Generative-AI-Enhanced Learning Environments and Applications
A special issue of Education Sciences (ISSN 2227-7102).
Deadline for manuscript submissions: closed (30 April 2025) | Viewed by 3965
Special Issue Editors
Interests: pedagogical research; artificial neural networks; evolutionary computing
Special Issues, Collections and Topics in MDPI journals
Interests: deep learning; big data analytics; smart systems; human–robot collaboration; GenAI in higher education
Special Issues, Collections and Topics in MDPI journals
Interests: generative AI in education; computer science education; machine learning
Interests: intelligent manufacturing; CAD/CAPP/CAM; human–robot collaboration; digital twins; Industry 4.0
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the ever-evolving arena of education, the advent of generative artificial intelligence (GenAI) presents a frontier brimming with potential that is yet to be fully realized, especially within the context of higher education. Despite centuries of evolution in teaching methodologies, the core essence of learning has remained largely unchanged since the era of Confucius. Today, as we stand on the brink of a new educational paradigm, the integration of GenAI into learning environments beckons as a promising yet underexplored area upon which to embark. The burgeoning field of GenAI offers innovative tools and methodologies that could revolutionize educational practices, yet the path for its effective incorporation into higher education remains nebulous. There is a pressing need for comprehensive case studies, empirical research, and practical applications to illuminate the capabilities and limitations of GenAI in educational settings.
This Special Issue, titled "Generative-AI-Enhanced Learning Environments and Applications", aims to bridge this gap by providing a platform for scholarly discourse and exploration into the integration and application of GenAI within higher educational settings. It seeks to elucidate the impact, potential, and challenges of adopting GenAI technologies, with a focus on developing robust, evidence-based frameworks for their implementation. Through empirical studies, case analyses, and theoretical contributions, this Special Issue endeavours to advance our understanding of how GenAI can be synergized with existing educational paradigms to foster more engaging, effective, and personalized learning experiences.
The themes of this Special Issue are organized around three core areas of inquiry, reflecting the multifaceted implications of GenAI in education. These are as follows:
- The Integration of GenAI into New or Existing Teaching Frameworks: This theme includes the seamless incorporation of GenAI into established educational methodologies such as problem-based learning, experiential learning, and others. Under this theme, this Special Issue seeks contributions that demonstrate how GenAI can enhance traditional teaching approaches, innovate assessment methods, and contribute to the development of new pedagogies and ethics in education.
- Using GenAI from the Learner's Perspective: Focusing on the student experience, this Special Issue invites studies and reports on how learners interact with GenAI tools, including personal tutoring systems, ChatGPT as a personal assistant, and prompt engineering in educational contexts. Contributions may address the impact of these technologies on learning outcomes, student engagement, and the personalization of the learning journey.
- Effective Human–AI Partnership and Interaction: This theme encompasses the dynamics of collaboration between humans and AI in the higher education ecosystem. It includes the development of human–AI partnerships, the systematic use of GenAI as a facilitative tool in teaching and learning, and the exploration of ethical considerations and best practices for human–AI interaction.
Through these themes, this Special Issue aims to generate a rich dialogue on the transformative potential of GenAI in enhancing learning environments and applications, paving the way for informed and innovative educational practices in so doing.
We look forward to receiving your contributions.
Dr. Jianhua Yang
Dr. Xin Lu
Dr. Michael O'Dea
Dr. Wei Wang
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.
Keywords
- generative AI
- educational technology
- human-AI partnership
- experiential learning
- personalized tutoring
- pedagogical ethics
- prompt engineering
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