• Journal for History of Mathematics
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• v.17 no.4
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• pp.133-152
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• 2004

In this paper, we discuss students' conceptual development of eigen value and eigen vector in differential equation course based on reformed differential equation using the mathematical model of mass spring according to historico-generic principle. Moreover, in setting of small group interactive learning, we investigate the students' development of mathematical attitude.

• Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.67-77
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• 2014

Most engineering software tools use typical menu-based user interfaces, and they may not be suitable for learning tools because the solution processes are hidden and students can only see the results. An educational tool for simple beam analyses is developed using a pen-based user interface with a computer so students can write and sketch by hand. The geometry of beam sections is sketched, and a shape matching technique is used to recognize the sketch. Various beam loads are added by sketching gestures or writing singularity functions. Students sketch the distributions of the loadings by sketching the graphs, and they are automatically checked and the system provides aids in grading the graphs. Students receive interactive graphical feedback for better learning experiences while they are working on solving the problems.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.415-425
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• 2019

This study proposes a new approach to control Moving Stuff Action Through Iterative Learning robot with dual arm for smart factory. When robot moves object with dual arm, not only position of each hand but also contact force at surface of an object should be considered. However, it is not easy to determine every parameters for planning trajectory of the an object and grasping object concerning about variety compliant environment. On the other hand, human knows how to move an object gracefully by using eyes and feel of hands which means that robot could learn position and force from human demonstration so that robot can use learned task at variety case. This paper suggest a way how to learn dynamic equation which concern about both of position and path.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.55-56
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• 2019

본 논문은 유아기 언어 발달 시기에 한글의 기초 단계를 학습하기 위해 기존의 교육 방식과는 달리 시각적, 청각적 효과로 몸의 감각을 통해 사물을 배우며 이러한 자극으로 정보를 기억하고 축적할 수 있는 에듀테인먼트 콘텐츠를 개발한다. 유아의 호기심을 자극할 뿐만 아니라 모바일 플랫폼과의 상호작용을 통해 재미와 즐거움을 키우며 나아가 지식을 얻을 수 있다.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.573-577
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• 2015

Safety is paramount for construction industry throughout the world. Human errors which contribute to more than half of construction accidents, could be proactively prevented through effective education and training methods. Although Virtual Reality (VR) and Augmented Reality (AR) have gained much attention in various disciplines, few studies applied them for construction safety education. This research presents a new approach in construction safety education by utilizing VR and AR. The vision of aligning teaching & learning strategies is examined in order to ensure the potential benefits of the new method. This innovative approach shifts safety education from "Listen, and I will forget. See, and I may remember" towards "Practice, and I understand".

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.27-32
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• 2024

Recently, there has been a growing interest in integrating physical toys into video gaming within the game content business. This paper introduces a novel method that leverages low-cost camera as an alternative to using sensor attachments to meet this rising demand. We address the limitations associated with low-cost cameras and propose an optical design tailored to the specific environment of model car recognition. We overcome the inherent limitations of low-cost cameras by proposing an optical design specifically tailored for model car recognition. This approach primarily focuses on recognizing the underside of the car and addresses the challenges associated with this particular perspective. Our method employs a transfer learning model that is specifically trained for this task. We have achieved a 100% recognition rate, highlighting the importance of collecting data under various camera exposures. This paper serves as a valuable case study for incorporating low-cost cameras into vision systems.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.360-374
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• 2024

A personalized course recommendation algorithm based on deep learning in an online education cloud platform is proposed to address the challenges associated with effective information extraction and insufficient feature extraction. First, the user potential preferences are obtained through the course summary, course review information, user course history, and other data. Second, by embedding, the word vector is turned into a low-dimensional and dense real-valued vector, which is then fed into the compressed interaction network-deep neural network model. Finally, considering that learners and different interactive courses play different roles in the final recommendation and prediction results, an attention mechanism is introduced. The accuracy, recall rate, and F1 value of the proposed method are 0.851, 0.856, and 0.853, respectively, when the length of the recommendation list K is 35. Consequently, the proposed strategy outperforms the comparison model in terms of recommending customized course resources.

• The Journal of the Korea Contents Association
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• v.14 no.2
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• pp.205-222
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• 2014

This study analyzed the effects of interactivity on the learning attitude in the tablet PC-based digital textbook environment. Most of digital textbook studies focused on comparison of learning effect between digital textbook and paper textbook. This study, instead, focused on the interaction between students and digital textbook, and examined the hypothesis that, in the digital textbook-based learning environment, interactivity factors affect learning attitude. The results showed that active control, two-way communication, and synchronicity have significant effects on the learning attitude. Those findings indicate that it's necessary to effectively realize interactivity in the process of developing digital textbooks. Also, important implication is not the fixed interactivity but how students perceive the digital textbook and make use of it. Therefore, for the interactive digital textbook, perceived user control, two-way communication, and synchronicity should be realized properly.

• Smart Media Journal
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• v.13 no.5
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• pp.45-51
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• 2024

Recently, realistic contents such as virtual reality(VR) and augmented reality (AR) are widely used for education to provide beneficial learning environments with thee-dimensional(3D) information and interactive technology. Specially, AR technology will be helpful to intuitively understand by adding virtual objects registered in the real learning environment with effective ways. In this paper, we developed an AR learning system using 3D spatial information in the 2D based textbook for studying math related to geometry. In order to increase spatial learning effect, we applied to solid shapes such as prisms and pyramids in mathematics education process. Also, it allows participants to use various shapes and expression methods (e.g., wireframe mode) with interaction. We conducted the experiment with our AR system, evaluated achievement and interest. Our experimental study showed positive results, our results are expected to provide effective learning methods in various classes through realistic visualization and interaction methods.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.4
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• pp.231-241
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• 2006

Creating controllable, responsive avatars is an important problem in computer games and virtual environments. Recently, large collections of motion capture data have been exploited for increased realism in avatar animation and control. Large motion sets have the advantage of accommodating a broad variety of natural human motion. However, when a motion set is large, the time required to identify an appropriate sequence of motions is the bottleneck for achieving interactive avatar control. In this paper, we present a novel method for training avatar behaviors from unlabelled motion data in order to animate and control avatars at minimal runtime cost. Based on machine learning technique, called Q-teaming, our training method allows the avatar to learn how to act in any given situation through trial-and-error interactions with a dynamic environment. We demonstrate the effectiveness of our approach through examples that include avatars interacting with each other and with the user.