Peng Chen
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Peng Chen has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Bin Zou
Department of Applied Linguistics, Xi’an Jiaotong-Liverpool University
1 shared publication - Xin Guan
Department of Applied Linguistics, Xi’an Jiaotong Liverpool University, Suzhou 215123, China
1 shared publication - Yinghua Shao
Department of Applied Linguistics, Xi’an Jiaotong Liverpool University, Suzhou 215123, China
1 shared publication
Latest Publications
- Top Cited PapersOpen Access
- 5 February 2023
- Published by MDPI AG in Sustainability
- Vol. 15 (4) , 2872
Supporting Speaking Practice by Social Network-Based Interaction in Artificial Intelligence (AI)-Assisted Language Learning
In recent decades, the rapid development of artificial intelligence (AI) technology has led to the increasing use of AI speaking apps in foreign language learning. This research investigates the impact of social network-based interaction on students’ English speaking practice with the assistance of AI speaking apps in China. During the summer vacation, 70 students from different Chinese universities and majors were recruited for the experiment. They were required to practice speaking skills with AI apps for five weeks and were divided into two groups. Participants in the experimental group were encouraged to engage in various interactive activities when practicing speaking with AI apps, while those in the control group were asked to use AI speaking apps without interaction. Data were collected through questionnaires and semi-structured interviews as well as pre-and post-tests. The results indicated that students generally held positive attitudes towards interactive activities when using AI apps to practice their spoken English. The finding also showed that social network-based interaction can effectively improve learners’ speaking skills in the AI context. This study contributes to the research on the implementation and promotion of AI speaking apps with social networking and extends the previous studies on network-based interaction to the AI-assisted learning environment. An investigation of interactions based on Chinese social network-based platforms such as WeChat can be further applied to other social networking platforms such as Facebook or WhatsApp in different cultural contexts for AI-assisted speaking practice.
- 5 February 2023
- Published by MDPI AG in Sustainability
- Vol. 15 (4) , 2872
Top Cited PapersOpen AccessSupporting Speaking Practice by Social Network-Based Interaction in Artificial Intelligence (AI)-Assisted Language Learning
In recent decades, the rapid development of artificial intelligence (AI) technology has led to the increasing use of AI speaking apps in foreign language learning. This research investigates the impact of social network-based interaction on students’ English speaking practice with the assistance of AI speaking apps in China. During the summer vacation, 70 students from different Chinese universities and majors were recruited for the experiment. They were required to practice speaking skills with AI apps for five weeks and were divided into two groups. Participants in the experimental group were encouraged to engage in various interactive activities when practicing speaking with AI apps, while those in the control group were asked to use AI speaking apps without interaction. Data were collected through questionnaires and semi-structured interviews as well as pre-and post-tests. The results indicated that students generally held positive attitudes towards interactive activities when using AI apps to practice their spoken English. The finding also showed that social network-based interaction can effectively improve learners’ speaking skills in the AI context. This study contributes to the research on the implementation and promotion of AI speaking apps with social networking and extends the previous studies on network-based interaction to the AI-assisted learning environment. An investigation of interactions based on Chinese social network-based platforms such as WeChat can be further applied to other social networking platforms such as Facebook or WhatsApp in different cultural contexts for AI-assisted speaking practice.