Integrating Automatic Speech Recognition Technology Into Vocabulary Learning in a Flipped English Class for Chinese College Students

Abstract

Although the automatic speech recognition (ASR) technology is increasingly used for commercial purposes, its impact on language learning has not been extensively studied. Underpinned by the sociocultural theory, the present work examined the effects of leveraging ASR technology to support English vocabulary learning in a tertiary flipped setting. A control group and an experimental group of college students participated in a 14-week study. Both groups had their English classes in a flipped fashion, but the experimental group was assigned with ASR-assisted oral tasks for pre-class self-learning. The pre- and post-intervention in-class task performance of both groups was audio-recorded and transcribed for data analysis. The triadic complexity-accuracy-fluency (CAF) framework was adopted to evaluate the participants' vocabulary learning. The between- and within-subjects effects were examined mainly through procedures of MANCOVA and mixed-design repeated measures ANCOVA. Results showed that on all the metrics of lexical complexity and speed fluency, the experimental group outperformed the control group, and had significant growth over time. On the other hand, the control group only improved significantly overtime on the G-index. On lexical accuracy, there was no significant difference between the two groups, and the within-subjects effect was not significant for either group. The findings lent some support to Skehan's Trade-off Hypothesis and discussions were conducted regarding the triarchic CAF framework.

Exploring the effects of automatic speech recognition technology on oral accuracy and fluency in a flipped classroom

“…Automatic speech recognition (ASR) technology has gradually attracted the attention of researchers and practitioners in foreign language (FL) education and a growing number of studies have been carried out to investigate its special effects on the learners' oral performance in the target language (e.g. Evers & Chen, 2020, 2021; Franco et al, 2010; Jiang, Jong, Wu, et al, 2022; van Doremalen et al, 2016). Apart from various ASR‐based commercial systems available such as Duolingo and iFlyRec, some academic ASR‐based language learning programs have been developed in educational institutions (e.g.…”

Blended Learning Strategies of College English Learning in Chinese Higher Education: A Systematic Review

“…This underscores the significant role of blended learning strategies in enhancing students' English language achievements. Despite its favorable attributes, some scholars (Jiang, 2022;Ma, 2022;Cao, 2019) contended that blended learning is conceptually straightforward but somewhat intricate to implement. Effective integration of blended learning necessitates collaborative efforts from teachers and students.…”

“…Strong proficiency in the English language is deemed essential for English learners. Nevertheless, English language skills continue to pose challenges for these learners, encompassing reading, writing, speaking, and listening (Yao, 2019;Jiang, 2022;Wang, 2020). Previous literature has unveiled that the subpar writing abilities of English learners stem from the intricacies of writing conventions and the predicaments associated with anticipating reader responses (Li, 2022).…”

“…As for the latter, several factors affecting students' reading comprehension have been identified, including limited vocabulary, restricted use of original English reading materials, and difficulties in accessing the learning platform due to network issues. Jiang (2022) explained the use of Quizlet software by Chinese college students to learn English. The results showed that students have positive attitudes towards using Quizlet software to help them learn English and believe that it can increase their motivation to learn the language.…”

“…Chinese higher education sector is already equipped with the most promising and latest frameworks (Rui, 2014), and blended learning has been used as a tool to promote the adoption of these models and transform the higher education sector for the next generation (Lim et al, 2019). Despite the increased trends of research in Chinese English learning, the systematic reviews are focused more on comparing traditional teaching methods and blended learning models Sun (2018); Jiang (2022), students' or teachers' perspectives on blended learning methods Lin (2019); Qian (2022); Jiang (2021), thereby leaving a gap. Therefore, there is an urgent need to review blended learning strategies used for Chinese college students in the Chinese English courses.…”