### Abstract

This paper proposes a method of automatically analyzing the characteristics of e-learning contents, using e-learning time data stored in learning history databases. Although many studies exist on mathematical models of the response time, they have the disadvantage that the parameters are difficult to interpret and estimate. The response curve of e-learning time data proposed in this paper has the unique feature of deriving its two-parameter model by employing the Entropy maximization method with certain restrictions so as to make it easier to interpret the parameters. The two parameters α and β in the model are interpreted as follows: α represents the complexity of the content (i.e., the number of simple cognitive processes required to understand or solve the content) and β represents the expected time of a simple cognitive process in the content. This means that the average learning time for a content is divided into the two parameters α and β, so that the average learning time for a content is equivalent to the product of α and β. Based on these parametric properties, this paper proposes a new content evaluation method using the α-β plane, or α-β chart. Incorporating this evaluation method, the authors have developed a LMS (Learning Management System), the effectiveness of which is demonstrated in practical situations. The results show that the system let a teacher grasp contents characteristic easily and is effective for contents improvement

Original language | English |
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Title of host publication | IEEE International Conference on Computer Systems and Applications, 2006 |

Pages | 994-1002 |

Number of pages | 9 |

Volume | 2006 |

Publication status | Published - 2006 |

Externally published | Yes |

Event | IEEE International Conference on Computer Systems and Applications, 2006 - Sharjah Duration: 2006 Mar 8 → 2006 Mar 8 |

### Other

Other | IEEE International Conference on Computer Systems and Applications, 2006 |
---|---|

City | Sharjah |

Period | 06/3/8 → 06/3/8 |

### Fingerprint

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*IEEE International Conference on Computer Systems and Applications, 2006*(Vol. 2006, pp. 994-1002). [1618474]

**On-line content analysis system using e-learning time data.** / Ueno, Maomi; Nagaoka, Keizo.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*IEEE International Conference on Computer Systems and Applications, 2006.*vol. 2006, 1618474, pp. 994-1002, IEEE International Conference on Computer Systems and Applications, 2006, Sharjah, 06/3/8.

}

TY - GEN

T1 - On-line content analysis system using e-learning time data

AU - Ueno, Maomi

AU - Nagaoka, Keizo

PY - 2006

Y1 - 2006

N2 - This paper proposes a method of automatically analyzing the characteristics of e-learning contents, using e-learning time data stored in learning history databases. Although many studies exist on mathematical models of the response time, they have the disadvantage that the parameters are difficult to interpret and estimate. The response curve of e-learning time data proposed in this paper has the unique feature of deriving its two-parameter model by employing the Entropy maximization method with certain restrictions so as to make it easier to interpret the parameters. The two parameters α and β in the model are interpreted as follows: α represents the complexity of the content (i.e., the number of simple cognitive processes required to understand or solve the content) and β represents the expected time of a simple cognitive process in the content. This means that the average learning time for a content is divided into the two parameters α and β, so that the average learning time for a content is equivalent to the product of α and β. Based on these parametric properties, this paper proposes a new content evaluation method using the α-β plane, or α-β chart. Incorporating this evaluation method, the authors have developed a LMS (Learning Management System), the effectiveness of which is demonstrated in practical situations. The results show that the system let a teacher grasp contents characteristic easily and is effective for contents improvement

AB - This paper proposes a method of automatically analyzing the characteristics of e-learning contents, using e-learning time data stored in learning history databases. Although many studies exist on mathematical models of the response time, they have the disadvantage that the parameters are difficult to interpret and estimate. The response curve of e-learning time data proposed in this paper has the unique feature of deriving its two-parameter model by employing the Entropy maximization method with certain restrictions so as to make it easier to interpret the parameters. The two parameters α and β in the model are interpreted as follows: α represents the complexity of the content (i.e., the number of simple cognitive processes required to understand or solve the content) and β represents the expected time of a simple cognitive process in the content. This means that the average learning time for a content is divided into the two parameters α and β, so that the average learning time for a content is equivalent to the product of α and β. Based on these parametric properties, this paper proposes a new content evaluation method using the α-β plane, or α-β chart. Incorporating this evaluation method, the authors have developed a LMS (Learning Management System), the effectiveness of which is demonstrated in practical situations. The results show that the system let a teacher grasp contents characteristic easily and is effective for contents improvement

UR - http://www.scopus.com/inward/record.url?scp=33750829180&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33750829180&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:33750829180

SN - 1424402123

SN - 9781424402120

VL - 2006

SP - 994

EP - 1002

BT - IEEE International Conference on Computer Systems and Applications, 2006

ER -