in this area of research.

• The Journal of Information Systems
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• v.32 no.4
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• pp.95-118
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• 2023

Purpose This study employed the Technology Acceptance Model (TAM) to understand students' acceptance of online learning systems. Specifically, this study investigated the factors influencing the behavioral intention of South Korean major university students to use online learning systems for educational purposes in the period when their university life had largely returned to the state it was in before the COVID-19 pandemic. Design/methodology/approach This study examined the impact of four external factors: self-efficacy, personal innovativeness, perceived enjoyment, and system quality, on two TAM constructs: perceived ease of use and perceived usefulness. Additionally, this study explored how perceived ease of use and perceived usefulness affect the behavioral intention to use online learning systems. We conducted an online-based survey using a structured questionnaire. The data collected from the survey were then subjected to Structural Equation Modeling (SEM) analysis to test the study's hypotheses and examine the relationships among the various constructs. Findings The findings reveal that perceived usefulness and ease of use significantly influence students' behavioral intentions to use online learning systems. Furthermore, factors of self-efficacy, perceived enjoyment, and system quality positively affect perceived usefulness and ease of use. Notably, personal innovativeness impacts ease of use but not perceived usefulness.

• The Mathematical Education
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• v.56 no.2
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• pp.161-175
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• 2017

The purpose of this study is to compare and analyze the impact on low-achievers in mathematics who studied mathematics using Blended e-learning and Personalized system of instruction after school. Blended e-learning is defined as the management of e-learning using the e-study run by the education office in local. Personalized system of instruction was proceeded as follows; (1) all students are given a syllabicated learning task and a study guide, (2) students study the material autonomously according to their own pace for a certain period of time, (3) the teacher strengthens the students' motivation through grading and feedback after students study a subject and solve the evaluation problem. The learning materials for Personalized system of instruction are re-edited the offline education contents provided by the blended e-learning to the level of students. The 118 $7^{th}$ grade students from the D middle school participated in this study. The results were verified by achievement tests before and after the study, as well as survey regarding their attitude toward mathematics. The results are as follows. First, Blended e-learning has more positive impacts than Personalized system of instruction in mathematics achievement. Second, there was no difference in mathematics achievement according to their self-directed learning between Blended e-learning and Personalized system of instruction. Third, both types utilizing Blended e-learning and Personalized system of instruction have positive effect on attitude toward mathematics, and there is not their difference between two methods of teaching and learning mathematics.