INTEGRASI COMPUTATIONAL THINKING DALAM PEMBELAJARAN: STRATEGI PEDAGOGIS UNTUK MENGEMBANGKAN POLA PIKIR ANALITIS PESERTA DIDIK

Abstract

Digital transformation in education requires the strengthening of higher order thinking competencies to enable learners to address complex, data rich, and often ill structured problems. One key competency relevant to these demands is Computational Thinking (CT), which encompasses decomposition, pattern recognition, abstraction, and algorithmic thinking. This article aims to examine CT as a pedagogical strategy for developing learners’ analytical thinking and to formulate a framework for integrating CT into learning across subjects and educational levels. The study employs a conceptual review approach through a literature review and theoretical synthesis of recent international studies. The findings indicate that CT can be positioned as a systematic thinking framework that strengthens problem analysis, logical reasoning, and decision making processes. The integration of CT can be operationalized through instructional strategies such as problem based learning, project based learning, inquiry learning, and digital learning, provided that appropriate scaffolding and assessment of thinking processes are applied. Furthermore, CT integration should be designed progressively in accordance with learners’ cognitive development from primary to higher education. This article offers a conceptual model of CT integration and implementation recommendations to support educators and curriculum developers in designing meaningful learning experiences oriented toward the development of analytical thinking.