AI-Enabled Academic Work in Higher Education: University Faculty Teaching and Research Practices
Category: Publication
Keywords: Generative artificial intelligence; university faculty; AI-enabled academic work; higher education; responsible AI; faculty practices; academic integrity; faculty development.
This Research Topic calls for rigorous empirical and conceptual contributions on how university faculty use generative AI and other AI-enabled tools in everyday teaching and research. It focuses on situated practices such as course and assessment design, feedback, student supervision, literature review, data analysis, writing, and project management, while examining how AI reshapes academic tasks through augmentation, reallocation, or substitution. The collection seeks evidence on the effects of AI use on teaching quality, student learning, research rigor, academic labor, workload, and professional roles. It also addresses responsible use, including academic integrity, authorship, transparency, bias, equity, and responsible governance at the departmental and program levels. Particular attention is given to differences across disciplines, career stages, language contexts, cultures, and resource environments. The findings are intended to inform faculty development, communities of practice, departmental decision-making, and evidence-based institutional guidelines.
Initiator(s):
Frontiers in Education
Deadline: 10.10.2026
Language(s): English
Publication-Type: Article / Journal
Post created by: Virginia Signorini