Computational Thinking Skill Level of Senior High School Students Majoring in Natural Science

Abstract

Computational thinking (CT) is a skill integrated into various curricula in many countries. However, lack of student acceptance and limited assessment become challenges to integrating skill into the curriculum, specifically in developing countries like Indonesia. Therefore, this study aimed to validate the Indonesian version of the Computational Thinking Scale (CTS) and determine the CT skill level of high school students majoring in science. This study was conducted using a quantitative approach with a cross-sectional survey design. Participants were purposively selected based on certain criteria from a population of high schools in Yogyakarta, Indonesia. In this study, data were collected from 526 students with 19 items of CTS questionnaires and analysed using the Rasch model measurement. The findings showed that the adapted CTS met the fit criteria based on Rasch model measurement, except for one item. Based on the logit mean value of +1.69, the level of students' CT ability falls into the good category, where the most frequently implemented aspect is the problem-solving aspect, while the least frequently implemented aspect is algorithmic thinking. According to Differential Item Function analysis, there were differences in student responses based on coding experience. This study is expected to contribute to the field of CT assessment in science education. In addition, the results of this study can be an affirmation for educational policy makers in developing countries to integrate CT into the curriculum of natural science majors.