Improving Unplugged Computational Thinking Skills Through Integrated Problem-Based and Differentiated Learning in Indonesia

Abstract

Industry 4.0 era is characterized by the development of technology and the existence of flexible and effective data exchange. This has an impact on the emergence of new jobs that require the ability to solve problems effectively and efficiently, especially computational thinking. This Classroom Action Research aims to improve students’ computational thinking (abstraction, data collection, data analysis and algorithms) in solving problems about probability through problem-based learning integrated with differentiation learning. This research was conducted in four stages: planning, implementation, observation, and reflection. Thirty-four students of class X-E7 SMA Negeri 5 Surakarta in Indonesia were the subjects of this research. It was concluded that the application of problem-based learning model integrated with differentiated learning (content and process) significantly improves students’ computational thinking skills and promotes cognitive development through problem-solving activities. The improvement of computational thinking ability is caused by: data collection activities in the form of dice/coin simulations, abstraction activities of sample points and important information in the problem, activities to formulate solution steps (algorithms) and data analysis activities in the form of interpretation of results and calculations. Differentiated learning (content and process) plays a role in improving students’ computational thinking through ability-based scaffolding and content based on their interests and learning modalities.