Deep Learning, AI Tools, and Intercultural Competence in Developing EFL Students’ Speaking Performance

Titi Rokhayati; Zulia Chasanah; Tengku Nazatul Shima

doi:10.21580/vjv16i133221

Authors

Titi Rokhayati University of Muhammadiyah Purworejo, Central Java , Indonesia
Zulia Chasanah University of Muhammadiyah Purworejo, Central Java , Indonesia
Tengku Nazatul Shima Universiti Teknologi MARA, Selangor, Malaysia https://orcid.org/0000-0001-9193-1131

DOI:

https://doi.org/10.21580/vjv16i133221

Keywords:

artificial intelligence, deep learning, EFL speaking performance, higher education, intercultural competence

Abstract

This study examined the effectiveness of a technology-integrated deep learning model combined with intercultural competence in improving university students’ English speaking performance by describing their baseline speaking competence, developing and implementing the model, testing its effectiveness, and examining how its intercultural element shaped fluency, accuracy, and appropriateness. A quasi-experimental pretest–posttest control group design was used with 70 students in three intact classes, two experimental (n = 44) and one control (n = 26). The model followed a cycle of speaking practice, AI-mediated feedback, intercultural reflection, and re-performance, with YouTube, ChatGPT, ELSA Speak, and Flip each assigned to a specific phase. Speaking was scored with an analytic rubric covering fluency, accuracy, and appropriateness. At pretest, all classes performed at an intermediate level (M = 69.6–74.6). Both experimental classes made very large gains (d = 2.76 and 2.94), whereas the control class improved less (d = 1.10). The experimental group gained 6.31 points more than the control group (t(68) = 6.20, p < .001, d = 1.53). In the experimental group’s posttest scores, appropriateness accounted for the largest share (37.9%), followed by accuracy (31.5%) and fluency (30.7%), reflecting the pragmatic focus of the tasks. These results suggest that pedagogical design matters more than the tools themselves, and future research should use randomised, multi-institutional designs with validated intercultural measures and delayed posttests.

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Author Biographies

Zulia Chasanah, University of Muhammadiyah Purworejo, Central Java

English Department

Tengku Nazatul Shima, Universiti Teknologi MARA, Selangor

Akademi Pengajian Bahasa, Universiti Teknologi MARA,

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