Mobile Learning and Competency-Based Education in TVET: A Bibliometric Synthesis
DOI:
https://doi.org/10.3991/ijim.v20i08.61205Keywords:
quality education, competency-based learning, educational technology, workforce development, learning outcomesAbstract
Mobile learning has emerged as a transformative approach in education, yet a comprehensive synthesis of its application in Technical and Vocational Education and Training (TVET) remains limited. This study maps the research landscape, identifies key themes, evaluates theoretical frameworks, and uncovers research gaps in mobile learning for TVET from 2020 to 2026. A Bibliometric-Systematic Literature Review (B-SLR) was conducted following PRISMA 2020 guidelines using the Scopus database (N = 600 records). Bibliometric analysis employed VOSviewer and the Bibliometrix R package; quality assessment used MMAT 2018. Systematic review of 58 included studies revealed that technology-enhanced pedagogical approaches generally improved learning outcomes in TVET, although effect sizes varied by intervention type and context. VR/AR interventions showed moderate to large effect sizes (d = 0.40–0.84) with some studies reporting null findings, while gamification and LMS-based approaches demonstrated positive but design-dependent results. Nine thematic clusters were identified, with AI and smart technology among the fastest-growing. TAM and UTAUT dominated theoretical frameworks (43.1%), revealing a critical gap in learning-quality-oriented theories. A sub-analysis comparing medical-CBME studies (n = 14) with traditional TVET studies (n = 44) revealed divergent theoretical orientations and assessment challenges. Southeast Asia emerged as the dominant research region, though this concentration warrants caution in generalizing findings. Infrastructure and digital divide constituted the most frequently reported barrier, while psychomotor skills assessment frameworks represented the most TVET-distinctive unaddressed challenge. This study recommends prioritizing longitudinal research, AI integration, the development of psychomotor assessment tools, cross-cultural validation, and cost-effectiveness analysis.
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