• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.813-819
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• 2024

This study was conducted to highlight the need for systematic and tailored learning support strategies for students at A University in the Jeonbuk region, based on the results of the university's self-developed Multi-Dimensional Learning Competency Test (MLCT). The research aimed to analyze foundational data to accurately diagnose students' learning competencies according to their characteristics and provide customized learning support. A total of 773 participants were involved in the study, which analyzed the MLCT components of 'Motivation,' 'Cognition,' 'Behavior,' 'Emotion,' and 'Environment' across different groups based on sex, grade level, and college affiliation. The findings underscore the necessity of developing and disseminating various learning competency analysis tools to ensure that students can adapt well to university life and engage in successful learning activities without dropping out. This calls for the development of systematic learner diagnosis methods and tailored learning support programs.

• Journal of Christian Education in Korea
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• v.77
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• pp.225-249
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• 2024

Research Purpose : Based on artificial intelligence, this study considers learners' characteristics, learning content, and individual learning, and analyzes the collected learning data to develop a model that supports customized learning for individual learners. Research content and method : In order to achieve the research purpose, the literature was analyzed to investigate the structure of customized learning support, learning data analysis, and learning activities, and based on the investigated data, the area and detailed components of the customized learning support model were derived. did. A draft model was constructed through literature analysis, and the first expert Delphi survey was conducted on the draft model with five experts. The model was revised by reflecting the results of the first Delphi, and the validity of the revised model was verified through the second expert Delphi. The model was elaborated through expert Delphi, and the final model was constructed through this. Conclusion and Recommendation : Through research, customized learning support area, class management system area, and learning analysis data area were formed, and detailed elements were derived for each area. The results of this study provide basic data that can be used as a reference for constructing a customized learning support system based on artificial intelligence, taking into account the university's class environment.

• Journal of Practical Engineering Education
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• v.12 no.1
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• pp.49-60
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• 2020

With the advent of the knowledge-based era of the fourth industrial revolution, a paradigm shifts in university education. As a complete overhaul of university educational methods is required, strengthening competence through personalized is emerging as one of the solutions to the problem. To provide appropriate education accordingly focusing on individual learners, more studies at various levels are needed about understanding the characteristics of learners and ways to support them at universities. This study aims to conduct an exploratory research for adapting personalized learning at K University and explore effective ways to support. First, through literature review, the theoretical basis of personalized learning considering the diverse characteristics of learners and domestic and overseas cases of are examined. Secondly, a pilot study is conducted with K University students as subjects. FGI, study style diagnosis, one-on-one follow-up interviews are conducted and competency-based learning performance analysis and study style diagnosis result paper are provided to selected participants. Finally, major issues and implications are suggested to support the effective personalized learning of K university students.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.13-22
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• 2024

In the current epoch of educational technology (EdTech), the realization of a personalized learning system has become increasingly important. This is due to the growing diversity of today's learners in terms of backgrounds, learning styles, and abilities. Traditional educational methods that deliver the same content to all learners often fail to take this diversity into account. This paper identifies models that comprehensively analyze learners' characteristics, interests, and learning histories to meet the growing demand for learner-centered education. Based on these models, we have designed a personalized learning system. This system is structured to support autonomous learning tailored to the learner's current level and goals by identifying strengths and weaknesses based on the learner's learning history. In addition, the system is designed to extend necessary learning elements without changing its architecture. Through this research, we can identify the essential foundations for constructing a user-tailored learning system and effectively develop a system architecture to support personalized learning.

• Journal of The Korean Association of Information Education
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• v.15 no.1
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• pp.155-162
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• 2011

It is proven that students learn more effectively when they apply Empirical knowledge which they have experienced or been facing. Therefore, the customized training supporting systems for information communication ethics education for primary school is developed. It provide resources on the internet such as teaching methodology, teaching materials, real life examples and applications related to information communication ethics education to the teachers. Each resource is categorized according to the topic and it improved information communication ethics education by providing customized resources on the topic. It is also helpful for users to select necessary resources by informing the suitability between the subject and the resources and to lift the burden on searching the data.

• Communications of Mathematical Education
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• v.36 no.3
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• pp.417-438
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• 2022

The purpose of this study is to suggest implications for mathematics teaching and learning when using AI-based educational platforms that support personalized mathematics learning. To this end, we selected five platforms(Knock-knock! Math Expedition, knowre, Khan Academy, MATHia, CENTURY) and analyzed how the AI-based educational platforms for mathematics reflect the three elements(PLP, PLN, PLE) to support personalized learning. The results of this study showed that although the characteristics of PLP, PLN, and PLE implemented on each platform varied, they were designed to form PLEs that allow learners to make their autonomous decisions about learning based on PLP and PLN. The significance of this study can be found in that it has improved the understanding and practicability of personalized mathematics learning with the AI-based educational platforms.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.423-424
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• 2015

본 논문은 학습 수준에 따라 개인별 또는 그룹별로 학습이 가능하도록 지원하는 단체 학습 시스템을 제안한다. 제안하는 시스템은 교수자가 학습능력과 수준의 차이에 따라 학습자를 수준별로 그룹을 임의로 설정하여 설정된 개별 학습자 혹은 학습자 그룹별로 각기 다른 학습 콘텐츠를 제공하도록 함으로써 학생들이 같은 공간, 간은 시간대에 있더라도 개인별 맞춤 학습을 진행하는 것이 가능하다. 개별 학습자 또는 학습자 그룹별로 학습을 독립적으로 진행할 수 있도록 제어함으로써 모든 학습자는 개인화된 학습 시스템을 각기 사용하는 것과 같은 효과를 누리게 된다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.637-639
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• 2020

본 논문에서는 소외계층 영재학생을 위한 온라인 학습 멘토링 운영 방안을 도출하였다. 소외계층 영재학생에게 필요한 맞춤형 과제, 실생활 문제, 학업 관리를 지원하기 위하여 맞춤형 과제와 피드백, 학업 상담으로 이루어진 온라인 학습 멘토링 운영 방안을 도출하였다. 맞춤형 과제에서는 소외계층 영재학생의 수준에 따라 실생활 주제를 활용한 과제를 제시하였으며, 피드백을 통하여 과제의 결과물을 평가받을 수 있도록 구성하였다. 학업 상담에서는 학업 계획 및 관리 능력을 향상시키기 위하여 전문가와 함께 상담을 진행할 수 있도록 하였다. 후속 연구에서는 온라인 학습 멘토링을 소외계층 영재학생에게 운영하고, 온라인 학습 멘토링의 효과를 분석하는 연구가 진행되어야 한다.

• Korea Information Processing Society Review
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• v.16 no.5
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• pp.55-62
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• 2009

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.67-75
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• 2020

The 'level of difficulty' is one of the major factors for learners when selecting learning contents. However, the criteria for the difficulty level is mostly defined by the contents providers. This approach does not support the personalized education which should consider the abilities and environments of various learners. In this research, the knowledge of the learners and contents were formalized and generalized to resolve the issue, and object models, including a metric for personalized difficulty level, were designed in order to be applied for experiments. And then, based on 100 contents for music education and 20 learners, we performed simulations with an implemented tool to validate our approach. The experimental results showed that our method can calculate the personalized difficulty levels considering the similarities between the knowledges from the learning state and the contents. Our approach can be effectively applied to the on-line learning management system which contains easy access to the learning state and contents data.