The AI Adaptation Gap in Higher Education: Students, Faculty, and Administrative Staff

A recent study explored artificial intelligence (AI) usage patterns and attitudes among students, faculty, and administrative staff within a large university specializing in teacher education. Analyzing data from 2121 participants across these groups, the research investigated the frequency and contexts of AI use, perceived usefulness, trust, control, academic integrity concerns, responsible-use norms, institutional policy clarity, and perceived improvements in output quality. The findings aim to illuminate the current state of AI adaptation within this specific higher education environment.

Why it matters

Understanding the 'AI Adaptation Gap' across different constituent groups within higher education provides critical insights into the readiness and challenges of integrating AI technologies. This knowledge is essential for developing coherent institutional strategies that address diverse needs and concerns, ensuring effective and responsible AI adoption.

Key insights

• The study surveyed 1809 students, 250 faculty members, and 62 administrative staff, totaling 2121 participants.
• Data collection utilized role-adapted 75-item questionnaires.
• The questionnaires covered frequency and contexts of AI use, perceived usefulness, trust, and control.
• Academic integrity concerns and responsible-use norms regarding AI were assessed.
• Institutional policy clarity related to AI and perceived improvement in output quality were also examined.
• Analytical methods included descriptive statistics, Welch group comparisons, and pooled ordinary least squares (OLS) models.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2608.25063