• Journal of Digital Convergence
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• v.19 no.10
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• pp.39-48
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• 2021

This study aimed to analyze the level of professors' understanding and perception of adaptive learning and proposed how college can implement successful adaptive learning in college classes. For research purposes, online survey was conducted by 162 professors of A university in capital region. As a result, professors seemed to feel pressure to provide students personalized feedback and gave concerned that students don't study enough in advance before participating in class. It was also found that professors realized that they have low level of understanding about adaptive learning, while they revealed intention to make use of adaptive learning in their class. They also answered that adaptive learning system is the most helpful support for encouraging professors to apply adaptive learning in real class. We proposed what is required to encourage professor to implement adaptive learning in their class.

• Journal of The Korean Association of Information Education
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• v.16 no.2
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• pp.173-180
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• 2012

This study looks for the requirements for adaptive courseware and provides background for developing effective adaptive courseware. Most adaptive courseware does not adequately reflect the requirements of learners. If it properly reflected learners' requirements well, it could be used more effectively. therefore, this study analyzes and suggests the requirements of an adaptive courseware for pre-service teachers who are majoring in computer education. The study methods were factor analysis and frequency analysis through survey. The results show that the important elements of an adaptive courseware are a learning style designed according to individual differences as well as an instruction model appropriate to the subject domain. The study examined adaption by learner level, by learning objective, by learning style, by method of learning content, and by learning history in that order. Therefore while the most of adaptive courseware support learning style; we propose that the adaptive courseware will support learning objects and instruction model as well.

• The Journal of the Korea Contents Association
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• v.10 no.10
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• pp.479-493
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• 2010

Along with the transformation of the knowledge-based environment, e-learning has become a main teaching and learning method, prompting various research efforts to be conducted in this field. One major research area in e-learning involves adaptive learning systems that provide personalized learning content according to each learner's characteristics by taking into consideration a variety of learning circumstances. Active research on ontology-based adaptive learning systems has recently been conducted to provide more efficient and adaptive learning content. In this paper, we design and propose an adaptive learning system based on the concept lattice of Formal Concept Analysis (FCA) with the same objectives as those of ontology approaches. However, we are in pursuit of a system that is suitable for learning of specific domains and one that allows users to more freely and easily build their own adaptive learning systems. The proposed system automatically classifies the learning objects and concepts of an evolved domain in the structure of a concept lattice based on the relationships between the objects and concepts. In addition, the system adaptively constructs and presents the learning structure of the concept lattice according to each student's level of knowledge, learning style, learning preference and the learning state of each concept.

• Journal of The Korean Association of Information Education
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• v.17 no.4
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• pp.383-391
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• 2013

This study developed an adaptive instruction system for individual learning. We applied Gregorc's learning style to support the adaption. This proposed Instruction system provides instruction content based on a more effective instruction method that takes into consideration the learner's individual learning style. We applied Gregorc's learning style to create a clear treatment of differing learning styles. Proposed adaptive instruction system was applied to college students studying computer learning. A t-test indicated that our proposed adaptive instruction system resulted in positive effects in an overall style comparison. In addition, our Abstract-Sequential learning style indicated the most effective results while the Abstract-Random learning style indicated no difference between the experimental and comparative groups in each style analysis for Gregorc's learning style.

• The Journal of Korean Association of Computer Education
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• v.12 no.6
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• pp.53-67
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• 2009

In this study we surveyed the characteristics of the Semantic Web and ontology technology, analyzing the studies which applied ontology to e-Learning. In addition, we investigated the models which should be considered in the adaptive learning, analyzing the existing adaptive learning systems. On the basis of the analysis of them, we sought the ways to apply ontology for supporting the adaptive learning in the e-learning system, designing an ontology-based adaptive learning system. The system made up for the weak points of the existing ontology-based learning systems. That is, it appropriately diagnoses learners' knowledge level of learning concepts, classifying the learning styles in detail, and providing their corresponding learning methods and content. By adapting the learning content to the learners' individual learning style and knowledge level, this system would support their learning more efficiently and more effectively.

• The Journal of the Korea Contents Association
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• v.4 no.1
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• pp.8-17
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• 2004

In this paper, we design an intelligent loaming management logics which provide personalized teaming considering adaptive learning content dement and content sequencing. We enhance the existing functional model including adaptive learning management functions. Also, we present a system architecture to implement the adaptive learning management system. We realize the adaptive teaming management system based on the SCORM run-time engine.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.517-535
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• 2021

The development of digital technology has not only brought many changes to our lives, but also many changes to the online education environment. The emergence of micro-learning is to meet the needs of individual learners who hopes to receive personalized learning content immediately when they need it. Therefore, Micro-learning can be said to be 'adaptive' education. This research attempts to explore the development principles of adaptive micro-learning through literature research and case analysis. The results of the research draw four aspects of the development principles, including adaptive learning environment, adaptive learning content, adaptive learning sequence and adaptive learning evaluation, as well as detailed elements of each aspect. Micro-learning is a new form of e-learning that reflects the needs of the current society. As exploratory research, this research attempts to point out the direction for future follow-up research.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.201-206
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• 2018

Recently, as technologies for realizing artificial intelligence have become more common, machine learning is widely used. Machine learning provides insight into collecting large amounts of data, batch processing, and taking final action, but the effects of the work are not immediately integrated into the learning process. In this paper proposed an adaptive learning model to improve the performance of real-time stream analysis as a big business issue. Adaptive learning generates the ensemble by adapting to the complexity of the data set, and the algorithm uses the data needed to determine the optimal data point to sample. In an experiment for six standard data sets, the adaptive learning model outperformed the simple machine learning model for classification at the learning time and accuracy. In particular, the support vector machine showed excellent performance at the end of all ensembles. Adaptive learning is expected to be applicable to a wide range of problems that need to be adaptively updated in the inference of changes in various parameters over time.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.667-669
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• 2004

적응적 웹기반 기법에서 학습자의 반응이나, 탐색 행동의 근본적인 원인이 되는 학습 동기, 지각 등에 대한 판단을 정확히 할 수 없기 때문에, 학습자에게 완전히 적응적인 수업 환경을 조성해 주는 데는 한계가 있다. 이러한 한계를 극복하기 위한 대안으로 학습자간 상호작용이나 협동 학습을 지원하는 웹기반 교수 시스템이 제안되고 있다. 본 논문에서는 웹기반 환경에서 학습자들간의 협동학습을 효과적으로 지원하는 적응형 교수 시스템을 제안한다. 본 시스템은 협동학습 공간에서 주어진 과제를 수행하기 위해 발생되는 학습자들의 대화와 서로간의 상호작용을 분석하여 적절한 조언을 제공함으로서 협동학습이 효과적으로 이루어 질 수 있도록 지원한다.

• The Journal of Korean Association of Computer Education
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• v.9 no.1
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• pp.61-70
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• 2006

In the area of e-learning education, SCORM2004 that is suggested by ADL and is a defacto standard allows to design and apply various interrelations among learning objects which organize learning process through consolidating IMS Simple Sequencing into S&N. In this paper, we intend to realize a web_based adaptive learning management that enable to guide experientially the learning activity through the SCORM 2004 S&N and the Traffic-Signal-Lamp Metaphor. This adaptive system allows professor to design the learning courseware realizing various learning strategies to be able to reuse same learning contents and student to be leaded a adaptive learning through being supplied immediately the state and evaluation of learning.