Innovation, AI, and education
- Submission status
- Open
- Submission deadline
This Collection supports and amplifies research related to SDG 4 - Quality Education, SDG 9 - Industry, Inovation & Infrastructure, SDG 10 - Reduced Inequalities and SDG 17 - Partnerships for the Goals.
Rapid advancements in innovation and artificial intelligence (AI) are reshaping educational ecosystems globally. From personalised learning and predictive analytics to content generation and adaptive assessment, AI’s integration into teaching, learning, administration, and policy represents one of the most profound shifts in contemporary education. However, while technological possibilities proliferate, critical questions about equity, ethics, pedagogy, human agency, and policy remain underexplored—particularly across diverse disciplinary and global perspectives.
This Collection seeks to explore the multifaceted intersections between innovation, artificial intelligence, and education. It aims to examine not only how AI is transforming educational practices, but also how innovation in education—broadly defined—can respond to and shape these changes. The Collection aspires to foster dialogue across academic silos and global regions, spotlighting both the opportunities and challenges of AI-driven transformation in education through a humanistic and social scientific lens.
While numerous publications address AI from purely technological or pedagogical standpoints, this collection uniquely invites contributions that critically examine innovation and AI in education from diverse disciplinary, geographic, and methodological perspectives—including philosophical, sociological, historical, cultural, and policy-oriented approaches. By weaving together humanistic inquiry, social science research, and insights from education, the Collection fills a critical gap in AI scholarship, particularly at the intersection of ethics, innovation systems, and global educational development.
We invite submissions across a range of disciplines and contexts that speak to topics such as:
- Sociocultural implications of AI in educational settings
- Innovation ecosystems in global and regional education sectors
- Algorithmic bias, data justice, and the ethics of AI in education
- Pedagogical transformations: blended, personalised, and hybrid models
- Institutional readiness and teacher development in AI adoption
- Historical precedents of educational technological revolutions
- Public policy, governance, and regulatory challenges
- Cross-border collaborations and knowledge transfer in AI
- AI and equity in access to education in the Global South
- Intersections of AI with Indigenous, rural, or marginalised education contexts
The Collection is intentionally interdisciplinary and welcomes contributions from (but not limited to): education studies, sociology, anthropology, political science, philosophy, cultural studies, history, public policy, media studies, international development, and digital humanities. Policymaking-proximate and practitioner-informed research is especially encouraged.
Target research communities include: education researchers and policymakers; AI and ethics scholars; innovation and futures studies communities; comparative and international education networks; digital humanities and cultural theorists; sociologists and historians of education; open education and ed-tech policy communities.
We are not seeking highly technical or narrowly defined computer science or machine learning articles that do not address humanistic, social scientific, or educational concerns. Submissions should demonstrate clear relevance to education and/or broader societal implications.
