An intelligent language tutoring system for handling errors caused by transfer

Abstract

This research addresses how an Intelligent Language Tutoring System can effectively help to solve a practical problem of transfer’ in students’ second language learning of Chinese. Our empirical data shows that the problem of transfer accounts for most of the errors observed in the linguistic output of English-speaking students in their study of Chinese. This accords with views of other experts on transfer in the field of second language learning, such as Selinker [15], Cornu [6], Sheen [16] and Cowan [7]. A technique of mixed grammar of Chinese and English is used to tackle the problem of transfer. In this paper, we describe the importance of transfer, explain the data that has been collected, present an overview of the three main models, demonstrate the technique that we use to handle errors of transfer and finally discuss how our system is going to be evaluated.