ANALYZING COMPUTATIONAL THINKING SKILLS USING THE RASCH MODEL ABOUT LEARNING ENVIRONMENT AND GENDER

This research analyzes Computational Thinking abilities using the Rasch model in Futuhiyyah High School students regarding sound waves regarding the learning environment and gender. This type of mixed methods research uses a concurrent embedded design. Data were analyzed using Wright maps and different measures assisted by Minister software. The Computational Thinking ability profile of the class: Only 7 out of 27 students had very high abilities. They exceeded the measured value of the decomposition indicator question which was the most difficult question, namely 4.46. Students' Computational Thinking abilities in terms of the learning environment, 18.52% of students in boarding schools and 7.41% of non-cottage students were able to solve very difficult questions, namely decomposition indicators and algorithmic thinking by exceeding the respective indicator's measure values of 4.10 and 4. 46. Students' Computational Thinking ability in terms of gender, 7.41% of male students and 18.52% of female students were able to solve very difficult questions, namely indicators of decomposition and algorithmic thinking. The results of the different measures, boarding school students were higher in answering questions on indicators of abstraction, generalization, and decomposition, while non-residential students focused on evaluation indicators and algorithmic thinking. Male students were higher in answering questions on the indicators of abstraction, generalization, and algorithmic thinking, while female students were higher on the indicators of evaluation and algorithmic thinking.