International Journal of
Information and Education Technology

Abstract—The aim of this research is to examine how the adoption level of Generative Artificial Intelligence (GAI) influences not only the number of academic outputs produced by academicians but also their instructional innovation, assessment practices, and pedagogical processes. This relationship is evaluated through a mixed-method approach combining quantitative and qualitative analyses. The population of the research consists of 515 academicians working in state and private/foundation universities in Türkiye as of the 2024–2025 academic year. In the study, a mixed method research design was used: Generative Artificial Intelligence Acceptance Scale (GAIAS) and academic output indicators were used for quantitative data, and qualitative data were collected with open-ended questions. Quantitative findings revealed that GAI acceptance level showed significant differences according to academic title, institution type, and partially gender variables. Academicians working in foundation universities had higher scores for performance and expectation of GAI. Weak and often insignificant relationships were determined between GAI acceptance and Google Scholar and Web of Science h-index/number of publications in the short term. Qualitative findings show that academicians use GAI most frequently in article writing, data analysis, and literature review; their usage motivations are concentrated around increasing productivity, ease of access to information, and saving time. In addition, participants drew attention to ethical problems, accuracy risk, and the danger of over-reliance, despite the potential of GAI to increase academic productivity. The research results show that the effect of GAI on the number of academic outputs depends on contextual factors and may become more evident in the long term.

Keywords—generative artificial intelligence, acceptance level, academic output, higher education

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Cite: Engin Bayra, Emel Aydın, Fatma Nur Çoban, and Adem Çilek, "Exploring the Effects of Generative Artificial Intelligence Adoption on Academic Productivity and Pedagogical Innovation: A Mixed-Methods Analysis," International Journal of Information and Education Technology, vol. 16, no. 6, pp. 1463-1472, 2026.

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).