Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

Impact Factor

1.60

CiteScore

Chin-Hwa Kuo This email address is being protected from spambots. You need JavaScript enabled to view it.1 and Chen-Chung Chi1

1CSIE, Tamkang University, Tamsui, Taiwan 251, R.O.C.


 

Received: May 14, 2014
Accepted: October 24, 2014
Publication Date: December 1, 2014

Download Citation: ||https://doi.org/10.6180/jase.2014.17.4.04  


ABSTRACT


For numerous people who are English as a foreign language (EFL) learners, reading English articles is an effective activity for improving reading comprehension. In this research, an article recommendation system that identifies articles of suitable difficulty levels for EFL learners was designed. The system design was based on the vocabulary sets of the General English Proficiency Test (GEPT). Using text mining and classifying techniques, the system compares the difficulty levels of articles found on news Web sites and in textbooks, as well as articles written by EFL high school students. In this study, language learners’ current language proficiency levels were assessed to create the learning environment introduced in Krashen’s second language acquisition theory. The document classification verification results indicated that the reading material recommendation system (which is based on GEPT vocabulary sets as the foundation of article feature extraction) can effectively classify the difficulty levels of vocabularies contained in articles of various difficulty levels. Additionally, articles that complied with learners’ language levels based on the evaluation results were used as the reading materials for learning purposes.


Keywords: Article Recommendation System, Cosine Similarity, Document Readability, Second Language Acquisition


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