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Teaching Research Writing with AI: A Case Study of Academic Development Courses in Higher Education
Introduction: Rapid advances in artificial intelligence are reshaping higher education and intensifying debate about the effectiveness, risks, and ethical implications of AI supported learning and academic writing. Yet faculty experiences with AI for research writing remain comparatively underexamined.
Purpose: To examine university faculty members’ experiences and perceptions of using AI tools to support research writing and publication practices in higher education, with particular attention to issues of AI literacy and responsible use..
Method: This exploratory design based case study reports two one day immersion courses delivered through the university writing center at HSE University in Fall 2023 and Spring 2024. Participants were two cohorts of trainees (Case 1 n = 19; Case 2 n = 15) and two course instructors. Data comprised post course trainee feedback covering course usefulness, content, assignments, activities, instructor performance and feedback, and self reported involvement, as well as semi structured interviews with instructors about teaching and writing with AI tools. Numeric feedback items were analyzed using descriptive statistics in R. Interview data were analyzed using thematic analysis focused on key takeaways, concerns, and suggestions for improvement.
Results: Trainees rated the courses highly, especially the practice oriented format (Case 1 mean = 9.4 out of 10; Case 2 mean = 9.5). Instructors corroborated strong engagement but reported that an eight hour single day schedule increased cognitive load and reduced pedagogical stamina. Ethical concerns differed across cohorts: responsible AI use was discussed extensively in Case 1, whereas Case 2 participants mainly acknowledged the need for ethical use. Participants also demonstrated heterogeneous AI literacy and limited prior exposure to AI tools, reported by seven trainees in Case 1 and six trainees in Case 2.
Conclusion: Findings informed immediate redesign of the writing center’s offerings by strengthening attention to AI ethics and literacy, extending course formats, and maintaining hands on learning as a core principle. Course designers should consider participants’ prior experience, ensure reliable access to a curated set of tools, allocate time for guided familiarization and task completion, and plan for classroom management in mixed literacy groups. The study contributes faculty focused evidence to discussions of AI mediated research writing and motivates experimental testing of AI integrated pedagogical frameworks, including Intelligent TPACK.