### Abstract

The inexact event such as the cognition would properly be analyzed using fuzzy graph rather than using crisp graph. In this paper, we present an analysis method of the teaching material structure by applying fuzzy graph. At first, we make teaching material structure graph and teach m a them, a tics. After the lessons, we give quizzes and collect test scores. We get similarity structure matrix (graph), partition tree, connectivity matrix (graph) and approximate graph by analyzing the test score. We get cognition graph by combining partition tree and approximate graph. By comparing teaching material graph with cognition graph, vie verify/improve teaching material structure graph. We also illustrate its practical effectiveness with the case study concerning the quiz of "permutation" and "combination" to high school students.

Original language | English |
---|---|

Pages (from-to) | 589-594 |

Number of pages | 6 |

Journal | ICIC Express Letters |

Volume | 6 |

Issue number | 3 |

Publication status | Published - 2012 Mar |

### Fingerprint

### Keywords

- Cognition structure graph
- Connectivity graph
- Fuzzy graph
- Partition tree
- Similarity graph
- Teaching materials

### ASJC Scopus subject areas

- Computer Science(all)
- Control and Systems Engineering

### Cite this

*ICIC Express Letters*,

*6*(3), 589-594.

**Eaching material structure analysis applying fuzzy graph.** / Nagashima, Kenichi; Takizawa, Takenobu.

Research output: Contribution to journal › Article

*ICIC Express Letters*, vol. 6, no. 3, pp. 589-594.

}

TY - JOUR

T1 - Eaching material structure analysis applying fuzzy graph

AU - Nagashima, Kenichi

AU - Takizawa, Takenobu

PY - 2012/3

Y1 - 2012/3

N2 - The inexact event such as the cognition would properly be analyzed using fuzzy graph rather than using crisp graph. In this paper, we present an analysis method of the teaching material structure by applying fuzzy graph. At first, we make teaching material structure graph and teach m a them, a tics. After the lessons, we give quizzes and collect test scores. We get similarity structure matrix (graph), partition tree, connectivity matrix (graph) and approximate graph by analyzing the test score. We get cognition graph by combining partition tree and approximate graph. By comparing teaching material graph with cognition graph, vie verify/improve teaching material structure graph. We also illustrate its practical effectiveness with the case study concerning the quiz of "permutation" and "combination" to high school students.

AB - The inexact event such as the cognition would properly be analyzed using fuzzy graph rather than using crisp graph. In this paper, we present an analysis method of the teaching material structure by applying fuzzy graph. At first, we make teaching material structure graph and teach m a them, a tics. After the lessons, we give quizzes and collect test scores. We get similarity structure matrix (graph), partition tree, connectivity matrix (graph) and approximate graph by analyzing the test score. We get cognition graph by combining partition tree and approximate graph. By comparing teaching material graph with cognition graph, vie verify/improve teaching material structure graph. We also illustrate its practical effectiveness with the case study concerning the quiz of "permutation" and "combination" to high school students.

KW - Cognition structure graph

KW - Connectivity graph

KW - Fuzzy graph

KW - Partition tree

KW - Similarity graph

KW - Teaching materials

UR - http://www.scopus.com/inward/record.url?scp=84856773470&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84856773470&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:84856773470

VL - 6

SP - 589

EP - 594

JO - ICIC Express Letters

JF - ICIC Express Letters

SN - 1881-803X

IS - 3

ER -