RESPONSIBLE AI-READINESS IN HIGHER EDUCATION: VALIDATING A DUAL-MODEL FRAMEWORK FOR FACULTY DEVELOPMENT

Abstract

Aim/Purpose This study validates a responsible artificial intelligence (AI) framework designed to strengthen AI-readiness among higher education faculty in India. Background With the increasing use of AI in education, faculty require structured support; however, faculty development models for responsible AI integration remain limited. Methodology A mixed-methods pilot study with ten humanities and performing arts faculty used a dual-model evaluation approach. Three sessions from the framework were implemented, and data were collected through knowledge-attitude-practice (KAP) surveys, cognitive-affective-psychomotor (CAP) performance rubrics, and reflective responses. Contribution This study validates a dual-model framework for faculty development regarding responsible AI readiness. Findings The adapted KAP survey demonstrated strong reliability, with higher AI knowledge associated with more positive attitudes. However, knowledge did not consistently translate into practice, highlighting the need for structured hands-on learning. CAP-based performance assessments and reflections indicated improved ethical awareness, critical engagement, and foundational AI-integration skills. Recommendations for Practitioners Institutions should embed structured AI-training for faculty, with authentic instructional tasks. Recommendations for Researchers Future research should test this approach across larger and more diverse institutional contexts. Impact on Society Developing AI-ready faculty can foster ethical and future-focused learning environments. Future Research Future studies should expand across disciplines and examine longer-term outcomes.