Vocabulary Learning in an Automated Graded Reading Program

Adult L2 learners are often encouraged to acquire new words through reading in order to promote language proficiency. Yet preparing suitable reading texts is often a challenge for teachers because the chosen texts must have a high percentage of words familiar to specific groups of learners in order to allow the inference of word meanings from context. With the help of word lists research and advances in quantitative corpus analyses using word frequency computer programs, this study selected sixteen articles from the computer corpus of a local Chinese-English magazine and used them to construct an online English extensive reading program. A preliminary assessment of the reading program was conducted with 38 college students over twelve weeks based upon vocabulary gains from a pretest to a posttest. The results showed that learners improved their vocabulary scores after using the reading program. The online extensive reading syllabus demonstrated that such a design for a reading program is technically feasible and pedagogically beneficial and provides value in both vocabulary gains and learner satisfaction.