Enhancing English Communicative Competence through AI Tools in Vocational Higher Education: A Study Among English for Professional Purposes (EPP) Students
Keywords:
Communicative Competence, AI tools, english for professional purposes, EPP, AI-assisted language learning, generative AI, TALL, TALE, TELL, vocational higher education, language learning strategiesAbstract
This paper explores the impact of AI tools in promoting language competence (LC) among English for Professional Purposes (EPP) students in vocational higher education. Low LC among EPP learners has implications for academic performance, social integration, and self-confidence at the individual level, and overall student quality and graduate output at the institutional level. A qualitative study was implemented with a focus on exploring the AI tools being employed by EPP learners for language learning, the frequency of use, and the features of the AI tools that promote language competence among EPP learners. Qualitative interview data from nine (9) respondents were analyzed for codes related to the research objectives. Findings highlighted the role of AI features that support feedback, translation, vocabulary auto-suggestion, assessment, and self-monitoring in promoting language competence. Participants also believe higher language competence is related to more frequent use of these AI tools. The study bridges the current gap in the enhancement of communicative competence among EPP students and contributes to ongoing discourse on the specific role of AI-Assisted Language Learning (AALL) within the broader technology-aided language learning (TALL) and language learning strategies (LLS) discourse. Future studies employing quantitative approaches and longitudinal studies will contribute to enhancing the findings while also addressing the development of a clear model for promoting the various components and overall communicative competence of vocational EPP students.
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