Improving Chinese University Students' Speaking Performance in Mobile-Assisted English Learning
Year: 2016
Type: dissertation
Study design: Clinical Trial
Abstract: Using guidelines from expectancy-value theory, I investigated the effect of positive feedback on Chinese university students’ English speaking performance in a mobile learning context. Aged between 18 and 22 (M=20.09, SD = .69), a total of 99 Chinese university students (n female = 53) who were learning English as a foreign language performed two mobile-assisted decision-making tasks in pairs. Each student submitted an audio recording of their group decision summary at the end of each task. Between the two tasks, students in the comparison group and the intervention group respectively received neutral and positive feedback on their performance in the first task. The students’ audio recordings of their summaries were used to assess their speaking performance in three different aspects: complexity, accuracy and fluency. Students’ language learning beliefs, engagement with mobile technology, task values and expectancies for the task were measured before and after they performed the two mobile-assisted language learning tasks. The use of positive feedback was found to have neither positive nor negative effect on students’ speaking accuracy or fluency, but significantly improved the complexity of their speaking performance. Neither task values nor expectancy beliefs were found to significantly predict speaking performance. Results are discussed in terms of the relationship among students’ expectancy beliefs, speaking performance, and their second language proficiency. Findings from this study help guide task implementations to influence performance and suggest a new, more detailed measure of expectancy beliefs to better capture the different aspects of language performance.
Source: Figshare
Author: Ying Liu
Language: English
Subfield: Language and Linguistics
Field: Arts and Humanities
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W2597648386
