Research Trends in Computational Thinking: A Systematic Content Analysis of Publications - Edi Daenuri Anwar; Sarwi; Ani Rusilowati; Bambang Subali; Hartono; Siti Alimah (Postgraduate, University of Mataram, 2026)
Computational thinking (CT) is an essential skill for solving complex problems. This study aims to identify and analyze CT frameworks used as instructional techniques across various subjects. This research employs a literature review method. Data were obtained from the ERIC database using the keywords “computational thinking”, “science education.” From more than 600 articles published between 2012 and 2021, 32 articles were selected based on inclusion criteria. The selection process followed systematic stages: identification, screening, eligibility, and inclusion. Data were analyzed using content analysis focusing on publication year, source, subject area, research participants, educational level, and CT frameworks. The results indicate that CT is implemented across multiple educational levels, from preschool to higher education, and is integrated into various subjects. CT approaches are frequently combined with STEM and constructivist approaches to enhance problem-solving skills. Common CT components include decomposition, pattern recognition, abstraction, and algorithmic thinking, along with several variations of other CT components. Overall, CT is an effective approach that can be applied across disciplines to develop problem-solving and critical thinking skills. The integration of CT in learning is recommended to improve the quality of education in the digital era.