Generative AI for Academic Writing among Indonesian History Education Lecturers - Putut Wisnu Kurniawan; Aksendro Maximilian; Hajjah Zulianti; Nurdin Hidayat (Proceeding International Conference on Digital Education and Social Science, 2025)
Since the Generative artificial intelligence (GenAI) is potentially reshaping academic writing and publication, this study aims to investigate how Indonesian history education lecturers adopt GenAI across the workflow of writing to publication. It also aims to identifies the perceived benefits, risks, and supports needed for responsible use. To obtain these purposes, a qualitative study involved 50 lecturers from Sumatra, Java, Kalimantan, Sulawesi, and Bali was conducted. Data were gathered through questionnaires, semi structured interviews, and focus group discussions. Thematic analysis, supported by triangulation across instruments, was used to identify patterns of use and challenge. The most frequently used tools were ChatGPT, Grammarly, Google Translate, Gemini, QuillBot, and Turnitin. Adoption was driven by simplicity and efficiency. Indonesian history lecturers reported using GenAI for (a) idea generation and research design, (b) literature synthesis, (c) data analysis, (d) content editing and proofreading, and (e) preparation for publication and dissemination. Four recurring challenges tempered these benefits: safeguarding academic integrity, uneven digital literacy, over reliance on automated outputs, and concerns about data validity and accuracy. Overall, participants framed GenAI as a productivity aid rather than a replacement for scholarly judgment. In conclusion, these outcomes contribute to the wider discussion on technology in higher education by providing educators and policymakers with information about how to maintain a balance between academic rigor and innovation.