University Instructors’ Reception of Generative AI in Academic Research: Perceptions, Practices, and Challenges

Abstract

Universities have begun to use generative artificial intelligence (GenAI) in research well before agreeing on how its use ought to be governed. This study draws on reception theory and on technology acceptance research to ask how faculty members take up GenAI in their scholarship; reception is treated here as an active process in which the technology may be interpreted, negotiated, or resisted. Data came from 257 faculty members at public and private Jordanian universities, who completed a survey covering perceived usefulness, research practices, trust, ethical challenges, institutional support, and future adoption. GenAI was rated useful (M = 3.60), and respondents meant to keep using it (M = 3.50). Its actual use across research tasks, however, was moderate (M = 3.14), and trust in its outputs sat barely above the scale midpoint (M = 3.14). Of all the dimensions, ethical concern received the highest mean rating (M = 3.89), with 84.8% of respondents agreeing that outputs must be verified and 89.5% that GenAI use should be disclosed. Institutional support alone fell below the midpoint (M = 2.90), and it bore little relation to use. Future adoption was predicted by frequency of use, usefulness, trust, institutional support, and familiarity (R² = .53); ethical concern was not a significant predictor in the final model. Faculty aged 30–39 generally reported the most favourable reception, whereas discipline, experience, and publication record made little difference. A cluster analysis distinguished three reception positions, engaged-critical (37.4%), negotiated-pragmatic (34.6%), and guarded-sceptical (28.0%), which nevertheless showed similarly strong endorsement of verification and disclosure. Overall, the findings indicate a pattern of critical acceptance and support the development of explicit institutional guidance and training on responsible GenAI use in research.