• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.6
• /
• pp.1099-1104
• /
• 2020

In order to provide various types of application services based on the Internet, it is ideal to guarantee the quality of service(QoS) for each flow. However, realizing these ideas is not an easy task.. It is effective to classify multiple flows having the same or similar service quality requirements into same group, and to provide service quality for each group. The queue management mechanism in the router plays a very important role in order to efficiently transmit data and to support differentiated quality of service for each service. In order to efficiently support various multimedia services, an intelligent and adaptive queue management mechanism is required. This paper proposes an intelligent queue management mechanism based on deep reinforcement learning that decides whether to deliver packets for each group based on the traffic information of each flow group flowing in for a certain period of time and the current network state information.

• Korea Science and Art Forum
• /
• v.19
• /
• pp.623-633
• /
• 2015

Use of technology through utilization of ICT (Information Communication Technology) in field study area is rapidly increasing. Thus, when applying ICT to experiential education, apart from experiential education contents in simple form, the demand for new high quality contents is increasing considering change in education paradigm focusing on creativity. As a result, high quality interactive experiential education content for developing self-directed future talents is required. As a result of this, the development of ARD-based ICT experiential education content system that enhances learning effect of students by integrating ARD-based (Augmented Reality Display) ICT and experiential education to promote existence and immersion is being tested. This paper aims to improve efficacy and achieve vitalization through case analysis of AR-based ICT experiential education content. As a result of case analysis, the composition of content for improving education content included 1) constant securing and strengthening of experiential education content, 2) necessity for development of participating education content by diverse age groups, 3) development of differentiated ICT experiential education content, and 4) securing professional manpower and development of content in connection with education process. Therefore, with the efficacy of ARD-based ICT experiential education content, this study can first, enhance bond between students, second, enable self-directed learning, third, increase practical understanding in contents that were difficult to control by textbook contents, and fourth, increase interest and immersion in learning. Therefore, the contents on new converging technology that can maximize the development of constant content and cooperation between ICT technology and pedagogy for educating creativity and autonomy of ICT experiential education content.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.6
• /
• pp.13-22
• /
• 2024

There is a need for and positive aspects of article-based advertising, but as exaggerated and disguised information is delivered due to some indiscriminate 'article-based advertisements', readers have difficulty distinguishing between general articles and article-based advertisements, leading to a lot of misinterpretation and confusion of information. is doing Since readers will continue to acquire new information and apply this information at the right time and place to bring a lot of value, it is judged to be even more important to distinguish between accurate general articles and article-like advertisements. Therefore, as differentiated information between general articles and article-like advertisements is needed, as part of this, for readers who have difficulty identifying accurate information due to such indiscriminate article-like advertisements in Internet newspapers, this paper introduces IT and AI technologies. We attempted to present a method that can be solved in terms of a system that incorporates, and this method was designed to extract articleable advertisements using a knowledge-based natural language processing method that finds and refines advertising keywords and deep learning technology.

• Communications of Mathematical Education
• /
• v.28 no.1
• /
• pp.81-96
• /
• 2014

Now, most of programs developed were presented as form of item pool by dividing problems by section and level for the level differentiated course, so the utilization is decreasing at the field caused by unconsidered school underachievement elements by achievement. Especially, the study on teaching materials and effective measures map for mid-low level students with low utilization is more urgent. Therefore, in this study we will promote teaching method for improving learning achievement at high school. The development teaching materials(the performance evaluation and diagnostic assessment, reconstruction of textbooks) will be applied to classes for the underachieving students directly, and the achievement in the experimental class was significantly improved compared to the comparative class and the meaningful conclusions could be drawn as results of conducting same assessment based on the experimental class and the comparative class.

• The Journal of the Korea Contents Association
• /
• v.19 no.2
• /
• pp.66-78
• /
• 2019

This study aimed to investigate the effects of scaffolding on creativity in Wiki-based collaborative learning. Wiki-based collaborative learning was implemented over three sessions among 67 sixth graders in an elementary school, and subjects were divided into three groups: Group 1 had a teachers' scaffolding and self-questioning script; Group 2 had a teachers' scaffolding; and Group 3, the control group, had no scaffolding. Results showed a significant difference in creativity among the groups with different types of scaffolding(Wilks' Lambda=.238, F=8.678, p < .001). Group 1, had significantly higher performance compared to the Group in creativity. However, when self-questoning script and a teachers' scaffolding were offered, self-scaffolding was not found to have a significant effect on learners' Originality of creativity. Group 2 showed higher performance in Originality of creativity when only a teachers' scaffolding was offered in the collaborative learning. The results of this study suggest that teachers' scaffolding and self-scaffolding have positive effects on creativity, but the need for a differentiated self-scaffolding strategy to identify the factors that influence creativity in wiki-based collaborative learning.

• The Mathematical Education
• /
• v.62 no.4
• /
• pp.531-549
• /
• 2023

Despite the significance of mathematics teacher guidebooks as a support for teacher learning, there are few studies that address how elementary mathematics teacher guidebooks support teacher learning. The purpose of this study was to analyze the educative features of elementary mathematics teacher guidebooks for grades 3 and 4. For this, six units from each of ten kinds of teacher guidebooks were analyzed in terms of seven dimensions of Teacher Learning Opportunities in Korean Mathematics Curriculum Materials (TLO-KMath). The results of this study showed that mathematics content knowledge for teaching was richly provided and well organized. Teacher guidebooks provided teacher knowledge to anticipate and understand student errors and misconceptions, but were not enough. Sample dialogues between a teacher and students were offered in the teacher guidebooks, making it easier for teachers to identify the overall lesson flow and key points of classroom discourse. Formative assessment was emphasized in the teacher guidebooks, including lesson-specific student responses and their concomitant feedback examples per main activity. Supplementary activities and worksheets were provided, but it lacked rationales for differentiated instruction in mathematics. Teacher knowledge of manipulative materials and technology use in mathematics was provided only in specific units and was generally insufficient. Teacher knowledge in building a mathematical community was mainly provided in terms of mathematical competency, mathematical classroom culture, and motivation. This paper finally presented implications for improving teacher guidebooks to actively support teacher learning.

• Journal of the Korean Society of Earth Science Education
• /
• v.16 no.2
• /
• pp.234-246
• /
• 2023

This study uses Gagne's 'Differentiated Model of Giftedness and Talent (DMGT)' to collect and extract major life events of Jang Young-sil, and to investigate how giftedness was formed and developed in his life history, and what factors enabled him to demonstrate his talent in the field of science and technology. In addition, based on the framework of Gagne's Differentiation Model for Giftedness and Talent(DMGT), we analyzed the mechanism of giftedness manifestation of Jang Young-sil and sought to explore the direction of gifted education based on this. To sum up the results of the study, first, in Giftedness(G), it was found that Jang Young-sil had excellent scientific and technological skills. Second, motivation, determination, self-management, and personality factors that constitute the inner catalyst(IC) of the individual have had an impact on the development of giftedness. Third, it influenced the social environment and peer giftedness in environmental catalysis(EC). Fourth, the catalyst of chance or chance(C) was the factor that had the greatest influence on Jang Young-sil's manifestation of giftedness. Fifth, informal learning and non-institutional formal learning in the developmental process(LP) influenced the manifestation of giftedness. In this way, the talent development factors of people such as Jang Young-sil provide implications for the need to understand the manifestation mechanism of giftedness in the future, develop examination tools that can detect giftedness, and develop customized programs that can develop giftedness.

• Journal of Intelligence and Information Systems
• /
• v.16 no.4
• /
• pp.99-112
• /
• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.

• Journal of The Korean Association of Information Education
• /
• v.19 no.3
• /
• pp.311-322
• /
• 2015

This study analyzed the trend and problems in the design of contents developed by teachers, and suggested strategies for improvement. It analyzed the contents ranked as the first level in the Research Competition on Educational Informatization for the last 3 years. Concerning the 8 types of instructional activities and the 6 types of knowledge acquisition, most contents took limited types(i.e., the individual tutoring type, the concept learning type and the principle learning type). In addition, when the contents were evaluated according to the quality certification criteria for educational software, it was found that the quality level of the design was low in many criteria. When the content analysis was applied for the in-depth analysis of design characteristics, various problems were found in the areas such as evaluation, feedback and learning objectives. Also other common problems were found in the design areas such as level-based differentiated learning, interaction between students and contents, presentation of text and narration, utilization of information on a student, screen design, the content level appropriate for students. In relation to the problems found from the analysis, some strategies for improvement were suggested concerning the following topics: question selection and guidance for evaluation, content and types of feedback, statement of learning objectives, selection of content, interaction, and screen design.

• Journal of Korean Home Economics Education Association
• /
• v.33 no.4
• /
• pp.65-84
• /
• 2021

The purpose of this study was to develop and evaluate the Home Economics(HE) Flipped Problem-Based Learning(FPBL) education plans focusing on 'food selection and storage' unit for middle school students. The results of this study are as follows. First, middle school students who participated in the class had mainly experienced lecture-style classes previously, but they preferred group activity classes to lecture-style classes. Their 'preferred on-line class tools' was 'Miricanvas', and the 'helpful on-line class tools for learning' was 'Tinkerbell'. Second, the HE FPBL education plan was designed and developed to conduct block time classes, twice a week for 3 weeks by applying the '13 stages of FPBL'. The main topic of the class is "food selection and storage that protects health and the environment". The practical and unstructured problems in the FPBL was to participate in the 'Food Selection and Storage to Protect Health and Environment' mission development contest of a TV entertainment program. Learning materials(stepping video, reading materials, activity sheets, and evaluation tools for process-based evaluation) were developed. The 206 senior students at a middle school in Haeundae-gu, Busan, took the class for three weeks and evaluated it as a good class that helps them learn, is satisfactory, interesting, and suitable, leads to class participation, and is differentiated from other teaching methods.