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Mapping the Mobile Shift

A Bibliometric Exploration of Mobile Learning Innovations in STEM Education

Bibliographic Data

ID22431741
AuthorsR P Antonio (0000-0002-2832-7203, Bulacan State University), Camille Lozano Espino (Bulacan State University)
Year2026
Volume14
Issue1
Pages46-65
Publication date2026-01-01
Open AccessYes
TypeARTICLE
VenueInternational Journal of Education in Mathematics, Science and Technology (JOURNAL)
Journal identifiersISSN: 2147-611X • E-ISSN: 2147-611X
PublisherISTES Organization (PUBLISHER)
DOI10.46328/ijemst.5257
OpenAlexW7117761025
LanguageEN

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.

Collaborative learning · Digital Learning · Educational technology · Higher education · Mobile device · Mobile technology · Technology integration · Thematic analysis · E-Learning and COVID-19 · Innovative Educational Technologies · Mobile Learning in Education

Highly citedNo

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Open DOIOpen Access
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