Developing a Mobile-Assisted Software Application to Observe University Students’ Vocabulary Growth Through Extensive Reading

Abstract

Based on a consensus of what makes good training of extensive reading, this paper aims to demonstrate how a mobile-assisted extensive reading (MAER) tool including a recommendation service and an online assessment was designed to support a reading process of the printed articles in a setting where English is learned as a foreign language. It was intended that learners could still use a paper format to read the topics closely matched their interests and vocabulary levels. This paper also shows how this tool was implemented in a class as a case study. 35 English majors studying in a freshmen class were observed in a ten-week period to use the system. Up to 3 hours guided by MAER, they were able to read up to 24 articles on average. Moreover, their vocabulary recognition level was found to have a significant improvement according to a paired-samples t-test. The implications and suggestions for using or developing MAER are then offered in consideration of the findings.