Relationship between higher-order thinking skills and computational thinking in Biology: A STEM-integrated perspective on gender differences

Abstract

This study examined the relationship between Computational Thinking Skills (CTS) and Higher-Order Thinking Skills (HOTS) among high school students majoring in biology in Jakarta, Indonesia, using a quantitative, correlational, and cross-sectional research design. Data were collected from 72 students (36 male, 36 female) selected from a population of 144 students through cluster random sampling across all classes, with a stratified procedure within the sampled clusters to achieve a balanced gender composition of 36:36 as an intentional design feature. The CTS test, adapted from the Bebras Computational Thinking Challenge (Blokhuis, 2016), consists of 18 items covering four components abstraction, algorithm design, decomposition, and evaluation while the HOTS test, based on the revised Bloom’s taxonomy (Anderson & Krathwohl, 2016), consists of 39 multiple-choice questions targeting analysis (C4), evaluation (C5), and creation (C6). Internal consistency in this sample was Cronbach’s α = 0.766 for the CTS and α = 0.540 for the HOTS; the lower HOTS coefficient is discussed as a measurement limitation in Section 5. Overall proficiency was low (CTS = 28.3%; HOTS = 42.2%). Pearson correlations and simple linear regressions showed a significant positive relationship between CTS and HOTS in both subgroups (males: R = 0.626, R² = 0.391; females: R = 0.709, R² = 0.503; both p < 0.001). A direct moderation test found that the CTS × gender interaction was not significant (b = −0.054, t = −0.711, p = 0.480; ΔR² = 0.004), indicating that the difference in R² values does not reflect a significant difference in slope based on gender. Given the cross-sectional nature of this study, the results are interpreted as associative and predictive, not causal; intervention and longitudinal studies are needed.