Computational thinking is an approach to understanding and solving complex problems by applying computational concepts and techniques. This study uses a bioinformatics database to analyze the computational thinking test question items qualitatively and quantitatively. The method used in this study is mixed, with the research design being a convergent parallel design. The qualitative data collection technique is a sheet of suggestions, inputs, and comments from experts in assessment in education, computational thinking, and bioinformatics. In contrast, the quantitative data collection technique is an expert assessment sheet and a test of questions to 127 pre-service biology teachers by producing reliability values and an infit-outfit index. The results obtained qualitatively show that CTT has high recency and complexity, and there are improvements related to the language and multiple answer options used. The quantitative results showed that the computational thinking problem was included in the very feasible category with a value of 91.83; the reliability value that was included in the category was very low, but each item was included in the accepted category with an infit-outfit index range of 0.7-1.3. Based on these results, following up on the measurement of students' computational thinking more widely using CTT is interesting.
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