Advancing AI Education: Virtual Learning, Technology Integration, and Instructional Design

Dear Colleagues,

Artificial intelligence is reshaping how learners access content, how teachers design instruction, and how institutions assure quality at scale. The rapid diffusion of generative and predictive systems across learning management platforms, assessment ecosystems, and virtual classrooms creates new opportunities for personalization, feedback, and equity, while raising questions about validity, transparency, and professional practice. This Special Issue invites rigorous studies that advance theory, evidence, and design knowledge in AI education across formal and non-formal settings. We welcome empirical, methodological, and design-based contributions that clarify what works, for whom, and under what conditions, with attention to ethics, policy, and capacity building. Submissions may include quantitative, qualitative, mixed-methods, or computational approaches that produce actionable insights for researchers, practitioners, and decision-makers. Our goal is to curate a coherent body of work that connects virtual learning environments, technology integration strategies, and instructional design principles with measurable outcomes in learning, teaching, and assessment.

Aim & Scope:

• Advance theoretical and practical understanding of AI-enabled virtual learning and instructional design.
• Evaluate the effectiveness, efficacy, and efficiency of AI-integrated pedagogies and assessment.
• Surface ethical, cultural, and policy considerations that shape adoption and impact.
• Share open methods, datasets, and design patterns that support replication and scaling.

Suggested Themes:

• AI literacy and teacher professional development.
• Generative AI for course design, feedback, and tutoring.
• Adaptive learning, recommender systems, and mastery pathways.
• Assessment with AI: validity, reliability, comparability, and bias auditing.
• Learning analytics, predictive modelling, and early warning systems.
• Human–AI collaboration in studio, lab, and project-based learning.
• Equity, accessibility, and Universal Design for Learning with AI tools.
• Responsible and ethical AI, governance, and policy in education.
• XR, simulation, and intelligent virtual laboratories.

Dr. Musa Adekunle Ayanwale
Dr. Damola Olugbade
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Education Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.