توضیحات
ABSTRACT
As a nearly global language, English as a Foreign Language (EFL) programs are essential for people wishing to
learn English. Researchers have noted that extensive reading is an effective way to improve a person’s command
of English. Choosing suitable articles in accordance with a learner’s needs, interests and ability using an elearning
system requires precise learner profiles. This paper proposes a personalized English article
recommending system, which uses accumulated learner profiles to choose appropriate English articles for a learner. It employs fuzzy inference mechanisms, memory cycle updates, learner preferences and analytic
hierarchy process (AHP) to help learners improve their English ability in an extensive reading environment. By using fuzzy inferences and personal memory cycle updates, it is possible to find an article best suited for bot a
learner’s ability and her/his need to review vocabulary. After reading an article, a test is immediately provided
to enhance a learner’s memory for the words newly learned in the article.
INTRODUCTION
With advances in network technologies, geographic barriers are hardly a problem now for global communication.
Languages, whether written or spoken, are the major tools for cyber communication, and English, with its wide
popularity, has been recognized as a global language. For non-native English-speaking people, extensive reading is
common way to improve a person’s command of English. English is even taken as a major course in primary schools in many countries where English as a Foreign Language (EFL) is taught, especially East Asia. One of the keys to success in English learning depends on a person’s vocabulary volume.
Year:2012
Publisher: Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan
By: Tung-Cheng Hsieh, Tzone-I Wang, Chien-Yuan Su and Ming-Che Lee
File information: English Language /16 Page / Size : 1Mb
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سال: 2012
ناشر: Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan
کاری از: Tung-Cheng Hsieh, Tzone-I Wang, Chien-Yuan Su and Ming-Che Lee
اطلاعات فایل: زبان انگلیسی/ 16 صفحه/ حجم : 1 مگابایت
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