This systematic review maps the landscape of microlearning research within software engineering education, critically examining how this pedagogical approach is being applied to develop the multifaceted competencies required of modern software professionals. Following PRISMA-ScR guidelines, the review synthesized 21 empirical studies from 2015 to 2026, analyzing their pedagogical approaches, technological integrations, curriculum coverage, and evidence of effectiveness. The findings reveal a field marked by creative experimentation yet significant fragmentation: while microlearning effectively engages students and conveys discrete programming and project management knowledge through gamified, mobile, and project-based formats, its application remains narrowly concentrated on introductory coding, leaving advanced competencies such as software architecture, requirements engineering, and testing strategies virtually unexplored. The review further exposes critical gaps in the evidence base, including the absence of longitudinal and transfer studies, the conflation of platform engagement with learning, and methodologically fragile claims of effectiveness. Enthusiasm for microcredentials and AI-personalized learning considerably outstrips empirical support, with implemented systems relying on rule-based logic rather than adaptive intelligence and credentialing frameworks lacking validation of employer recognition or employment outcomes. This review concludes that while microlearning holds genuine potential for just-in-time skill development in a rapidly evolving discipline, its role in software engineering education must be strategic and supplemental rather than comprehensive. The field must urgently move from promotional advocacy toward rigorous, comparative, and longitudinal research that assesses higher-order competencies and authentic professional capability, lest its promise remain unfulfilled.
Building similarity graph...
Analyzing shared references across papers
Loading...
Franklin Parrales-Bravo
Education Sciences
Universidad Complutense de Madrid
Central University of Ecuador
University of Guayaquil
Building similarity graph...
Analyzing shared references across papers
Loading...
Franklin Parrales-Bravo (Fri,) studied this question.
www.synapsesocial.com/papers/69bf899af665edcd009e9742 — DOI: https://doi.org/10.3390/educsci16030487