<![CDATA[Recent technological advancements have led to various educational innovations, including adaptive Learning, which customizes content and instructional methods to meet the diverse needs and abilities of individual students. Several empirical studies have utilized adaptive learning platforms to support differentiated Learning in science. However, to date, there has yet to be a comprehensive review of the findings in this area. This study aims to explore research trends related to differentiated Instruction through adaptive learning platforms in science education, as documented in Scopus-indexed journal articles published between 2019 and 2024. The research follows PRISMA guidelines, employing the Publish or Perish application for the search system, with data sourced from SCOPUS. The search yielded 368 articles, and screening based on specific inclusion and exclusion criteria resulted in 23 papers that were subsequently analyzed. This study highlights various adaptive technology methods used in science education, emphasizing Learning Management Systems (LMS) and Artificial Intelligence (AI). LMS emerges as the most frequently utilized, followed by AI and assessment platforms. Crucial factors for successful implementation include real-time feedback and accessibility to technology. Although these platforms improve learning outcomes, issues regarding student engagement and satisfaction persist. Educational institutions should assess their technological infrastructure and provide training for educators to leverage new features effectively. Additionally, developers should focus on enhancing personalization options, while further research is necessary to address students' emotional needs better and enhance their motivation. Keywords: adaptive learning, differentiated instruction, science education, teaching, systematic literature review.DOI: http://dx.doi.org/10.23960/jpmipa/v25i2.pp914-931]]>
