• School Mathematics
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• v.2 no.1
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• pp.203-241
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• 2000

This study aims to suggest a model of task development for mathematics performance assessment and to develop performance tasks for the fifth graders in the primary school on the basis of this model. In order to achieve these aims, the following inquiry questions were set up: (1) to develop open-ended tasks and projects for the fifth graders, (2) to develop checklists for measuring the abilities of mathematical reasoning, problem solving, connection, communication of the fifth graders more deeply when performance assessment tasks are implemented and (3) to examine the appropriateness of performance tasks and checklists and to modify them when is needed through applying these tasks to pupils. The consequences of applying some tasks and analysing some work samples of pupils are as follows. Firstly, pupils need more diverse thinking ability. Secondly, pupils want in the ability of analysing the meaning of mathematical concepts in relation to real world. Thirdly, pupils can calculate precisely but they want in the ability of explaining their ideas and strategies. Fourthly, pupils can find patterns in sequences of numbers or figures but they have difficulty in generalizing these patterns, predicting and demonstrating. Fifthly, pupils are familiar with procedural knowledge more than conceptual knowledge. From these analyses, it is concluded that performance tasks and checklists developed in this study are improved assessment tools for measuring mathematical abilities of pupils, and that we should improve mathematics instruction for pupils to understand mathematical concepts deeply, solve problems, reason mathematically, connect mathematics to real world and other disciplines, and communicate about mathematics.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.509-515
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• 2005

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved it more powerful than traditional artificial neural networks (ANNs)(Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al, 2005; Kim, 2003). The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is cost-sensitive. Therefore, it is necessary to convert the output of the classifier into well-calibrated posterior probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create probabilities (Platt, 1999; Drish, 2001). This study applies a method to estimate the probability of outputs of SVM to bankruptcy prediction and then suggests credit scoring methods using the estimated probability for bank's loan decision making.

• Journal of Korean society of Dental Hygiene
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• v.19 no.4
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• pp.615-624
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• 2019

Objectives: This study explored job satisfaction experience and meaning of work in dental hygienists. Methods: In-depth interviews were conducted with 13 clinical dental hygienists who had been working in dental clinics for more than 10 years. The analysis method used was developed by Giorgi, including all four steps. Results: The results of the interview were categorized into five central meanings: recognition and trust (including patient's trust, trust in the boss, recognition in the hospital, and intimacy), growth (growth of the hospital, growth in jobs, and problem-solving skills), professional pride (self-esteem, extension of work and changes of awareness, and being able to help others), reward (financial compensation and psychological rewards), and meaning of life given by work (the process of maturing, self-representation, and vitality of life). Conclusions: Based on this study, we need to develop tools to measure dental hygienists' level of job satisfaction as well as follow-up research on ways to improve it.

• The Journal of Industrial Distribution & Business
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• v.12 no.6
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• pp.47-55
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• 2021

Purpose: Organizational crime is an offense committed by an individual or an official in a corporate entity for organizational gain. This study aims to explore the literature on challenges facing digital forensics and further discuss possible solutions to such challenges as far as the protection of corporate crime is concerned. Research design, data and methodology: Qualitative textual methodology matches the interpretative approach since it is a quality method meant to consider the inductivity of strategies. Also, a qualitative approach is vital because it is distinct from the techniques used in optimistic paradigms linked to science laws. Results: For achieving justice through the investigation of digital forensic, there is a need to eradicate corporate crimes. This study suggests several solutions to reduce corporate crime such as 'Solving a problem to Anti-forensic Techniques', 'Cloud computing technique', and 'Legal Framework' etc. Conclusion: As corporate crime increases in rate, the data collected by digital forensics increases. The challenge of analyzing chunks of data requires digital forensic experts, who need tools to analyze them. Research findings shows that a change of the operating system and digital evidence interpretation is becoming a challenge as the new computer application software is not compatible with older software's structure.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.225-237
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• 2022

The term "artificial intelligence" is considered a component of sophisticated technological developments, and several intelligent tools have been developed to assist organizations and entrepreneurs in making business decisions. Artificial intelligence (AI) is defined as the concept of transforming inanimate objects into intelligent beings that can reason in the same way that humans do. Computer systems can imitate a variety of human intelligence activities, including learning, reasoning, problem-solving, speech recognition, and planning. This study's objective is to provide responses to the questions: Which factors should be taken into account while deciding whether or not to use AI applications? What role do these elements have in AI application adoption? However, this study proposes a framework to explore the significance and relation of success factors to AI adoption based on the technology-organization-environment model. Ten critical factors related to AI adoption are identified. The framework is empirically tested with data collected by mail surveying organizations in Vietnam. Structural Equation Modeling is applied to analyze the data. The results indicate that Technical compatibility, Relative advantage, Technical complexity, Technical capability, Managerial capability, Organizational readiness, Government involvement, Market uncertainty, and Vendor partnership are significantly related to AI applications adoption.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.175-179
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• 2021

Computer Science Unplugged activities are activities to learn about computer science through learning tools other than programming programs. Existing unplugged activities focus on the procedural thinking process and focus on guiding the thinking process through play. There is a lack of research on unsupervised learning, which plays an important role in machine learning, which has recently attracted attention. In this study, we designed and conducted an unplugged activities for unsupervised learning that analyzes data using video media familiar to elementary school students. The results on the effectiveness of the class were analyzed using the bebras challenge. As a result of analyzing the scores of the pre-test and post-test, it was confirmed that the students' computational thinking and problem-solving ability improved.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.9-16
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• 2024

AI or Artificial Intelligence has been a significant tool used in the organisational backgrounds for an effective improvement in the management methods. The processing of the information and the analysis of the data for the further achievement of heightened efficiency can be performed by AI through its data analytics measures. In the medical field, AI has been integrated for an improvement within the management of the medical services and to note a rise in the levels of customer satisfaction. With the benefits of reasoning and problem solving, AI has been able to initiate a range of benefits for both the consumers and the medical personnel. The main benefits which have been noted in the integration of AI would be integrated into the study. The issues which are noted with the integrated AI usage for the medical sector would also be identified in the study. Medical Image Processing has been seen to integrate 3D image datasets with the medical industry, in terms of Computed Tomography (CT) or Magnetic Resonance Imaging (MRI). The usage of such medical devices have occurred in the diagnosis of the patients, the development of guidance towards medical intervention and an overall increase in the medical efficiency. The study would focus on such different tools, adhered with AI for increased medical improvement.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.803-812
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• 2021

This study explored the concept of artificial intelligence and the problem-solving process that can be explained through literature research. Through this study, the educational meaning and application plan of artificial intelligence that can be explained were presented. XAI education is a human-centered artificial intelligence education that deals with human-related artificial intelligence problems, and students can cultivate problem-solving skills. In addition, through algorithmic education, it is possible to understand the principles of artificial intelligence, explain artificial intelligence models related to real-life problem situations, and expand to the field of application of artificial intelligence. In order for such XAI education to be applied in elementary schools, examples related to real world must be used, and it is recommended to utilize those that the algorithm itself has interpretability. In addition, various teaching and learning methods and tools should be used for understanding to move toward explanation. Ahead of the introduction of artificial intelligence in the revised curriculum in 2022, we hope that this study will be meaningfully used as the basis for actual classes.

• Journal of Korean Elementary Science Education
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• v.23 no.4
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• pp.344-356
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• 2004

In this study, we developed the program for 'Discretionary Activity' focusing on the multiple activities with everyday-life materials to enhance scientific creativity (MAEM-SC), which was specifically for students in the 6-7th grade according to the 7th curriculum in Korea. As important factors for scientific creativity, we selected the ability to find out the context relevant to scientific problems, the ability to connect the problem context to scientific knowledge, the ability to invent the ways to solve the problem scientifically, and ability to concentrate on the scientific problem solving activity. The topics of the program were drawn from common and familiar things in our everyday contexts, such as human body, everyday tools, food, play and toys, and everyday episodes. The multiple activities here mean the activities which are systematically constructed with the various types of activities with a specific intention. The multiple activities were designed in three types, that is, series type, parallel type, and combination type. Each of them consists of the several activities as follows: estimating and measuring, carrying out an experiment using body, inventing implement (tools), thinking statistically, writing creatively with scientific themes, and connecting one concept to another concept etc. Through a trial of the program, we found that this program has some positive influence on the enhancement both of the ability to find out the context relevant to scientific problems and the ability to connect it to the students' existing scientific knowledge.

• Journal of The Korean Association of Information Education
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• v.18 no.2
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• pp.357-370
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• 2014

The purpose of this research was to develop the tools needed to evaluate the effectiveness of using digital textbooks and smart education. We then developed the tools to evaluate the effectiveness of smart education and digital textbook utilization, which were an identification of 1) seven essential 21st century skills, definitions of each, and prerequisite abilities; 2) five 21st century teacher competencies, definitions of each, and prerequisite abilities; To develop the questionnaire, we conducted a literature review in this area, consulted experts, observed classes, interviewed members of focus groups, and met with policy makers from the Ministry of Education and KERIS. The student questionnaire(26 Questions developed) included; creativity and innovation, critical thinking and problem solving, communication, collaboration, ICT literacy, self-directed learning, and adaptability. The teacher questionnaire(24 questions developed) included; 21st Century Skills, ICT Literacy, Rapport building with learners, Instructional design, Evaluation and reflection. The tools we developed will be able to use for evaluating the effectiveness of smart education and digital textbooks.