### 抄録

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.

元の言語 | English |
---|---|

ページ（範囲） | 589-594 |

ページ数 | 6 |

ジャーナル | ICIC Express Letters |

巻 | 6 |

発行部数 | 3 |

出版物ステータス | Published - 2012 3 |

### Fingerprint

### ASJC Scopus subject areas

- Computer Science(all)
- Control and Systems Engineering

### これを引用

*ICIC Express Letters*,

*6*(3), 589-594.

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

研究成果: Article

*ICIC Express Letters*, 巻. 6, 番号 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 -