IJIET 2025 Vol.15(9): 1997-2012
doi: 10.18178/ijiet.2025.15.9.2399
doi: 10.18178/ijiet.2025.15.9.2399
Impact of the Application of Mobile Integrated Speech Recognition and Automated Writing Evaluation Software on the University Learners’ EFL Speaking Competence
Wenyi Li1,*, Maslawati Mohamad1, and Huay Woon You2
1. Faculty of Education, Universiti Kebangsaan Malaysia, Selangor, Malaysia
2. Pusat PERMATA@Pintar Negara, Universiti Kebangsaan Malaysia, Selangor, Malaysia
Email: p121641@siswa.ukm.edu.my (W.L.); maslawati@ukm.edu.my (M.M.); hwyou@ukm.edu.my (H.W.Y.)
*Corresponding author
2. Pusat PERMATA@Pintar Negara, Universiti Kebangsaan Malaysia, Selangor, Malaysia
Email: p121641@siswa.ukm.edu.my (W.L.); maslawati@ukm.edu.my (M.M.); hwyou@ukm.edu.my (H.W.Y.)
*Corresponding author
Manuscript received April 17, 2025; revised May 12, 2025; accepted June 5, 2025; published September 18, 2025
Abstract—Developing speaking competence remains a challenge for university learners in English as a Foreign Language contexts due to limited opportunities for oral practice and individualized feedback. This study examined the impact of a mobile-based approach that integrates automatic speech recognition and automated writing evaluation on the speaking competence of Chinese university learners. A quasi-experimental design was implemented with 104 first-year students enrolled in the compulsory English course. Participants were randomly assigned to an experimental group, which engaged in weekly speaking tasks supported by speech recognition and writing evaluation technologies, or a control group that followed traditional instruction. Both groups received the same syllabus and classroom teaching to control for instructional differences. Speaking performance was assessed through pre- and post-tests rated across four analytic dimensions: grammar and vocabulary, discourse management, pronunciation, and interactive communication. Results showed that the experimental group made significantly greater gains than the control group in all four dimensions, with the largest improvements observed in pronunciation and interactive communication, followed by grammatical accuracy and discourse organization. In addition, qualitative data from reflective journals, focus group interviews, and annotated screenshots indicated that learners perceived the integrated use of speech recognition and writing evaluation tools as effective for identifying language problems, promoting self-regulated practice, and increasing speaking confidence. These findings suggest that mobile-based automatic speech recognition and automated writing evaluation can provide effective, accessible, and scalable support for multidimensional oral development in university-level English language education.
Keywords—speaking competence, automatic speech recognition, automated writing evaluation, mobile learning, oral English development
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords—speaking competence, automatic speech recognition, automated writing evaluation, mobile learning, oral English development
Cite: Wenyi Li, Maslawati Mohamad, and Huay Woon You, "Impact of the Application of Mobile Integrated Speech Recognition and Automated Writing Evaluation Software on the University Learners’ EFL Speaking Competence," International Journal of Information and Education Technology, vol. 15, no. 9, pp. 1997-2012, 2025.
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).