• 대한공업교육학회지
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• v.44 no.2
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• pp.142-163
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• 2019

The purpose of this study is to analyze the effect of problem solving ability and satisfaction of university students who are pre-technology teachers in woodworking products(birdhouse) making program using design thinking. Survey responses are analyzed by statistical programs(SPSS ver.20) such as satisfaction, confidence in problem solving, difficulties and causes of difficulties according to gender and grade of 33 students who conducted experience programs in extra-curricular programs to improve creativity and problem solving ability. The main conclusions of this study are as follows: First, the average of total satisfaction about experience programs is 4.39, which is somewhat high. The highest average response is 'feelings of accomplishment' and 'advice in the surroundings'(M = 4.46). There is no significant difference between male and female, and grade. The students interest in group-based different birdhouse woodworking together with the help of the surrounding people by the process of design thinking rather than practice to follow. Therefore, I'd like to recommend to other students due to this program shows a high self-confidence, sense of accomplishment, and satisfaction. Second, the total average response of students 'self-confidence for problem solving at the group based making experience program using design thinking is 3.80. In result of group activities, the students have self-confidence of 'problem-solving ability and deal with difficult situations'. Later, in making programs, complementing difficulties of making can enhance the satisfaction of the students. Third, in the survey questionnaire related with problem solving ability confidence, between 'I have the ability to solve many problems' and 'I always have the ability to cope with new and difficult business situations' show the highest correlation. Therefore, in order to improve self-confidence of problem solving ability, it is necessary to prepare teaching learning programs that can strengthen problem solving ability. Fourth, in the new design and making process not a given product design, the most difficult step is 'the process of rework and modifying idea product'. The main reason that students have difficulty in the production process is 'lack of knowledge and ability to produce'. To make various woodworking products using design thinking process, it can be helpful to make works if you have enough training on woodworking and design thinking before product making. The students' satisfaction about team-based learning using design thinking that helps improving creativity and problem solving ability is high. Therefore, the result of the research in other making activity program that design thinking is applied and analyzed can improve students' problem solving ability.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of Korean Home Economics Education Association
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• v.30 no.3
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• pp.43-66
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• 2018

The purpose of this study was to conduct the instruction for 'Family Life Planning' based on backward design and measured the learners' understanding and satisfaction for testing validity. In short, the result of this study are as follows: In this study, first of all, the students could explain significant concepts, knowledge, and principles for the planning of family life; they could interpret and apply them; they have perspectives on them; they could empathize them; and they could have self-knowledge. The students could also accomplish high achievements for important concepts related to the field of family life planning. In conclusion, this study showed that the developed instruction was very effective for the students to achieve fruitful results, accelerating the learners' persistent understanding. Second, the learners had high satisfaction on the instruction of Family Life Planning based on backward design with the average score of 3.68 out of the perfect score 4. The students could be satisfied with the developed instruction since they could have high interest in the class thanks to diverse learning materials, and they could take an active part in the learning tasks based on group activities and questions. Also they could apply the contents that they learned through task performances to new situation and context. Therefore, this study proved that the developed instruction enhanced the learners' satisfaction on class.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.189-207
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• 2020

The government has achieved quantitative growth in university start-up education while supporting start-up education. However, it failed to systematize start-up education from an academic, policy, and practical perspective and to reveal the relationship between education and achievements in supporting start-ups. Therefore, there is a lack of interest and effort to promote effective education. In Europe, in-depth research has already been done over many years to establish an EntreComp system. Competences create values for others and attempt to apply them to education, viewing them as the people's lifelong competitiveness. On the other hand, it is urgent to improve the education system as domestic university start-up education is mainly focused on cultural level start-up skills and easy-to-access education from a business administration perspective. Based on this, the entrepreneurship competence-based start-up education system was designed. Next, eight EntreComp frames were drawn for university students through the Focus Group Interview (FGI) and Delphi survey methods, as well as domestic and international prior studies on EntreComp. In 2018, 919 start-up education programs of 42 start-up leading universities were conducted to derive the status of education by EntreComp. Prior studies of 25 entrepreneurship competences, including data from Bacigalupo et al.(2016), which studied EntreComp in the EU, were investigated and reflected the frequency of research and the importance of education and start-up perspectives. Based on the purpose of the university start-up education presented in this study, the entrepreneurship competence frame consisting of a total of eight, including spotting opportunities, value creation, self improvement, mobilising resources, technology application, strategic management, relationship, and learning through experience, was derived through expert verification. It also investigated the current status of education by competence, the degree of reflection of competence education, and the relationship with the results of support for start-ups that reflect the number of students enrolled in each university. Through this, it was suggested that future start-up education at universities could be improved from the EntreComp perspective. It has a differentiation in research in that it conducted a thorough survey using the data on start-up courses operated by leading startup universities for a certain period. However, it is difficult to generalize because the number of samples of leading startup universities is limited. Nevertheless, this study proposes the educational goal of advancing university start-up education from the perspective of entrepreneurial competence, cultivating future required competences, and fostering entrepreneurial talents that create value for others. In addition, it is meaningful in that it presents a clear direction for subsequent research by preparing a framework for research from a more essential perspective on the entrepreneurship competence frame.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.3
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• pp.247-262
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• 2022

In domestic tunnels, it is mandatory to install CCTVs in tunnels longer than 200 m which are also recommended by installation of a CCTV-based automatic accident detection system. In general, the CCTVs in the tunnel are installed at a low height as well as near by the moving vehicles due to the spatial limitation of tunnel structure, so a severe perspective effect takes place in the distance of installed CCTV and moving vehicles. Because of this effect, conventional CCTV-based accident detection systems in tunnel are known in general to be very hard to achieve the performance in detection of unexpected accidents such as stop or reversely moving vehicles, person on the road and fires, especially far from 100 m. Therefore, in this study, the region of interest is set up and a new concept of inverse perspective transformation technique is introduced. Since moving vehicles in the transformed image is enlarged proportionally to the distance from CCTV, it is possible to achieve consistency in object detection and identification of actual speed of moving vehicles in distance. To show this aspect, two datasets in the same conditions are composed with the original and the transformed images of CCTV in tunnel, respectively. A comparison of variation of appearance speed and size of moving vehicles in distance are made. Then, the performances of the object detection in distance are compared with respect to the both trained deep-learning models. As a result, the model case with the transformed images are able to achieve consistent performance in object and accident detections in distance even by 200 m.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.210-223
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• 2023

This study developed elementary and middle school career education programs linked to science subjects and local natural resources, and explored learning effects and implications for developing and operating career programs. In order to achieve the research purpose, a 10-hour career education program using local natural and social resources was developed and applied to 25 elementary and middle school students in rural areas. As a result of the study, most of the elementary and middle school students who participated in this study were not well aware of the natural and social resource value of the area where they lived. Therefore, when developing and operating a regional-based career education program for elementary and middle school students in rural areas, it is necessary to operate a separate teaching/learning activity time so that students can fully know the natural and social information and resource values of the region. In addition, in order to enhance students' participation and interest in career education programs, it is necessary to organize the operation of the program in groups, not individuals, and to guide students in detail by dividing the program's performance process into several sub-steps. Finally, the core material of regional-linked career education-related programs focused more on their own content, that is, agricultural products grown by parents, and future job settings were higher in start-ups that directly operate companies such as travel agencies and manufacturing companies. Given the recent emphasis on career education in the curriculum, it is suggested that local students should pay more attention to finding materials with local resource value in the field of geoscience, which is closely related to natural resources, and developing and operating them as career education programs linked to local resources.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1283-1297
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• 2023

Mid-wave infrared (MWIR) imagery, due to its ability to capture the temperature of land cover and objects, serves as a crucial data source in various fields including environmental monitoring and defense. The KOMPSAT-3A satellite acquires MWIR imagery with high spatial resolution compared to other satellites. However, the limited spatial resolution of MWIR imagery, in comparison to electro-optical (EO) imagery, constrains the optimal utilization of the KOMPSAT-3A data. This study aims to create a highly visible MWIR fusion image by leveraging the edge information from the KOMPSAT-3A panchromatic (PAN) image. Preprocessing is implemented to mitigate the relative geometric errors between the PAN and MWIR images. Subsequently, we employ a pre-trained pixel difference network (PiDiNet), a deep learning-based edge information extraction technique, to extract the boundaries of objects from the preprocessed PAN images. The MWIR fusion imagery is then generated by emphasizing the brightness value corresponding to the edge information of the PAN image. To evaluate the proposed method, the MWIR fusion images were generated in three different sites. As a result, the boundaries of terrain and objects in the MWIR fusion images were emphasized to provide detailed thermal information of the interest area. Especially, the MWIR fusion image provided the thermal information of objects such as airplanes and ships which are hard to detect in the original MWIR images. This study demonstrated that the proposed method could generate a single image that combines visible details from an EO image and thermal information from an MWIR image, which contributes to increasing the usage of MWIR imagery.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• Communications of Mathematical Education
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• v.25 no.2
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• pp.403-430
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• 2011

The purpose of the study was to investigate how the use of graphing calculators influence on forming students' mathematical concept of algebra, students' mathematical connection, and attitude toward mathematics. First, graphing calculators give instant feedback to students as they make students compare their written answers with the results, which helps students learn equations and linear inequalities for themselves. In respect of quadratic inequalities they help students to correct wrong concepts and understand fundamental concepts, and with regard to functions students can draw graphs more easily using graphing calculators, which means that the difficulty of drawing graphs can not be hindrance to student's learning functions. Moreover students could understand functions intuitively by using graphing calculators and explored math problems volunteerly. As a result, students were able to perceive faster the concepts of functions that they considered difficult and remain the concepts in their mind for a long time. Second, most of students could not think of connection among equations, equalities and functions. However, they could understand the connection among equations, equalities and functions more easily. Additionally students could focus on changing the real life into the algebraic expression by modeling without the fear of calculating, which made students relieve the burden of calculating and realize the usefulness of mathematics through the experience of solving the real-life problems. Third, we identified the change of six students' attitude through preliminary and an ex post facto attitude test. Five of six students came to have positive attitude toward mathematics, but only one student came to have negative attitude. However, all of the students showed positive attitude toward using graphing calculators in math class. That's because they could have more interest in mathematics by the strengthened and visualization of graphing calculators which helped them understand difficult algebraic concepts, which gave them a sense of achievement. Also, students could relieve the burden of calculating and have confidence. In a conclusion, using graphing calculators in algebra and function class has many advantages : formulating mathematics concepts, mathematical connection, and enhancing positive attitude toward mathematics. Therefore we need more research of the effect of using calculators, practical classroom materials, instruction models and assessment tools for graphing calculators. Lastly We need to make the classroom environment more adequate for using graphing calculators in math classes.

• Journal of the Korean Society of Earth Science Education
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• v.10 no.2
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• pp.173-184
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• 2017

The purpose of this study is to examine the effects of science classes using the geological materials of a locality on academic achievement and scientific attitude of elementary school students. For this study, the class unit is 'stratum and fossils', 2nd semester of 3rd grade, and the geological materials of a locality is applied for class. The geological materials used in teaching and learning of 'stratum and fossil' unit are photographs & video data relating to geological phenomenon, and rock & fossils samples collected in Jeollanam-do province. This study has been aimed at 2 classes 47 students of 3rd grade in G elementary school of G metropolitan. One class 23 students are the research group to apply science class using the geological materials in a locality, on the order hand another class 24 students are the comparison group to apply general science classes. The results of this study are follows. First, a positive relationship was identified between academic achievement and science class applying the geological materials in a locality in the research group. This shows that academic achievement was improved by science class applying the geological materials in a locality. Second, a positive relationship was identified between scientific attitude and science class applying the geological materials in a locality in the research group. This shows that scientific attitude was improved by science class applying the geological materials in a locality. Third, by the results of interview with students who was participated in science class applying the geological materials in a locality, it shows that they have interest and curiosity about local geology. Above results means that science class applying the geological materials in a locality help elementary schools students improve the educational effect about 'stratum and fossils' unit. Thus, it is needed to use the geological materials of a locality in science class relating to the geology units of elementary school science in order to improve academic achievement and scientific attitude of elementary school students.