Development and validation of Generative Artificial Intelligence Readiness and Perception (GenAI-RP) Scale for faculty and students in higher education

Abstract This study developed and validated a suite of Generative Artificial Intelligence Readiness and Perception (GenAI-RP) Scale for faculty and students in higher education. Three subscales, including a) Readiness, b) Benefit, and c) Challenge were created based on a review of relevant literature and validated through content experts’ review and confirmatory factor analysis (CFA). The Readiness scale includes three factors: a) GenAI Comprehension, b) Ethical Awareness of GenAI, and c) GenAI Utilization and Proficiency. The Benefit scale consists of two factors: a) Effectiveness and b) Empowerment. Lastly, the Challenge scale has three factors: a) Ethics and Privacy Concerns, b) Negative Educational Impact, and c) Accuracy and Sensitivity. All scales demonstrated a satisfactory model fit for both groups based on CFA, except the challenge scale for faculty.

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Publication Details

Journal
Educational Technology Research and Development
Published
2026-09-24
DOI
https://doi.org/10.1007/s11423-026-10713-z
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Development and validation of Generative Artificial Intelligence Readiness and Perception (GenAI-RP) Scale for faculty and students in higher education

Ji Yae Bong, Beth Allred Oyarzun, Daniel W. Maxwell, Stella Yun Kim
Educational Technology Research and Development
Artificial Intelligence in Healthcare and Education
article

Development and validation of Generative Artificial Intelligence Readiness and Perception (GenAI-RP) Scale for faculty and students in higher education

Ji Yae Bong, Beth Allred Oyarzun, Daniel W. Maxwell, Stella Yun Kim
article en

Abstract

Abstract This study developed and validated a suite of Generative Artificial Intelligence Readiness and Perception (GenAI-RP) Scale for faculty and students in higher education. Three subscales, including a) Readiness, b) Benefit, and c) Challenge were created based on a review of relevant literature and validated through content experts’ review and confirmatory factor analysis (CFA). The Readiness scale includes three factors: a) GenAI Comprehension, b) Ethical Awareness of GenAI, and c) GenAI Utilization and Proficiency. The Benefit scale consists of two factors: a) Effectiveness and b) Empowerment. Lastly, the Challenge scale has three factors: a) Ethics and Privacy Concerns, b) Negative Educational Impact, and c) Accuracy and Sensitivity. All scales demonstrated a satisfactory model fit for both groups based on CFA, except the challenge scale for faculty.

Educational Technology Research and Development
University of North Carolina at Charlotte (US)
Quality Education
Openalex Percentile: Top 15%
Artificial Intelligence in Healthcare and Education
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