• Journal of Information Science Theory and Practice
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• v.12 no.1
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• pp.77-86
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• 2024

As the significance of knowledge convergence continues to grow, universities are making efforts to develop methods that promote multidisciplinary learning. To address this educational challenge, our paper applies network theory and text mining techniques to analyze university curricula and introduces a graphical syllabus rendering method. Visualizing the course curriculum provides a macro and structured perspective for individuals seeking alternative educational pathways within the existing system. By visualizing the relationships among courses, students can explore different combinations of courses with comprehensive search support. To illustrate our approach, we conduct a detailed demonstration using the syllabus database of Yonsei University. Through the application of our methods, we create visual course networks that reveal the underlying structure of the university curriculum. Our results yield insights into the interconnectedness of courses across various academic majors at Yonsei University. We present both macro visualizations, covering 18 academic majors, and visualizations for a few selected majors. Our analysis using Yonsei University's database not only showcases the value of our methodology but also serves as a practical example of how our approach can facilitate multidisciplinary learning.

• Computers and Concrete
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• v.32 no.3
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• pp.263-286
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• 2023

Experimenting with concrete to determine its compressive and tensile strengths is a laborious and time-consuming operation that requires a lot of attention to detail. Researchers from all around the world have spent the better part of the last several decades attempting to use machine learning algorithms to make accurate predictions about the technical qualities of various kinds of concrete. The research that is currently available on estimating the strength of concrete draws attention to the applicability and precision of the various machine learning techniques. This article provides a summary of the research that has previously been conducted on estimating the strength of concrete by making use of a variety of different machine learning methods. In this work, a classification of the existing body of research literature is presented, with the classification being based on the machine learning technique used by the researchers. The present review work will open the horizon for the researchers working on the machine learning based prediction of the compressive strength of concrete by providing the recommendations and benefits and drawbacks associated with each model as determining the compressive strength of concrete practically is a laborious and time-consuming task.

• Computers and Concrete
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• v.33 no.2
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• pp.137-145
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• 2024

The technique of experimentally determining concrete's compressive strength for a given mix design is time-consuming and difficult. The goal of the current work is to propose a best working predictive model based on different machine learning algorithms such as Gradient Boosting Machine (GBM), Stacked Ensemble (SE), Distributed Random Forest (DRF), Extremely Randomized Trees (XRT), Generalized Linear Model (GLM), and Deep Learning (DL) that can forecast the compressive strength of ternary geopolymer concrete mix without carrying out any experimental procedure. A geopolymer mix uses supplementary cementitious materials obtained as industrial by-products instead of cement. The input variables used for assessing the best machine learning algorithm not only include individual ingredient quantities, but molarity of the alkali activator and age of testing as well. Myriad statistical parameters used to measure the effectiveness of the models in forecasting the compressive strength of ternary geopolymer concrete mix, it has been found that GBM performs better than all other algorithms. A sensitivity analysis carried out towards the end of the study suggests that GBM model predicts results close to the experimental conditions with an accuracy between 95.6 % to 98.2 % for testing and training datasets.

• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.167-174
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• 2013

The objectives of this study are to investigate core learning ability necessary for the 21st century and to develop core human resources required for social and national development in the future. The '21st Century Learning Ability Project' is to approach the existing knowledge and learning multidisciplinary and interactively based on the learning ability of each learner and individually and socially valuable themes. Even in Korea, a variety of intersubject integrative educational curriculum was attempted to cultivate learning ability. However, there are not enough teachers who can teach the differences between the content and characteristics for each subject by fully understanding them. Thus, it is difficult to apply them easily to the field of education. Thus, this study develops the multidisciplinary customized educational curriculum in order to develop the learning ability necessary for the 21st century, analyzes the reality of the educational curriculum integrating the academic knowledge in order to support this effectively. As a result, this study offers the interdisciplinary customized integrated model applicable to elementary and middle schools.

• Journal of Engineering Education Research
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• v.9 no.4
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• pp.10-18
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• 2006

Today it is critical for all engineers to have the capability of interacting in teams with members of different background and to meet the challenges that they will encounters in their careers. To satisfy such needs multidisciplinary engineering-design courses are attracting more attentions than ever in the engineering education community. In this paper we analyze the learning effectiveness of interdisciplinary design teams in an engineering design course in Dongguk University. The comparison analysis between monodisciplinary teams and interdisciplinary ones demonstrates higher learning effectiveness of interdisciplinary teams. In addition, the student evaluation of learning effectiveness points out that communication skill is one of the most important factors for a successful project. Such results show that multidisciplinary design courses must gain wider acceptance in engineering education and engineering students must have more chances to experience multidisciplinary teamwork.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.197-206
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• 2012

The objectives of this study are to investigate core learning ability necessary for the 21st century and to develop core human resources required for social and national development in the future. The '21st Century Learning Ability Project' is to approach the existing knowledge and learning multidisciplinary and interactively based on the learning ability of each learner and individually and socially valuable themes. Even in Korea, a variety of intersubject integrative educational curriculum was attempted to cultivate learning ability. However, there are not enough teachers who can teach the differences between the content and characteristics for each subject by fully understanding them. Thus, it is difficult to apply them easily to the field of education. Thus, this study develops the multidisciplinary customized educational curriculum in order to develop the learning ability necessary for the 21st century, analyzes the reality of the educational curriculum integrating the academic knowledge in order to support this effectively. As a result, this study offers the interdisciplinary customized integrated model applicable to elementary and middle schools.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.635-657
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• 2015

The current society characterized by knowledge-based information technology and multiculturalism put more emphasis on problem-solving skills, creative thinking, and communication skills than any other periods did. In response to the demand of the current times, multidisciplinary, or convergence courses and majors are being created and conducted in college education, yet, with the lack of specific teaching and learning model for the convergence courses. In this context, this study aimed to examine PBL as an instructional model for the convergent approaches in classroom, since PBL has been regarded as a model for fostering the 21st century learning capabilities for student coupled with the learning principles of authentic tasks, learner-centeredness, collaborative learning. This study, after conducted a PBL course for the general art education during the summer semester of 2014, analyzed the result using data collected from students' reflective journals, in-depth interviews, and SNS posts among the students. The result presented students' enhanced self-respect, increased interest in their learning and communication skills, and their recognition of the value on diversity and empathetic attitudes toward each others. In conclusion, PBL showed its potential as an alternative instructional model for the multidisciplinary and convergent learning in college education.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.531-537
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• 2014

In this paper, we introduce a model of the teaching and learning method for multidisciplinary convergence capstone design at Kongju National University's Engineering Department. At Kongju national University, various capstone design works are designed and proceeded by multidisciplinary students at the summer session. The multidisciplinary approach described in this paper includes the involvement of five department's student who have not collaborated in capstone design experience. This study focuses on multidisciplinary capstone design education by using the micro controller board called Arduino Uno that consists of an assortment of sensors and actuators. The result of self-satisfaction survey was shown the meaningful teaching process for the engineering department students who could have more creative and industrial experiences. As a result, we are able to get the result of the possible directions for future technology education in the area of convergence multidisciplinary capstone design.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.145-148
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• 2013

최근 디지털 기술의 고도화로 인하여 테크놀로지가 급속도록 발전하면서 다양한 정보통신 기술과 지식의 융합을 교육 환경에 적용하는 스마트러닝에 대한 관심이 집중되기 시작하였다. 이러한 스마트러닝 환경의 장점들을 통해 학생들이 더욱 효과적으로 교육받을 수 있게 되었다. 학생들은 모바일 기기의 접근성에 대한 인식이 확대되고 모바일 기기와 교육용 프로그램을 활용한 학습이 활성화 되고 있다. 이에 본 연구에서는 스마트기기를 이용한 학습과 평가가 이루어질 수 있는 방안에 대해 알아보고자 한다.

• Computers and Concrete
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• v.32 no.4
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• pp.373-381
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• 2023

Fly ash, granulated blast furnace slag, marble waste powder, etc. are just some of the by-products of other sectors that the construction industry is looking to include into the many types of concrete they produce. This research seeks to use surrogate machine learning methods to forecast the compressive strength of self-compacting concrete. The surrogate models were developed using Gradient Boosting Machine (GBM), Support Vector Machine (SVM), Random Forest (RF), and Gaussian Process Regression (GPR) techniques. Compressive strength is used as the output variable, with nano silica content, cement content, coarse aggregate content, fine aggregate content, superplasticizer, curing duration, and water-binder ratio as input variables. Of the four models, GBM had the highest accuracy in determining the compressive strength of SCC. The concrete's compressive strength is worst predicted by GPR. Compressive strength of SCC with nano silica is found to be most affected by curing time and least by fine aggregate.