Development of a reading material recommendation system based on a knowledge engineering approach

Ting-Chia Hsu, Gwo Jen Hwang, Chih Kai Chang

Research output: Contribution to journalArticle

50 Citations (Scopus)

Abstract

In a language curriculum, the training of reading ability is one of the most important aspects. Previous studies have shown the importance of assigning proper articles to individual students for training their reading ability; nevertheless, previous experience has also shown the challenges of this issue owing to the complexity of personal factors as well as the diverse properties of the candidate articles to be taken into consideration. This study proposes a knowledge engineering approach for developing reading material recommendation systems by eliciting domain knowledge from multiple experts. Experimental results on 29 senior high school students show that the developed system is able to provide expert-like recommendations to the students by taking preferences and knowledge levels of individual students as well as categories and traits of articles into consideration.

Original languageEnglish
Pages (from-to)76-83
Number of pages8
JournalComputers and Education
Volume55
Issue number1
DOIs
Publication statusPublished - 2010 Aug 1

Fingerprint

Knowledge engineering
Recommender systems
Students
engineering
student
expert
level of knowledge
ability
Curricula
candidacy
curriculum
language
school
knowledge
experience

Keywords

  • Improving classroom teaching
  • Intelligent tutoring systems

ASJC Scopus subject areas

  • Computer Science(all)
  • Education

Cite this

Development of a reading material recommendation system based on a knowledge engineering approach. / Hsu, Ting-Chia; Hwang, Gwo Jen; Chang, Chih Kai.

In: Computers and Education, Vol. 55, No. 1, 01.08.2010, p. 76-83.

Research output: Contribution to journalArticle

@article{6e0f5ccfa28d4f6089f12683e5c2c54d,
title = "Development of a reading material recommendation system based on a knowledge engineering approach",
abstract = "In a language curriculum, the training of reading ability is one of the most important aspects. Previous studies have shown the importance of assigning proper articles to individual students for training their reading ability; nevertheless, previous experience has also shown the challenges of this issue owing to the complexity of personal factors as well as the diverse properties of the candidate articles to be taken into consideration. This study proposes a knowledge engineering approach for developing reading material recommendation systems by eliciting domain knowledge from multiple experts. Experimental results on 29 senior high school students show that the developed system is able to provide expert-like recommendations to the students by taking preferences and knowledge levels of individual students as well as categories and traits of articles into consideration.",
keywords = "Improving classroom teaching, Intelligent tutoring systems",
author = "Ting-Chia Hsu and Hwang, {Gwo Jen} and Chang, {Chih Kai}",
year = "2010",
month = "8",
day = "1",
doi = "10.1016/j.compedu.2009.12.004",
language = "English",
volume = "55",
pages = "76--83",
journal = "Computers and Education",
issn = "0360-1315",
publisher = "Elsevier Limited",
number = "1",

}

TY - JOUR

T1 - Development of a reading material recommendation system based on a knowledge engineering approach

AU - Hsu, Ting-Chia

AU - Hwang, Gwo Jen

AU - Chang, Chih Kai

PY - 2010/8/1

Y1 - 2010/8/1

N2 - In a language curriculum, the training of reading ability is one of the most important aspects. Previous studies have shown the importance of assigning proper articles to individual students for training their reading ability; nevertheless, previous experience has also shown the challenges of this issue owing to the complexity of personal factors as well as the diverse properties of the candidate articles to be taken into consideration. This study proposes a knowledge engineering approach for developing reading material recommendation systems by eliciting domain knowledge from multiple experts. Experimental results on 29 senior high school students show that the developed system is able to provide expert-like recommendations to the students by taking preferences and knowledge levels of individual students as well as categories and traits of articles into consideration.

AB - In a language curriculum, the training of reading ability is one of the most important aspects. Previous studies have shown the importance of assigning proper articles to individual students for training their reading ability; nevertheless, previous experience has also shown the challenges of this issue owing to the complexity of personal factors as well as the diverse properties of the candidate articles to be taken into consideration. This study proposes a knowledge engineering approach for developing reading material recommendation systems by eliciting domain knowledge from multiple experts. Experimental results on 29 senior high school students show that the developed system is able to provide expert-like recommendations to the students by taking preferences and knowledge levels of individual students as well as categories and traits of articles into consideration.

KW - Improving classroom teaching

KW - Intelligent tutoring systems

UR - http://www.scopus.com/inward/record.url?scp=77949874553&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77949874553&partnerID=8YFLogxK

U2 - 10.1016/j.compedu.2009.12.004

DO - 10.1016/j.compedu.2009.12.004

M3 - Article

AN - SCOPUS:77949874553

VL - 55

SP - 76

EP - 83

JO - Computers and Education

JF - Computers and Education

SN - 0360-1315

IS - 1

ER -