<![CDATA[Science process skills (SPS) are competencies in physics education that enable students to engage in scientific inquiry, critical thinking, and problem-solving. In the context of 21st-century education, strengthening SPS has become important for supporting quality and sustainable science education. This study aims to identify patterns, issues, and research directions related to science process skills (SPS) in physics education from 2000 to 2025. This research focuses on the significance of SPS as a competency for the 21st century, particularly in enhancing the quality of science education in accordance with Sustainable Development Goal (SDG) 4 on Quality Education. Furthermore, the study emphasizes how international collaboration in SPS research plays a role in achieving SDG 17 by fostering partnerships in publications and research networks. The study uses bibliometric analysis, with data sourced from Scopus totaling 377 documents and processed using RStudio software. The analysis covers annual publication trends, keyword networks, collaborations between authors and countries, topic development, and publication sources. The results show a significant rise in publications since 2010, peaking in 2019, along with a shift in research focus from curriculum issues to digital technology integration, STEM/STEAM approaches, and virtual laboratories. International collaborative networks have expanded over time but remain regionally concentrated, particularly in North America and Southeast Asia, while collaborations involving Africa and parts of the Middle East remain limited. These findings demonstrate global growth and structural gaps in the development of SPS research. This study concludes that the development of SPS research is increasingly moving towards innovation in physics education and 21st-century competencies relevant to the SDG 4 agenda, as well as mapping the role of global research collaboration in line with SDG 17. Limitations include reliance on a single data source and metadata quality. Future research should expand data sources and employ comprehensive bibliometric methods.]]>
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