A Systematic Review of Instruments and Frameworks for Measuring Faculty AI Integration Knowledge, Attitudes, and Behaviors in Higher Education

• In Event: AERA Roundtable Session Thursday 9:45 am - Gold 4
  In Roundtable Session: AI and Instructional Design

Abstract

As artificial intelligence (AI) is rapidly integrated into higher education, it necessitates a systematic understanding of faculty readiness to adopt these innovative technologies. This review synthesizes 19 empirical studies (2015-2025) examining faculty AI adoption through knowledge, attitudes, and behavioral measures. Employing PRISMA guidelines, our analysis identified three critical findings: (1) While Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) frameworks dominate the literature, they inadequately capture AI-specific pedagogical and ethical concerns; (2) Faculty adoption patterns show significant disciplinary and geographical variation; (3) Existing measurement instruments lack comprehensive validation, particularly regarding longitudinal stability and cross-cultural applicability. The authors propose the Faculty AI Readiness and Integration Framework (FAIR-IF) as an integrated framework to address these gaps.

Authors

• Richard Dickson Amoako, University of Tennessee

• Jennifer A. Morrow, University of Tennessee