STRATEGIES FOR INTEGRATING ARTIFICIAL INTELLIGENCE TOOLS INTO PROJECT-BASED ENGLISH LANGUAGE TEACHING TO ENHANCE STUDENTS' COMMUNICATIVE COMPETENCE
Keywords:
This chapter presents the methodological framework underpinning the investigation of strategies for integrating artificial intelligence (AI) tools into project-based English language teaching (PBLT) with the aim of enhancing students' communicative competence.Abstract
This methodological chapter presents the research design for a doctoral study investigating strategies for integrating artificial intelligence (AI) tools into project-based English language teaching (PBLT) to enhance learners' communicative competence. Grounded in Canale and Swain's (1980) model of communicative competence and Long's (1996) Interaction Hypothesis, the study adopts a mixed-methods action research design implemented over three iterative cycles in an authentic tertiary EFL classroom. Quantitative data are collected through pre- and post-intervention communicative competence assessments and structured questionnaires, while qualitative data are drawn from classroom observations, semi-structured interviews, student reflective journals, and AI-interaction logs. The intervention embeds generative AI tools—conversational chatbots, automated feedback systems, and AI-assisted collaborative platforms—within a sequence of extended, real-world communicative projects. Data are analyzed using descriptive and inferential statistics alongside thematic analysis, with triangulation ensuring methodological rigor. The chapter details the research paradigm, questions, context, procedure, instruments, and ethical safeguards, arguing that a convergent mixed-methods action research approach is best suited to capturing both measurable gains in communicative competence and the situated, evolving classroom dynamics of AI-mediated project-based instruction.
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