The spirit of Web 2.0 is through the collective power of communities to create, share and comment on the opinions of the user and others. The purpose of this study is to use the concept of Web 2.0 to design an English article recommendation system for senior high school students who are reading and learning. Five different databases of English vocabularies are utilized in this work. They are the GEPT level six, Intelligent Web-based Interactive Language Learning (IWiLL), senior high school English textbooks (SHSETs), the Web News collected on the Internet and PyDict English-Chinese dictionary. First, IWiLL, SHSETs and Web News Corpus are used for data pre-processing. Then they are combined with the GEPT level six to do article difficulty calculation. Lastly, phrases of three words in the article are compared with PyDict dictionary to translate into Chinese for learners to remember and learn. In this study, the system is combined with Facebook; therefore, learners only need to use a Facebook account to log on to the system with the use of Facebook Social Plugins components so that learners who like the article may share and recommend it to friends on Facebook. This is not limited to studying indoors, as learners can also use smart mobile devices outdoors to connect to the Internet in order to achieve ubiquitous learning.