Modeling of the students scenario on a learning course

Yuji Shinoda, Kenji Yoshida, Hirotaka Nakayama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Adjusting the content to each student is a major issue in e-Learning. From this viewpoint, a learning course as a series of content also must be adjusted according to the performance of the students. We propose a method that combines clustering and decision tree learning for constructing scenarios of the students' actions. The global statuses of the students are reflected to the clusters, and the local and sequential actions of the students are reflected to the decision trees. The results of e-Learning tests gathered from Japanese junior high school students was processed by our proposed method. We graded the clusters by adaptation to the trees, and selected a set of clusters as a scenario for the students. These scenarios have a possibility of aiding the adjustment, and revision of learning courses.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings
Pages573-579
Number of pages7
Volume5177 LNAI
EditionPART 1
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008 - Zagreb
Duration: 2008 Sep 32008 Sep 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5177 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008
CityZagreb
Period08/9/308/9/5

Fingerprint

Electronic Learning
Students
Decision tree
Scenarios
Modeling
Decision trees
Adjustment
Clustering
Series
Learning

Keywords

  • Clustering
  • Decision Tree
  • E-learning
  • K-means
  • User model

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Shinoda, Y., Yoshida, K., & Nakayama, H. (2008). Modeling of the students scenario on a learning course. In Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings (PART 1 ed., Vol. 5177 LNAI, pp. 573-579). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5177 LNAI, No. PART 1). https://doi.org/10.1007/978-3-540-85563-7-73

Modeling of the students scenario on a learning course. / Shinoda, Yuji; Yoshida, Kenji; Nakayama, Hirotaka.

Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings. Vol. 5177 LNAI PART 1. ed. 2008. p. 573-579 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5177 LNAI, No. PART 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shinoda, Y, Yoshida, K & Nakayama, H 2008, Modeling of the students scenario on a learning course. in Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings. PART 1 edn, vol. 5177 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 5177 LNAI, pp. 573-579, 12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008, Zagreb, 08/9/3. https://doi.org/10.1007/978-3-540-85563-7-73
Shinoda Y, Yoshida K, Nakayama H. Modeling of the students scenario on a learning course. In Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings. PART 1 ed. Vol. 5177 LNAI. 2008. p. 573-579. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-540-85563-7-73
Shinoda, Yuji ; Yoshida, Kenji ; Nakayama, Hirotaka. / Modeling of the students scenario on a learning course. Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings. Vol. 5177 LNAI PART 1. ed. 2008. pp. 573-579 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
@inproceedings{f8266d7db79e4bbaa300720b2e32654c,
title = "Modeling of the students scenario on a learning course",
abstract = "Adjusting the content to each student is a major issue in e-Learning. From this viewpoint, a learning course as a series of content also must be adjusted according to the performance of the students. We propose a method that combines clustering and decision tree learning for constructing scenarios of the students' actions. The global statuses of the students are reflected to the clusters, and the local and sequential actions of the students are reflected to the decision trees. The results of e-Learning tests gathered from Japanese junior high school students was processed by our proposed method. We graded the clusters by adaptation to the trees, and selected a set of clusters as a scenario for the students. These scenarios have a possibility of aiding the adjustment, and revision of learning courses.",
keywords = "Clustering, Decision Tree, E-learning, K-means, User model",
author = "Yuji Shinoda and Kenji Yoshida and Hirotaka Nakayama",
year = "2008",
doi = "10.1007/978-3-540-85563-7-73",
language = "English",
isbn = "3540855629",
volume = "5177 LNAI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 1",
pages = "573--579",
booktitle = "Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings",
edition = "PART 1",

}

TY - GEN

T1 - Modeling of the students scenario on a learning course

AU - Shinoda, Yuji

AU - Yoshida, Kenji

AU - Nakayama, Hirotaka

PY - 2008

Y1 - 2008

N2 - Adjusting the content to each student is a major issue in e-Learning. From this viewpoint, a learning course as a series of content also must be adjusted according to the performance of the students. We propose a method that combines clustering and decision tree learning for constructing scenarios of the students' actions. The global statuses of the students are reflected to the clusters, and the local and sequential actions of the students are reflected to the decision trees. The results of e-Learning tests gathered from Japanese junior high school students was processed by our proposed method. We graded the clusters by adaptation to the trees, and selected a set of clusters as a scenario for the students. These scenarios have a possibility of aiding the adjustment, and revision of learning courses.

AB - Adjusting the content to each student is a major issue in e-Learning. From this viewpoint, a learning course as a series of content also must be adjusted according to the performance of the students. We propose a method that combines clustering and decision tree learning for constructing scenarios of the students' actions. The global statuses of the students are reflected to the clusters, and the local and sequential actions of the students are reflected to the decision trees. The results of e-Learning tests gathered from Japanese junior high school students was processed by our proposed method. We graded the clusters by adaptation to the trees, and selected a set of clusters as a scenario for the students. These scenarios have a possibility of aiding the adjustment, and revision of learning courses.

KW - Clustering

KW - Decision Tree

KW - E-learning

KW - K-means

KW - User model

UR - http://www.scopus.com/inward/record.url?scp=57849093620&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=57849093620&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-85563-7-73

DO - 10.1007/978-3-540-85563-7-73

M3 - Conference contribution

SN - 3540855629

SN - 9783540855620

VL - 5177 LNAI

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 573

EP - 579

BT - Knowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings

ER -