How to Use ChatGPT to Support Research Writing Among Preservice Teachers

Abstrak

Generative artificial intelligence (GenAI), particularly ChatGPT, has rapidly entered academic writing workflows in higher education, yet evidence from Global South preservice teacher contexts remains sparse. Grounded in the Technological Pedagogical Content Knowledge (TPACK) framework and the Unified Theory of Acceptance and Use of Technology (UTAUT), this study examines how graduating preservice teachers integrate ChatGPT into research writing, what motivates adoption, and how such use maps onto anticipated professional roles. A sequential explanatory mixed-methods design was employed, combining an institutional census survey (n = 197) with three focus group discussions (FGDs; 27 volunteers). Descriptive statistics were computed for survey constructs, and reflexive thematic analysis was applied to verbatim transcripts following Braun and Clarke (2006). ChatGPT use concentrated at high-yield, low-risk stages — most frequently grammar and style polishing (64% always) and brainstorming (57% always) — with markedly lower use for statistical explanation (19% always). Four themes emerged: continuous multi-stage drafting support, deliberate timing to protect authorial voice, source-anchored prompting to reduce hallucinations, and systematic verification routines. Participants rated ChatGPT highly relevant to roles including personalized learning (67% very relevant) and ethical AI stewardship (48% very relevant). When embedded within structured writing pedagogy — human-first planning, anchored prompting, and process-transparent verification — ChatGPT functions as a cognitive scaffold. Teacher education programs should institutionalize these practices to cultivate research writing fluency and the professional judgment required for AI-aware classroom leadership