Self Directed Learning Skills and Computational Thinking Abilities of Elementary School Students in Science Learning - Vani Qhairum Nisa Utami; Yanti Fitria (Universitas Pendidikan Ganesha, 2025)
This study was motivated by the low level of students’ self directed learning and computational thinking skills, which affect problem solving abilities and the development of higher order thinking skills in science learning. The aim of this study was to analyze the relationship between students’ independent learning in science and their computational thinking abilities. This research employed a mixed methods approach, integrating quantitative and qualitative methods simultaneously. The subjects involved were elementary school students as the research population. Data were collected through questionnaires, tests, structured interviews, observation, and documentation. The instruments were designed to measure students’ self directed learning skills and computational thinking abilities. Quantitative data were analyzed using Pearson correlation to examine the relationship between variables, while qualitative data were analyzed descriptively to strengthen the interpretation of the findings. The results indicate a very strong and positive relationship between self directed learning and computational thinking abilities. These findings suggest that improving students’ learning independence significantly contributes to enhancing their computational thinking skills. The study concludes that instructional strategies emphasizing self regulation and structured problem solving should be systematically implemented to support the development of 21st century skills. The implications highlight the importance of designing learning approaches that foster students’ independence and analytical thinking skills in a sustainable manner.