The Global Trends and Outcomes of the Deep Learning Approach in Biology Education: A Systematic Literature Review (2021–2026)
Keywords:
Deep Learning, Biology Education, Systematic Literature Review, PRISMA, Bibliometric Analysis, Learning Outcomes.Abstract
This study aims to analyze global trends, implementation across educational levels, and learning outcomes of the Deep Learning approach in Biology education from 2021 to 2026. A Systematic Literature Review (SLR) was conducted following PRISMA guidelines, supported by bibliometric analysis using VOSviewer. The final Google Scholar search in September 2026 identified 1,000 records, of which only 10 articles met the inclusion criteria due to limited relevance to Biology education. Results showed that 70% of articles were published in 2026. Quantitative methods predominated (50%), followed by Research and Development (30%) and qualitative approaches (20%). Bibliometric analysis identified deep learning as a central keyword associated with digital technology, instructional models, and laboratory activities. Regarding author affiliations, 70% of articles involved Indonesian researchers, while others represented Indonesia–Thailand collaborations and affiliations in Norway and the United States. Studies primarily focused on senior high schools (50%), followed by elementary (20%), junior high schools (10%), and multiple educational levels. Ecology and environmental topics were most frequently examined. Reported outcomes included cognitive abilities, higher-order thinking skills, science process skills, scientific and digital literacy, and sustainability-oriented attitudes and character development. These findings highlight the need for broader research across educational contexts to strengthen evidence and assess outcome consistency.
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Copyright (c) 2026 Marzukah, Nurul Intan Cahyani, Sri Herawati Ali, Arifah Novia Arifin
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