Mapping the Mobile Shift: A Bibliometric Exploration of Mobile Learning Innovations in STEM Education
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| Title: | Mapping the Mobile Shift: A Bibliometric Exploration of Mobile Learning Innovations in STEM Education |
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| Language: | English |
| Authors: | Ronilo P. Antonio (ORCID |
| Source: | International Journal of Education in Mathematics, Science and Technology. 2026 14(1):46-65. |
| Availability: | International Journal of Education in Mathematics, Science and Technology. Necmettin Erbakan University, Ahmet Kelesoglu Education Faculty, Meram, Konya, 42090, Turkey. e-mail: ijermst@gmail.com; Web site: https://www.ijemst.net/index.php/ijemst/index |
| Peer Reviewed: | Y |
| Page Count: | 20 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Information Analyses |
| Descriptors: | STEM Education, Electronic Learning, Educational Innovation, Educational Trends, Learning Theories, Educational Strategies, Cooperative Learning, Technology Uses in Education, Artificial Intelligence, Adoption (Ideas), Journal Articles, Citations (References) |
| ISSN: | 2147-611X |
| Abstract: | Given the rapid proliferation of mobile technologies and their potential to reshape science, technology, engineering, and mathematics (STEM) education, there is a pressing need to systematically examine how research in this domain has evolved over time. This study maps the intellectual structure and emerging trends of mobile learning (m-learning) in STEM education through a comprehensive bibliometric analysis. Drawing from a corpus of 1,462 journal articles indexed in Scopus, the study employed citation, co-citation, and co-word analyses using VOSviewer to uncover influential authors, dominant themes, and evolving conceptual patterns. The findings reveal three major research domains: foundational learning theories, pedagogical strategies, and user acceptance models. Four thematic clusters were identified: immersive and collaborative learning through emerging technologies, AI integration in digital pedagogy, infrastructural and accessibility challenges in developing contexts, and adoption of m-learning in higher education systems. Despite a marked growth in research output, the study highlights persistent challenges, including inequitable access to mobile technologies, insufficient teacher training, and weak alignment between mobile tools and STEM learning objectives. These limitations underscore the need for constructivist-aligned instructional designs, investment in scalable infrastructure, and institutional policy support, particularly in underserved educational settings. This study represents one of the first large-scale bibliometric investigations of m-learning in STEM education. By synthesizing a fragmented body of literature, it reveals critical research gaps and provides a roadmap for future inquiry, with particular attention to AI-driven learning design, inclusive pedagogies, and sustainable technology integration in STEM education. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1494241 |
| Database: | ERIC |
| Abstract: | Given the rapid proliferation of mobile technologies and their potential to reshape science, technology, engineering, and mathematics (STEM) education, there is a pressing need to systematically examine how research in this domain has evolved over time. This study maps the intellectual structure and emerging trends of mobile learning (m-learning) in STEM education through a comprehensive bibliometric analysis. Drawing from a corpus of 1,462 journal articles indexed in Scopus, the study employed citation, co-citation, and co-word analyses using VOSviewer to uncover influential authors, dominant themes, and evolving conceptual patterns. The findings reveal three major research domains: foundational learning theories, pedagogical strategies, and user acceptance models. Four thematic clusters were identified: immersive and collaborative learning through emerging technologies, AI integration in digital pedagogy, infrastructural and accessibility challenges in developing contexts, and adoption of m-learning in higher education systems. Despite a marked growth in research output, the study highlights persistent challenges, including inequitable access to mobile technologies, insufficient teacher training, and weak alignment between mobile tools and STEM learning objectives. These limitations underscore the need for constructivist-aligned instructional designs, investment in scalable infrastructure, and institutional policy support, particularly in underserved educational settings. This study represents one of the first large-scale bibliometric investigations of m-learning in STEM education. By synthesizing a fragmented body of literature, it reveals critical research gaps and provides a roadmap for future inquiry, with particular attention to AI-driven learning design, inclusive pedagogies, and sustainable technology integration in STEM education. |
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| ISSN: | 2147-611X |
