FACULTY’S EMOTIONAL INTELLIGENCE AND RESISTANCE TO ARTIFICIAL INTELLIGENCE ADOPTION: IMPLICATIONS FOR JOB PERFORMANCE IN HIGHER EDUCATION OF RAJASTHAN
Shraddha Sahay1, Dr. Surbhi Mathur2, Dr. Poornima Mathur3
1Research Scholar, Rajasthan Technical University, Kota, India
2Faculty of Management, Manipal University, Jaipur, India
3Associate Professor, ISIM, Jaipur, India
Abstract: Over the past several decades, education has made great progress due to advancements in information and communication technology (ICT). Artificial intelligence (AI) is a potential technology for revolutionizing education and learning. However, incorporation of AI in education should prioritize emotional management, not only academic achievements, as it is vital in the educational process (González et al., 2023). This study examines how emotions and artificial intelligence impact learning and interpersonal interactions in educational environments. Automated grading, plagiarism detection, virtual assistants, and adaptive learning systems can alter higher education teaching and research. Many faculty members reject AI adoption because they see it as a threat to their positions. Eliminating such resistance may need emotional intelligence (EI). Higher EI faculty can better handle stress, emotions, and technology. This may improve their teaching, research, and institutional contributions. This study examines how Emotional Intelligence (EI) affects teacher opposition to AI adoption and job performance in Rajasthan, India, higher education institutions. Based on theories of emotional regulation and technology resistance, the study suggests that teachers with greater EI can better manage stress, adjust to technological disruptions, and adopt AI-enabled practices, lowering resistance and improving performance. Chi Square and Annova analyzes data from a quantitative, cross-sectional survey using verified EI, technology resistance, and work performance measures. The findings aim to extend theoretical understanding by integrating emotional and technological dimensions of faculty performance. Additionally, they provide practical insights for policymakers and administrators to develop EI-based interventions and training programs that facilitate smoother AI integration in higher education.
Keywords: Emotional Intelligence, Artificial Intelligence Adoption, Resistance to Technology, Job Performance, Higher Education, Rajasthan.