
The Adoption of Artificial Intelligence and Inertia in Higher Education
Exploring Complex Resistance to Technological Change
- English
- ePUB (mobile friendly)
- Available on iOS & Android
The Adoption of Artificial Intelligence and Inertia in Higher Education
Exploring Complex Resistance to Technological Change
About this book
This research monograph explores the complex resistance to integrating Artificial Intelligence (AI) within higher education institutions. Despite the significant potential of AI to enhance education, faculty adoption remains inconsistent and is often met with skepticism.
This book investigates key factors contributing to this resistance, such as leadership deficits, funding barriers, cultural inertia, and faculty attitudes toward technological change. Drawing on qualitative and quantitative empirical data, case studies from U.S. and international institutions, and theoretical analysis, the book uncovers underlying concerns about job security and professional identity.
It points to actionable strategies for overcoming these barriers and will be relevant for scholars, researchers, advanced students, and educators grappling with issues navigating technological integration in academia and with interests in the sociology of education, educational technology, and higher education administration.
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Information
Table of contents
- Cover
- Half Title
- Series
- Title
- Copyright
- Dedication
- Contents
- About the Author
- List of Tables
- Preface
- Acknowledgments
- Introduction: Understanding Inertia in Higher Education AI Adoption
- 1 Leadership and Funding Constraints
- 2 Institutional Hierarchies and Cultural Dynamics
- 3 Regional Disparities and Global Perspectives
- 4 Disciplinary Variations and Cultural Resistance
- 5 Generational and Personality Influences
- 6 Professional Identity, Job Security, and Existential Concerns
- 7 Institutional Politics, Succession Planning, and Collaborative Leadership
- 8 Bridging the Generational Divide: Mentorship and Sustainable Cooperation
- 9 Conclusion: Strategic Frameworks for Sustainable AI Adoption
- Index