Integrasi Artificial Intelligence Dan Computational Thinking untuk Problem Solving Dalam Pembelajaran Fisika - Siti Nurul Hidayah; Pujianto Pujianto; Heru Kuswanto (Universitas Nggusuwaru, 2026)
This study aims to analyze research trends, integration models, and the contribution of Artificial Intelligence (AI) and Computational Thinking (CT) to problem-solving skills in physics learning. The study employed a systematic literature review (SLR) approach by adapting the PRISMA 2020 guidelines. The review process consisted of identification, screening, eligibility assessment, and inclusion of articles obtained from various scientific databases. A total of 30 articles published between 2019 and 2026 that met the inclusion criteria were analyzed using content analysis and thematic synthesis. The findings indicate that computational thinking is the most dominant research focus, while the application of artificial intelligence in education has expanded through adaptive learning media, intelligent tutoring systems, educational chatbots, and interactive digital platforms. The synthesis reveals that artificial intelligence provides adaptive and interactive learning environments, whereas computational thinking supports learners in developing decomposition, pattern recognition, abstraction, and algorithm design skills that facilitate problem-solving processes. Although studies specifically integrating artificial intelligence and computational thinking in physics education remain limited, the reviewed literature highlights their significant potential to enhance students’ problem-solving abilities. This study implies that the integration of artificial intelligence and computational thinking can serve as an alternative instructional strategy in physics education to support the development of twenty-first-century skills.