Exploring EFL Students' Pronunciation through the Implementation of the AI Reading Progress Feature - Yujie He; Yu Zhou; Xuehao Wang; Linsen Liu; Xiyuan Song; Weine Liu (PT. Giovani Publisher, 2026)
This study aims to explore the pronunciation abilities of English as a Foreign Language (EFL) students through the implementation of an artificial intelligence-based feature, namely Reading Progress. This study uses a quantitative descriptive approach supported by qualitative analysis to identify patterns of pronunciation improvement and phonological difficulties experienced by students. Data were collected through recordings of students' readings, which were automatically analyzed by an AI system, then interpreted based on the level of pronunciation accuracy and the types of phoneme errors that occurred. The results showed a significant increase in students' pronunciation accuracy, characterized by a consistent upward trend in each learning session. In addition, it was found that certain vowel sounds such as /ɪ/ and /ə/, as well as fricative consonants such as /ʃ/ and /z/, were the main challenges for students in the early stages of learning. With repeated use of the AI ​​feature, the frequency of errors in these phonemes decreased significantly. Other findings indicate that the use of Reading Progress not only improves pronunciation abilities but also encourages students' independent learning and metacognitive awareness through real-time and personalized automatic feedback. Thus, the integration of AI technology in EFL learning has proven to be effective as an innovative strategy to improve students' pronunciation quality systematically and sustainably.