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22대 대한민국 국회 국회정보길라잡이 국회의원검색
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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

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