This article provides an overview of the diverse ways in which computational thinking has been operationalised in the literature. Computational thinking has attracted much interest and debatably ranks in importance with the time-honoured literacy skills of reading, writing, and arithmetic. However, learning interventions in this subject have modelled computational thinking differently. We conducted a systematic review of 81 empirical studies to examine the nature, explicitness, and patterns of definitions of computational thinking. Data analysis revealed that most of the reviewed studies operationalised computational thinking as a composite of programming concepts and preferred definitions from assessment-based frameworks. On the other hand, a substantial number of the studies did not establish the meaning of computational thinking when theorising their interventions nor clearly distinguish between computational thinking and programming. Based on these findings, this article proposes a model of computational thinking that focuses on algorithmic solutions supported by programming concepts which advances the conceptual clarity between computational thinking and programming.

Epistemic understanding of science is essential for critical evaluation of scientific claims. In principle, developing students' epistemic understanding would enhance students' capability in evaluating scientific claims. However, findings on this "expected" connection have been inconclusive. This paper seeks to examine this discrepancy between epistemic understanding in theory, and the practical application of this

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Understandings of the nature of scientific inquiry (NOSI), as opposed to engaging students in inquiry learning experiences,