Advanced Research on Intelligence, Learning, and Technology: New Directions in Education

A Special Issue of Journal of Intelligence (ISSN 2079-3200).

Deadline for manuscript submissions: 31 August 2027 | Viewed by 356

Editors


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Guest Editor
Department of Educational Science, Bursa Uludağ University, Bursa, Turkey
Interests: educational technology; technology-enhanced learning; technology acceptance and integration; digital behavior; social media use and well-being; teacher education

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Guest Editor
Department of Mathematics Education, Düzce University, Düzce, Turkey
Interests: pedagogical content knowledge; computational thinking; artificial intelligence in education; mathematics curriculum; mathematics education for gifted

Special Issue Information

Dear Colleagues,

Intelligence and learning have long been central to educational research, yet the rapid integration of technology into learning environments is reshaping how we understand, measure, and cultivate them. Digital tools, adaptive platforms, artificial intelligence, and learning analytics offer new ways to study cognitive and non-cognitive abilities, while raising fresh theoretical and methodological questions.

While a growing body of work addresses these themes separately—focusing on assessment, on cognitive processes, or on educational technology in isolation—fewer efforts bring them together. This Special Issue aims to bridge these strands, inviting research that connects intelligence, learning, and technology within authentic educational contexts, from primary and secondary schooling to higher education and lifelong learning.

We welcome empirical studies, systematic reviews, and theoretical or methodological contributions. Topics of interest include, but are not limited to, the following:

  • Technology-enhanced learning and its effects on cognitive and non-cognitive development;
  • Intelligent tutoring systems and adaptive learning environments;
  • Learning analytics and educational data mining to understand learning processes;
  • Assessment of cognitive and emotional abilities in digital and online contexts;
  • Artificial intelligence applications in teaching, learning, and assessment;
  • Individual differences in technology-supported and personalized learning;
  • Technology acceptance and integration in educational settings;
  • Digital tools for developing higher-order thinking and self-regulated learning;
  • Interdisciplinary perspectives connecting psychology, education, and the learning sciences.

By highlighting emerging directions and integrative approaches, this Special Issue seeks to advance both theory and educational practice, offering new insights into how intelligence and learning can be understood and fostered in an increasingly technology-rich world.

Dr. Şule Betül Tosuntaş
Dr. Şahin Danişman
Guest Editors

Manuscript Submission Information

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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-anonymized 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

  • intelligence
  • learning
  • educational technology
  • technology-enhanced learning
  • technology acceptance
  • cognitive abilities
  • learning analytics
  • artificial intelligence in education
  • cognitive and emotional assessment
  • individual differences

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Published Papers (1 paper)

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33 pages, 16142 KB  
Article
Meta-Analyzing the Impacts of Social Robots on Children’s Social and Emotional Development over Two Decades
by Kejun Zhang, Zaipeng Zhang, Wenjia Cui, Zhen Gao, Cixian Lv, Taghreed Ali Alsudais and Xinghua Wang
J. Intell. 2026, 14(10), 246; https://doi.org/10.3390/jintelligence14100246 - 4 Oct 2026
Viewed by 47
Abstract
Social robots are increasingly being integrated into school and home settings to support children’s development. However, their effectiveness in fostering children’s social and emotional learning (SEL) remains insufficiently understood. To address this gap, this study presents a meta-analysis of 66 empirical studies comprising [...] Read more.
Social robots are increasingly being integrated into school and home settings to support children’s development. However, their effectiveness in fostering children’s social and emotional learning (SEL) remains insufficiently understood. To address this gap, this study presents a meta-analysis of 66 empirical studies comprising 166 effect sizes and 3468 participants. The findings indicate that social robot interventions produce an overall small-to-moderate positive effect on children’s social and emotional competence. Moderator analyses identified robot role as the only statistically significant moderator of intervention effectiveness. None of the other examined moderator variables showed statistically significant between-group differences. Nevertheless, some descriptive patterns were observed in the estimated effects, with relatively larger effect sizes for cartoon-like and physical robots, individual interaction methods, and generative AI-enabled robots, as well as for longer interventions. Among child characteristics, relatively larger effect sizes were observed for older children, children with special development needs, and those from developed countries. However, these numerical differences should be interpreted cautiously, as they were not supported by statistically significant between-group tests. They therefore do not provide sufficient evidence that these characteristics systematically moderate intervention effectiveness, but may indicate patterns worthy of further investigation. Overall, this study synthesizes the growing evidence base on social robot interventions and provides a basis for identifying potentially relevant intervention characteristics for future research. Full article
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