Enhancing Oral Language Skills with Pi AI: A Study on Speaking and Pronunciation Gains

Saved in:
Bibliographic Details
Title: Enhancing Oral Language Skills with Pi AI: A Study on Speaking and Pronunciation Gains
Language: English
Authors: Behnam Behforouz, Afrooz Poorghorban, Ali Al Ghaithi
Source: Online Learning. 2026 30(1):507-530.
Availability: Online Learning Consortium, Inc. P.O. Box 1238, Newburyport, MA 01950. Tel: 888-898-6209; Fax: 888-898-6209; e-mail: olj@onlinelearning-c.org; Web site: https://olj.onlinelearningconsortium.org/index.php/olj/index
Peer Reviewed: Y
Page Count: 24
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, English (Second Language), Second Language Learning, Individualized Instruction, Technology Uses in Education, Foreign Countries, Pronunciation, Speech Skills, Influence of Technology, College Students
Geographic Terms: Oman
ISSN: 2472-5749
2472-5730
Abstract: Learners often struggle with speaking and pronunciation due to insufficient practice and feedback opportunities in real situations, which classroom instruction cannot provide adequately. This paper examined the effectiveness of Pi AI, an AI-powered chatbot, in improving speaking and pronunciation among Omani EFL learners. In this investigation, 60 students were randomly divided into experimental (n = 30) and control groups (n = 30). Speaking pretests were conducted to ensure all participants had similar speaking skills. While both groups received regular classroom instruction, the experimental group received additional practice through Pi AI for a month of treatment period. Speaking posttests were conducted to compare the results with the pretests. Findings showed that the experimental group performed better than their peers in the control group on both speaking and pronunciation posttests. The findings are helpful for students, teachers, and educational institutions.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1508018
Database: ERIC
Be the first to leave a comment!
You must be logged in first