• Proceedings of The KACE
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• 2018.08a
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• pp.81-84
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• 2018

정보기술(IT)이 발달함에 따라 프로그래밍 학습에 대한 관심이 크게 증가하고 있으며, 특히 2018년도부터는 소프트웨어 교육(코딩 교육)이 의무화가 되었다. 하지만 아직도 대부분의 프로그래밍 학습 방법은 교재의 내용을 확인한 다음 편집 에디터에 코딩을 한 후, 빌드 및 실행하는 과정을 거쳐 결과를 확인하는 다소 번거로운 방법을 거치고 있다. 본 연구에서는 프로그래밍 학습자가 보다 편리하게 학습할 수 있도록 전자책 뷰어가 갖추어야 할 스마트한 기능들을 제시하고 구현하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.223-225
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• 2022

미래 변화에 대응하는 역량으로 디지털 리터러시가 제시되고 있다. 국내에서는 2022 교육과정 개정의 중점 사항으로 미래 변화에 대응하는 역량으로 디지털 기초 소양을 강화한다. 한편 코로나19로 원격수업이 확대되면서 LMS(Learning Management System)의 사용이 증가하였다. LMS는 디지털 기기, 소프트웨어를 활용하므로 디지털 리터러시를 함양할 수 있는 기회가 될 것이다. 본 연구에서는 학교 현장에서 활용되는 Microsoft의 Teams, Google의 Classroom, KERIS의 위두랑과 e학습터를 비교하고 디지털 리터러시 내용 요소와 LMS 기능을 관련지어 활용방안을 제시하였다. 본 연구를 통해 LMS를 활용하면서 디지털 리터러시를 기를 수 있을 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.23-26
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• 2006

최근 대부분의 이러닝(E-Learning)을 교육하는 사이트는 학습 콘텐츠를 검색하는 방법이 단순한 리스트의 나열과 택스트 매칭(Text matching)방법을 사용하는 단점이 있다. 이를 보완하기 위해 좀 더 컴퓨터가 정보 데이터의 의미를 분석하여 검색이 가능하도록 개념 네트워크인 시맨틱웹(Semantic Web)이 등장하였다. 본 논문에서는 이러한 시맨틱웹의 온톨로지(Ontology) 언어 중에 토픽맵(Topic Maps)을 사용하여 많은 양의 학습 정보 데이터를 쉽고도 정확하게 연결 지어 학습 콘텐츠에 대한 정보를 표현하고, 구조화할 수 있는 방법을 모색해 보고자 한다. 학습자의 관심분야 정보, 학습객체의 학습 권장자의 정보와 함께 학습 경험과 검색 빈도수를 분석한 협력 필터링과 학습 에이전트의 개인화 기법을 동시에 사용하여 선호도를 분석한다. 이 선호도를 가지고 학습자의 메타데이터를 생성하고, 로그 데이터를 따로 데이터베이스에 저장한다. 이러한 학습자의 정보와 학습 콘텐츠간의 정보를 상호 연결하여, 그 토픽맵을 사용하여 연관관계를 정의해 줌으로써 학업성취도를 높이고, 학습자 개개인의 성향에 가장 알맞은 학습 콘텐츠를 탐색해가는 네비게이터(Navigator)를 설계하였다.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.13-28
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• 2021

Reinforcement Learning (RL) is a machine learning algorithm that repeat the closed-loop process that agents perform actions specified by the policy, the action is evaluated with a reward function, and the policy gets updated accordingly. The key benefit of RL is the ability to optimze the policy with action evaluation. Hence, it can effectively be applied to developing advanced intelligent systems and autonomous systems. Conventional RL incoporates a single policy, a reward function, and relatively simple policy update, and hence its utilization was limited. In this paper, we propose an extended RL model that considers multiple instances of RL elements. We define a formal model of the key elements and their computing model of the extended RL. Then, we propose design methods for applying to system development. As a case stud of applying the proposed formal model and the design methods, we present the design and implementation of an advanced car navigator system that guides multiple cars to reaching their destinations efficiently.

• The Journal of Sustainable Design and Educational Environment Research
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• v.23 no.1
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• pp.1-11
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• 2024

Complex school facilities are being considered to meet increased public demands for culture and welfare in Korea, given the decreasing population. In this context, Gyeongi-do Hwaseong City's E-umteo is recognized as a relatively well-operated school complex. Therefore, this study considered seven E-umteo branches as case studies to examine the operations of educational programs and understand the techniques employed in the spatial configuration of E-umteo. To this end, field observations and interviews with facility operators were conducted. The case analysis results revealed that educational programs could be classified into three types: learning sharing , community communication, and lifelong learning. Furthermore, the learning sharing type was classified into education and physical education while the community communication type was classified into the community and convenience types. Meanwhile, lifelong learning was identified as the most actively used type by differentiating specialized programs. With regard to the spatial composition between the school and the "pitcher," only the connection and independent types were observed, and no integral type was discovered. Therefore, integrated future studies are mandated.

• Journal of Korean Elementary Science Education
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• v.40 no.1
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• pp.13-21
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• 2021

This study analyzed the effects of 'online biology learning using E-learning system' on elementary school students' science-related attitudes. Samples of the study were composed of 95 sixth-grade students of N elementary school in Seoul, Korea. The learning was conducted for 11 times over a month. The main results of this study are as follows. First, for the paired t-test, a statistically significant difference between the pre and post scores of science-related attitudes was found. After conducting the online biology learning science related attitudes scores of students generally declined. "The boredom caused by simply watching online biology contents" is the decisive cause of the decline in science-related attitude scores analyzed through interviews. Second, in ANCOVA, according to 'levels of meta-cognition'. there was no statistically significant difference in scores of science-related attitudes. but, there was statistically significant difference in science-related attitudes according to 'adoption of scientific attitudes'. Students of high meta-cognition type showed a greater decline in scores than students of low meta-cognition type. Based on the results of this study, implications for research of online biology education and elementary science education are discussed.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1403-1404
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• 2011

본 논문에서는 동영상과 다양한 데이터들을 매쉬업하여 통합미디어컨텐츠(UMC : United Media Contnets)를 수월하게 제작하고 재생시켜주는 E.M.P.Z(Editor Media Player Zone)의 개발에 대해 기술한다. E.M.P.Z는 에디터를 사용하여 다양한 데이터를 편집하는 기능과 UMC를 재생하기 위한 플레이어 기능, 그리고 웹기반환경에서 검색 및 플레이기능 등을 제공하며, 학습을 위한 동영상강의, 스포츠중계, 광고 등의 다양한 분야에서 활용 가능하다.

• The Mathematical Education
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• v.61 no.2
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• pp.257-271
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• 2022

As information and communication technologies are being developed so rapidly, education research is actively conducted to provide optimal learning for each student using big data and artificial intelligence technology. In this study, using the mathematics learning data of elementary school 5th to 6th graders conducting blended mathematics classes, we tried to find out what factors predict mathematics academic achievement and developed an artificial intelligence model that predicts mathematics academic performance using the results. Math learning propensity, LMS data, and evaluation results of 205 elementary school students had analyzed with a random forest model. Confidence, anxiety, interest, self-management, and confidence in math learning strategy were included as mathematics learning disposition. The progress rate, number of learning times, and learning time of the e-learning site were collected as LMS data. For evaluation data, results of diagnostic test and unit test were used. As a result of the analysis it was found that the mathematics learning strategy was the most important factor in predicting low-achieving students among mathematics learning propensities. The LMS training data had a negligible effect on the prediction. This study suggests that an AI model can predict low-achieving students with learning data generated in a blended math class. In addition, it is expected that the results of the analysis will provide specific information for teachers to evaluate and give feedback to students.

• The Journal of Information Technology
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• v.6 no.3
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• pp.87-95
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• 2003

This research demonstrated the efficiency, when compared to the textbook-based learning method, of developing web-based Courseware and utilizing it in the class so that students could study on their own the mobile parts of Technology-home economics. The contents are as follows: It is designed based on Namo Web Editor 5.1, in conjunction with Java script, PHP, Mysql, and so on. Procedures are as follows: First, students learn a small unit and then have a quiz. After logging in, they are tested on what they have learned. Finally, they send the result to the teacher by e-mail. To verify the results of this research, we make two groups. Each group has 34 students. One group are taught by using developed Courseware program, the other group are taught by present teaching program.The result shows the difference in achievement to the extent of significance P<0.05. In conclusion, it proved to be effective.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.674-679
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• 2017

As the importance of the 4th industrial revolution and ICT technology increased, it became a software centered society. Existing software training was limited to the composition of the learning environment, and a lot of costs were incurred early. In order to solve these problems, a learning method using a web compiler was developed. The web compiler supports various software languages and shows compilation results to the user via the web. However, Web compilers that support artificial intelligence technology are missing. In this paper, we designed and implemented a tensor flow based web compiler, Google's artificial intelligence library. We implemented a system for learning artificial intelligence by building a meteorJS based web server, implementing tensor flow and tensor flow serving, Python Jupyter on a nodeJS based server. It is expected that it can be utilized as a tool for learning artificial intelligence in software centered society.