Analisis Sentimen dari Perspektif Peserta Implementasi Computational Thinking Dengan Block-Based Programming Dan Permainan Robot

Abstract

Computational Thinking (CT) is the ability to solve complex problems by analyzing, understanding issues, and logically developing appropriate solutions. Possessing CT skills enables individuals to think in a structured manner when faced with complex problems, making it easier to adapt and compete in the future. This ability is highly valuable for anyone, including students from elementary to high school. Enrichment material on logical thinking skills for high school students is currently provided as an extracurricular activity integrated into Information and Computer Technology (ICT) subjects. The ICT curriculum includes office administration, graphic design, and programming. However, programming material often cannot be effectively delivered to students due to the limited expertise of teachers in this field. Unfortunately, this situation is regrettable because programming is not solely about technical programming skills but primarily about CT and problem-solving abilities. In this Community Service activity, workshops will be conducted on the implementation of CT for high school students and several High School (SMA) teachers, utilizing two approaches: block-based programming and robot gaming. Block-based programming involves implementing CT using blocks of code arranged to produce a function. On the other hand, the CT approach using robot gaming will involve utilizing Edison robots, which can be implemented in Science, Technology, Engineering, and Mathematics (STEM) subjects. Results from satisfaction surveys conducted among participants in the implementation activities of block-based programming and robot gaming indicate that they perceived significant benefits in enhancing computational thinking among high school students, thus preparing them better for global competition in the future. Meanwhile, from the processed feedback data using sentiment analysis, it was found that 83.3% provided positive feedback, 16.7% were neutral, and there were no negative comments.