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  4. Robotics in higher education and its impact on digital learning
 
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Robotics in higher education and its impact on digital learning

Journal
Frontiers in Computer Science
ISSN
2624-9898
Date Issued
2025
Author(s)
Zamora Lascano, Patrick
Facultad de Ingenierías
Lozada, Alan
Facultad de Ingenierías
Buele, Jorge
Facultad de Ingenierías
Avilés-Castillo, Fátima
Centro de Investigación de Ciencias Humanas y de la Educación
Type
journal-article
DOI
10.3389/fcomp.2025.1607766
URL
https://cris.indoamerica.edu.ec/handle/123456789/9392
Abstract
In recent years, robotics has transformed various industrial processes but has also influenced teaching methodologies. Although there are literature reviews on its application in professional training, many are outdated or lack a current focus on its impact in higher education. Addressing this gap, the present mini review examines the impact, challenges, and opportunities of this technology in the university setting. To this end, a search was conducted in the PubMed, Scopus, IEEE Xplore, APA PsycNet, and Web of Science databases, selecting 11 studies that addressed diverse applications of robotics, including educational robotics, robotic telepresence, human-robot interaction, and artificial intelligence applications. Their effects on teaching, the factors influencing their adoption, and the strategies used to optimize their implementation were analyzed. The findings show that educational robotics enhances student motivation and engagement, with prediction models reaching an accuracy of 98.78% in assessing academic engagement. Additionally, robotic telepresence emerges as an effective alternative for hybrid education, and social robots and AI-based tutors demonstrated their potential to personalize learning. However, methodological and structural challenges persist, such as the need to develop more accurate evaluation metrics and ensure accessibility and educational equity. Future research should focus on improving these aspects, enabling more efficient integration to enhance teaching processes. This study was registered in the Open Science Framework under the code: 10.17605/OSF.IO/KHDTU.
Subjects
  • artificial intelligen...

  • educational robotics

  • higher education

  • personalized learning...

  • stem

Views
4
Acquisition Date
Aug 31, 2025
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