GENDER-RESPONSIVE DESIGN IN DIGITAL LEARNING PLATFORMS: A SYSTEMATIC LITERATURE REVIEW AND NETWORK ANALYSIS OF RESEARCH THEMES AND EVOLUTION

Abstract

Gender-responsive design in digital learning platforms has gained significant attention, yet the research landscape remains fragmented. Understanding thematic clusters and research evolution patterns is crucial for advancing inclusive educational technology. This study integrates a systematic literature review with network analysis to map research themes, identify knowledge gaps, and provide evidence-based recommendations for the development of gender-responsive digital learning platforms. This method conducted a systematic search of the Scopus database (2010-2025), yielding 497 studies on gender considerations in digital learning platforms. Following PRISMA guidelines, 407 studies underwent a full systematic review. Complementary Systematic Literature Network Analysis (SLNA) was performed using VOSviewer software with keyword co-occurrence analysis (78 keywords, minimum occurrence threshold=6). Network analysis revealed four major research themes: (1) Technology Infrastructure and Platform Development (n=~20 keywords), (2) Gender Demographics and Equity Considerations (n=~18 keywords), (3) Educational Outcomes and Performance Assessment (n=~25 keywords), and (4) Specialized Applications including Entrepreneurship Education (n=~15 keywords). Temporal analysis revealed a clear evolution from foundational digital learning concepts (2010-2018) to sophisticated, gender-responsive design approaches (2022-2025). "Entrepreneurship education" emerged as a central bridging concept with high connectivity across clusters. The research landscape demonstrates mature interdisciplinary integration between gender considerations and technology implementation. Priority research opportunities include gender-responsive entrepreneurship education platforms, advanced inclusive design methodologies, and culturally adaptive digital learning systems. SLNA provides quantitative validation for systematic review findings, while identifying novel research directions that are not apparent through traditional review methods alone