Prompt, Evaluate, Revise: AI-Assisted User Manual Creation in Academic Practice

Year 2025, Volume: 8 Issue: 1, 103 - 347, 30.06.2025

Işın Öner , Zehra Begüm Bengi

https://doi.org/10.29228/transLogos.78

Abstract

This study explores the effective use of artificial intelligence (AI) as a tool in technical documentation, focusing specifically on Turkish-language content creation. Conducted with graduate-level students in a translation quality standards course, the project investigates how AI-assisted writing can support the development of user manuals through a structured classroom project. The students were asked to generate specific sections of a user manual in Turkish by interacting with ChatGPT, using prompts aligned with the IEC/IEEE 82079-1 standard and core principles of technical writing. The project unfolded in four stages: prompt development, AI-generated drafting, human assessment of outputs, and human-guided and AI-assisted revision. Each student engaged in iterative prompting and post-editing, evaluating not only the quality of the AI-generated texts but also their own role in guiding and improving the results. As the assignment progressed, the students encountered and addressed various limitations of ChatGPT—such as visual recognition failures, incorrect safety symbol usage, and inconsistencies in warning categories—often learning through trial and error. By analyzing the prompts, outputs, and student-led revisions, the study offers practical insight into the potential and constraints of AI-supported documentation workflows. It highlights the importance of human expertise in both subject knowledge and AI interaction. Ultimately, the paper raises a central question for both education and industry: is AI a supportive means for technical communicators, or is it increasingly shaping the very goals and practices of the field itself?

Keywords

human content creators , artificial intelligence , ChatGPT , prompt engineer , field expertise

References

• Acar, Ferit. 2022. “A Study on Operationalizing Applied English Translation Programs in Turkey: An Examination in Terms of Competencies, Sector and Academy.” Unpublished PhD diss., Istanbul 29 Mayıs University.
• Alimen, Nilüfer. 2023. “Makine Çevirisinden Sohbet Robotu Çevirisine: ChatGPT ile Deneysel Bir Çalışma.” [From machine translation to chatbot translation: An experimental study with ChatGPT.] In RumeliDE Journal of Language and Literature Studies, no. 36, 1532–1548. doi:10.29000/rumelide.1369589.
• Alimen, Nilüfer, Senem Öner Bulut, and Ayşe Banu Karadağ. 2023. “Yapay Zekâ, Dil ve Çeviri.” [AI, language, and translation.] In Yapay Zekâ: Disiplinlerarası Yaklaşımlar [AI: Interdisciplinary approaches], edited by Berrin Küçükcan and Banu Fulya Yıldırım, 81–103. Istanbul: Vakıfbank Kültür.
• Doğan, Mehmet Ferit. 2025. “From Prompts to Precision: A Comparative Experimental Study of Translation Quality Outputs with Focus on Role-Based (Persona) Prompting for Medical Texts.” Unpublished master’s thesis, Istanbul 29 Mayıs University.
• Electrolux. Use & Care Manual: High Performance Blender. https://na2.electroluxmedia.com/Original/Electrolux/Electrolux%20Assets/Document/Complete%20Owners%20Guide/English/5304532467en.pdf.
• IEC/IEEE. 2019. IEC/IEEE 82079-1:2019 Preparation of Information for Use (Instructions for Use) of Products – Part 1: Principles and General Requirements.
• Massardo, Isabella, and Jaap Van der Meer. 2017. The Translation Industry in 2022, A Report from the TAUS Industry Summit Amsterdam, March 22–24, 2017. De Rijp: TAUS BV.
• O’Brien, Sharon. 2012. “Translation as Human–Computer Interaction.” Translation Spaces 1 (1): 101–122. doi:10.1075/ts.1.05obr.
• O’Brien, Sharon. 2023. “Human-Centered Augmented Translation: Against Antagonistic Dualisms.” Perspectives 32 (3): 391–406. doi:10.1080/0907676X.2023.2247423.
• Öner Bulut, Senem. 2019. “Integrating Machine Translation into Translator Training: Towards ‘Human Translator Competence’?” transLogos Translation Studies Journal 2 (2): 1–26. doi:10.29228/transLogos.11.
• Öner, Işın, and Senem Öner Bulut. 2021. “Post-Editing Oriented Human Quality Evaluation of Neural Machine Translation in Translator Training: A Study on Perceived Difficulties and Benefits.” transLogos Translation Studies Journal 4 (1): 100–124. doi:10.29228/transLogos.33.
• Öner, Işın, and Zehra Begüm Bengi. 2024. “Essential or Obsolete? The Role of Human Competencies in the Tech-Driven Language Services Industry.” transLogos Translation Studies Journal 7 (1): 78–104. doi:10.29228/transLogos.66.
• Öztürk Baydere, Hilal. 2022. “Makine Çevirisi ve Dijitalleşme Bağlamında Çevirmenlik Mesleğinin Dönüşümü.” [Transformation of the translation profession within the context of machine translation and digitalization.] Unpublished PhD diss., Istanbul University.
• Öztürk Baydere, Hilal. 2023. “Rethinking Translator Competence in the Machine Translation Era.” transLogos Translation Studies Journal 6 (1): 45–74. doi:10.29228/transLogos.54.
• PACTE. 2003. “Building a Translation Competence Model.” In Triangulating Translation: Perspectives in Process Oriented Research, edited by Fabio Alves, 43–66. Amsterdam: John Benjamins.
• PACTE. 2005. “Investigating Translation Competence: Conceptual and Methodological Issues.” Meta 50 (2): 609–619. doi:10.7202/011004ar.
• Sayın, Ayşe Betül. 2025. “Learning to Learn: Translators’ Post-Editing Patterns and Priming.” Unpublished PhD diss., Istanbul 29 Mayıs University.