Generative AI in Education: Theoretical Explorations and Practical Investigations

Dear Colleagues,

The impact of artificial intelligence (AI), particularly generative AI technologies, has become the most important and urgent topic in every sector of society, including the field of education. AI technologies bring unprecedented new opportunities and possibilities to education at all levels and, at the same time, present various challenges and potential risks. On the one hand, AI technologies bring new hopes to realizing the age-old dream of truly personalized learning, providing new opportunities for authentic learning and assessment, and new tools for interactive, immersive, and experiential learning. On the other hand, educators around the world struggle with how to approach AI technologies, such as what to include in and how to design AI-related curricula, how to effectively use AI technologies to support teaching and learning, how to create diverse pathways to AI-rich careers, and how to address the privacy, safety, and security issues inherent in AI technologies. The fast-changing AI technology landscape also presents another layer of complexity to issues on educational equity and equality. With the potential to bridge the digital divide, AI may also create further inequality for learners from disadvantaged backgrounds.

We call for pioneering research endeavors to investigate the various issues related to AI in education. Both theory development and practical implementations examining how to meaningfully integrate AI technologies in education are much-needed explorations and will make crucially important contributions to the field.

The aim and scope of the Special Issue:

This Special Issue aims to contribute to the literature by focusing on innovative strategies and practices that explore the various topics related to the integration of AI technologies into educational settings. Specifically, this Special Issue calls for papers that investigate effective strategies for the successful integration of AI technologies in teaching and learning, including original research endeavors that apply cutting-edge AI technology advances in learning theories, incorporate pioneering instructional strategies, or integrate emerging AI technologies to resolve educational problems, as well as research that adopts innovative perspectives to examine the complexity of AI in education. Rigorous empirical studies are preferred, and we also welcome systematic reviews and theoretical explorations.

Suggested themes shall include, but are not limited to:

1. AI-supported personalized learning: For example, how can AI help to cater to individual learning styles and paces? How can AI technologies be used effectively to provide personalized feedback and support? Using AI to analyze student data for predicting performance and tailoring interventions.
2. The ethical and societal implications of AI in education: For example, how to address potential biases in AI-driven educational tools, how to manage the ethical concerns related to using AI technologies, what are the impacts of AI on teachers and students? How AI technologies can help address equity and diversity issues?
3. AI-enhanced assessment, such as the reliability and validity of AI systems in evaluating student work, AI’s role in supporting authentic assessment, the use of AI to assess non-cognitive skills including collaboration, creativity, and problem-solving.
4. Using AI to support collaborative and social learning, such as the role of AI in enhancing group learning, teamwork, and peer-to-peer learning; using AI to foster a sense of community in online and blended learning environments; the development of AI that understands and responds to social dynamics in learning contexts.
5. Using AI to create immersive, interactive, and experiential educational experiences.
6. AI literacy: How to define AI literacy? What knowledge and skills are needed? How to develop AI literacy in K-16 education?
7. Teacher support and professional development in AI technology: How AI technologies can assist teachers in lesson planning, classroom management, and student engagement? What AI technologies and resources can support preservice teacher training, ongoing teacher training and professional growth? How teachers and AI can work together to enhance the learning experience.
8. Future directions and emerging technologies, such as the intersection of AI with other technologies, including AR/VR, online learning settings, blended learning; the long-term impact of AI on education outcomes; and challenges and solutions for scaling AI in educational institutions globally.

Dr. Jing Lei
Prof. Xibin Han
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 100 words) can be sent to the Editorial Office for announcement on this website.

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-blind 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 1800 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.

• AI in education
• AI literacy
• AI technologies in educational settings