AI-SUPPORTED MENTORING: SPEAKING PRACTICE WITH STIMULER IN FUTURE ENGLISH TEACHER TRAINING
Keywords:
speaking proficiency, pre-service English teachers, diagnostic assessment, mixed methods, oral interaction, artificial intelligenceAbstract
DOI: https://doi.org/10.46296/yc.v10i19.0947
Abstract
The speaking skill is an essential requirement in pre-service EFL teacher education as future instructors must be able to communicate effectively, control classroom interaction and provide models of proper spoken language. This study involved a mixed-methods, descriptive, cross-sectional, field-based, and non-experimental design to assess the speaking proficiency of students of the “Pedagogy of National and Foreign Languages: English” educational program at Universidad Laica Eloy Alfaro de Manabí and to investigate teachers’ perceptions and ideas regarding the factors determining success in this field. 197 students were enrolled in the program, while the analytical sample consisted of 26 complete diagnostic speaking assessments, which were selected on the basis of convenience sampling. 11 students were assessed according to A1-A2 descriptors and 15 students, according to B1 descriptors. Four English language teachers participated in semi-structured interviews, which were analyzed thematically. Cambridge speaking scales were used to evaluate grammar and vocabulary, pronunciation, interactive communication, and global achievement, as well as discourse management at the level of B1 students. As to pronunciation, it was the strongest area in both types of students (A1-A2: M = 3.27, SD = 1.01; B1: M = 2.53, SD = 0.64); the lowest mean values were acquired in the assessment of grammar and vocabulary (M = 2.09, SD = 1.45; M = 1.60, SD = 0.63, respectively). Teacher perceptions coincide with the diagnostic profile regarding limited vocabulary retrieval, anxiety, insufficient spontaneous interaction, low exposure to English, and listening-comprehension difficulties. The findings support recommendations for more frequent guided interaction, integrated listening-speaking practice, peer collaboration, and systematic feedback within the English Language Program.
Keywords: speaking proficiency, pre-service English teachers, diagnostic assessment, mixed methods, oral interaction, artificial intelligence.
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