• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.519-525
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• 2006

Advances in information and telecommunication technology increasingly reveal the potential of computer supported education. However, most computer supported learning systems until recently did not pay much attention to different characteristics of individual learners. Intelligent learning environments adaptive to learner's preferences and tasks are desired. Each learner has different preferences and needs, so it is very crucial to provide the different styles of learners with different learning environments that are more preferred and more efficient to them. This paper reports a study of the intelligent learning environment where the learner's preferences are diagnosed using learner models, and then user interfaces are customized in an adaptive manner to accommodate the preferences. In this research, the learning user interfaces were designed based on a learning-style model by Felder & Silverman, so that different learner preferences are revealed through user interactions with the system. Then, a learning style modeling is done from learner behavior patterns using Decision Tree and Neural Network approaches. In this way, an intelligent learning system adaptive to learning styles can be built. Further research efforts are being made to accommodate various other kinds of learner characteristics such as emotion and motivation as well as learning mastery in providing adaptive learning support.

• The Mathematical Education
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• v.62 no.3
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• pp.303-326
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• 2023

Mathematics is a discipline with a strong systemic structure, and learning deficits in previous stages have a great influence on the next stages of learning. Therefore, it is necessary to frequently check whether students have learned well and to provide immediate feedback, and for this purpose, intelligent tutoring system(ITS) can be used in math education. For this reason, it is necessary to reveal how the intelligent tutoring system is effective in personalized adaptive learning. The purpose of this study is to investigate the functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics. To achieve this goal, literature reviews and surveys with students were applied to derive implications. Based on the literature reviews, the functions of intelligent tutoring system for personalized adaptive learning were derived. They can be broadly divided into diagnosis and evaluation, analysis and prediction, and feedback and content delivery. The learning and lesson plans were designed by them and it was applied to fifth graders in elementary school for about three months. As a result of this study, intelligent tutoring system was mostly supporting personalized adaptive learning in mathematics in several ways. Also, the researcher suggested that more sophisticated materials and technologies should be developed for effective personalized adaptive learning in mathematics by using intelligent tutoring system.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.421-428
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• 2006

Intelligent Tutoring System(ITS), which offers individualized learning environment that consider many learners' variable, is realized by the effective alternative to take the place of domain expert. Accordingly, research on Learning Companion System(LC) is currently noticing. However, to develop LCS which applies effective interaction, it is necessary to combine several LCs, and personalized knowledge base have to be made first. Therefore, in this paper, we propose the 'Knowledge Base Object Medel', which is based on connectionist' in cognition structure, represents learner's knowledge to self-learnig object, and grows adaptive object by proprietor, verify the validity. This model lays the groundwork for design of personalized knowledge base, offers clue to development of adaptive ITS using knowledge base object.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.438-448
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• 2005

This paper proposes an adaptive tutoring system that provides learning materials dynamically according to the learners' teaming character and ability. Our system, in which a learning phase and a test phase are linked together, supports the personalized instruction-learning by providing the teaming materials by level in the learning phase according to the teaming ability estimated in the test phase. We design and implement a tutoring system consisted of an evaluation component and a learning component. An evaluation component uses a computerized adaptive test(CAT) based on item response theory to evaluate learners' ability while a learning component employs fuzzy level set theory so that teaming contents are provided to learners according to learners' level.

• The Journal of Korean Association of Computer Education
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• v.9 no.1
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• pp.29-39
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• 2006

In this paper, we propose an adaptive tutoring system, which analyzes learning process, subject materials, and test items of students, diagnoses learning problems of them, and then gives proper advice accordingly. In the system, learning materials are constructed using concept map, on which the relationships among learning concepts are represented. Concept map can be used for several purposes in instruction process. Our work considers that new learning knowledge is dependent on what is already known. That is, it means that precedent concepts should be thoroughly learned for students to comprehend new concepts. After grasping the learning state of students for precedent concepts to be required before learning new concepts, our system provides proper learning materials for want of them, diagnoses the concepts which students have trouble to understand in the learning process, and provides suggestions for it.

• Journal of The Korean Association of Information Education
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• v.2 no.2
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• pp.201-208
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• 1998

Recently software complexity will continue to increase dramatically in the coming decades because of the dynamic and distributed nature of both data and applications. Not only must software systems assist in coordinating tasks among humans, they must also help mannage cooperation among distributed programs. Software agent may properly respond to these requirements. This paper investigates the adaptive characteristics found in adaptive tutoring agents. To funcion effectively throughout the range of situations presented by such a dynamic and extremely-distributed information entities, an agent must be highly adaptive. Adaptivity exists in several key aspects of agent's behavior to its dynamic situation. My goal is to show the various aspects of internal adaptivity that could be applied to build comprehensive agents that function effectively in tutoring agent system.

• The KIPS Transactions:PartA
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• v.10A no.4
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• pp.321-330
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• 2003

This paper proposes an agent-based adaptive tutoring system that monitors learning process of learners' and provides learning materials dynamically according to the analyzed learning character. Furthermore, it uses fuzzy concept to evaluate learners' ability and to provide learning materials appropriate to the level of learners'. For this, we design a courseware knowledge structure systematically and then construct a fuzzy level set on the basis of it considering importance of learning targets, difficulty of learning materials and relation degree between learning targets and learning materials. Using agent, monitoring continually the learning process of learners 'inferencing to offer proper hints in case of incorrect answer in learning assesment, composing dynamically learning materials according to the learning feature and the evaluation of assesment, our system implements effectively adaptive instruction system. Moreover, appling the fuzzy concept to the system could naturally consider and ideal with various and uncertain items of learning environment thus could offer more flexible and effective instruction-learning methods.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.3
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• pp.71-78
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• 2001

Since web-based tutoring systems are generally composed with passive and static hypertext, they could not provide adaptive learning environments according to learning ability of each student. In this study, we suggest an intelligent tutoring system, which grasps the learning state of student and provides each student with dynamic learning materials suitable to individual feature based on learning result. It is an agent based system, in which, courseware knowledge for learning is effectively constructed, the proper feedback according to learning assessment is inferred, and it is given to each student.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.152-158
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• 2001

Since web_based tutoring systems are generally composed with passive and static hypertext, they could not provide adaptive learning environments according to learning ability of each student. In this study, we suggest an intelligent tutoring system, which grasps the learning state of student and provides each student with dynamic learning materials suitable to individual feature based on learning result. It is an agent based system, in which, courseware knowledge for learning is effectively constructed, the proper feedback according to learning assessment is inferred, and it is given to each student.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6455-6460
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• 2013

Learner modeling forms the foundations for intelligent tutoring systems that provide adaptive and active learning guidance for learning and education quality enhancement. The aim of this study was to develop learner modeling technologies to form the foundation of intelligent tutoring systems. Specific research tasks include learner modeling building techniques, diverse learner state diagnosis methods and educational data mining.