• The Mathematical Education
• /
• v.56 no.1
• /
• pp.119-130
• /
• 2017

The purpose of this study is to explain the long term growth and development of elementary teachers' Professional Learning Communities(PLC) about mathematics implemented on an institutional basis. Especially, it is meaningful to analyze and present the development process and characteristics of PLC, which was started by the basis on the collaboration of a National University of Education and its affiliated elementary school. In this study, PLC activities during three years were analyzed according to the capacities and dimensions of a professional learning community. The developmental capacity of the PLC analyzed in this study can be summarized as follows. In the first year, development of organizational competence in terms of capacity, resources, structure, and system of exchanges was the main factor in personal competence, and the development of individual competence began to share collective learning and practice. In the second year, personal exchanges were active in all the topics of activities, and personal level competence was activated such that more activities of critical knowledge formation were performed on an individual level. On the basis of the development of the individual level formed in the second, individual competence and organizational capacity developed. Factors that have influenced the development of capacities of PLC include: disclosure of activities outside the community, participation in outsiders, provision of procedures to share equal participation and leadership, voluntary and critical participation of teachers, improvement of mathematics teaching methods, sharing themes and visions.

• The Journal of the Korea Contents Association
• /
• v.15 no.12
• /
• pp.407-420
• /
• 2015

This study analyzes the effect of CoP(Community of Practice) influence factors on satisfaction and learning culture activation in R&D groups. Research model and hypothesis is designed the relationship the effect factors for CoP which are consist of personal factor, interacting factor, support factor and environmental factor and satisfaction and the learning culture activation focused on comparing between maturity and immaturity CoP member group. It conducted an analysis based on 371 survey responses significantly. Hence, interacting, supporting and personal factor have a significant positive effect on satisfaction but environmental factor was negative effect to it. CoP Satisfaction has a positive effect on the learning culture activation. However average between two groups has not a statistically significant difference in all of the factors. At the result, interacting between members is the most important factor to the successful CoP development of R&D groups.

• The Transactions of the Korea Information Processing Society
• /
• v.5 no.6
• /
• pp.1583-1592
• /
• 1998

Recently, massive amount of infonnation is provided for the internet users. So users want to search information on Internet, but it is difficult to search information what you want. In this paper, we propose a personal Web-agent system using Case-based learning, Web-Guide. Web-Guide consists of two sub-system, interface-system and learning-system. Interface-system operates other web-browser nearly the same and connects user to system. And interface-system transfer datas of current page to learning-queue. Learning-system visit and evaluate the value of each page in learning-queue using evaluation-function that gave weight values occupied by analyzing tag used the character of HTML document. After all users who are known about artificial intelligence well and not made experiments by using Web-Guide, they reached their desired sites faster than before.

• Korean Journal of Childcare and Education
• /
• v.10 no.1
• /
• pp.5-26
• /
• 2014

This study examined the effects of web-based learning experiences, learning style, and Internet self-efficacy that influence beginning child care teachers belief about web-based learning. The participants were 215 beginning child care teachers who work in child care centers. Data were analyzed by means of frequency analysis, correlation, and multiple regression for SPSS windows. The results were as follows: First, significant statistical differences were detected in web-based learning experiences and beliefs about web-based learning. Online teacher learning community use and frequency were significant gaps in beliefs about web-based learning. Second, there were statistical differences in learning styles and beliefs about web-based learning. And teachers with assimilator learning style showed high difficulty beliefs about web-based learning. Third, teachers' belief about web-based learning was significantly related to Internet self-efficacy. It means that teachers that have high Internet self-efficacy show high belief about web-based learning. Forth, among the teachers' personal variables, a higher level of online teacher learning community use and Internet self-efficacy predicted higher beliefs about web-based learning. Thus, this study suggested the importance of web-based learning experiences and Internet self-efficacy to beliefs about web-based learning. And it implicated ways to improve positive beliefs about web-based learning of beginning child care teachers.

• Journal of the Korean School Mathematics Society
• /
• v.21 no.4
• /
• pp.377-400
• /
• 2018

With the rapid industrialization and the advent of the era of the Fourth Industrial Revolution, the importance of character education is on the rise. The purpose of this study is to develop the Instructional model that can make the school classroom as a democratic learning community based on general classes and naturally realize the character education in addition to the other subject-matter education. A draft of the instructional model was implemented to confirm that the factors of the character education in mathematics could be improved. The toughness index was measured by using the Character Scale for School Mathematics(CSSM) before and after implementation. Based on the results of the measurement, we completed a P (personal) instruction model and a S (social) instruction model that can enhance the factors of the character education in mathematics based on the democratic learning community through the advisory committee.

• International Journal of Advanced Culture Technology
• /
• v.9 no.4
• /
• pp.162-168
• /
• 2021

This is a group pretest-posttest design study that aim to evaluate the effect of problem-based learning using flipped learning to self leadership, nursing leadership, and confidence of nursing students. The subjects were 87 4th nursing students who took nursing management from March 15 to April 26, 2021. A questionnaire was used to measure self leadership, nursing leadership, and confidence. The measurement of self leadership is a 5-point Likert scale that employs a questionnaire. Flipped learning uploaded a 5-8 minute lecture video, and the subjects learned on learning management system, using smart device. PBL teaching was developed about personal growth, cooperation, nursing excellence, creative problem solving, influence. As a result of the study, self leadership was significantly improved after education than before education(t=-6.27, p<.001). Nursing leadership and confidence were significantly changed before and after education(t=-16.10, p<.001; t=-2.37, p<.001). According to the results of this study, the PBL teaching method using flipped learning is an effective teaching and learning strategy for improving leadership, and confidence. In future studies, it will be necessary to develope and verify specific teaching and learning methods by applying nursing experts in consideration of the type of leadership.

• Asia pacific journal of information systems
• /
• v.32 no.4
• /
• pp.803-829
• /
• 2022

With the advances in technology and the trend towards increased computer-based experiential learning in education settings, business games are being increasingly used by business educators. This article utilizes Toulmin's Sensemaking Framework to investigate the sensemaking process of business professionals to reveal how they consciously reason about the value of business games for learning complex business concepts and principles. Using the analysis of responses from 43 business professionals, our study identifies key areas where business professionals find value in business games and the limitations of using business games. First, business games are found to be an effective tool when teaching practical business skill sets to business professionals. Second, business games enhance the overall learning process in professional business training. Third, despite the advantages, some pitfalls in applying business games to practice are found. We also found sub-themes, claims, and argument patterns of how business professionals evaluate the value of business games through a grounded theory qualitative analysis method. Analysis results show several ground-warrant patterns exist in the arguments on values of business games including general principle - causal reasoning, personal experience - generalization, and personal projection - generalization. With these findings, we believe this paper contributes to the theory and practice of business game design, development, and the game playing and learning process.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.3
• /
• pp.560-574
• /
• 2011

In this paper, we propose a hybrid method of Machine Learning (ML) algorithm and a rule-based algorithm to implement a lightweight Named Entity (NE) extraction system for Korean SMS text. NE extraction from Korean SMS text is a challenging theme due to the resource limitation on a mobile phone, corruptions in input text, need for extension to include personal information stored in a mobile phone, and sparsity of training data. The proposed hybrid method retaining the advantages of statistical ML and rule-based algorithms provides fully-automated procedures for the combination of ML approaches and their correction rules using a threshold-based soft decision function. The proposed method is applied to Korean SMS texts to extract person's names as well as location names which are key information in personal appointment management system. Our proposed system achieved 80.53% in F-measure in this domain, superior to those of the conventional ML approaches.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2024.05a
• /
• pp.294-297
• /
• 2024

Malware detection has become increasingly critical with the proliferation of end devices. To improve detection rates and efficiency, the research focus in malware detection has shifted towards leveraging machine learning and deep learning approaches. This shift is particularly relevant in the context of the widespread adoption of end devices, including smartphones, Internet of Things devices, and personal computers. Machine learning techniques are employed to train models on extensive datasets and evaluate various features, while deep learning algorithms have been extensively utilized to achieve these objectives. In this research, we introduce TabNet, a novel architecture designed for deep learning with tabular data, specifically tailored for enhancing malware detection techniques. Furthermore, the Synthetic Minority Over-Sampling Technique is utilized in this work to counteract the challenges posed by imbalanced datasets in machine learning. SMOTE efficiently balances class distributions, thereby improving model performance and classification accuracy. Our study demonstrates that SMOTE can effectively neutralize class imbalance bias, resulting in more dependable and precise machine learning models.

• The Journal of the Korea Contents Association
• /
• v.9 no.5
• /
• pp.346-354
• /
• 2009

This paper proposes a new learning recommendation system for learning patterns that educators are applying to learners using item-based method. The proposed method in this paper first collects personal learning methods based on learning information that learners are performing through the internet contents site. Then this system recommends a learning method which is estimated most properly to learners after classifying learning elements based on these information. The students of a middle school took part in the experiment in order to evaluate the proposed system, and the students were divided into three groups according to their grades. We gave inter-attribute and intra-attribute weights to learning elements applying to each group for recommending the most efficient method to improve learning achievement. The experiment showed that the learning achievement of learners in the proposed method is improved considerably compared to the previous grades.