Generative AI Tools & Software for Education

About this Research Topic

Background

Generative Artificial Intelligence (AI) has brought many opportunities within the field of education, where it has enabled the automation of complex tasks with unprecedented success, such as the generation of teaching materials, the provision of timely feedback, and content personalization, among others (Misiejuk et al., 2025; Wang et al., 2024). Existing commercial solutions are often meant to do one thing: be helpful assistants that aid humans in their tasks. However, this role does not align well with pedagogical principles in which students have to engage in active learning and productive struggle (Rus & Kendeou, 2025). Therefore, ad-hoc solutions in which Generative AI tools are adapted to educational settings and pedagogical values while taking advantage of their potential are needed. In this vein, several education technology researchers and professionals have begun to develop their own AI-powered software and tools. The field is still in its early stages, but we can already benefit from lessons learned, insights gained, and emerging practices from pioneers.

In this Research Topic, we call for contributions that explore the design, development, implementation, and/or evaluation of generative AI tools and software tailored specifically for educational purposes. We invite researchers, developers, educators, and practitioners to share their latest contributions. We are interested in submissions that go beyond the application of general-purpose AI tools and instead focus on solutions intentionally designed to support pedagogical goals, promote self-regulated learning, or address the ethical, practical, technical, or cognitive challenges associated with AI use in education. Topics may include, but are not limited to:

● Customized chatbots developed for real-time learner support

● Authoring tools for the creation of teaching and learning materials

● Multi-agent systems or intelligent environments with generative capabilities

● Automated scoring/feedback tools for writing or coding, among other tasks

● Platforms that enable teacher- or student-driven customization of AI features

● Plugins or add-ons that bring generative AI into existing learning platforms (e.g., LMS integrations)

● Software designed to support specific pedagogical models (e.g., collaborative learning, game-based learning)

● Comparative evaluations or technical case studies of different AI-based educational software


References Misiejuk, K., López-Pernas, S., Kaliisa, R., & Saqr, M. (2025). Mapping the landscape of generative artificial intelligence in learning analytics: A systematic literature review. Journal of Learning Analytics, 12(1), 12–31. https://doi.org/10.18608/jla.2025.8591 Rus, V., & Kendeou, P. (2025). Are LLMs actually good for learning? AI & Society, 1–2. https://doi.org/10.1007/s00146-025-02323-9 Wang, S., Xu, T., Li, H., Zhang, C., Liang, J., Tang, J., Yu, P. S., & Wen, Q. (2024). Large Language Models for education: A survey and outlook. In arXiv [cs.CL]. https://doi.org/10.48550/ARXIV.2403.18105

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Review
• Systematic Review
• Technology and Code

Keywords: AI, software, education, Artificial Intelligence, automation, generative AI

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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