• Journal of The Korean Association For Science Education
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• v.25 no.7
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• pp.746-753
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• 2005

In order to be efficient teachers should understand the current level of leaners through diagnostic evaluation. However, it is arduous to administer a diagnostic examination in every class because of various limitations. This study examined, the major issues arising from the development of a new science diagnostic evaluation system by incorporating the using knowledge state analysis method. The proposed evaluation system was based on the knowledge state analysis method. Knowledge state analysis is a method where by a distinguished collection of knowledge uses the theory of knowledge space. The theory of knowledge space is very advantageous when analyzing knowledge in strong hierarchies like mathematics and science. It helps teaching plan through methodically analyzing a hierarchy viewpoint for students' knowledge structure. The theory can also enhance objective validity as well as support a considerable amount of data fast by using the computer. In addition, student understanding is improved through individualistic feedback. In this study, an evaluation instrument was developed that measured student learning outcome, which is unattainable from the existing method. The instrument was administered to pre-service physics teachers, and the results of student evaluation was analyzed using the theory of knowledge space. Following this, a revised diagnostic evaluation system for facilitating student individualized learning was constructed.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.123-131
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• 2015

Recently the development of ICT has a big impact on education field, and diffusion of smart devices has brought new education paradigm. Since people has an opportunity to use various contents anytime and communicate in an interactive way, the method of learning has changing. In 2011, Korean government has established the smart education promotion plan to be a first mover in the paradigm shift from e-learning to smart learning. Especially, government aimed to improve the quality of learning materials and method in public schools, and also to decrease the high expenditure on private education. However, the achievement of smart education policy has not emerged yet, and the refinement of smart learning policy and strategy is essential at this moment. Therefore, the purpose of this study is to propose the successful strategies for smart learning in public education. First, this study explores the status of public education and smart learning environment in Korea. Then, it derives the key success factors through SWOT(Strength, Weakness, Opportunity, Threat) analysis, and suggests strategic priorities through AHP(Analytic Hierarchy Priority) method. The interview and survey were conducted with total 20 teachers, who works in public schools. As a results, focusing on weakness-threat(WT) strategy is the most prior goal for public education, to activate the smart learning. As sub-factors, promoting the education programs for teachers($W_2$), which is still a weakness, appeared as the most important factor to be improved. The second sub-factor with high priority was an efficient optimizing the capability of new learning method($S_4$), which is a strength of systematic public education environment. The third sub-factor with high priority was the extension of limited government support($T_4$), which could be a threat to other public schools with no financial support. In other words, the results implicate that government institution factors should be considered with high priority to make invisible achievement in smart learning. This study is significant as an initial approach with strategic perspective for public education. While the limitation of this study is that survey and interview were conducted with only teachers. Accordingly, the future study needs to be analyzed in effectiveness and feasibility, by considering perspectives from field experts and policy makers.

• Knowledge Management Research
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• v.24 no.4
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• pp.219-235
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• 2023

The advancement of digital technology and the impact of COVID-19 have brought about changes in corporate innovation and organizational culture, thereby highlighting the significance of Smart Learning in the field of HRD (Human Resource Development). This trend has led to an increased interest in personalized Smart Learning among employees due to the growth of hybrid work and the widespread adoption of smart work practices. This study aimed to illuminate the relative importance of the factors that constitute Smart Learning from the perspective of HRD practitioners. Through a review of prior literature, Smart Learning hierarchy and factors most fitting to the current context were identified, and their relative importance was determined using the AHP method. Consequently, in the first-tier factors, importance was confirmed in the order of 'Learning Activities', 'Teaching Activities', 'Learning Content', 'Assessment and Evaluations', and 'Learning Time and Space'. At the second-tier encompassing all factors, 'Pedagogical Strategy', 'Learning Results', 'Learning Tasks', 'Learning Goal', and 'Learning Support' emerged within the top five factors. These findings are significant in that they redefine the concept of smart learning and propose an academic framework for future research. Additionally, from a practical perspective, it is anticipated that this study will contribute valuable insights for HRD practitioners, aiding them in focusing on which factors to prioritize for enhancing and advancing Smart Learning initiatives.

• Journal of Agricultural Extension & Community Development
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• v.4 no.1
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• pp.305-315
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• 1997

The propose of this study was to analyze the relationships among the levels of training & development evaluation (reaction, learning, transfer). The study has been conducted on 730 trainees who attended in the basic accounting program in L training and development institution through three incidents of tracked research such as reaction survey right after the conclusion of training, learning evaluation through test, and an evaluation of the transferability after 3 months of training. Questionnaires and test papers for analyses were used after their reliability, validity, difficulty, and discrimination have been verified on a pre-test. The research has been conducted for six months from 4 March 1996 to the end of August 1996, and data have been collected through direct research and survey through mail. The collected data have been worked on at SAS program for Windows with a statistical significance level of 5%. Statistical method that had been used was Pearson's correlation coefficient. The result and conclusion acquired from this study were as follows: Between reaction and learning, learning and transfer of training, only a weak positive correlation exists and explanation or prediction variance showing hierarchical relationship was quite weak with 1%. Thus, this research not only does not strongly support Kirkpatrick(1976)'s hierarchical model of $reaction{\rightarrow}learning{\rightarrow}transfer$, but also indicates that the separate measurement on each levels of training evaluation needs to be done. On the other hand, there was a relatively strong positive correlation between reaction and transfer of training. Based on the result, the conclusion, and the restriction perceived through this study, the following suggestions were made. 1. There is a need to empirically analyze and verify the hierarchy of all levels of training evaluation including the evaluation of the fourth level (result) such as organizational productivity, organizational satisfaction, and separation rate. 2. A great deal of efforts will be needed to systematically analyze what the relationships are among the methods measuring the level of evaluation of the training and development, and to apply this result to the training field.

• Convergence Security Journal
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• v.18 no.4
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• pp.19-25
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• 2018

In this paper, we propose an user-centered integrated lost-goods management system through a ranking system based on weight and a hierarchical image classification system based on Deep Learning. The proposed system consists of a hierarchical image classification system that automatically classifies images through deep learning, and a ranking system modules that listing the registered lost property information on the system in order of weight for the convenience of the query process.In the process of registration, various information such as category classification, brand, and related tags are automatically recognized by only one photograph, thereby minimizing the hassle of users in the registration process. And through the ranking systems, it has increased the efficiency of searching for lost items by exposing users frequently visited lost items on top. As a result of the experiment, the proposed system allows users to use the system easily and conveniently.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.123-132
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• 2024

The purpose of this study was to extract hierarchical learning elements in the area of 'Algorithms and Programming' in the 2022 revised secondary informatics curriculum. Intrinsic validity was secured by considering the core ideas presented in the curriculum and the content elements of 'knowledge/understanding', 'process/skills', and 'values/attitudes', and extrinsic validity of the learning elements was obtained through FGI and CVR with 25 experts. The learning elements derived from this study are 7 in the first stage, 18 in the second stage, and 26 in the third stage for middle schools, and 8 in the first stage, 23 in the second stage, and 27 in the third stage for high schools. Although the scope and size of knowledge in each stage may differ, the hierarchy of knowledge in the first stage, which is materialized in the second and third stages, provides direction on how knowledge should be taught. This study is expected to contribute to the implementation of the new curriculum in schools and to improve teachers' understanding of the curriculum.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.663-670
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• 2017

The purpose of this study is to define On-line Video Syllabus Template which is based on adaptive mode with interaction.A syllabus has the significance as a teaching and learning plan. However, it has not only been considered as a formal document, has also been limited into a simple query since it has been made into a fragmentary structure, lacking of link between other services and reuse. Additionally, this paper is aimed to design three-dimensional syllabus which makes it possible to provide students with practical information related to teaching and learning and share it with teachers and students. The following is the technique proposed in this paper. It is made to be served for the Syllabus centered on teaching and learning, which is including the definition of hierarchy structure, the media contents application according to the learner's preference and real-time variation function. On-line Video Syllabus provided through LMS has availability and credibility of teaching and learning, in that it enable increased utilization by strengthening convenience.

• The Journal of Korean Association of Computer Education
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• v.9 no.6
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• pp.29-39
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• 2006

The Web is evolving quantitatively into an explosive development. However, users usually have heavy burden of searching information because of the absence of contextual meaning on the Web. Due to an enormous amount of information, users have to endure for finding strong cohesive keywords by themselves and read each of the documents with enduring effort. This paper proposes an efficient method of searching more relative documents than current KEM-based searching systems on the Web by using contextual meaning. We designed a domain ontology on computer hardware, and a searching system which was searching those e-Learning objects. Owing to the Ontology-applied search system, information such as educational materials and related multimedia can be easily provided to the users. Further, learners could be informed of relationship of knowledge, e.g., class hierarchy, properties and values, and so on. The request results are semantically related to users' needs, and thus the system provides a learner-centered searching.

• Journal of Korean Elementary Science Education
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• v.20 no.1
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• pp.31-43
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• 2001

The purposes of this study were grasping the degree of students' understanding for course contents through the concept mapping strategy as meaningful learning in science and measuring the effect for change of conception and changing the misconception. The results of the study were as follows: 1. Before the lesson, only 10.7％ of students had scientific conception of molecular motion. Other students had various kinds of misconceptions. 2. The extent of concept formation after lesson through the using concept mapping strategy was tested. As a result, compared with the controlled group, the experimental group showed higher extent of sound concept formation (statistical significance level 0.05). 3. The differences between the experimental group and the control group were analyzed into quantitative and qualitative points of view. The results of the comparison showed that the maps of the students were well configured in the categories of the relationship, the hierarchy and the examples; while students showed lower abilities in the category of the cross-links. 4. The student's attitudes to ward concept mapping was positive. Most of the students answered that teaching strategy of concept mapping benefits them in meaningful learning outcomes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5097-5106
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• 2010

Two perspectives on developing better decision capabilities for a warranty system can be identified: one involving the inclusion of a 'learning' module and the other the inclusion of a 'prioritization' capability. This paper demonstrates how a warning process can be included in a warranty system by coupling with a neural network's learning capabilities. In addition to the neural network, a method is employed for assigning priorities to warning criteria by using the analytic hierarchy process (AHP). Thus, it is possible to construct an integrated system with three components: the warranty system, the AHP module, and the neural network system. A case study is provided to enhance the accuracy of warning/detection judgment in a warranty system for automobile companies, having many factors related to the warranty system.