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

Source
arXiv — Computers and Society
Published
Last verified
27 Aug 2026
Confidence
High
Evidence
Original document retained
Reading time
1 min
Country
International
Relevant to
Research & Evidence, Technology & Data, People & Capability, Policy & Regulation, Risk & Compliance

Executive summary

What happened, and why should leadership care?

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 this matters

Why is this strategically important?

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

What should be noted from the evidence?

  • 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.

Evidence and confidence

How far can this assessment be trusted?

High confidence. Named institution, original document retained and analysis corroborated.

Analysis is prepared editorially by Aziz Shuaib Ausi. The original publication remains the authoritative record, and executive judgement remains entirely human.

Source

Where does this originate?

Reported by arXiv — Computers and Society · International. This briefing summarises the publication for executive use; the document itself is not reproduced here.

Read the original publication