Video Self-Modeling (VSM) as a Strategy to Instruct CFL Students’ Sentence-Level Stress

Abstract

Sentence-level stress is one of the major means of expressing information focus in oral speaking, and it is of importance for Chinese as a foreign language (CFL) learners to accurately receive and send the right information in conversation. However, research related to teaching stress, especially sentence-level stress, is indeed scarce. In this study, we investigate whether video self-modeling (VSM) is applicable to improve CFL students’ sentence-level stress. VSM, as an innovative strategy, only shows the positive targeted behavior by using videos or audios of oneself, and aims to decrease students’ frustration and the negative influence caused by failed accomplishments. Twelve beginning-level CFL students, taken as the experimental group, received the edited perfect pronunciation audios with their own voice and used these own-voice audios to train their sentence-level stress. At the same time, another twelve advanced-level CFL students were taken as the control group, and received traditional instructional strategies from their class teacher. The whole training continued for ten sessions during a period of two and half months. Quantitative results show that with the help of VSM, CFL students’ sentence-level stress improved significantly as compared to the control group, with increased scores on the pronunciation of sentence-level stress words and increased scores in all three parameters: pitch, intensity, and duration. A post-training survey revealed that the participants’ preference for using their own voice as instructional material resulted in a feeling of success and satisfaction. The findings corroborate the importance of computer-assisted language learning in the second language (L2) field, and add solid evidence of using VSM in foreign-language training.