About the Journal
The Review of Artificial Intelligence in Education (published by ALUMNI IN) is a dedicated platform to explore and disseminate advances and innovations in the field of artificial intelligence (AI) applied to education. Our aim is to provide a prominent space for critical analysis and review of the latest trends, technologies, and methodologies that are shaping the educational landscape through AI. By bringing together scholars, researchers, and education professionals, we seek to establish an interdisciplinary dialogue and deepen the understanding of the possibilities and challenges of AI in fostering learning.
Focus and Scope: The "Review of Artificial Intelligence in Education" encompasses a wide range of topics at the intersection of artificial intelligence and education, including, but not limited to:
- Development and analysis of intelligent tutoring systems
- Personalization of learning through AI
- Use of data analytics for educational optimization
- Adaptive and individualized learning with AI
- Gamification and simulation in AI-assisted education
- Human-machine interaction in educational settings
- Ethics and privacy in AI in educational contexts
- Integration of AI into curricula and pedagogical practices
- Automated assessment and real-time feedback
Challenges and Concerns in AI-Enhanced Education
This journal aims to serve as a leading forum for scholarly discussion, critical analysis, and empirical research on the challenges and concerns raised by the integration of Artificial Intelligence in educational settings. Our focus spans various dimensions, including but not limited to:
Ethical and Privacy Issues: We invite contributions that explore the ethical dilemmas and privacy challenges posed by AI in education. This includes investigations into data privacy, consent protocols, ethical use and storage of student information, and the development of frameworks to guide ethical AI practice in educational contexts.
Bias and Inequality: The journal seeks research that addresses the manifestation of bias in AI systems and its implications for educational equity. Studies might examine how AI algorithms can inherit and amplify biases present in training data, the impact on student outcomes, and strategies for mitigating bias and promoting fairness in AI-enhanced education.
Dependence on Technology: Contributions are encouraged that critically assess the implications of technology dependence in educational environments. This encompasses analyses of how overreliance on AI technologies might affect the role and autonomy of educators, impact student learning experiences, and alter traditional educational dynamics.
Accessibility and Digital Divide: The journal is interested in research that sheds light on the digital divide and accessibility issues within AI-enhanced education. Papers may investigate how AI technologies either bridge or widen gaps in educational access, particularly for students from marginalized or underserved communities, and propose solutions to enhance digital equity.
Target Audience: The "Review of Artificial Intelligence in Education" is intended for scholars, researchers, educators, industry professionals, and decision-makers who are interested in exploring the possibilities and challenges of AI in education. We also invite contributions from experts in ethics, regulation, and policy related to AI in educational contexts.
Editorial Themes: Our journal consists of sections that reflect our mission of critical analysis and rigorous review. These sections include:
- Scientific Review Articles: In-depth analyses of recent research and emerging trends in the application of AI in education, with an emphasis on synthesis and critical evaluation.
- Case Studies and Best Practices: Concrete examples of successful implementations of AI in education, highlighting lessons learned and best practices.
- Ethical and Social Reflections: Explorations of ethical, legal, and societal issues related to the use of AI in education, stimulating discussion and awareness.
- Expert Interviews: In-depth conversations with leaders and innovators in the field of AI in education, offering valuable insights and unique perspectives.
- Book and Tool Reviews: Critical evaluations of books, software, and tools relevant to the AI in education community.
Qualitative Studies: This theme encourages submissions of qualitative research that provides in-depth insights into the experiences, perceptions, and contextual challenges of implementing AI in educational settings. Studies may explore teacher and student perspectives, the impact of AI on learning processes, classroom dynamics, or the socio-cultural implications of technology-enhanced education.
Book Reviews: The journal seeks reviews of recent books that contribute to the discourse on AI in education, especially those that address ethical considerations, equity issues, technological dependence, and accessibility. Reviews should critically assess the book's content, relevance to the journal's focus, and its contribution to the field.
Perspectives: This section invites opinion pieces, commentaries, and reflective essays that offer unique viewpoints on the use and impact of AI in education. Contributions may include discussions on policy implications, ethical dilemmas, future trends in AI education, or theoretical explorations of digital learning environments.
By emphasizing critical review and the dissemination of innovative knowledge, the "Review of Artificial Intelligence in Education" aims to drive the ongoing evolution of AI integration in the educational domain, inspiring collaboration and creative thinking.