<![CDATA[This study aims to map the evolution of research on computational thinking (CT) within the context of science and technology, with a particular focus on science education and physics learning. Through a content analysis of a corpus of scholarly publications from 2015 to 2023, this study seeks to identify annual trends in research on computational thinking and computational thinking skills in the context of science and technology, with a deeper exploration of the context of science education and physics learning. A content analysis guide was employed as the research instrument. In synthesizing the articles, four main aspects were examined: (1) the number of publications per year, (2) research subject areas, (3) research types, and (4) the treatments and variables measured in computational thinking research in science education and physics learning. An analysis of the number of publications, research areas, methodologies, treatments, measured variables, and findings revealed a significant increase in interest in CT in 2022, particularly in the social sciences. Quasi-experimental research emerged as the dominant approach, with a focus on developing and evaluating learning interventions that integrate CT. The use of technology in computational thinking activities to enhance students' computational thinking skills in science education and physics learning was highlighted. The findings of this study have important implications for future research, such as expanding the diversity of research methodologies, delving deeper into CT instruments and data analysis techniques, conducting more in-depth studies on technology products designed to enhance computational thinking skills, and exploring a wider range of learning contexts.]]>
Copyrights © 2024
