Assessing computational thinking skills of science and mathematics upper-secondary school students

Computational thinking (CT) is a thinking skill developed and integrated into curricula worldwide in recent years. However, limited assessment is one of the challenges in integrating CT skills into the educational curriculum of developing countries such as Indonesia. This study aimed to develop and validate a CT assessment instrument tailored for upper-secondary school students majoring in science and mathematics in Indonesia. The cross-cultural assessment adaptation method was adopted, comprising six stages: translation, synthesis, back-translation, expert committee review, pretesting, and research audit. Twelve experts were involved in the content validation stage to assess the feasibility of the instrument adapted in Indonesia. The validation process was followed by a pilot test with 501 upper-secondary students majoring in science and mathematics (220 female and 281 male). The data collected were analyzed using the Rasch model measurement. The findings showed that all adapted items met the fit based on the Rasch model measurement, except one spatial question item. The instrument demonstrated high item reliability, although person reliability was relatively low, indicating variation in student responses. The average upper-secondary school students majoring in science have good CT skills. Based on the differential item function value, there are two gender-biased items and four age-biased items. This study hopes to contribute to the literature on CT assessment by providing references and alternative tests for researchers and teachers to use in assessing CT in upper-secondary school students.