Enhancing EFL Speaking Performance through AI-Powered Conversational Agents: A Mixed-Methods Study at Dong Nai Technology University

Abstract The current paper examines the efficiency of AI-assisted conversational agents in enhancing the speaking proficiency of Vietnamese EFL university students. To conduct the research, a mixed methods design was used, including a quasi-experiment along with questionnaire and interview-based qualitative data. In total, 80 participants were randomly divided into experimental and control groups, during the course of eight to ten weeks. The results show that there is a noticeable improvement in the speaking proficiency of the experimental group in terms of fluency, accuracy, and complexity when compared to those in the control group who have received conventional training. Besides, the former group of learners became more motivated, confident, and less anxious about speaking English. Despite the benefits, some issues such as technical difficulties and inaccurate feedback have been mentioned.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-13
DOI
https://doi.org/10.5281/zenodo.19556187
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing EFL Speaking Performance through AI-Powered Conversational Agents: A Mixed-Methods Study at Dong Nai Technology University

Vu Thi Duyen
Zenodo (CERN European Organization for Nuclear Research)
AI in Service Interactions
article

Enhancing EFL Speaking Performance through AI-Powered Conversational Agents: A Mixed-Methods Study at Dong Nai Technology University

Vu Thi Duyen
article en

Abstract

Abstract The current paper examines the efficiency of AI-assisted conversational agents in enhancing the speaking proficiency of Vietnamese EFL university students. To conduct the research, a mixed methods design was used, including a quasi-experiment along with questionnaire and interview-based qualitative data. In total, 80 participants were randomly divided into experimental and control groups, during the course of eight to ten weeks. The results show that there is a noticeable improvement in the speaking proficiency of the experimental group in terms of fluency, accuracy, and complexity when compared to those in the control group who have received conventional training. Besides, the former group of learners became more motivated, confident, and less anxious about speaking English. Despite the benefits, some issues such as technical difficulties and inaccurate feedback have been mentioned.

Zenodo (CERN European Organization for Nuclear Research)
Lac Hong University (VN)
Quality Education
Openalex Percentile: Top 5%
AI in Service Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Enhancing EFL Speaking Performance through AI-Powered Conversational Agents: A Mixed-Methods Study at Dong Nai Technology University — Vu Thi Duyen · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS