Evaluating the Effectiveness of ChatGPT Voice for Improving English Speaking Skills in Vocational EFL Classrooms

Authors

  • Ajah Saputra Universitas Muhammadiyah Sampit
  • Nur Irma Yanti Universitas Muhammadiyah Sampit

DOI:

https://doi.org/10.52760/jadila.v6i4.849

Keywords:

ChatGPT Voice; artificial intelligence; English speaking skills; vocational high school; EFL learning

Abstract

The integration of artificial intelligence (AI) into English language teaching has created new opportunities to enhance students' speaking skills through interactive and personalized learning experiences. However, empirical evidence regarding the effectiveness of ChatGPT Voice in vocational high school settings remains limited. This study aimed to examine the effectiveness of ChatGPT Voice in improving the English speaking skills of tenth-grade students in the Accounting and Finance Program at SMKN 1 Kota Besi, Indonesia. A pre-experimental one-group pretest–posttest design was employed involving 24 students selected through total sampling. Data were collected using speaking performance tests administered before and after three instructional meetings integrating ChatGPT Voice into speaking activities. Students' speaking performances were assessed using Brown's analytical speaking rubric, covering pronunciation, grammar, vocabulary, fluency, and comprehension. The data were analyzed using descriptive statistics, the Shapiro–Wilk normality test, a paired-samples t-test, and Cohen's d effect size. The findings revealed that the mean speaking score increased from 57.71 in the pre-test to 75.21 in the post-test. The paired-samples t-test indicated a statistically significant improvement (t(23) = 7.840, p < .001), while the effect size analysis demonstrated a large educational effect (d = 1.60). These findings suggest that ChatGPT Voice can serve as an effective supplementary instructional tool for enhancing English speaking skills in vocational EFL classrooms. Future studies are recommended to involve larger samples, longer intervention periods, and experimental designs with comparison groups to further validate these findings.

Downloads

Download data is not yet available.

References

Brown, H. D., & Abeywickrama, P. (2019). Language assessment: Principles and classroom practices (3rd ed.). Pearson.

Chang, W. L., & Sun, J. C. Y. (2024). Evaluating AI's impact on self-regulated language learning: A systematic review. System, 126, 103484. https://doi.org/10.1016/j.system.2024.103484

Cohen, L., Manion, L., & Morrison, K. (2018). Research methods in education (8th ed.). Routledge.

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage Publications.

Derakhshan, A., Fathi, J., & Pawlak, M. (2021). The interplay between teacher credibility, student motivation, and willingness to communicate in efl contexts.

Field, A. (2024). Discovering statistics using IBM SPSS Statistics (6th ed.). Sage Publications.

Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2023). How to design and evaluate research in education (11th ed.). McGraw-Hill.

Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning (Updated ed.). Center for Curriculum Redesign.

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeiffer, F., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410

Richards, J. C. (2022). Teaching English through interaction: Principles and practices. Cambridge University Press.

Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments. 10(15), 1-25. https://doi.org/10.1186/s40561-023-00237-x

UNESCO. (2023). Guidance for generative AI in education and research. UNESCO.

Wei, L. (2023). Artificial intelligence in language instruction: Impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in Psychology, 14, 1261955. https://doi.org/10.3389/fpsyg.2023.1261955

Yang, Y., Wen, Y., & Song, Y. (2024). Evaluating AI's impact on self-regulated language learning: A systematic review. System, 126, 103484. https://doi.org/10.1016/j.system.2024.103484

Zhai, X. (2023). ChatGPT for next generation science learning. Journal of Educational Technology Systems. 29(3), 42-46. https://doi.org/10.2139/ssrn.4331313

Downloads

Published

2026-11-10

How to Cite

Saputra, A., & Yanti, N. I. (2026). Evaluating the Effectiveness of ChatGPT Voice for Improving English Speaking Skills in Vocational EFL Classrooms. Jadila: Journal of Development and Innovation in Language and Literature Education, 6(4), 231–245. https://doi.org/10.52760/jadila.v6i4.849