When EFL Students Integrated AI Technology into Their Academic Writing: What Should the Lecturers do to Identify, Prevent and Assess Students’ Skills? - Darwin; Saugadi; Nuralan, Sitti (LPPM Universitas Madako Tolitoli, 2025)
This study aims to explore the methodologies employed by educators in identifying, preventing, and evaluating students' academic writing when integrating AI into the process. A single case study approach was used, selecting five English as a Foreign Language (EFL) lecturers from various higher education institutions across Indonesia as respondents. The selection criteria emphasized their expertise in academic writing and AI, demonstrated through their contributions to Scopus-indexed journals, as well as their comprehensive understanding of AI applications. Data collection was conducted through semi-structured interviews, both online and in person. The collected data were analyzed using descriptive principles, including data reduction, data display, and conclusion or verification. The findings revealed a range of methodologies employed by educators. Lecturers primarily focused on writing style, argument complexity, and originality to identify AI's influence. Prevention strategies emphasized enhancing foundational writing skills, encouraging independent research, and promoting academic integrity. For evaluation, lecturers balanced content quality, structural aspects, creativity, and critical thinking, while ensuring academic integrity through plagiarism detection tools. These findings provide valuable insights into the evolving landscape of educational practices and underscore the importance of adapting methodologies to accommodate technological advancements.