Generative Artificial Intelligence for Sustainable Education: Learning Individualization and Student Support
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Education and Approaches".
Deadline for manuscript submissions: 22 February 2027 | Viewed by 21
Special Issue Editors
Interests: the educational context of the application of smart technologies; the creation of learning objects; contextual modeling of learning objects; the integrity of the processes of development adaptation and search; generative AI in education
Special Issue Information
Dear Colleagues,
This Topic focuses on the transformative role of Generative Artificial Intelligence (GenAI) in enabling individualized learning pathways and comprehensive student support across diverse contexts in different sectors of education, i.e., engineering, medicine, etc. Its scope encompasses AI-driven personalization, adaptive assessment, intelligent tutoring systems, learning analytics, accessibility tools, and ethical, policy, and governance considerations related to GenAI in education. The purpose of this Special Issue is to critically examine how GenAI can enhance learner engagement, inclusiveness, equity, and educational effectiveness while addressing challenges such as bias, data privacy, transparency, and teacher agency. It aims to provide evidence-based insights, methodological innovations, and practical frameworks for researchers, educators, policymakers, and technology developers.
This Topic supplements the existing literature by moving beyond conceptual discussions of AI in education toward empirically grounded, sustainability-oriented applications of generative models. While prior studies have explored adaptive learning and educational data mining, few have systematically examined GenAI’s capacity to support long-term educational sustainability. Contributions will relate GenAI-enabled learning individualization to the Sustainable Development Goals—particularly SDG 4 (Quality Education)—by demonstrating how scalable, inclusive, and resource-efficient AI systems can reduce educational inequalities, support lifelong learning, and optimize institutional resources. By integrating socio-economic, technological, and policy perspectives, this issue advances an interdisciplinary understanding of how GenAI can contribute to resilient, equitable, and sustainable education systems.
Dr. Daina Gudonienė
Dr. Evelina Stanevičienė
Guest Editors
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Keywords
- generative AI
- support
- inclusion
- individualization
- education
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