Call for papers

Artificial Intelligence for Education: Innovation, Ethics, and Accessibility in Learning Transformation

Guest Editors:

  • María Soledad Ramírez-Montoya, Tecnológico de Monterrey, Mexico, solramirez@tec.mx, 0000-0002-1274-706X
  • Miguel Morales-Chan, Universidad Galileo, Guatemala, amorales@galileo.edu, 0000-0002-8742-8186
  • Francisco José García Peñalvo, Universidad de Salamanca, fgarcia@usal.es, 0000-0001-9987-5584

Brief Description

The Ibero-American Journal of Learning Technologies (IEEE-RITA), the official publication of the IEEE Education Society, invites researchers, educators, and educational technology developers to submit their contributions to the monograph “Artificial Intelligence for Education: Innovation, Ethics, and Accessibility in Learning Transformation.”

Artificial Intelligence (AI) is redefining how teaching and learning take place, enabling unprecedented personalization, automating educational tasks, and creating new forms of interaction between teachers, students, and intelligent systems. However, adopting these technologies poses significant challenges in terms of equity, accessibility, ethics, and sustainability.

This monograph aims to provide a space for academic reflection and discussion on AI’s advances, applications, challenges, and opportunities in education, from the development of innovative technologies to their impact on teaching-learning processes. Additionally, it seeks to address ethical and regulatory implications, promoting a Human-Centered AI approach that ensures the responsible and beneficial use of these technologies.

The role of AI in open education, Open Educational Resources (OER), and open science will also be explored, highlighting how these technologies can foster equitable access to knowledge and strengthen international collaboration in the educational field.

We expect contributions that analyze, from theoretical and practical perspectives, how AI can serve as a catalyst for a more inclusive, personalized, and ethical education, empowering teachers and students for an equitable future.

Topics of Interest

  • AI models and architectures for education: Development of intelligent teaching systems, virtual assistants, adaptive tutoring platforms, automated assessment tools, and generative AI systems for educational content production.
  • Intelligent agents and virtual assistants in education: Design, implementation, and evaluation of conversational agents and educational chatbots, virtual learning assistants, intelligent pedagogical agents, and AI-based tutoring systems.
  • AI for personalized learning: Content recommendation algorithms, student modeling, adaptability in learning, and technologies for developing personalized educational pathways.
  • Ethics, equity, and transparency in AI applied to education: Algorithmic bias, data privacy, explainability of AI models in educational settings, regulation, and policies for responsible AI use.
  • AI and accessibility in education: AI applications for the inclusion of students with disabilities, digital accessibility solutions, and technologies to reduce educational gaps in vulnerable communities.
  • Human-AI interaction in learning environments: Human-centered design for intelligent educational systems, co-creation of AI technologies with teachers and students, and analysis of the relationship between AI and user agency.
  • Assessment of AI impact on learning and teaching: Studies on the impact of AI tools on academic performance, evaluation methodologies for AI-mediated learning experiences.
  • Generative AI and its impact on education: Use of generative models for creating educational materials, automated generation of learning exercises/activities and assessments, AI-powered tools for language and/or STEM education.
  • Machine learning and learning analytics: Educational data mining, predictive models for student retention, early detection of learning difficulties through AI.
  • Open science and AI-powered OER: AI for the creation, personalization, and dissemination of Open Educational Resources, the impact of AI on open education, and its role in knowledge democratization.
  • The future of teaching with AI: Development of digital and AI literacy skills for teachers and students, pedagogical strategies for AI integration into curricula, AI and computational thinking education at different educational levels.

Keywords:

AI in education, personalized learning, intelligent tutoring, educational data mining, AI agents, LLMs, chatbots, AI ethics, OER, open science, AI transparency, user-centered design, educational equity, AI accessibility, generative AI in education, learning analytics.

Important Dates:

  • April 30, 2025: Submission deadline.
  • May 15, 2025: Review notifications to authors.
  • May 30, 2025: Deadline for revised submissions.
  • June 10, 2025: Final decision to authors.
  • June 20, 2025: Submission of the final version for publication.
  • Publication in IEEE-RITA of accepted papers (early access): immediate.

Publication Guidelines:

  • Papers must be submitted in English. Accepted articles will have their English version published in IEEE Xplore and an open-access version in Spanish or Portuguese in VAEP-RITA.
  • Free publication for articles up to 10 pages.
  • Submission via the IEEE Author Portal.
  • Papers previously presented at conferences are accepted if they include at least 30% significant new content.
  • Papers accepted in the first phase with major revisions that do not meet the required changes will be rejected in the second phase.