• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.6-10
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• 2009

In these days, recommendation service in mobile environments is in the limelight due to the spread of mobile devices and an increase of information owing to advancement of computer network. The restaurant recommendation system reflecting user preference was proposed. This system uses Bayesian network to model user preference and analytical hierarchical process to recommend restaurants, but static inference model for user preference used in the system has some limitations that cannot manage changing user preference and enormous user survey must be preceded. This paper proposes a learning method for Bayesian network based on user requests. The proposed method is implemented on mobile devices and desktop, and we show the possibility of the proposed method through experiments.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.408-413
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• 2020

본 논문은 아고다 사이트의 호텔 정보를 크롤링하여 사용자의 선호 호텔을 구글에서 제공하는 Tensorflow로 인공신경망 딥러닝 학습하여 사용자가 선호하는 호텔을 맞춤 추천하는 애플리케이션의 설계 및 구현에 대하여 서술한다. 본 애플리케이션은 해외(베트남) 호텔을 취향에 맞게 추천받을 수 있도록 만들어진 애플리케이션으로 기존의 필터링 방식으로 추천하는 방식의 애플리케이션들과 달리 사용자의 취향을 딥러닝 학습을 통해 파악하고 최적의 호텔 정보를 추천하는 기능을 제공한다. 본 애플리케이션에 사용된 선호 호텔 예측 모델은 약 84%의 정확도를 보이며 추천 별점으로 표시되어 사용자가 각 호텔에 대해 얼마만큼 선호도를 갖는지 알 수 있다.

• Journal of Gifted/Talented Education
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• v.22 no.1
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• pp.39-59
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• 2012

This study has two purposes: The first is to compare gifted with non-gifted about learning styles and examine differences in the preference of learning styles between group characteristics depending on gender. The second is to examine differences between gifted and non-gifted about the preference of learning styles. The participants were 152 students from the middle schools in A City. 76 students of them belonged to the gifted group and the rest were non-gifted group. LSDI Learning Styles Diagnostic Inventory has been employed as measurement tools. Besides descriptive statistics, ANOVA, ${\chi}^2$ analysis were used to measure items. The results from data analysis are as follows. First, there was difference in learning styles between gifted and non-gifted. Second, there was not difference in the preference of learning styles between groups depending on the gender. Finally, this study discussed the results and their implication, the direction of future research in understanding and interpreting of learning styles for their practical usages.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06b
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• pp.269-271
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• 2011

이러닝은 기능적인 요소기술의 구현에 초점을 두었던 단계를 지나 학습자의 학습 능력과 취향, 선호도 및 학습습관을 고려하며 사용자의 편의와 학습의 품질을 근본적이고 획기적으로 개선하기 위한 유러닝으로 발전하고 있다. 이와 함께 IMS 학습설계는 병렬세션관리, 협동학습과 혼합학습 지원 측면에서 그 동안 국내외에서 개별학습을 지원하는 표준안으로 활용되어온 ADL의 SCORM 국제표준이 갖는 한계 문제점을 해결할 수 있는 대안으로서 등장하였다. 하지만 제정된 이후로 개정이 되지 않아 유러닝을 지원하기 위해서는 개선이 요구되고 있다. 이를 위해 본 논문에서는 지식서비스 USN 산업원천 기술개발 과제의 세부과제인 'U-러닝 환경 표준 및 표준 명세 개발 및 검증' 과제에서 맞춤형 학습을 지원하고 사용자 편의를 제공할 수 있도록 확장된 학습설계 표준에 대하여 소개한다.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.69-75
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• 2022

This study investigated the English learners who are over 40 on their attitudes and perception for lifelong education by dividing them into age groups of middle aged and elderly learners. To this end, from May 20, 2020 to June 30, 2021, 80 participants attending lifelong education centers in North Gyeongsang province were surveyed on the demographic characteristics and interest, necessity, passion, advantage, hindrance, learning motivation, preferred subjects, and learning methods. As a result, it was found that elderly learners showed a more positive English learning attitude than middle-aged learners, and both groups considered the communication area important in their learning motivation and preferred subjects. In regard to hindrance toward English learning, different factors were shown according to the age groups along with lack of confidence in English. Differences were also shown in preferred learning methods. This study suggested the possibility of learning outcomes according to the positive learning attitude of elderly learners along with the need for detailed English program design according to learners' age.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.133-136
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• 2000

우리는 인터넷을 통한 사용자의 선호도(preference)를 분석하고 협력적 여과 기술을 학습하여 유머문서를 추천하는 MrHumor 시스템을 구축하였다. MrHumor에서는 사용자집합이 유머문서 집합에 대하여 보여준 등급매김값을 토대로 사용집합의 백터공간(vector space)를 설정하고 노이즈에 강하면서 효율적인 학습을 위해 선형 PCA를 이용하여 축소된 2차원 공간상에서 유머문서의 통계적 특성을 반영하여 적응형 k-NN으로 지엽성을 적적히 조절하여 새로운 문서에 대한 선호도를 추정하게 된다.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.339-348
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• 2016

The purpose of this study was to identify the Kolb's learning style and preference for instructional methods of undergraduate nursing students. Data were collected from 174 students at a university in D city using a structured questionnaire from October 19 to October 21 2015. Learning style ratio of nursing students was accommodator 34.5%, converger 33.9%, assimilator 16.1%, diverger 15.5% and preference scores for instructional methods were discussion 7.27, direct instruction 7.26, peer teaching 7.22, independent study 6.54, project 6.25, instruction through technology 5.77, game 5.45, simulation 4.23. A significant difference was found in experience of flipped learning between four learning styles groups of nursing students. However, there was no significant difference in the preference of instructional methods between the four learning styles groups. Most of the students were in the middle range of the learning styles. The assessment of nursing students' learning styles is expected to help educator to plan teaching strategies.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.595-596
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• 2020

2020학년도 1학기는 외부 환경 요인으로 인해 대학교육시스템에 큰 변화가 발생한 시기라고 할 수 있다. 컴퓨터공학 분야의 대표적인 실습기반 교과목인 프로그래밍 수업에서 학습자들에게 온라인 수업이지만 대면 수업의 실재감을 제공하는 방법을 모색할 필요성이 대두되었다. 본 연구에서는 다양한 유형의 수업 방식을 온라인 수업에 활용하여 대면 수업 수준의 실재감을 학습자에게 제공하고 학습효과를 높이고자 하였다. 강의 동영상 수업과 상호작용을 포함한 실시간 수업을 혼합하여 수업한 후 설문 조사를 통해 실시간 수업을 선호하는 학습자들이 수업목표인 프로그램 개발 능력을 타 학습자들보다 잘 습득하여 수업 만족도가 높았고, 이를 통해 온라인 수업에서 실시간 수업이 능동적인 학습자들에게는 대면 수업과 동등한 수준의 학습 효과가 있었음을 조사·분석하였다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.127-135
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• 2011

It is required that an e-learning system has a content recommendation component which helps a learner choose an item. In order to predict items concerning learner's interest, collaborative filtering and content-based filtering methods have been most widely used. The methods recommend items for a learner based on other learner's interests without considering the knowledge level of the learner. So, the effectiveness of the recommendation can be reduced when the number of overall users are relatively small. Also, it is not easy to recommend a newly added item. In order to address the problem, we propose a content recommendation method based on the similarity and the difficulty of an item. By using a recommendation function that reflects both characteristics of items, a higher-level leaner can choose more difficult but less similar items, while a lower-level learner can select less difficult but more similar items, Thus, a learner can be presented items according to his or her level of achievement, which is irrelevant to other learner's interest.

• The Journal of Korean Association of Computer Education
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• v.20 no.1
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• pp.39-47
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• 2017

The purpose of this study is to analyze research trends and the learners' preference for subject area of SW education content. First, we analyzed trends in the subject areas of various SW education contents in recent research literature, textbooks, and textbooks. Based on this, we defined six subject areas as storytelling, game, media art, educational learning contents, simulation. Also, we analyzed the case of college students based on the reason of SW implementation theme selection, selection method, and preference theme. As a result, the students were mainly influenced by their interests and teachers in the reason of topic selection, and they showed higher preference in game and storytelling subject area. We hope that this research will be reflected in balanced SW education contents design according to learner level in the future.