• Communications of Mathematical Education
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• v.23 no.4
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• pp.1043-1058
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• 2009

This study concerns with the effects of group projects performed by the students in college math classes. The study result shows that 61% of the students get more self-confidence and interest in mathematics through working projects. In addition, the result reveals that one of the essential factors for successful college mathematics class is to provide a strong motivation for learning to students. For effective teaching through group projects, this paper suggests that 1) the number of students in the class be 20 or less, 2) the projects group be consisted of two members, 3) the instructor should select proper problems to students' level from extra-textbooks, 4) the problems should be interesting, positive and challenging, 5) each group should take only one problem, 6) the groups be provided with enough references and materials, 7) each student in the group be cared to feel importance and necessity of mathematics and cooperative work, 8) the students should work with math joyfully, 9) the instructor remind the students that we live with mathematics in real life, 10) 2-month be a necessary and appropriate term in working projects.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.209-227
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• 2023

The government continues to announce measures to revitalize smart construction technology based on BIM for productivity innovation in the construction industry. In the design phase, the goal is design automation and optimization by converging BIM Data and other advanced technologies. Accordingly, in the basic design of the Namhae Seomyeon-Yeosu Sindeok National Road Construction Project, a domestic undersea tunnel project, BIM-based design was carried out by developing tunnel design automation technology using 3D spatial information according to the tunnel design process. In order to derive the optimal alignment, more than 10,000 alignment cases were generated in 36hr using the generative design technique and a quantitative evaluation of the objective functions defined by the designer was performed. AI-based ground classification and 3D Geo Model were established to evaluate the economic feasibility and stability of the optimal alignment. AI-based ground classification has improved its precision by performing about 30 types of ground classification per borehole, and in the case of the 3D Geo Model, its utilization can be expected in that it can accumulate ground data added during construction. In the case of 3D blasting design, the optimal charge weight was derived in 5 minutes by reviewing all security objects on the project range on Dynamo, and the design result was visualized in 3D space for intuitive and convenient construction management so that it could be used directly during construction.

• Communications of Mathematical Education
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• v.28 no.3
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• pp.395-422
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• 2014

In this paper, we obtain the step inteaching high school leve-based class utilizing cooperative learning lessons using level-type tutoring to improve academic achievement and mathematics attitudes. The details are as follows. First, we develop the teaching and learning model for the level-type instructional development and for the application to project work. Second, we seek to height academic achievement by applying the level-type work sheets in conjunction with cooperative learning. For this problem, we will focus on the following issues. First, how will you using level-type tutoring level TAI cooperative learning in order to improve academic achievement and develop the learning ability in mathematics? Second, how can you step utilizing TAI instructional level of cooperative learning in mathematics classes to improve mathematics learning attitudes? Third, how will you some reaction step work sheets utilizing level TAI cooperative learning of students for mathematics. Results of this study are as follows. First, in the experimental group compared to the comparison group was improved academic achievement. Second, in the experimental group compared to the comparison group learning attitudes could help. Third, the level of cooperative learning instructional model utilizing the TAI in the experimental group compared to the comparison group represents a significant response was seen.

• Journal of The Korean Association For Science Education
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• v.37 no.1
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• pp.169-179
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• 2017

The aim of this study is to see school science education from the perspective of CoP (Community of Practice) and to explore the possibility of strategic CoP in Korean school settings. To do this, we conducted a survey using SCaCoP instrument with more than 1600 students from 14 science core schools (SCSs), which were selected across the country, and analyzed their school curriculum, which can be summarized as follows: First, compared to other tracks in SCSs, like the Nature and the Humanity Classes, students of the Science Core Class (SCC) showed significantly higher scores of CoP features for all five factors of SCaCoP (i.e. responsibility of learning, common interest, mutual relationship, open participation, and practice). Second, students of SCC considered activities that require interaction and collaboration among community members (like experiments, hands-on activities, club activities, project works, R&E) to be very positive. Third, SCC students thought that the educational activities of SCSs were not only effective to CoP aims (i.e. self-driven learning, sharing learning outcomes, peer collaboration) but also positive to general aims of science education (i.e. acquiring knowledge, understanding scientific concepts, science-related attitudes). In other words, it appears that educational activities that were effective in vitalizing the CoP have positive effects on ordinary science education, too. These features of SCSs illustrate its possibility of forming strategic COPs in the context of often government-driven Korean education and of bringing in the innovations of school science education.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.151-162
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• 2020

Education is one of the priority sectors specified in Tanzania, and it has committed to provide 11 years of compulsory free basic education for all from pre-primary to lower secondary level. Despite the Government's efforts to provide free basic education to all children, there are 2.0 million (23.2 per cent) out of 8.5 million children at the primary school age of 7-13, who are out of school in Tanzania. The ICT class should be offered as a regular class in all secondary schools in Tanzania, recommended by the ministry of education. However, many schools are struggling to implement this mandate. Most of schools offer the ICT class with theory without any real hardware. Some schools were given with computers but they were not maintained for operation. There is a huge task to make ICT education universal. Main issues include: remoteness (off-grid area), lack of ICT teachers, lack of resources such as hardware, infrastructure, and lack of practical lessons or projects to be used at schools. An innovative blended ICT/STEM education program is being conducted not only for Tanzanian public and private/international schools, but also for out-of-school adolescents through institutions, NGO centers, home visits and at the E3 Empower academy center. For effective STEM education to take place and remain sustainable, more practical curriculum, and close-up teacher support need to be accompanied concurrently. Practical, project-based simple coding lessons have been developed and employed that students experience true learning. The effectiveness of the curriculum has been demonstrated in various project centers, and it showed that students are showing new interests in exploring new discovery, even though this was a totally new area for them. It has been designed for an easy replication, thus students who learned can repeat the lessons themselves to other students. The ultimate purpose of this project is to have IT education offered as universally as possible throughout the whole Tanzania. Quality education for all children is a key for better future for all. Previously it was hoped that education with discipline will improve the active learning. But now more than ever, we believe that children have the ability to learn on their own with given proper STEM education tools, guidelines and environment. This gives promising hope to all of us, including those in the developing countries.

• Journal of Ship and Ocean Technology
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• v.12 no.4
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• pp.1-6
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• 2008

Nowadays, the computational capability and graphical power based on PCs increase very rapidly every year. As a result, the complicated engineering or scientific problems that could have only been handled by supercomputers a couple of decades ago can now be routinely run on PCs. Besides, the PCs can be assembled in parallel to increase its computational capability theoretically without limitation. The Web-based interface and communication tools are also being enhanced very rapidly and the real-time distance learning (E-Learning) and project cooperation on web get increasing attention. Using the-state-of-the-art computational method, a number of complicated and computationally intensive problems are being solved by PCs. The results can be well demonstrated on screen by graphics and animation tools. Those examples include the simulations of fully nonlinear waves, their interactions with floating bodies, global-motion analysis of multi-unit floating production system including complicated mooring lines and risers. Several examples will be presented in this regard. Also, Web and java-applet based educational tools have been developed at Texas A&M University for better understanding of waves and wave-body interactions. The background and examples of such Web-based educational tools published in Kim et al. (2003) are briefly introduced here.

• Fourth Industrial Review
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• v.3 no.1
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• pp.1-12
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• 2023

Purpose - In Korea, where 64% of the land is forested, mountaineering is a leisure activity enjoyed by the majority of the people. As new technologies named the 4th industrial revolution spread more after the Covid-19 pandemic, we propose a human and technology convergence curriculum for mountaineering and trekking education to enjoy safety in the field of mountaineering and trekking using cutting-edge technology. Research design, data, and methodology - After examining the current state of the mountaineering industry and preceding studies on mountaineering and camping, and learning about BAC the 100 famous mountains, mountaineering gamification, and Gamification We designed an AI convergence curriculum using. Result - Understanding the topography and characteristics of mountains in Korea, acquiring mountaineering information through AI convergence, selecting mountaineering equipment suitable for the season, terrain, and weather, setting educational goals to safely climb, and deriving term project results. A total of 15 A curricula for teaching was proposed. Conclusion - Artificial intelligence technology is applied to the field of mountaineering and trekking and used as a tool, and it is expected that the base of mountaineering will be expanded through safe, efficient, fun, and sustainable education. Through this study, it is expected that the AI convergence education curriculum for mountaineering and trekking will be developed and advanced through several studies.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.80-88
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• 2017

Although hazard identification is one of the most important steps of safety management process, numerous hazards remain unidentified in the construction workplace due to the dynamic environment of the construction site and the lack of available resource for visual inspection. To this end, our previous study proposed the collective sensing approach for safety hazard identification and showed the feasibility of identifying hazards by capturing collective abnormalities in workers' walking patterns. However, workers generally performed different activities during the construction task in the workplace. Thereby, an additional process that can identify the worker's walking activity is necessary to utilize the proposed hazard identification approach in real world settings. In this context, this study investigated the feasibility of identifying walking activities during construction task using Wearable Inertial Measurement Units (WIMU) attached to the worker's ankle. This study simulated the indoor masonry work for data collection and investigated the classification performance with three different machine learning algorithms (i.e., Decision Tree, Neural Network, and Support Vector Machine). The analysis results showed the feasibility of identifying worker's activities including walking activity using an ankle-attached WIMU. Moreover, the finding of this study will help to enhance the performance of activity recognition and hazard identification in construction.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.41-49
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• 2019

We are to build an unsupervised machine learning-based language model which can estimate the amount of information that are in need to process words consisting of subword-level morphemes and syllables. We are then to investigate whether the reading times of words reflecting their morphemic and syllabic structures are predicted by an information-theoretic measure such as surprisal. Specifically, the proposed Morfessor-based unsupervised machine learning model is first to be trained on the large dataset of sentences on Sejong Corpus and is then to be applied to estimate the information-theoretic measure on each word in the test data of Korean words. The reading times of the words in the test data are to be recruited from Korean Lexicon Project (KLP) Database. A comparison between the information-theoretic measures of the words in point and the corresponding reading times by using a linear mixed effect model reveals a reliable correlation between surprisal and reading time. We conclude that surprisal is positively related to the processing effort (i.e. reading time), confirming the surprisal hypothesis.