Data Literacy and Computational Thinking Among Secondary Science Teachers: A Quantitative Study of Levels, Differences and Instructional Integration

Abstract

Objectives. This study examined the levels of data literacy (DL) and computational thinking (CT) skills among secondary science teachers, the extent of their integration into science instruction, and the relationships between these competencies and instructional integration. Materials and methods. Using a descriptive-correlational design, 53 secondary science teachers in Masbate, Philippines, completed three researcher-developed Likert-type instruments measuring DL, CT, and DL-CT integration into science instruction. Data were analyzed using means and standard deviations, the Wilcoxon Signed-Rank Test, and Spearman rank-order correlation. Results. Teachers rated themselves Proficient in both DL (M = 3.92, SD = 0.63) and CT (M = 3.84, SD = 0.64), with a statistically significant difference between the two, W = 288.00, p = .040, r = .28. Teachers reported a Highly Integrated level of DL-CT instructional integration (M = 3.90, SD = 0.82). Spearman correlations revealed strong positive associations of both DL (rs = .740) and CT (rs = .757) with integration, both p < .001, with algorithmic thinking emerging as the single strongest correlate (rs = .785). Conclusion. Secondary science teachers demonstrated proficient but uneven data literacy and computational thinking skills, with abstraction and access to computational tools emerging as relative weaknesses. Both competencies played a substantial and complementary role in supporting integrated science instruction, and targeted professional development addressing these weaker areas is recommended.