ARTIFICIAL INTELLIGENCE–POWERED WRITING TOOL PAPERPAL FOR ENGAGING PHD STUDENTS IN ACADEMIC WRITING

Abstract

Purpose. Doctoral students writing in English as a foreign language frequently encounter linguistic, rhetorical, and affective challenges that undermine engagement and progress on their dissertations. Although artificial intelligence-powered writing tools (AI-PWTs) are increasingly used in higher education, empirical evidence regarding their pedagogical integration at the doctoral level remains limited. This study examines PhD students’ knowledge, attitudes, and practices regarding AI tools and assesses the potential contribution of integrating Paperpal into an Academic Writing course. Method. A mixed-methods classroom-based case study was conducted with 42 PhD students at a Ukrainian pedagogical university. Quantitative data were collected through two structured surveys and pre- and post-intervention evaluation of writing drafts assessed across seven criteria. Paired-samples t-tests were used to examine within-subject changes. Qualitative data were obtained from open-ended questions in surveys, reflective accounts, and a SWOT analysis and analysed thematically. Findings. Results indicate widespread, but predominantly unsystematic, use of general-purpose AI tools prior to the intervention. Following structured integration of Paperpal, statistically significant improvements in the analysed writing samples were observed across all seven criteria, with the largest improvement in ethical AI use. Participants reported increased motivation, greater confidence, and more responsible AI practices. Implications for research and practice. The findings suggest that AI-PWTs can function as formative scaffolds in doctoral writing pedagogy when embedded within structured instruction and ethical guidance. The study provides empirical evidence supporting the integration of supervised AI in postgraduate education and highlights the need for institutional frameworks, digital literacy training, and longitudinal research.