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Enhancing Teachers' Job Satisfaction through the Artificial Intelligence Utilization

Title: Enhancing Teachers' Job Satisfaction through the Artificial Intelligence Utilization
Language: English
Authors: Nimesh P. Bhojak (ORCID 0000-0001-9786-8559); Mohammadali Momin; Dhimen Jani; Ashish Mathur (ORCID 0000-0003-3932-0549)
Source: Journal of Applied Research in Higher Education. 2026 18(3):761-784.
Availability: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
Peer Reviewed: Y
Page Count: 24
Publication Date: 2026
Intended Audience: Policymakers
Document Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Descriptors: Foreign Countries; Higher Education; College Faculty; Job Satisfaction; Artificial Intelligence; Technology Uses in Education; Computer Assisted Instruction; Technology Integration; Educational Technology; Teaching Experience; Influence of Technology
Geographic Terms: India
DOI: 10.1108/JARHE-03-2024-0126
ISSN: 2050-7003; 1758-1184
Abstract: Purpose: This research paper investigates the utilization of artificial intelligence (AI) among teachers in higher education (universities and colleges) in India and its impact on teaching activities. The study explores teachers' perceptions, attitudes and the factors influencing the integration of AI in their teaching practices. Design/methodology/approach: A questionnaire-based survey was conducted involving 500 teachers in higher education (university and college) in India. Data analysis included descriptive statistics, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structure equation modeling. Findings: The study addresses teachers' expectations and attitudes toward AI integration in teaching practices. Results suggest that AI can potentially enhance teaching practices among teachers in higher education in India. The findings contribute to understanding AI adoption in teaching, providing insights for educational institutions and policymakers. Further research is recommended to validate the results across different regions and academic settings, leading to the development of strategies and support systems for successful AI implementation in teaching practices. Originality/value: The originality of this research lies in its investigation of the integration of AI in college teaching practices among teachers in India. It contributes to the existing literature by exploring teachers' perceptions, attitudes and the factors influencing the adoption of AI, providing valuable insights for educational institutions and policymakers in the Indian context.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1507587
Database: ERIC