廣泛閱讀在英文學習上,已經成為增進學習者閱讀能力及語文程度的一個重要且有效的方法。而隨著網際網路快速發展,人們可以從網路上藉由閱讀文章來吸收知識。然而很多學習者常常對英文閱讀感到相當困擾,原因在於每位學習者的英文閱讀能力都不盡相同,而他們又讀到難度高過自己英文程度的文章。倘若能根據學習者的英文閱讀能力提供難度適中的文章給他們,此閱讀策略較能增進學習者的動力跟興趣。本篇論文提出一個適性化英文線上閱讀系統。我們的系統從一些線上新聞網站搜集新聞當閱讀題材,並且計算每篇新聞文章的難度。學習者透過我們系統閱讀每日新聞及學習英文時,在閱讀完畢後,系統會提供學習者一個回饋模組來調查其學習情形,並且分析學習者提供的回饋資料及學習情形。根據我們分析出來的資料,學習者在下次閱讀時系統會提供適當程度的文章給他們閱讀。此外本系統也整合了英文學習中聽的部份,讓學習者除了閱讀文章之外,也能多一種方式來學習英文。
In English learning, extensive reading has been recognized as a powerful and effective method for improving learners’ reading ability and increasing their language proficiency. With the rapid development of the Internet, the learners can absorb knowledge through reading English articles in the Internet. However, many learners are often confused with reading English articles. The reason is that every learner’s reading ability is different and they read the difficulty level of articles which exceed their reading level of English. If we provide learners with articles which suit their reading level, this reading strategy can increase their learning motivation and confidence. This thesis proposes a web-based adaptive reading system for English learners. Our system collects the news from English news websites as materials of reading and computes the difficulty level of each news article. After the learners finish reading a news article through our system, the system offers a feedback module to investigate their situation of learning for learners, and analyzes the information of feedback. According to the information our system analyzes, the system will provide news articles of suitable reading level for them next time when the learners read a news article. In addition, our system also offers the audio of news articles to let learners have an alternative way of learning English besides reading the articles.