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Introduction This article offers a thorough examination of relevant literature in the WoS, Scopus, and Eric databases for the period 2012–2022, utilizing the PRISMA model (2020) to address STEM and gender gap factors. Methods A comprehensive search of the Web of Science, Scopus, and Eric databases spanning the years 2012 to 2022 was conducted. Employing the PRISMA (2020) model, inclusion and exclusion criteria were applied to identify pertinent studies that examined the relationship between STEM education and the gender gap. After rigorous evaluation, 24 articles that adhered to the established criteria were selected. These articles were thoroughly analyzed to extract relevant information pertaining to the factors contributing to the gender gap in STEM fields and educational interventions designed to alleviate these disparities. Results This analysis hinges on two fundamental dimensions. The first addresses the factors that contribute to the gender gap in STEM fields, while the second focuses on educational interventions crafted to mitigate bias. These interventions include activities aimed at enhancing skills in science, mathematics, engineering, and technology as well as fostering a growth mindset. The findings of this review suggest that research on gender and STEM predominantly emphasizes key issues using quantitative methodologies; however, it is recommended to explore other methodologies as well. Discussion The practical implications of this research relate to identifying critical areas in need of attention to address the identified gap and recognizing the necessity of diversifying the methods and tools used for gathering information to explore new factors that could account for gender biases in scientific fields. The study’s limitations lie in its exclusive focus on the binary gender gap between women and men without considering other relevant factors. Future analyses should incorporate the intersectionality perspective.
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Stored only when both papers are in the corpus — 34 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.