Effectiveness of Block Programming and Quarky Robots to Improve Computational Abilities Thinking through the STEMC Approach - Muzakiah Muzakiah; Irwandi Irwandi; Elin Yusibani; Intan Mulia Sari; Romarzila Omar; Rini Oktavia (Jurnal Penelitian Pendidikan IPA, 2024)
The results of PISA 2022 show that Indonesian students are still weak in science literacy, mathematics, and technology-based problem solving, which are the basis for developing computational thinking (CT) skills. CT includes four primary indicators: decomposition to break down significant problems into smaller parts, pattern recognition to find similarities in data, abstraction to filter out irrelevant information, and algorithms to design systematic steps in solving problems. There are many ways to train CT, so this study uses block programming and the Quarky robot. This approach was chosen because it is visual and interactive and makes it easier to apply CT concepts practically, making it suitable for building 21st-century skills. The study was conducted in two high schools in Banda Aceh, involving 20 students from school A and 26 students from school B. Students were divided into two study groups in each school. Learning activities were designed based on STEMC in the form of Student Worksheets (LKPD), which include interactive learning scenarios, block programming challenges, and exploration of the Quarky robot's functions to solve real problems. The activities were arranged in stages, from a basic introduction to applying CT concepts in solving complex problems. The results showed a significant increase in students' CT abilities, especially in the algorithm indicator. Although both schools progressed, school B recorded higher growth, with better pre-test and post-test results than school A. This shows that block programming-based learning and Quarky robots effectively improve CT skills, which is essential in 21st-century education