SCAFFOLDING ACADEMIC WRITING FOR EFL LEARNERS THROUGH AI TOOLS: A MIXED METHOD STUDY

Abstract

The integration of AI tools in academic environments has drawn considerable interest from researchers and educators globally. This study examines the effectiveness of AI tools and their practical applications in English as a Foreign Language (EFL) academic writing. A sequential mixed-methods design is used to investigate AI use in EFL writing through thematic analysis, interviews and survey data. Qualitative thematic analysis, following Braun and Clarke's (2006) framework, is applied to five contemporary research articles (2023-2024) sourced from reputable databases, and key themes are identified. Subsequently, a survey administered to captures EFL students' perspectives on AI in academic writing. Adding to the depth of the analysis EFL teachers interviews are conducted. Braun and Clarke’s six-phase Thematic Analysis framework is followed: data familiarization, initial coding, theme identification, theme review, theme definition and naming, and report production. (Braun et al., 2006) This study discusses the role of AI applications by presenting insights from EFL educators and students. Analysis indicates that AI tools substantially enhance EFL students’ writing skills, although some limitations and ethical concerns arise when implementing AI for academic writing. (Mahapatra & Santosh, 2024) Four main themes emerge: Enhancement of Writing Skills, Support for Writing Processes, Fostering Autonomy and Motivation, and Ethical and Functional Challenges. Each category includes three sub-themes. This study underscores the value of AI tools in developing EFL writers' skills while emphasizing the need for balanced use. As a qualitative investigation, future research may prioritize more practical approaches.