Advances of AI in Talent Development: Synergies Between Creativity, Cognitive Intelligence, and Socio-Emotional Growth
A special issue of Journal of Intelligence (ISSN 2079-3200). This special issue belongs to the section "Studies on Cognitive Processes".
Deadline for manuscript submissions: 20 November 2025 | Viewed by 164
Special Issue Editors
Interests: cognitive and neural mechanisms of creative ideation; the impact of artificial intelligence on innovation talent cultivation and associated neurocognitive mechanisms; development, enhancement, and neural plasticity of creativity via computational approaches
Interests: intelligence; giftedness; intellectual assessment; mathematical learning; mathematical disabilities; mathematical and scientific creativity; intelligence and emotion
Special Issue Information
Dear Colleagues,
We are pleased to invite you to contribute to this Special Issue, “Advances of AI in Talent Development: Synergies Between Creativity, Cognitive Intelligence, and Socio-Emotional Growth.” This issue aims to explore the evolving intersection between artificial intelligence and talent development, with a particular focus on how AI technologies can enhance human potential across multiple domains—cognitive, creative, and emotional.
The Special Issue welcomes contributions that investigate how AI tools—such as machine learning, adaptive learning systems, and generative AI—support the identification, nurturing, and assessment of talent. Topics may include AI-assisted creativity development, emotional intelligence modeling, personalized learning algorithms, and the role of AI in fostering social–emotional learning.
By situating this Special Issue within the existing literature on AI in education, creativity studies, and cognitive development, we aim to bridge disciplinary gaps and highlight innovative applications of AI in talent cultivation. This collection will provide a platform for theoretical, empirical, and practice-based contributions that explore ethical considerations, effectiveness, and future implications.
We welcome original research articles, reviews, conceptual papers, and case studies from interdisciplinary perspectives, including education, psychology, AI, neuroscience, and human development.
We look forward to receiving your contributions.
Prof. Dr. Yadan Li
Prof. Dr. Jacques Grégoire
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. Journal of Intelligence 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 2600 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
- artificial intelligence
- talent development
- creativity and innovation
- cognitive intelligence
- social-emotional learning
- personalized learning
- human–AI collaboration
- adaptive education technologies
- emotional intelligence modeling
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