Academic Writing Lecturers' Perceptions on Generative AI Use In Academic Contexts

Abstract

This qualitative case study explores Academic Writing lecturers perceptions of students use of generative artificial intelligence (AI) tools in higher education contexts. Framed by the Technology Acceptance Model (TAM), the research examines lecturers evaluations of AIs perceived usefulness, ease of use, attitudes toward use, and behavioral intentions regarding its integration in academic writing courses. Data were collected through in-depth, semi-structured interviews with three Academic Writing lecturers at a university in Garut, Indonesia, and analyzed using thematic analysis. The findings reveal that lecturers perceive generative AI as a dual-edged catalyst: it offers substantial efficiency in brainstorming, structuring arguments, and language refinement, yet raises significant concerns about academic integrity, cognitive dependency, superficial learning, and erosion of critical thinking. Lecturers adopt a stance of critical acceptance, viewing AI as a pedagogical partner rather than a substitute for human intellectual effort. Their behavioral intentions focus on strategic regulation, including transparency mechanisms such as AI logs and prompt histories, negotiating meaning in revisions, and redesigning process-oriented assessments to preserve authentic learning. This study contributes to the discourse on AI in education by illuminating nuanced, ethically grounded educator perspectives and providing practical recommendations for institutional policy and pedagogical adaptation in the generative AI era, particularly in Indonesian higher education contexts.