About AI in Education

Aims

AI in Education is an international, peer-reviewed, open access journal that advances research at the intersection of artificial intelligence and education. We publish rigorous empirical, theoretical, and methodological work that explains how AI can improve teaching, learning, and assessment while safeguarding equity, privacy, transparency, and safety. We welcome studies at the classroom, institutional, and system level; design-based research; mixed-methods evaluations; replications and registered reports; as well as well-argued negative results. Submissions should follow high standards of reporting, including providing clarity about data, instruments, code, and reproducibility whenever feasible.

Scope

We invite contributions on topics including, but not limited to, the following:

• Generative AI and large language models in education: classroom uses, learning outcomes, reliability, harm mitigation, retrieval-augmented and tool-augmented tutoring, and multilingual and accessibility use cases.
• Multimodal and embodied AI: vision and audio for feedback and orchestration, AR and VR, simulation and digital twins, and educational robotics.
• Educational robotics and embodied learning: the design, deployment, and evaluation of robot-mediated instruction across K-12 and higher education; human–robot interactions for tutoring, feedback, and assessment; social robots, telepresence, and collaborative robots in labs and makerspaces; tangible interfaces and physical computing; programming by demonstration and reinforcement learning in classroom contexts; inclusion and assistive applications; safety, privacy, and ethics for working with minors; and field experiments, longitudinal studies, and cost-effectiveness analyses.
• Personalization and adaptive systems: intelligent tutoring systems, mastery-based progression, game-informed learning, efficacy, and cost-effectiveness.
• Assessment, feedback, and academic integrity: AI-enhanced formative assessments, redesign of assessments for AI-rich contexts, metacognition, and trust and verification.
• Teacher augmentation and human–AI co-orchestration: planning, differentiation, classroom management, professional development, and AI literacy for educators and students.
• Learning analytics: causal inference, field experiments, privacy-preserving analytics, and dashboards aligned with pedagogical goals.
• Data governance and trustworthy AI: federated learning, differential privacy, synthetic data, documentation and model cards, auditing, and risk management.
• Policy, ethics, and regulation: alignment with international guidance and competency frameworks, and implications of the EU AI Act and related regulations for education.
• Systems and implementation at scale: on-device and edge AI, infrastructure, procurement and governance models, interoperability, and institutional operations.

MDPI Publication Ethics Statement

MDPI is a member of the Committee on Publication Ethics (COPE). MDPI takes the responsibility to enforce a rigorous peer-review together with strict ethical policies and standards to ensure to add high quality scientific works to the field of scholarly publication. Unfortunately, cases of plagiarism, data falsification, inappropriate authorship credit, and the like, do arise. MDPI takes such publishing ethics issues very seriously and our editors are trained to proceed in such cases with a zero tolerance policy. To verify the originality of content submitted to our journals, we use iThenticate to check submissions against previous publications.

Book Reviews

Authors and publishers are encouraged to send review copies of their recent related books to the following address. Received books will be listed as Books Received within the journal's News & Announcements section.

MDPI
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Copyright / Open Access

Articles published in AI in Education will be Open-Access articles distributed under the terms and conditions of the Creative Commons Attribution License (CC BY). The copyright is retained by the author(s). MDPI will insert the following note at the end of the published text:

Reprints

Reprints may be ordered. Please contact publisher@mdpi.com for more information on how to order reprints.

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Editorial Office

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