목차
Title page 1
Contents 4
Acknowledgments 6
Abbreviations 8
Introduction 9
Methodology 12
An Emerging Taxonomy of AI Tools in Education Across Developing Countries 14
Introduction 14
Student-focused personalized learning tools 14
Teacher-focused instructional support tools 16
Administrator and system support tools 17
Distinctive Features of AI-Powered Educational Tools in India and Nigeria 20
Introduction 20
Constraints on developing and deploying AI tools in education 22
Policy and regulatory environment for AI use in education 24
Perceptions of AI use among students, teachers, and policy makers 25
Policy Recommendations for AI in Education in Developing Countries 26
Introduction 26
Define the educational problem before adopting AI solutions 26
Invest in people, not just technology: Teacher capacity as the foundation 26
Reform procurement to enable innovation from start-ups and new entrants 27
Embrace experimentation, accept failure, and institutionalize learning 28
Address data and content gaps in local languages 28
Prioritize offline and SLM solutions for infrastructure-constrained settings 29
Establish data governance frameworks for educational AI 29
Establish mechanisms for continuous policy adaptation in a rapidly evolving AI landscape 30
Conclusion 32
References 33
Annex CS1A: Methodology and Instruments 35
Tables 5
TABLE CS1.1. Key AI or GenAI tools in India and Nigeria 18
Figures 5
FIGURE CS1.1. Types of GenAI tools prevalent in education systems in India and Nigeria 14
