MINI REVIEW article

Front. Comput. Sci.

Sec. Digital Education

Volume 7 - 2025 | doi: 10.3389/fcomp.2025.1607766

This article is part of the Research TopicDigital Learning Innovations: Trends Emerging Scenario, Challenges and OpportunitiesView all 11 articles

Robotics in Higher Education and Its Impact on Digital Learning

Provisionally accepted
Jorge  BueleJorge Buele*Patrick  ZamoraPatrick ZamoraAlan  LozadaAlan LozadaFátima  Avilés CastilloFátima Avilés Castillo
  • Universidad Tecnológica Indoamérica, Ambato, Ecuador

The final, formatted version of the article will be published soon.

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 Although there are literature reviews on its application in professional training, many are outdated or lack a current focus on its impact in higher education.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.

Keywords: Educational Robotics, higher education, personalized learning, artificial intelligence, stem

Received: 08 Apr 2025; Accepted: 09 May 2025.

Copyright: © 2025 Buele, Zamora, Lozada and Avilés Castillo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Jorge Buele, Universidad Tecnológica Indoamérica, Ambato, Ecuador

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