Analisis kebutuhan game naratif AI untuk berpikir komputasional - Siti Nurhayati; Eki Nugraha; Munir Munir (Universitas Pendidikan Indonesia, 2026)
Computational Thinking (CT) is a fundamental 21st-century competency that supports logical reasoning and problem-solving. However, its implementation in schools still faces challenges due to the concept's abstract nature and the lack of a contextually grounded learning approach, resulting in suboptimal student engagement. This study aims to analyze the needs of CT learning in the school environment as a basis for developing a more interactive, adaptive, and contextual AI-based narrative game learning model. This study was conducted because of a gap, namely, the integration of innovative approaches such as game-based learning, AI, and learning analytics has not been comprehensively implemented to support CT mastery. The method used is a sequential exploratory mixed-method design involving semi-structured interviews with Informatics teachers and the distribution of questionnaires to MTs students. The research findings indicate that CT learning is still hampered by abstract concepts, analog learning media, and low student engagement. The analysis results emphasize the urgent need for interactive, adaptive digital learning media with automatic feedback to improve students' understanding and motivation in mastering CT.