• Journal of The Korean Association of Information Education
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• v.18 no.4
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• pp.541-548
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• 2014

The goal of this study is to suggest evaluation tools to assess computational thinking(CT) skills in primary robot-based programs. In addition, the researcher has expanded its evaluation approaches to include interpersonal competencies from the socio-cultural perspectives, not just focusing on intrapersonal competencies. In order to pursue the research goal, one-semester robots programs for the fifth graders were designed, and evaluation tools including a learners' CT competencies survey and a learning process monitoring rubric were developed. The results of this study are meaningful because it has expanded the evaluation approaches to connect to the concepts of CT and to include interpersonal aspects from the socio-cultural perspectives.

• 한국정보교육학회:학술대회논문집
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• 2010.08a
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• pp.9-13
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• 2010

Supported by the Ministry of Knowledge Economy, this research explored the potentiality of the use of hands-on robots in elementary school curriculum. On the basis of the analysis of prior research, we defined the meaning and the characteristics of hands-on robots. The priority was given to the development of lesson plans in attempting to activate the use of robots in elementary school curriculum. Also considering the difficulties faced in schools and the characteristics of robot-based instruction, we classified hands-on robots according to the shape and the goal of use.

• Proceedings of The KACE
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• 2017.08a
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• pp.197-199
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• 2017

재난 상황이나 우주 공간과 같은 환경에서는 인간이 직접 작업을 수행하기가 매우 어렵다. 따라서 이러한 환경에서 인명 구조나 탐사 등을 진행할 때에는 원격으로 제어가능한 로봇을 활용하는 것이 효과적이다. 특히 이 로봇이 인간의 움직임을 실시간으로 모방한다면 직관적이고 순발력 있는 제어가 가능해진다. 본 연구에서는 키넥트 센서를 이용해 인간의 움직임을 인식하고 이 움직임을 모방하는 로봇핸드와 로봇암을 구현하였다. 하드웨어는 TETRIX와 EV3 플랫폼을 이용하여 설계하였고, 소프트웨어는 C# 기반의 KINECT for Windows SDK와 Visual Studio 2015로 구현하였다. 본 연구에서 구현한 시스템은 재난 현장에서의 인명 구조, 복구 상황에서와 우주 공간에서의 탐사 상황에서 유용하게 사용될 수 있을 것이다.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.239-245
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• 2020

With the recent revised curriculum, the importance of exploring children's play through new teaching media is increasing in kindergarten. In this study, it is to use the robot 'Bee-bot' for early children to uncover the changes that children have through free exploration and play. As a result of comparing the change of scientific problem-solving ability of 3, 4, and 5-year-olds, there were significant changes in all three sub-elements. We propose to us scientific problem-solving ability test tools, propose and apply ideas for problem-solving, conclusion on problem-solving Building. Through this, it was found that unplugged play using 'Bee-bot' is meaningful as a play environment and as a teaching medium for children aged 3, 4 and 5 years old.

• Journal of The Korean Association of Information Education
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• v.22 no.4
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• pp.419-425
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• 2018

The national curriculum includes the problem solving process, algorithms, and programming of SW education. The education using robots is one of attractive alternatives for students who have no interest of SW or are poor at programming. We have developed a courseware using robots for SW education based on paper art activities with narrative storytelling to enhance students' creative thinking and problem solving within limitation of class time in schools. We apply the courseware and obtained the result of pre and post-test on the creative problem solving ability of third graders in the elementary school The four factors of creative problem solving have shown significantly increase. In addition, it had an significant effects for understanding robot technology and for learning attitude using robots of SW or programming.

• Journal of Engineering Education Research
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• v.26 no.4
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• pp.22-35
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• 2023

As information and communication technology has developed remarkably, it has become possible to analyze various types of large-volume data generated at a speed close to real time, and based on this, reliable value creation has become possible. Such big data analysis is becoming an important means of supporting decision-making based on scientific figures. The purpose of this study is to develop a big data analysis tool that can analyze large amounts of data generated through engineering education. The tasks of this study are as follows. First, a database is designed to store the information of entries in the National Creative Capstone Design Contest. Second, the pre-processing process is checked for analysis with big data analysis tools. Finally, analyze the data using the developed big data analysis tool. In this study, 1,784 works submitted to the National Creative Comprehensive Design Contest from 2014 to 2019 were analyzed. As a result of selecting the top 10 words through topic analysis, 'robot' ranked first from 2014 to 2019, and energy, drones, ultrasound, solar energy, and IoT appeared with high frequency. This result seems to reflect the current core topics and technology trends of the 4th Industrial Revolution. In addition, it seems that due to the nature of the Capstone Design Contest, students majoring in electrical/electronic, computer/information and communication engineering, mechanical engineering, and chemical/new materials engineering who can submit complete products for problem solving were selected. The significance of this study is that the results of this study can be used in the field of engineering education as basic data for the development of educational contents and teaching methods that reflect industry and technology trends. Furthermore, it is expected that the results of big data analysis related to engineering education can be used as a means of preparing preemptive countermeasures in establishing education policies that reflect social changes.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.109-116
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• 2021

In this paper, we propose the educational model for a convergence minor by fusing culinary arts with robot technology to develop coding ability for the students in the culinary arts major which is not originally related to software field. It is meaningful that the educational model follows the trend along the development of the fourth industrial revolution technology and has the function to make the students who are not in software major grow as software experts. However there are difficulties in designing the convergence minor because the culinary arts major is distant to the robot technology in the view of technology. To overcome this difficulty the convergence minor is designed to attract the interest for the students in culinary arts major by construct educational subjects systematically such as cooking, dessert making, barista working, autonomous serving and so on based on robots. Also the practices in which various robots are utilized are included in the convergence minor to develop actual coding ability. By comparison to the other models of convergence minors, the proposed model shows enhanced educational effects in 20% than the others.

• The KIPS Transactions:PartA
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• v.18A no.5
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• pp.165-176
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• 2011

In this paper, we show how a curriculum using LEGO MINDSTORMS NXT robot based ROBOTC for undergraduate students has been developed, and we analyze the educational effect of the curriculum. The curriculum is composed of basic knowledge learning, practice with basic robots, practice with advanced robots, and creative design and implementation of robots. During the three year period since 2009, educational achievement has been analyzed by surveys for 6 classes, 94 students. According to the analysis, the curriculum has highly motivated the students and made them to achieve effectively our educational and academic goals. Also, we observe that the curriculum helped the students to improve their creativity and the problem solving skill, and that the students were autonomously and deeply involved in the homework and the term projects, which made them be very cooperative. Finally, the intensive practice with ROBOTC programming is shown to help students to improve their programming ability of C language.

• Journal of the Korea Convergence Society
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• v.1 no.1
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• pp.1-15
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• 2010

The Education has responsibility for predicting the social changes and cultivating global talent which the society needs. The ministry of education, science and technology in govern ment has been the concerns on social educational changes and thus built the '5 31 educational reform policy' in 1995 by the educational reform committee. As a solution of a social change, this paper reviews the three-phase educational information policies, and e-learning and u-learning which are the main technologies in educational information. Also, the technologies of e-learning can be divided into m-learning, t-learning, u-learning, r-learning, game-based learning according to the contents mass media. Among them, this paper introduces the concept of robot-learning, called r-learning, and compares it with u-learning.