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Adaptive Learning System based on the Concept Lattice of Formal Concept Analysis

FCA 개념 망에 기반을 둔 적응형 학습 시스템

  • 김미혜 (가톨릭대학교 컴퓨터교육과)
  • Received : 2010.09.09
  • Accepted : 2010.10.20
  • Published : 2010.10.28

Abstract

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.

Keywords

Adaptive Learning;Adaptive Learning System;Concept Lattice;Formal Concept Analysis

Acknowledgement

Supported by : 대구가톨릭대학교

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