Ethical Boundaries in GenAI-Driven Research: Language Researchers’ Reactions to Unethical Use of GenAI in Graduate Education
International Journal of Human-Computer Interaction, 2026 (SCI-Expanded, SSCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1080/10447318.2026.2682912
- Dergi Adı: International Journal of Human-Computer Interaction
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Compendex, INSPEC, Psycinfo, Academic Search Ultimate (EBSCO), Business Source Ultimate (EBSCO), Engineering Source (EBSCO), Psychology & Behavioral Sciences Collection (EBSCO), Technology Collection (ProQuest)
- Anahtar Kelimeler: Generative artificial intelligence (GenAI), scenario-based ethics, GenAI disclosure, graduate education, language researchers, supervisor perspectives, responsible AI use
- Atatürk Üniversitesi Adresli: Evet
Özet
The rapid integration of generative artificial intelligence (GenAI) tools into academic settings, particularly graduate education, where research integrity is required, has raised questions about their ethical use. Adopting a scenario-based qualitative design, this study focuses on exploring language researchers’ perspectives on and reactions to potentially unethical GenAI practices in graduate research with an extended technology acceptance (E-TAM) perspective and thus providing a process-oriented framework including preventive strategies for the unethical uses of GenAI in graduate research. Data were collected through semi-structured interviews with 10 language researchers from different universities, focusing on hypothetical scenarios, and were analyzed thematically. The findings revealed that participants mostly conceptualized GenAI uses presented in scenarios as ethically suspect. However, they pointed out that they might tolerate the use of GenAI in data analysis and consider it ethically contingent, provided that transparency, responsibility, and accountability are ensured. Language researchers also proposed preventive strategies to avoid unethical uses of GenAI in academic contexts, and a framework was developed based on these suggestions. This framework, suggesting that ethical GenAI use in graduate research practices is a shared responsibility of graduate students, their supervisors and institutions, can be used as a guide to promote ethical GenAI use in graduate education. This study contributes a theoretically informed and empirically grounded framework for promoting ethical GenAI use in graduate research by integrating language researchers’ insights with an E-TAM perspective through a scenario-based approach that reveals context-dependent ethical reasoning.