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Title page
Contents
Acknowledgements 3
Abstract 4
1. Introduction 7
2. Definitions, guidelines and conceptualisations 9
Definitions of artificial intelligence, equity and inclusion 9
Guidelines and frameworks related to artificial intelligence in education 11
Taxonomy to analyse the impact of artificial intelligence on equity and inclusion in education 12
3. Learner-centred tools to support equity and inclusion 14
Opportunities of learner-centred AI tools for equity and inclusion 14
Challenges of learner-centred AI tools for equity and inclusion 17
4. Teacher-led tools to support equity and inclusion 25
Opportunities of teacher-led tools for equity and inclusion 25
Challenges of teacher-led tools for equity and inclusion 30
5. Other institutional tools that can foster equity and inclusion 34
Opportunities of institutional tools for equity and inclusion 34
Challenges of institutional tools for equity and inclusion 35
6. Conclusions 37
Embracing the potential for adaptive learning while addressing privacy, ethical and accountability issues 37
Recognising the potential to enhance cultural responsiveness while keeping in mind inherent biases 37
Balancing the potential for accessibility with challenges such as techno-ableism and impact on socio-emotional skills 38
Developing and improving teacher training in AI 38
Exploring how to maintain educational integrity amidst the growing commercial influence in the sector 39
Encouraging research on the implications of AI for equity and inclusion in education, and clarifying the role of institutions at the national level in its systematic implementation 39
References 41
Table 2.1. Conceptualising equity and inclusion regarding digital technologies in education 10
Table 2.2. AI techniques and technologies 11
Table 2.3. Taxonomy of AI tools in education 13
Table 4.1. Teacher activities and AI 27
Figure 2.1. Definitions of equity and inclusion in education 10
Figure 3.1. Quantity and quality of digital resources by socio-economic profile of schools (2022) 19
Figure 4.1. Continuing professional learning needs by school characteristics (2018) 33
Boxes
Box 3.1. Algorithmic biases 22
Box 4.1. Aspects of teaching that AI could support 27
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